ALBA ROCIO CORRALES DUCUARA

UNIVERSIDAD POLITÉCNICA DE MADRID
ESCUELA TÉCNICA SUPERIOR DE INGENIEROS AGRÓNOMOS
CENTRO DE BIOTECNOLOGÍA Y GENÓMICA DE PLANTAS
CYCLING DOF FACTORS: MOLECULAR AND FUNCTIONAL
CHARACTERIZATION OF Arabidopsis thaliana AtCDF3 AND TOMATO
(Solanum lycopersicum L.) SlCDF3 IN RESPONSE TO ABIOTIC
STRESS.
TESIS DOCTORAL
ALBA ROCÍO CORRALES DUCUARA
Licenciada en Biología
Madrid, 2014
UNIVERSIDAD POLITÉCNICA DE MADRID (UPM)
DEPARTAMENTO DE BIOTECNOLOGÍA
CENTRO DE BIOTECNOLOGÍA Y GENÓMICA DE PLANTAS, CBGP (UPM-INIA)
ESCUELA TÉCNICA SUPERIOR DE INGENIEROS AGRÓNOMOS
CYCLING DOF FACTORS: MOLECULAR AND FUNCTIONAL
CHARACTERIZATION OF Arabidopsis thaliana AtCDF3 AND TOMATO
(Solanum lycopersicum L.) SlCDF3 IN RESPONSE TO ABIOTIC
STRESS.
Memoria presentada por Alba Rocío Corrales Ducuara
para optar al grado de Doctor en el programa de doctorado
“Biotecnología y Recursos Genéticos de Plantas y Microorganismos Asociados”
Departamento de Biotecnología (UPM)
Trabajo realizado en el CBGP (grupo consolidado “Respuestas a condiciones de estrés abiótico y
señalización energética en plantas”), bajo la dirección de Dr. Joaquín Medina Alcázar y el Profesor Jesús
Vicente-Carbajosa.
Madrid, Noviembre 2014
V°B° LOS DIRECTORES
Dr. Joaquín MedinaAlcázar
Profesor Jesús Vicente-Carbajosa
LA DOCTORANDA
Alba Rocío Corrales Ducuara
UNIVERSIDAD POLITÉCNICA DE MADRID
Tribunal nombrado por el Magfco. y Excmo. Sr. Rector de la Universidad Politécnica de Madrid el día de
Noviembre de 2014
Presidente:
Secretario:
Vocal:
Vocal:
Vocal:
Suplente:
Suplente:
Realizada la defensa y lectura de Tesis el día
Agrónomos.
EL PRESIDENTE LOS VOCALES
EL SECRETARIO
de 2015 en la Escuela Técnica Superior de Ingenieros
RECONOCIMIENTOS
Este trabajo ha sido realizado en el Centro de Biotecnología y Genómica de Plantas (CBGP),
Departamento de Biotecnología de la E.T.S.I Agrónomos de la Universidad Politécnica de Madrid (UPM),
en el marco del proyecto de investigación dirigido por el Doctor Joaquín Medina Alcázar, financiado por el
Instituto Nacional de Investigaciones Agrarias (INIA) proyecto (INIA, RTA 2009-00042-C02-02) de cuya
Beca de Formación de Personal Investigador (FPI-INIA) he sido beneficiaria.
En primer lugar quiero agradecer a mis directores de tesis, Dr. Joaquín Medina Alcázar y al
Profesor Jesús Vicente Carbajosa, por brindarme la oportunidad de formar parte de su grupo de
investigación, así como su orientación científica y enseñanza.
A la profesora Rosa Victoria Molina, al Doctor Sergio Gonzalez Nebauer y a todo su grupo de
investigación de la Universidad Politecnica de Valencia (UPM), por permitirme realizar una estancia en su
laboratorio y aprender a realizar ensayos de tolerancia a estrés abiótico con las líneas transgenicas de
tomate, también por su acogida y ayuda durante esta tesis.
A la Doctora Laura Carrillo Gil, por su continua supervisión, orientación y apoyo durante el
desarrollo de esta tesis.
Al Doctor Jan Zouhar, por haber leído y aportado sugerencias a esta tesis.
Al profesor Stephan Pollmann y a su grupo de investigación, por haberme permitido aprender a
realizar los distintos análisis metabolomicos realizados en este trabajo.
Al Doctor Abdelhafid Bendahmane y a todo su equipo de la Unidad de Investigación de Genomica
Vegetal (URGV) del Instituto Nacional de Investigación Agronómica de Francia (INRA), por su gran
acogida y por haberme permitido tabajar con la población mutagenizada de tomate (M82) de la plataforma
de Tilling para la identificación de líneas de tomate mutagenizadas.
A Mar González Ceballos, por su colaboración en la obtención de las líneas transgenicas de
35S::AtCDF3 y 35S::AtCDF3-stop de Arabidopsis.
ÍNDICE
RESUMEN............................................................................................................................. .......................iv
SUMMARY…………………………………………………………………………………………………...….…..vi
ABREVIATURAS………………………………………………………………………………………………......viii
1.- INTRODUCCIÓN GENERAL ............................................................................................................11
1.1.- EL TOMATE, Solanum lycopersicum L. ........................................................................................1
1.1.1.- Origen, taxonomía y morfología. ............................................................................................1
1.1.2.- El tomate como planta modelo. ..............................................................................................4
1.2.- IMPORTANCIA ECONÓMICA DEL TOMATE. ..............................................................................5
1.2.1.- Importancia económica en el mundo. .....................................................................................5
1.2.2.- Importancia económica del tomate en España. ......................................................................6
1.2.3.- Impacto del estrés abiótico en el cultivo de tomate.................................................................7
1.3.- ESTRÉS ABIÓTICO. ..................................................................................................................11
1.3.1.- Generalidades del estrés abiótico en plantas. ......................................................................11
1.3.2.- Efectos de la salinidad, las bajas temperaturas y la sequía sobre el crecimiento de la planta.
......................................................................................................................................................12
1.3.3.- Respuesta de la planta a la salinidad, las bajas temperaturas y la sequía. ...........................15
1.3.4.- Respuesta metabólica al estrés por salinidad, bajas temperaturas y sequía. ........................18
1.3.5.- Respuesta metabólica al estrés por salinidad, bajas temperaturas y sequía en tomate.....19
1.4.- REGULACIÓN DE LA EXPRESIÓN GÉNICA..................................................................................20
1.4.1.- Regulación de la transcripción. ............................................................................................20
1.5.- FACTORES DE TRANSCRIPCIÓN EN PLANTAS. .....................................................................21
1.6.- EXPRESIÓN GÉNICA Y REGULACIÓN BAJO ESTRÉS ABIÓTICO...........................................25
1.6.1.- Complejidad de la expresión génica y regulación. ................................................................25
1.6.2.- Factores de transcripción involucrados en la respuesta a estrés abiótico. ............................27
1.6.2.1.- Regulon CBF/DREB. ........................................................................................................27
1.6.2.2.- Regulon NAC y ZF-HD. ....................................................................................................29
1.6.2.3.- Regulon AREB / ABF. .......................................................................................................29
1.6.2.4.- Regulon MYB / MYC. ........................................................................................................30
1.6.3.- Expresión génica en respuesta a estrés abiótico en tomate. ................................................32
1.6.4.- Factores de transcripción involucrados en la respuesta estrés abiótico en tomate. ...............34
1.6.4.1.- Regulon CBF/DREB. ........................................................................................................34
1.6.4.2.- Regulon NAC y ZF-HD. ....................................................................................................35
1.6.4.3.- Regulon AREB / ABF. .......................................................................................................35
1.6.4.4.- Regulon MYB / MYC. ........................................................................................................36
1.7.- FACTORES DE TRANSCRIPCIÓN DE TIPO DOF. ....................................................................38
1.7.1.- Diferenciación de tejido........................................................................................................40
1.7.2.- Desarrollo de semilla. ..........................................................................................................41
1.7.3.- Regulación del metabolismo. ...............................................................................................42
1.8.- CYCLING DOF FACTORS (CDFS). ...........................................................................................44
i
2.- OBJETIVOS ......................................................................................................................................47
3.- Arabidopsis CYCLING DOF FACTOR 3 CDF3 REGULATE DROUGHT AND LOW TEMPERATURE
STRESS RESPONSE AND FLOWERING TIME IN Arabidopsis thaliana .............................................50
3.1.- INTRODUCTION. .......................................................................................................................50
3.2.- MATERIAL AND METHODS. ......................................................................................................54
3.2.1.- Plant material and growth conditions. ...................................................................................54
3.2.2.- Plasmid constructs and Arabidopsis transformation..............................................................55
3.2.3.- Tomato transformation. ........................................................................................................55
3.2.4.- Histochemical GUS staining and subcellular localization of AtCDF3 protein. ........................56
3.2.5.- Protoplast transformation and GUS assays. .........................................................................57
3.2.6.- RNA isolation and expression analysis by real-time RT-qPCR..............................................57
3.2.7.- Germination and post-germinative growth assay. .................................................................58
3.2.8.- Photosynthesis and leaf fluorescence measurement. ...........................................................59
3.2.9.- Drought and cold stress tolerance assay. .............................................................................60
3.2.10.- Microarray analysis. ...........................................................................................................60
3.2.11.- Metabolomic analyses. ......................................................................................................61
3.3.- RESULTS. ..................................................................................................................................62
3.3.1.- Abiotic stress response and expression pattern of AtCDF3. .................................................62
3.3.2.- AtCDF3 protein localize to the cell nucleus and display specific DNA-binding and activation
properties .......................................................................................................................................65
3.3.3.- Overexpression of AtCDF3 enhanced drought and low temperature tolerance in Arabidopsis.
......................................................................................................................................................68
......................................................................................................................................................71
3.3.4.- AtCDF3 overexpression increased photosynthesis and stomatal aperture. ...........................72
3.3.5.- The effect of AtCDF3 on drought tolerance is related to its transcriptional activity. ................73
3.3.6.- Transcriptome analysis of transgenic Arabidopsis overexpressing AtCDF3. .........................75
3.3.7.- The overexpression of AtCDF3 promotes important metabolic changes in vegetative tissues.
......................................................................................................................................................80
3.3.8.- Overexpression of AtCDF3 in tomato enhance osmotic and low temperature tolerance. .......82
3.4.- DISCUSSION. ............................................................................................................................85
3.4.1.- AtCDF3 involvement in abiotic stress responses. .................................................................85
3.4.2.- AtCDF3 as a regulatory link between carbon and nitrogen metabolism. ................................87
3.4.3.- AtCDF3 is involved in the cross-talk of abiotic stress responses and flowering time. .............88
4.- CHARACTERIZATION OF TOMATO CYCLING DOF FACTORS REVEALS CONSERVED AND
NEW FUNCTIONS IN THE CONTROL OF FLOWERINGTIME AND ABIOTIC STRESS
RESPONSES………………………………………………………………………………………………………..93
4.1.- INTRODUCTION. .......................................................................................................................93
4.2.- MATERIAL AND METHODS. ......................................................................................................96
4.2.1.- Database searches for the identification of DOF family members in .....................................96
Solanum lycopersicum L.................................................................................................................96
4.2.2.- Subcellular localization of tomato CDF proteins....................................................................97
4.2.3.- DNA-binding specificity of CDF proteins using the yeast one-hybrid assay. ..........................97
4.2.4.- Protoplast transformation and GUS assays. .........................................................................98
4.2.5.- Plant growth conditions and quantification of CDF gene expression in tomato. .....................98
4.2.6.- Plasmid constructs and plant transformation. .......................................................................99
4.2.7.- RNA measurements by RT-qPCR in Arabidopsis. .............................................................. 100
4.2.8.- Salt and drought stress tolerance tests. ............................................................................. 100
ii
4.2.9.- Metabolomic analyses. ...................................................................................................... 101
4.3.- RESULTS. ................................................................................................................................ 101
4.3.1.- Identification of CDF proteins in tomato plants. .................................................................. 101
4.3.2.- Tomato SlCDF1-5 proteins localize to the cell nucleus and display distinct DNA- binding and
activation properties. .................................................................................................................... 105
4.3.3.- Expression of tomato SlCDFs follows a circadian rhythm. .................................................. 107
4.3.4.- Expression of tomato SlCDF1-5 genes is differentially regulated during development. ...... 109
4.3.5.- SLCDF1-5 GENES ARE DIFFERENTIALLY INDUCED IN RESPONSE TO ABIOTIC STRESS
CONDITIONS. .............................................................................................................................. 110
4.3.6.- Overexpression of tomato SlCDF3 promotes late flowering in transgenic Arabidopsis plants.
.................................................................................................................................................... 110
4.3.7.- Overexpression of SlCDF1 and SlCDF3 has an impact in drought and salt tolerance in
transgenic Arabidopsis plants. ...................................................................................................... 113
4.3.8.- Overexpression of SlCDF3 in transgenic Arabidopsis plants induces metabolic changes and
accumulation of specific compounds. ............................................................................................ 117
4.4.- DISCUSSION. .......................................................................................................................... 120
4.4.1.- SlCDFs share a high degree of sequence similarity but display different DNA-binding affinities
and diverse transcriptional activation capabilities. ......................................................................... 120
4.4.2.- Expression of SlCDFs follows a circadian rhythm with two different patterns. ..................... 121
4.4.3.- Expression of tomato SICDF genes in Arabidopsis unveils a conserved function in the control
of flowering time. .......................................................................................................................... 122
4.4.4.-SlCDFs involvement in abiotic stress responses. ................................................................ 123
4.4.5.- Impact of SlCDFs expression on C/N metabolism. ............................................................. 124
4.4.6.- CDFs at the interplay between environmental conditions and flowering time. ..................... 125
5.- CONCLUSIONES ............................................................................................................................ 127
6.- BIBLIOGRAFÍA ............................................................................................................................... 131
SUPPLEMENTARY .............................................................................................................................. 155
iii
Resumen
RESUMEN
El tomate (Solanum lycopersicum L.) es considerado uno de los cultivos hortícolas de mayor
importancia económica en el territorio Español. Sin embargo, su producción está seriamente afectada por
condiciones ambientales adversas como, salinidad, sequía y temperaturas extremas. Para resolver los
problemas que se presentan en condiciones de estrés, se han empleado una serie de técnicas culturales
que disminuyen sus efectos negativos, siendo de gran interés el desarrollo de variedades tolerantes. En
este sentido la obtención y análisis de plantas transgénicas, ha supuesto un avance tecnológico, que ha
facilitado el estudio y la evaluación de genes seleccionados en relación con la tolerancia al estrés.
Estudios recientes han mostrado que el uso de genes reguladores como factores de transcripción (FTs)
es una gran herramienta para obtener nuevas variedades de tomate con mayor tolerancia a estreses
abióticos. Las proteínas DOF (DNA binding with One Finger) son una familia de FTs específica de plantas
(Yangisawa, 2002), que están involucrados en procesos fisiológicos exclusivos de plantas como:
asimilación del nitrógeno y fijación del carbono fotosintético, germinación de semilla, metabolismo
secundario y respuesta al fotoperiodo pero su preciso rol en la tolerancia a estrés abiótico se desconoce
en gran parte.
El trabajo descrito en esta tesis tiene como objetivo estudiar genes reguladores tipo DOF para
incrementar la tolerancia a estrés abiotico tanto en especies modelo como en tomate. En el primer
capítulo de esta tesis se muestra la caracterización funcional del gen CDF3 de Arabidopsis, así como su
papel en la respuesta a estrés abiótico y otros procesos del desarrollo. La expresión del gen AtCDF3 es
altamente inducido por sequía, temperaturas extremas, salinidad y tratamientos con ácido abscísico
(ABA). La línea de inserción T-DNA cdf3-1 es más sensible al estrés por sequía y bajas temperaturas,
mientras que líneas transgénicas de Arabidopsis 35S::AtCDF3 aumentan la tolerancia al estrés por
sequía, osmótico y bajas temperaturas en comparación con plantas wild-type (WT). Además, estas
plantas presentan un incremento en la tasa fotosintética y apertura estomática. El gen AtCDF3 se localiza
iv
Resumen
en el núcleo y que muestran una unión específica al ADN con diferente afinidad a secuencias diana y
presentan diversas capacidades de activación transcripcional en ensayos de protoplastos de Arabidopsis.
El dominio C-terminal de AtCDF3 es esencial para esta localización y su capacidad activación, la
delección de este dominio reduce la tolerancia a sequía en plantas transgénicas 35S::AtCDF3. Análisis
por microarray revelan que el AtCDF3 regula un set de genes involucrados en el metabolismo del carbono
y nitrógeno. Nuestros resultados demuestran que el gen AtCDF3 juega un doble papel en la regulación de
la respuesta a estrés por sequía y bajas temperaturas y en el control del tiempo de floración.
En el segundo capítulo de este trabajo se lleva a cabo la identificación de 34 genes Dof en tomate
que se pueden clasificar en base a homología de secuencia en cuatro grupos A-D, similares a los
descritos en Arabidopsis. Dentro del grupo D se han identificado cinco genes DOF que presentan
características similares a los Cycling Dof Factors (CDFs) de Arabidopsis. Estos genes son considerados
ortólogos de Arabidopsis CDF1-5, y han sido nombrados como Solanum lycopersicum CDFs o SlCDFs.
Los SlCDF1-5 son proteínas nucleares que muestran una unión específica al ADN con diferente afinidad
a secuencias diana y presentan diversas capacidades de activación transcripcional in vivo. Análisis de
expresión de los genes SlCDF1-5 muestran diferentes patrones de expresión durante el día y son
inducidos de forma diferente en respuesta a estrés osmótico, salino, y de altas y bajas temperaturas.
Plantas de Arabidopsis que sobre-expresan SlCDF1 y SlCDF3 muestran un incremento de la tolerancia a
la sequía y salinidad. Además, de la expresión de varios genes de respuesta estrés como AtCOR15,
AtRD29A y AtERD10, son expresados de forma diferente en estas líneas. La sobre-expresión de SlCDF3
en Arabidopsis promueve un retardo en el tiempo de floración a través de la modulación de la expresión
de genes que controlan la floración como CONSTANS (CO) y FLOWERING LOCUS T (FT). En general,
nuestros datos demuestran que los SlCDFs están asociados a funciones aun no descritas, relacionadas
con la tolerancia a estrés abiótico y el control del tiempo de floración a través de la regulación de genes
específicos
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particulares.
Summary
SUMMARY
Tomato (Solanum lycopersicum L.) is one of the horticultural crops of major economic importance
in the Spanish territory. However, its production is being affected by adverse environmental conditions
such as salinity, drought and extreme temperatures. To resolve the problems triggered by stress
conditions, a number of agricultural techniques that reduce the negative effects of stress are being
frequently applied. However, the development of stress tolerant varieties is of a great interest. In this
direction, the technological progress in obtaining and analysis of transgenic plants facilitated the study and
evaluation of selected genes in relation to stress tolerance. Recent studies have shown that a use of
regulatory genes such as transcription factors (TFs) is a great tool to obtain new tomato varieties with
greater tolerance to abiotic stresses. The DOF (DNA binding with One Finger) proteins form a family of
plant-specific TFs (Yangisawa, 2002) that are involved in the regulation of particular plant processes such
as nitrogen assimilation, photosynthetic carbon fixation, seed germination, secondary metabolism and
flowering time bur their precise roles in abiotic stress tolerance are largely unknown.
The work described in this thesis aims at the study of the DOF type regulatory genes to increase
tolerance to abiotic stress in both model species and the tomato. In the first chapter of this thesis, we
present molecular characterization of the Arabidopsis CDF3 gene as well as its role in the response to
abiotic stress and in other developmental processes. AtCDF3 is highly induced by drought, extreme
temperatures, salt and abscisic acid (ABA) treatments. The cdf3-1 T-DNA insertion mutant was more
sensitive to drought and low temperature stresses, whereas the AtCDF3 overexpression enhanced the
tolerance of transgenic plants to drought, cold and osmotic stress comparing to the wild-type (WT) plants.
In addition, these plants exhibit increased photosynthesis rates and stomatal aperture. AtCDF3 is localized
in the nuclear region, displays specific binding to the canonical DNA target sequences and has a
transcriptional activation activity in Arabidopsis protoplast assays. In addition, the C-terminal domain of
AtCDF3 is essential for its localization and activation capabilities and the deletion of this domain
significantly reduces the tolerance to drought in transgenic 35S::AtCDF3 overexpressing plants.
Microarray analysis revealed that AtCDF3 regulated a set of genes involved in nitrogen and carbon
vi
Summary
metabolism. Our results demonstrate that AtCDF3 plays dual roles in regulating plant responses to
drought and low temperature stress and in control of flowering time in vegetative tissues.
In the second chapter this work, we carried out to identification of 34 tomato DOF genes that were
classified by sequence similarity into four groups A-D, similar to the situation in Arabidopsis. In the D
group we have identified five DOF genes that show similar characteristics to the Cycling Dof Factors
(CDFs) of Arabidopsis. These genes were considered orthologous to the Arabidopsis CDF1 - 5 and were
named Solanum lycopersicum CDFs or SlCDFs. SlCDF1-5 are nuclear proteins that display specific
binding to canonical DNA target sequences and have transcriptional activation capacities in vivo.
Expression analysis of SlCDF1-5 genes showed distinct diurnal expression patterns and were differentially
induced in response to osmotic, salt and low and high temperature stresses. Arabidopsis plants
overexpressing SlCDF1 and SlCDF3 showed increased drought and salt tolerance. In addition, various
stress-responsive genes, such as AtCOR15, AtRD29A and AtERD10, were expressed differently in these
lines. The overexpression of SlCDF3 in Arabidopsis also results in the late flowering phenotype through
the modulation of the expression of flowering control genes such CONSTANS (CO) and FLOWERING
LOCUS T (FT). Overall, our data connet SlCDFs to undescribed functions related to abiotic stress
tolerance and flowering time through the regulation of specific target genes and an increase in particular
metabolites.
Director.
Director.
Dr. Joaquín MedinaAlcázar
Profesor. Jesús Vicente-Carbajosa
Alba Rocío Corrales Ducuara
vii
Abreviaturas
ABREVIATURAS
%: Porcentaje
3-AT: 3-aminotriazol.
ABA: Ácido abscísico.
aa: Amino acidos
ABRE: ABA responsive element - Elemento de respuesta a ABA.
bp: Pares de bases.
bZip: Basic Leucine Zipper
CaMV: Cauliflower mosaic virus – Virus del mosaico de la coliflor.
CDF1: Cyclin Dof Factor 1
CO: Constans
COR: COLD REGULATED
CRE: cis-regulatory element- Elemento regulador en cis.
DL: Día largo
DC: Día corto
DOF: DNA binding with one finger- Unión a DNA con un dedo de Zinc.
DRE: Dehydration-responsive element- Elemento de respuesta a deshidratación
ELF3: EARLY FLOWERING 3
FAO: Food and Agriculture Organization- Organización para la Alimentación y la Agricultura.
FKF1: (Flavin-binding, Kelch repeat, F-box-1)
GABA: γ-amino butírico
GI: GIGANTEA
DAG: DOF Affecting Germination
genes R: Genes de resistencia
GUS: β-Glucoronidasa
HMG: High Mobility Group
Ha: Hectáreas
LI: Línea de Introgresión
OBP1: OBF- binding factor-1
PSII: Fotosistema II
PEPC: C4 Fosfo-Enol-Piruvato-Carboxilasa
viii
Abreviaturas
PK: Piruvato quinas
QTLs: Quantitative trait loci.
ROS: Especies reactivas de oxígeno.
RT-qPCR: Real Time Quantitative PCR-PCR cuantitativa a tiempo real.
Rubisco: (Ribulosa-1,5-bifosfato)
RD29A: RESPONSIVE TO DEHYDRATION 29A
TF: Transcription Factor- Factor de Transcripción
Tn: Toneladas
WT: Wild type-Fenotipo Silvestre
Y1H: Hibrido de levadura
ix
1
INTRODUCCIÓN GENERAL
Introducción General
1.1.- EL TOMATE, Solanum lycopersicum L.
1.1.1.- Origen, taxonomía y morfología.
El tomate (Solanum lycopersicum L.) es una especie perteneciente a la familia de las solanáceas
al igual que la patata y el pimiento. El centro de origen del género Solanum, es la región andina que
incluye partes de Colombia, Ecuador, Perú, Bolivia y Chile (Nuez y Prohens, 2008). El lugar donde se
produjo su domesticación ha sido motivo de controversia. Sin embargo, antes de su introducción en
Europa y Asia ya presentaba un cierto grado de domesticación caracterizado por la forma, acostillado,
tamaño y color de los frutos (Nuez, 1995).
La introducción y difusión del tomate en Europa data del siglo XVI, pero hasta el siglo XVII no
presentó un incremento en su producción y consumo en Italia y la Península Ibérica (Nuez y Prohens,
2008). Comerciantes españoles y portugueses difundieron el tomate por Oriente Medio, África y Filipinas
a través de sus colonias ultramarinas (Nuez, 1995), y a partir del comercio en estos países el tomate llego
a establecerse en China, Japón e India, permitiendo así difusión por Asia. El tomate, es una planta
dicotiledónea perteneciente a la familia Solanaceae. Esta gran familia está compuesta por 96 géneros y
más de 2800 especies distribuidas en tres subfamilias Solanoideae (en la cual se encuentra el género
Solanum), Cestroideae y Solanineae (Foolad, 2007) su taxonomía aceptada es:
REINO:
Plantae
Subreino:
Traqueobinta
Superdivisión:
Spermatophyta
Clase:
Magnoliopsida
Subclase:
Asteridae
Orden:
Solanales
Suborden:
Solanineae
Familia:
Solanaceae
Subfamilia:
Solanoideae
Género:
Solanum
Especie:
lycopersicum
1
Introducción General
En la primera clasificación taxonómica, el tomate cultivado fue llamado Solanum lycopersicum por
Linnaeus (1953). En 1754, Miller designo el género Lycopersicon y la especie esculentum para el tomate
cultivado, esto ayudó a que el tomate fuera aceptado como alimento de consumo. La distinción entre el
género Lycopersicon y el Solanum, se basó inicialmente en caracteres diferenciales en hojas y anteras.
Así, en el género Lycopersicon su dehiscencia se produce en el lateral de las anteras y sus hojas son
generalmente pinadas. Mientras que en el género Solanum su dehiscencia se produce en el extremo de
las anteras y sus hojas son simples. Relaciones filogenéticas entre los géneros Lycopersicon y Solanum
han sido tema de debate a lo largo del tiempo algunos investigadores sugieren que Lycopersicon es un
género distinto, mientras que otros argumentan que este debía estar unido al Solanum. Así, basados en
estudios moleculares y morfológicos, se ha re adoptado el nombre Solanum lycopersicum para el tomate
cultivado (Foolad, 2007). Así mismo, otras especies del género Lycopersicon han sido asignadas al
Solanum.
El tomate es una planta perenne de porte arbustivo que se cultiva como anual, puede
desarrollarse de forma rastrera, semierecta o erecta, su crecimiento puede ser limitado en algunas
variedades determinadas e ilimitado en variedades indeterminadas (Figura 1.1A). Su sistema radicular,
está constituido por la raíz principal, las raíces segundarias y las raíces adventicias. El tallo principal es
un eje de 2-4 cm de grosor en su base, sobre el que se desarrollan los tallos secundarios (ramificación
simpodial). La hoja es compuesta e imparipinnada con foliolos peciolados y lobulados con bordes
dentados y recubierta de pelos glandulares. Una hoja típica de tomate cultivado tiene aproximadamente
0,5 m de largo con un gran foliolo terminal y varios foliolos laterales (Figura 1.1B). La flor de tomate es
regular e hipógina y consta de 5 ó más sépalos y pétalos dispuestos de forma helicoidal. Los estambres
que se alternan con los pétalos forman un cono estaminal que envuelve el gineceo (con un ovario bi o
plurilocular) (Figura 1.1C). Las flores se agrupan en inflorescencias de tipo racimoso unidas al eje floral
por un pedicelo articulado que contiene la zona de abscisión (Nuez, 1995) (Figura 1.1D). El número de
flores en cada inflorescencia depende de factores ambientales como la temperatura (Rost, 1996).
2
Introducción General
A
B
C
D
E
F
G
Figura 1.1. Características generales de la planta de tomate (Solanum lycopersicum L.) A) Planta entera, B) Hoja, C) Flor,
D) Inflorescencia, E) Fruto bilocular, F) Fruto plurilocular, G) Fruto adulto. Adaptado de C.M Jones
http://tgrc.ucdavis.edu/Data/Acc/taxon_images.aspx.
El fruto de tomate es una baya bi o plurilocular que se desarrolla a partir de un ovario
aproximadamente de unos 5-10mg (Figura 1.1 E-F). Un fruto adulto está constituido por: pericarpo, que
se compone de pared externa, pared interna y paredes radiales, tejido placentario y semillas (Figura
1.1G). El desarrollo del fruto tarda aproximadamente de 7 a 9 semanas en función del cultivar, la posición
en el racimo y las condiciones ambientales. El crecimiento del fruto se ajusta a una curva sigmoide simple
que se divide en tres periodos (Nuez, 1995; Cuartero y Muñoz., 1999):
i.
El primer periodo, denominado crecimiento lento, puede durar 2 ó 3 semanas y se
produce fundamentalmente por división celular. La transición del primer periodo al
segundo requiere una estimulación hormonal que es normalmente provista por el
crecimiento del tubo polínico y la fertilización del ovulo.
ii.
El segundo periodo, de crecimiento rápido, dura entre 3-5 semanas prolongándose hasta
el inicio de la maduración. En esta etapa el crecimiento de fruto se produce por aumento
del tamaño de las células preformadas. El tamaño de las vacuolas también aumenta y se
3
Introducción General
produce una acumulación de almidón, ácidos orgánicos y otros componentes que darán
características al fruto maduro.
iii.
Por último, un periodo de crecimiento lento que se extiende durante 2 semanas y en el
que no hay un aumento significativo del tamaño del fruto pero por el contrario se
producen los cambios metabólicos propios de la maduración. El tamaño del fruto está
estrechamente correlacionado con el número de semillas y el número de lóculos.
1.1.2.- El tomate como planta modelo.
El tomate es considerado un buen sistema modelo para estudios genómicos y de desarrollo del
fruto, por su facilidad de cultivo bajo un amplio rango de condiciones medioambientales, ciclo de vida
corto, elevado potencial reproductivo, fácil polinización y propagación vegetativa (Foolad, 2007). Además,
su uso en investigación está ampliamente aceptado por ser una especie diploide, con 2n=2x=24
cromosomas, con un genoma relativamente pequeño (950 Mbp) del cual un 75% corresponde a
heterocromatina, en cambio una gran proporción de genes se agrupan en grandes regiones eucromáticas
que se localizan en las regiones distales de los brazos cromosómicos (220 Mb). Esta característica
permitió la estrategia de secuenciamiento solo de regiones eucromáticas, para cubrir la mayor parte del
genoma (Mueller y col., 2005). En el año 2012, la iniciativa de secuenciación del genoma de tomate
completo la secuenciación de la línea LA1589 de Solanum pimpinellifolium L. dentro del Proyecto
Internacional del Secuenciamiento del Genoma del Tomate (SOL) (The tomato genome consortium 2012).
Estudios recientes han demostrado que la base para obtener el tomate moderno ha sido a partir
de los diferentes procesos de domesticación. Análisis evolutivo de 333 accesiones de tomate (S.
pimpinellifolium, S. lycopersium var. cerasiforme y S. lycopersicum), que representan varios orígenes
geografícos, tipos de consumo y especies mejoradas. Al igual que 10 accesiones de especies wild-type
(WT), incluyendo algunas donadoras de genes de resistencia (genes R) a enfermedades y 17 híbridos
comerciales modernos (F1). Demuestran que la domesticación y la mejora del cultivo de tomate, se ha
4
Introducción General
enfocado sobre dos grupos independientes de QTLs (Quantitative trait locus), que han permitido obtener
un cultivar ~100 veces más grande en comparción con su ancestro (Lin y col., 2014). De esta manera, la
domesticación y mejora ha incrementado la productividad del cultivo de tomate, pero ha disminuido su
base genetica. En la actualidad, se han realizado introgresiones de genes R de especies WT en cultivares
comerciales. Un ejemplo de ello es la introgresión del gen Tm-2a de Solanum peruvianum L. (PI 128650)
sobre el cromosoma 9 (51.7-54.7 Mb) de tomate, este gen confiere resistencia al Virus del mosaico del
tomate (Tomato mosaic virus; ToMV) (Tanksley y col., 1998). Por otra parte, otras dos grandes
introgresiones sobre el cromosoma 6 de tomate han sido importantes para la tolerancia a patógenos. La
introgresión del gen Mi-1 de S.peruvianum L. (PI 128657) que confiere resistencia a nematodos, y el gen
Ty-1 de Solanum chilense L. (LA1969) que conlleva resistencia al Virus del rizado amarillo del tomate
(Tomato yellow leaf curl virus; TYLCV) han sido útiles para aumentar la resistencia a plagas y
enfermedades. Ambas introgresiones ocupan la misma región genómica, impidiendo la recombinación de
ambos genes en un mismo cultivar. Otros estudios con diferentes líneas de introgresión (LIs) de Solanum
pennelli y Solanum lycopersicum cv. M82 han identificado genes candidatos para la tolerancia a estrés
abiótico y han proporcionado evidencia que son elementos transportables y presentan un rol en la
evolución de estas características (Bolger y col., 2014). Sin embargo, son pocas las variedades
comerciales que se conocen hasta en momento que responden eficazmente en la tolerancia a estrés
abiótico.
1.2.- Importancia económica del tomate.
1.2.1.- Importancia económica en el mundo.
El tomate, es el segundo cultivo vegetal más importante en el mundo después de la patata
(Solanum tuberosum L.) en términos de consumo per cápita (Pandey y col., 2011). En las últimas
décadas, la producción de tomate (fresco y cultivado) se ha incrementado alrededor de un 300% (Costa y
Heuvelink, 2005).
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Según datos de la FAO (Food and Agriculture Organization of the United Nations, www.fao.org),
en el año 2012 la producción mundial de tomate alcanzó 161,7 millones de toneladas (Tn) con un
superficie cultivada de más de 4,8 millones de ha. Los países con mayor producción en Tn a nivel
mundial fueron: China (50 millones) seguido por India (17 millones), Estados Unidos (13 millones),
Turquía (11 millones) y Egipto (8 millones). España ocupa el noveno lugar a nivel mundial con 4,0
Millones de Tn
millones de Tn al año y un área de 48.800 ha (FAOSTAT, 2012; Figura 1.2).
50000000
45000000
40000000
35000000
30000000
25000000
20000000
15000000
10000000
5000000
0
*
Figura 1.2. Producción mundial de tomate. Ranking de los principales países productores en el mundo en millones
de (Tn) (FAOSTAT, 2012).
En Europa, la producción de tomate está dividida en dos grandes sistemas. En el norte el sistema
de producción es intensivo bajo invernadero para obtener grandes cosechas de tomate fresco. Por otra
parte, en el Mediterráneo el sistema de producción está enfocado en zonas abiertas para el tomate
procesado y bajo estructuras cubiertas para el tomate fresco (Harvey y col, 2002).
1.2.2.- Importancia económica del tomate en España.
El tomate es un producto básico de la horticultura Española, ocupa el 14% de la superficie de
cultivo y aporta un 23% del valor de la producción del sector (Nuez, 1995). Entre los países productores
6
Introducción General
europeos, España es el segundo después de Italia (Tabla 1.1). Sin embargo, a diferencia de la situación
italiana, gran parte de la producción española se dedica al mercado fresco (Pazos, 2003). En el territorio
Español, el tomate es uno de los cultivos hortícolas de mayor producción. Según el Anuario de
Estadística Agraria (2011), el 65 % de la superficie cultivada es de cosecha al aire libre y el resto bajo
invernadero.
Tabla 1.1 Producción, superficie y rendimiento de los principales países productores de la Unión Europea
en 2012 (FAOSTAT, 2012).
Países
Producción (Tn)
Superficie (ha)
Rto (Kg/ha)
España
4.007.000
48.800
821,106.56
Italia
5.131.977
91.850
558,734.57
Francia
588.660
6.369
924,258.13
Grecia
979.600
16.000
612,250
Portugal
1.392.700
15.400
904,350.65
Total UE
15.133.447
506.583
408.493.57
En la actualidad, las provincias con mayor producción son: Extremadura (1.275.368 Tn), Almería
(892.510 Tn) y Murcia (311.065 Tn), que en los últimos años han emergido como una competitiva e
importante área en la producción y exportación de tomate fresco bajo invernadero (Costa y Heuvelink.,
2005).
1.2.3.- Impacto del estrés abiótico en el cultivo de tomate.
Como se ha mencionado anteriormente, el tomate (S. lycopersicum L.) es el segundo cultivo
hortícola más importante del mundo después de la patata (S. tuberosum L.). Sin embargo, su
productividad está influenciada por diferentes tipos de estrés abiótico (Pandey y col., 2011). El tomate
puede adaptarse a casi a todos los climas y regiones del mundo, su crecimiento y desarrollo es sensible
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Introducción General
a diferentes estreses medioambientales como: salinidad, sequía, temperaturas extremas y polución
ambiental (Foolad, 2005).
Entre los diferentes tipos de estrés abiótico que afectan la producción de tomate, el déficit hídrico o
estrés por sequía es el factor más devastador (Boyer, 1982). Las pérdidas en la producción agrícola a
causa de la sequía exceden a las producidas por otras causas, creando graves problemas a la tercera
parte de las áreas cultivables en el mundo (Blum, 1998; Kramer, 1980; Schonfeld y col., 1988; Foolad
2005; Bruce y col., 2002). España es uno de los países afectados por el fenómeno de la sequía; durante
el periodo de 1880-2000 más de la mitad de los años se han calificado como secos o muy secos. El
estrés por sequía afecta a todo el territorio español, aunque las zonas donde las precipitaciones anuales
no superan los 600mm como Andalucía, son los que sufren en mayor medida sus efectos.
La necesidad de agua en el cultivo de tomate varía en función de su estado de desarrollo. Al
principio del cultivo, la masa vegetal es muy pequeña y el consumo de agua es mínimo. Sin embargo,
este incrementa paulatinamente hasta el inicio del cuajado. Durante el cuajado del tomate las
necesidades hídricas aumentan considerablemente debido que la planta sigue produciendo hojas y tallos
nuevos, a la vez que van creciendo los frutos. En el periodo de maduración, las necesidades de agua
disminuyen (en variedades con floración y fructificación agrupadas) (Cuartero y col., 1995). Así, el tomate
de industria puede dejarse de regar cuando se tiene un 29-30% del fruto maduro sin que la cosecha
disminuya (Cuartero y col., 1995).
El crecimiento y desarrollo de la planta depende en gran parte de la absorción de agua que realice
el sistema radicular. La planta de tomate responde al estrés hídrico aumentando la relación raíz/parte
aérea; plantas cultivadas con déficit hídrico reducen su sistema radicular en comparación con plantas
cultivadas en condiciones control, pero en un grado menor que la reducción del desarrollo de la parte
aérea, (Brouwer, 1981). Una de las causas de este crecimiento diferencial reside en que la distribución de
agua en el suelo no es homogénea. El contenido de agua en el suelo repercute en la distribución del
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Introducción General
sistema radicular haciéndolo más profundo en el caso de presentarse déficit o más superficial cuando el
potencial hídrico del suelo es cercano a cero (Bierhuizen, 1981; Cuartero y col., 1995). Un bajo potencial
hídrico afecta a la expansión y división celular (Kirkham y col., 1991) afectando directamente al desarrollo
del fruto. Además, el déficit hídrico provoca cambios en el tamaño del fruto a corto plazo. Estudios
realizados por Johnson y colaboradores (1992), han demostrado que el diámetro del fruto puede
aumentar o disminuir según el sentido del gradiente de déficit hídrico entre el tallo y el fruto. Teniendo en
cuenta que el potencial hídrico del fruto permanece relativamente constante, las variaciones en el
potencial hídrico del tallo durante el día explican el aumento o disminución del diámetro del fruto.
Por otra parte, la salinidad es otro de los mayores estreses abióticos que afectan a la
productividad de cultivos en el mundo (Munns y Tester 2008; Peleg y col., 2012; Apse y Blumwald, 2002;
Foolad, 2004). Diferentes cultivos de interés agronómico incluido el tomate, S. lycopersicum son sensibles
a la salinidad (Foolad, 2004; Passam y col., 2007). Una alta salinidad en la zona radicular de la planta
impide un adecuado crecimiento y desarrollo, dando lugar a una reducción o pérdida total de la cosecha.
Según Foolad (2004), de los 14 billones de ha disponibles sobre la tierra, se estima que 6,5 billones de ha
pertenecen a regiones áridas y semiáridas y a su vez 1 billón son suelos salinos. Aproximadamente, el
22% de la tierra agrícola es salina (FAO, 2004) con un incremento de la tasa salinización del 10% por
año (Foolad, 2005). El problema de la salinidad en España es especialmente importante en sistemas
cerrados del sureste peninsular. La escasa disponibilidad de agua de óptima calidad y la búsqueda de la
misma origina altos costes de producción que afectan a la rentabilidad del cultivo. Algunos cultivares de
tomate son moderadamente sensibles a la salinidad en todos los estados de desarrollo de la planta
incluyendo: germinación de semilla, crecimiento vegetativo y crecimiento reproductivo (Jones y col., 1988;
Maas, 1986; Mass, 1990; Bolarin y col., 1993).
La salinidad del suelo se relaciona con un exceso de entre 0.20 y 0.25% de sodio, calcio,
magnesio, cloratos, sulfatos o carbonatos (Pandey y col., 2011). Se considera que un suelo es salino
cuando la conductividad eléctrica (CE) del extracto de saturación en la zona radicular excede 4 dSm -1 a
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Introducción General
25ºC (Foolad, 2004; FAO: Rome 2005). En la raíz, el estrés salino genera cambios en el crecimiento,
morfología y fisiología modificando así la absorción de agua e iones y la producción de moléculas
señalizadoras (hormonas). La salinidad produce un efecto negativo en la cantidad de biomasa. Una de las
razones por la que el crecimiento de la raíz se reduce en condiciones de estrés salino es que presenta
una disminución del crecimiento celular causada por: el bajo potencial de agua del medio externo, la
interferencia de iones salinos con los nutrientes esenciales o la toxicidad debida a la acumulación de
iones que conducen a la muerte celular. Además, la salinidad disminuye el crecimiento de los brotes de
tomate y causa una disminución del área foliar. La reducción en la tasa de crecimiento de la hoja está
relacionada con una reducción de la turgencia celular y de la tasa fotosintética (Cuartero y Muñoz., 1999).
Niveles de salinidad iguales o superiores de 8ds/m afectan el número de frutos por planta. La disminución
del número de frutos podría ser debido a la reducción del número de flores y/o del cuajado de las mismas,
que a su vez puede deberse a una disminución de la cantidad y/o fertilidad del polen (Cuartero y col.,
1995). El tamaño del fruto también se ve afectado por la salinidad ya que esto limita el transporte de agua
hacia el fruto produciendo un aumento de la tasa de acumulación de materia seca (Johnson y col., 1992).
En condiciones de salinidad (CE= 3-9 dSm-1) la reducción del tamaño del fruto es la principal causa de la
disminución de la producción (Van-Ieperen, 1996).
Por otra parte, el tomate es una planta termo-periódica (Went, 1994), requiere fluctuaciones de
temperatura entre el día y la noche. Se estiman como óptimas las diferencias térmicas noche/día de 67ºC (Verter, 1957). A su vez, las temperaturas óptimas están relacionadas con la iluminación (Calvert y
Slack, 1975). En condiciones mediterráneas, temperaturas diurnas de 21ºC a 27ºC (según radiación) y
nocturnas de 12ºC -15ºC se consideran las adecuadas para el cultivo (Brun y Lagier, 1984). El tomate es
altamente sensible al estrés por bajas temperaturas o chilling ya que en esas condiciones se produce una
inhibición de la germinación de semillas y del desarrollo reproductivo causando transformaciones
homeóticas florales (Lozano, 1998). Las bajas temperaturas afectan al desarrollo del fruto, pero la
temperatura mínima a la que planta sufre daño es difícil de precisar, debido a que depende del estado de
desarrollo de la planta, de su potencial hídrico y de la condición hídrica del suelo. Temperaturas alrededor
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Introducción General
de 1ºC producen síntomas de heladas en hojas (Cuartero, 1995), sin embargo, no es el principal
problema. Las fases más sensibles al frío son la germinación de la semilla y el cuajado del fruto, esta
última debida principalmente a una disminución de la fertilidad del polen y a una dificultad en la
dehiscencia de las anteras (Cuartero y col., 1995; Cuartero y Fernández-Muñoz, 1999).
1.3.- ESTRÉS ABIÓTICO.
1.3.1.- Generalidades del estrés abiótico en plantas.
Las plantas durante su desarrollo se enfrentan a condiciones ambientales adversas que afectan
negativamente a su crecimiento y productividad (Screenivasulu y col., 2007; Seki y col., 2007). El estrés
abiótico es la principal causa de las pérdidas de cultivos en el mundo, reduciendo su rendimiento en más
de un 50% (Bray y col., 2000), lo que supone pérdidas de cientos de millones de dólares cada año. En
términos generales los estreses abióticos más comunes son: salinidad, sequía, bajas y altas
temperaturas. La disminución de la disponibilidad de agua y las condiciones ambientales adversas,
sumado al incremento de la población humana están produciendo serios cambios en la agricultura
mundial (Mittler y Blumwald, 2010; Peleg y col., 2012). Recientes estudios han mostrado que para el año
2050 la población mundial necesitara un aumento de entre 70 a 100% más de alimento (World
Development Report 2008) principalmente en cultivos como: arroz (Oryza sativa L.), trigo (Triticum
aestivum L.) y maíz (Zea mays L.) (Godfray y col., 2010). Este incremento de la población mundial
aumenta la necesidad de producir estos cultivos en áreas donde las condiciones climáticas adversas son
un factor limitante (Pennisi, 2008; Nakashima y col., 2014).
Las plantas responden y se adaptan al estrés abiótico a través de mecanismos bioquímicos,
moleculares y fisiológicos que permiten su desarrollo y supervivencia (Munns, 2002; Chaves y col., 2003;
Osakabe y col., 2013; Yamaguchi-Shinozaki y Shinozaki, 2005). Las respuestas a uno o más estreses
varían dependiendo de la especie y el genotipo. Sin embargo, la respuesta al estrés también depende de
11
Introducción General
la duración y severidad del evento, así como de la edad y del estado de desarrollo de la planta cuando se
impone el estrés (Bray, 1997). En plantas de cultivo, la sensibilidad/tolerancia al estrés abiótico es
determinada por la pérdida de la cosecha y la tasa de supervivencia (Peleg y col., 2012). Además, en
respuesta a estos estreses un número determinado de genes son altamente regulados, mitigando los
efectos del estrés y ajustando el entorno celular y la tolerancia de la planta (Mahajan y col., 2005).
Entre los diferentes tipos de estrés abiótico, la salinidad, la sequía y las bajas temperaturas son de
las principales causas que limitan la productividad de cultivos en el mundo (Boyer, 1982; Araus y col.,
2008; Munns y Tester, 2008). Investigaciones previas, han estudiado los diferentes mecanismos de
respuesta a estrés tanto en sistemas modelo, particularmente Arabidopsis thaliana, como en cultivos de
interés agronómico. Esto ha sido un punto de partida para el desarrollo de nuevas aproximaciones
biotecnológicas de mejora genética, que permitan desarrollar nuevas variedades con mayor producción
bajo condiciones de estrés abiótico.
1.3.2.- Efectos de la salinidad, las bajas temperaturas y la sequía sobre el crecimiento
de la planta.
La exposición de las plantas a estreses medioambientales como salinidad, sequía y bajas
temperaturas causan efectos adversos sobre el crecimiento de plantas y la productividad de cultivos.
Estos efectos adversos se deben a alteraciones morfológicas y fisiológicas, a partir de cambios en
procesos como la división celular y el metabolismo incluyendo fotosíntesis (Saibo y col., 2009). Las
condiciones medioambientales pueden afectar a mecanismos específicos. La salinidad afecta a procesos
como el crecimiento, la fotosíntesis, la síntesis de proteínas, y el metabolismo de lípidos. Además, causa
efectos hiperosmóticos e hiperiónicos que producen la muerte de la planta. La fase inicial del estrés
salino es atribuida a un choque osmótico, similar al estrés causado por exceso de agua, y que es
probablemente constituida por un fuerte ajuste osmótico. La segunda fase presenta un periodo más
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Introducción General
extenso en la que se produce toxicidad por iones debido a su acumulación. Además, la salinidad causa
problemas a nivel celular: i) alteración del equilibrio iónico, influenciado por la dispersión de Na+; ii)
toxicidad de Na+ sobre el metabolismo celular, ya que tiene un efecto deletéreo sobre el funcionamiento
de algunas enzimas (Niu y col., 1995); iii) alta concentración de Na +, causa desbalance osmótico,
desorganización de membrana, reducción en el crecimiento e inhibición de la expansión celular,
reducción de la fotosíntesis y producción de especies reactivas de oxigeno (ROS) (Peleg y col., 2012;
Yeo, 1998). Por último, la salinidad causa efectos significativos sobre el desarrollo, reducción en el
tamaño de brotes, altura de la planta, número de hojas por planta y longitud de la raíz (Mohammad y col.,
1998).
Muy diferentes son los efectos observados en respuesta a bajas temperaturas como por ejemplo:
reducción en la expansión de la hoja, marchitamiento, clorosis y necrosis. El estrés por bajas
temperaturas afecta al desarrollo reproductivo en el momento de la antesis, produciendo esterilidad en las
flores. Además, produce daños a nivel de membrana (Steponkus y col., 1984, 1993), causa principal de
una fuerte deshidratación asociada al frío (Mahajan y Tuteja, 2005). Por otra parte, el estrés por bajas
temperaturas induce un número de alteraciones en los componentes celulares incluyendo, ácidos grasos
insaturados (Crossins, 1994), glicerolípidos (Lynch y Thompsom, 1982), cambios en la composición de
carbohidratos y proteínas, activación de canales de iones (Knight, 1996) y acumulación de sacarosa y
otros azúcares simples que se generan con la aclimatación al frío y también contribuyen a la
estabilización de la membrana (Mahajan y Tuteja, 2005).
En cuanto a los efectos causados por déficit hídrico o estrés por sequía, se presentan cambios
fisiológicos y bioquímicos a nivel celular que incluyen, perdida de turgencia, cambios en la composición y
fluidez de membrana y cambios en la concentración de solutos (Chaves y col., 2003). El estrés por sequía
causa reducción en la actividad fotosintética por la disminución en la actividad de las enzimas
fotosintéticas, acumulación de ácidos orgánicos, osmolitos y cambios en el metabolismo de
carbohidratos. Estas moléculas que regulan el balance osmótico se acumulan en las células de la planta
en respuesta al estrés y posteriormente son degradadas (Valliyodan y Nguyen, 2006; Tabaeizadeh,
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Introducción General
1998). Otros efectos fisiológicos de la sequía sobre la planta es la reducción del crecimiento, en
particular, el crecimiento de brotes, debido a una disminución de la actividad de las quinasas
dependientes de ciclinas (CDK) que causa reducción de la división celular (Shuppler y col., 1998). Por
otra parte, el crecimiento de hojas es más sensible que el crecimiento de raíz. La reducción de la
expansión de la hoja es beneficiosa para la planta bajo condiciones de déficit hídrico, debido a que se
produce una reducción de la transpiración.
En último término, la sequía, la salinidad y las bajas temperaturas son limitaciones
medioambientales que disminuyen la eficiencia fotosintética y afectan al crecimiento y a la productividad
de plantas. Estos estreses interfieren con la fotosíntesis en diferentes puntos: difusión de CO 2, eficiencia
del PSII, transporte electrónico, formación de ROS, contenido de ribulosa-1,5-bifosfato (RuBP)
(dependiente de ATP y NADPH), actividad de la ribulosa-1,5-bifosfato carboxilasa/oxigenasa (Rubisco) y
foto respiración. También inducen el cierre de estomas (Wilkinson y col., 2001; Zhu, 2002; Chaves y col.,
2003), disminuyen la asimilación de CO2 y consecuentemente reducen la tasa fotosintética (Figura 1.3).
El control de la apertura estomatica es un proceso mediado por ABA y posiblemente por otras señales
generadas en respuesta a estrés abiotico. Tanto las bajas temperaturas como el deficit hidrico pueden,
por diferentes razones, disminuir la sintesis de RuBP que depende de las concentraciones de ATP y
NADPH y la actividad de las enzimas del ciclo de Calvin, reduciendo la fotosíntesis y la tasa de
asimilación de CO2 (Saibo y col., 2009). Cuando la planta es expuesta a estos estreses medioambientales
la disponibilidad de CO2 dentro de la hoja (Ci) es limitado y/o la síntesis de ATP disminuye, la actividad
del ciclo de Calvin es reducido pero el PSII permanece activo, por lo que la concentración del aceptor final
NADP+ es generalmente baja (Figura 1.3). Por otra parte, la inhibición de la fotosintesis, disfunción
metabolica y daño en las estructuras celulares, desencadena una inhibición en la expansión celular que
inhibe el crecimiento de la planta, acelerando el desarrollo y senescencia (Chinnusamy y col., 2006;
Krasensky y Jonak, 2012; Mahajan y Tuteja, 2005). Bajo estos efectos, una disminución del cultivo es
debido a una senscencia prematura en los diferentes tejidos de la planta ya que reducen el crecimiento y
así el número los frutos (Albacete y col., 2014).
14
Introducción General
1.3.3.- Respuesta de la planta a la salinidad, las bajas temperaturas y la sequía.
Las plantas desarrollan una amplia variedad de mecanismos de respuesta y adaptación a los
cambios medioambientales. Estos desencadenan múltiples mecanismos a nivel fisiológico, bioquímico,
metabólico como molecular, que ayudan a mitigar los efectos impuestos por el estrés. Entender los
mecanismos de respuesta a estrés es de vital importancia para diseñar nuevas estrategias que permitan
mejorar la tolerancia de cultivos al estrés abiótico.
En respuesta a la salinidad las plantas desencadenan un ajuste osmótico crucial en la adaptación
a este estrés, debido a que permite mantener la turgencia y bajar el potencial hídrico, manteniendo la
actividad metabólica y activando el crecimiento cuando los niveles de sal disminuyen. La tolerancia a la
salinidad se produce cuando la planta tiene la habilidad de recuperarse del estrés osmótico y mantiene el
crecimiento y la fotosíntesis durante periodos prolongados. Las plantas toleran la salinidad del suelo a
partir de tres grandes mecanismos: la exclusión de Na+, tolerancia del tejido al Na+ y tolerancia osmótica
(Munns y Tester, 2008; Plett y Moller, 2010). Sin embargo, el impacto de cada uno de los mecanismos
varía dentro de cada especie y durante el ciclo de vida de la planta (Peleg y col., 2012). Por otra parte,
diferentes estudios han mostrado que Ca2+ juega un rol importante en la tolerancia a la salinidad. La
aplicación de Ca2+ de forma externa reduce los efectos tóxicos del NaCl. Una alta salinidad incrementa
los niveles de Ca2+ en el citosol que es transportado desde el apoplasto a los compartimentos
intracelulares (Knight y col., 1997).
Este incremento transitorio de Ca2+ en el citosol inicia la señal por el estrés y la transducción para
la adaptación al estrés. Una de las mayores consecuencias del estrés por NaCl es la perdida intracelular
de agua. Para contrarrestar esta pérdida de agua y proteger las proteínas celulares, las plantas acumulan
metabolitos conocidos como “solutos compatibles”. Estos no inhiben las reacciones metabólicas normales
(Ford y col., 1984). Entre los metabolitos observados que facilitan el ajuste osmótico se encuentran:
azúcares como fructosa, sacarosa, alcoholes y otros azúcares como trehalosa (Delauney y col., 1993).
15
Introducción General
Figura 1.3. Esquema de los mecanismos relacionados con la fotosíntesis que pueden ser afectados por la salinidad, la
sequía y las bajas temperaturas. Las flechas azules y marrónes corresponden a las señales por sequía, salinidad y bajas
temperaturas respectivamente. Condiciones ambientales adversas que causa estrés osmótico inducen cierre estomático,
limitando la tasa de asimilación de CO2. El ácido abscísico (ABA) está involucrado en la respuesta a salinidad y sequía y puede
mediar algunos efectos por bajas temperaturas. Las flechas gruesas representan la señal a la que contribuye. Las líneas
discontinuas representan las posibles interacciones. Fotosistemas I (PSI), Fotosistema (PSII), especies reactivas al oxigeno
(ROS), 3-fosofoglicerato (3PGA), ribulosa-1,5bifosfato (RuBP), fosfoglicolato (PG), factor de acoplamiento (FC), concentración
interna de CO2 (Ci), concentración de CO2 en el cloroplasto (Cc). Adaptado de Saibo y col., 2009.
La exposición de las plantas a las bajas temperaturas resulta en una serie de cambios fisiológicos
y bioquímicos. El primer cambio influye en la fluidez de la membrana celular y en la composición de
ácidos grasos (Murata y Los, 1997; Suzuki y col., 2001). Estos cambios producen un incremento del
contenido de lípidos poliinsaturados esenciales para la supervivencia de la planta cuando es sometida al
estrés, debido a los efectos negativos de las bajas temperaturas sobre los procesos metabólicos de la
membrana así como la respiración y fotosíntesis (Cossins, 1994). La exposición al frío también induce la
acumulación de otras proteínas que no están localizadas en las membranas celulares, y que en algunos
casos tienen un rol de protección (Bae y col., 2003; Gao y col., 2009). El contenido de azúcares también
16
Introducción General
es alterado en la planta en respuesta a bajas temperaturas. Diferentes estudios han encontrado una alta
correlación entre los niveles de azúcares y la tolerancia al frío en diferentes especies (Guy y col., 1992;
Sasaki y col., 1996; Sundblad y col., 2001). Finalmente, la exposición a bajas temperaturas desencadena
cambios estructurales en la planta, como modificaciones en la composición de la pared celular (Wei y col.,
2006)
La exposición de las plantas a una limitación de agua durante varios estadios del desarrollo
desencadena diferentes cambios fisiológicos durante su crecimiento. Estudios recientes han permitido
dilucidar los mecanismos de tolerancia a sequía en plantas, a través de aproximaciones moleculares y
genómicas con las que se han identificado un número determinado de genes que responden a la sequía a
nivel transcripcional (Seki y col., 2002; Guo y col., 2009). Las plantas responden rápidamente para
prevenir que la maquinaria fotosintética sufra daños irreversibles. La primera respuesta al déficit hídrico
es el cierre estomático para prevenir la perdida de agua por transpiración (Mansfield y col., 2005;
Osakabe y col, 2014). El ABA se acumula en el tejido de las plantas sometidas a estrés hídrico y
promueve la reducción de la transpiración vía cierre estomático. A través de estos mecanismos, las
plantas minimizan la perdida de agua y disminuyen el daño causado por el estrés (Mahajan y Tuteja,
2005). Bajo condiciones severas de sequía también se detecta una disminución de la actividad de la
enzima Rubisco. La actividad fotosintética mediada por la cadena de transporte electrónico es ajustada
por la disponibilidad de CO2 en la planta y en el fotosistema II (PSII), que disminuye en paralelo bajo
condiciones de sequía. Esto indica que la disminución en la tasa fotosintética bajo estrés por sequía es
debida principalmente por la deficiencia de CO2 (Loreto y col., 1995; Mahajan y Tuteja, 2005). Por otra
parte, las plantas superan el déficit hídrico a través del ajuste osmótico que producen determinados
procesos metabólicos. La acumulación de solutos en la célula derivado de estos procesos disminuyen el
potencial osmótico facilitando la resistencia a la deshidratación celular y manteniendo la turgencia de la
hoja (Ramanjulu y col., 2002; Mahajan y Tuteja, 2005). Estudios recientes han mostrado que la
acumulación de azúcares simples como glucosa y fructosa permiten un aumento en la actividad invertasa
en hojas de plantas sometidas al estrés por déficit hídrico (Pinhero y col., 2011).
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Introducción General
1.3.4.- Respuesta metabólica al estrés por salinidad, bajas temperaturas y sequía.
La amplia diversidad metabólica en plantas es producto de los continuos procesos de evolución.
En la actualidad, se conocen más de 200.000 metabolitos secundarios que participan en gran número de
funciones. Las condiciones ambientales afectan el crecimiento de la planta, y el metabolismo está
profundamente involucrado en la señalización y en la regulación fisiológica. El estrés abiótico afecta a la
biosíntesis, acumulación, transporte y almacenamiento de los metabolitos primarios y secundarios (Fraire
y Balderas, 2013). Uno de los mecanismos de defensa de las plantas frente al estrés abiótico es la
producción y acumulación de solutos compatibles. Entre los osmoprotectores de bajo peso molecular
producidos encontramos amino ácidos (asparagina, prolina y serina), aminas (poliaminas y glicinbetaina),
y ácido γ-amino butírico (GABA). Además, otros azúcares son producidos como: fructosa, sacarosa,
trehalosa, rafinosa, y polioles (myo-inositol, D-pinitol) (Krasensky y Jonak, 2012; Banu y col., 2010) y
otros grupos de antioxidantes como glutatión (GSH) y ascorbato que son acumulados en respuesta a
estrés oxidativo (Shabrawi y col., 2010; Phang y col., 2008).
Recientes estudios han mostrado que algunos solutos compatibles han sido conservados a lo largo de la
evolución (bacterias, plantas y algas) en respuesta a sequía. Análisis metabólicos con cromatografía de
gases-espectrometría de masas (CG-MS) confirman que el musgo Physcomitrella patens presenta una
acumulación de solutos compatibles en respuesta a sequía. En este estudio un grupo determinado de
metabolitos (maltitol, L-prolina, maltosa, isomaltosa y acido butírico) son diferencialmente afectados, y
presentan características similares a los reportados previamente en plantas de Arabidopsis sometidas a
déficit hídrico (Erxleben y col., 2012).
En respuesta a salinidad importantes rutas metabólicas están implicadas. Perfiles metabólicos
realizados en plantas de tabaco sometidas a varios tratamientos de salinidad (50mM de NaCl) han
mostrado una acumulación de sacarosa y fructosa vía gluconeogénesis en periodos cortos de
tratamiento. Sin embargo, a mayor concentración de sal (500mM de NaCl) durante periodos más largos
18
Introducción General
(días) los niveles de prolina, sacarosa y a su vez de glucosa y fructosa son elevados demostrando, que la
ruta de biosíntesis de azúcares y prolina son mecanismos metabólicos producidos en la respuesta a
salinidad en periodos de tiempo (cortos-lagos) (Zhang y col., 2001; Fraire y Balderas, 2013). Estos
estudios demuestran que la respuesta metabólica al estrés salino es variable y depende del género,
especie y cultivar.
1.3.5.- Respuesta metabólica al estrés por salinidad, bajas temperaturas y sequía en
tomate.
En tomate, la respuesta metabólica frente al estrés abiótico involucra una serie de adaptaciones
bioquímicas y fisiológicas, que ayudan a mitigar el efecto causado por el estrés. Diferentes compuestos
(prolina, azúcares solubles, azúcares alcoholes y compuestos de amonio cuaternario) son acumulados en
respuesta a sequía, salinidad y bajas temperaturas (Parvanova y col 2004; Gong y col., 2010). La
mayoría de estos, están involucrados en el metabolismo secundario y presentan algunas diferencias y
conexiones entre el los diferentes tipos de estrés abiótico (Gong y col., 2010).
Estudios realizados en plantas transgénicas de tabaco que sobreexpresan el gen ERD15 de S.
pinennelli han mostrado un incremento en la tolerancia a bajas temperaturas y sequía. Estas plantas
presentan un aumento en los contenidos de prolina y azúcares solubles. Además, muestran cambios en
el contenido de malondialdehido (MDA) un biomarcador del estrés oxidativo indicando que la sobreexpresión del SpERD15 en tabaco confiere una acumulación de solutos compatibles y aumenta la
estabilidad de membrana bajos diferentes tipos de estrés abiótico (Ziaf y col., 2011). Por otra parte, la
sobre-expresión de un FT zinc finger de tomate ZF2 incrementa los niveles de expresión de un grupo de
metabolitos secundarios involucrados en la biosíntesis de poliaminas, alcaloides y compuestos fenólicos
son cruciales para la adaptación a condiciones medioambientales, ya que mantienen la actividad
fotosintéticas y biosíntesis/señalización de hormonas (Hichri y col., 2014). Por último, Albacete y col.,
(2014), ha descrito que la interacción entre el metabolismo de la sacarosa y los factores hormonales
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Introducción General
(CKs, ABA, GA3 y etileno) es un factor clave en el esfuerzo fisiológico de la planta para mantener la
producción en condiciones de salinidad.
1.4.- REGULACIÓN DE LA EXPRESIÓN GÉNICA.
En organismos multicelulares, todas las células contienen en su secuencia de ADN la información
necesaria para hacer miles de proteínas diferentes y moléculas de ARN. Sin embargo, el patrón de
expresión de cada una de estas células puede ser muy distinto, debido a que pueden cambiar su modelo
de expresión en respuesta a cambios medioambientales, así como a señales de otras células. En
eucariotas, la expresión génica puede ser controlada a diferentes niveles o estados (Slater y col., 2008;
Alberts y col., 2008). Estos son clasificados en: i) remodelación de la cromatina, ii) regulación
transcripcional, en la que intervienen proteínas específicas denominadas factores de transcripción
generales, específicos y cofactores, iii) modificación nuclear de RNA, splicing y transporte, iv) traducción,
v) modificaciones post-traduccionales que afectan a la estructura y función de la proteína, vi) localización
de la proteína, vii) proteínas de recambio, y viii) recambio del RNA citoplasmático.
1.4.1.- Regulación de la transcripción.
El control transcripcional es uno de los mecanismos de regulación más importantes en todos los
organismos. La regulación de la expresión génica a nivel transcripcional controla muchos de los procesos
biológicos como: progresión a través del ciclo celular, balance metabólico y fisiológico y respuesta al
medio ambiente (Riechmann y col., 2000).
La transcripción de un gen inicia con la formación de un complejo de iniciación de la transcripción,
llamado complejo de pre-iniciación PIC (Pre-Initiation Complex). Este complejo se forma tras la unión de
la RNA- polimerasa II y el complejo FTIID (Factor de transcripción II D). El complejo FTIID está
compuesto por la proteína de unión a la caja TATA (TBP: TATA-box Binding Protein) y un número de
20
Introducción General
factores asociados y a este complejo de pre-iniciación se unen además otros factores transcripcionales
que interaccionan con secuencias específicas del promotor, llamados elementos reguladores en cis (CRE: Cis- Regulatory Elements). Estos elementos son secuencias cortas (5-10 pb) moduladas por otros
factores de transcripción (FTs) denominados co-reguladores ó co-factores que regulan la transcripción
interaccionando con el PIC o con los reguladores específicos que se unen al DNA, y pueden funcionar
como remodeladores de la cromatina (Jones y col., 2013)-
1.5.- FACTORES DE TRANSCRIPCIÓN EN PLANTAS.
Los FTs son proteínas que muestran secuencias específicas de unión al ADN, capaces de activar
y/o reprimir la transcripción de genes específicos y por lo tanto responsables de controlar los patrones
temporales y espaciales de la transcripción (Riechmann y col., 2000; Udvardi y col., 2007). En plantas, los
FTs son componentes esenciales en la regulación de algunos procesos de importancia agronómica tales
como rendimiento y respuesta a estrés biótico o abiótico (Hernando-Amado y col., 2012).
Un factor de transcripción típico de plantas contiene, con alguna excepción, una región de unión al
DNA, un sitio de oligomerización, un dominio de regulación de la transcripción y un dominio de
localización nuclear. Estos cuatro dominios estructurales son esenciales para su función (Liu y col., 1999;
Hernando-Amado y col., 2012):
i) Dominio de unión al DNA. Encargado de interactuar con los elementos reguladores en cis de
los promotores de genes diana y puede activar o reprimir su expresión. Este tipo de dominios
están muy conservados entre los FTs de una misma familia, hecho que sirve como criterio para
establecer la clasificación de los FTs.
ii) Dominio de localización nuclear (NLS: Nuclear Localization Signal). Este dominio es
necesario para el transporte de los FTs que se sintetizan en el citoplasma hacía el núcleo donde
llevan a cabo su función biológica.
21
Introducción General
iii)
Dominio de regulación transcripcional. Involucra tanto activadores transcripcionales como
represores, integra señales y resultados de expresión génica.
iv)
Dominio de oligomerización. Este dominio interacciona con otros FTs para formar complejos
regulatorios. Las variaciones de oligomerización incrementan la versatilidad de la maquinaria
transcripcional y tiene la capacidad de modular la expresión génica en plantas.
En plantas, se estima que entre un 5-10% del genoma codifica FTs, lo que indica la complejidad
de la regulación transcripcional en estos organismos (Udvardi y col., 2007). El genoma de A. thaliana
codifica alrededor de 1500 FTs lo que corresponde a un 5% de todo su genoma, porcentaje algo mayor
en comparación con otros organismos como: Caenorhabditis elegans y Drosophila melanogaster donde
representan un 4.5 y 3.5% respectivamente (Riechmann y col., 2000). En cuanto al genoma del tomate
(Solanum pimpinellifolium L. línea LA1589), se estima que codifica al menos 998 FTs de 62 familias
diferentes (Cai y col., 2010), lo que corresponde a un 2.8% del genoma y aproximadamente 34.727 genes
(The Tomato Genome Consortium 2012). Los FTs se pueden clasificar en diferentes familias de acuerdo
con su domino de unión a ADN, tanto el número como los miembros de cada familia han ido aumentado
en el curso de la evolución (Pabo y Sauer, 1992; Riechmann y col., 2000). Análisis filogenéticos en
eucariotas han mostrado que algunas familias de FTs presentan mayor expansión en plantas que en
otros eucariotas (Shiu y col., 2005). Existen también algunas familias de FTs exclusivas de plantas como:
AP2/EREBP, NAC, WRKY y DOF (Riechmann y col., 2000; Yanagisawa, 2002a; Moreno-Risueño y col.,
2007).
En la tabla 1.2 y 1.3 se presentan las principales familias de FTs en plantas al igual que en tomate
(S. pimpinellifolium). Las familias de FTs han sido identificadas a partir de análisis de secuencias de FTs
de otras especies previamente identificadas y disponibles en la base de datos de plantas PlantTFDB;
Tomato Transcription Factor Database (Zhang y col., 2010).
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Introducción General
Tabla 1.2. Principales familias de FTs en plantas. Adaptado de Riechmann y Ratcliffe, 2000, Riechmann y col., 2000;
Rueda, 2011.
Nº de genes
estimados
en Arabidopsis
Funciones de la Familia
Dominio de unión al ADN
DOF
41
Germinación de semilla, expresión específica en
endospermo y metabolismo del carbono.
AP2
150
Desarrollo floral, proliferación celular, metabolismo
secundario, respuesta a estrés biótico y abiótico,
respuesta a ABA y respuesta a etileno.
Dedo de Zinc estructurado por cuatro
cisteínas con un ion Zn2+.
Región de 68 amino ácidos (aa)con un
dominio conservado que forma una posible
α-hélice anfipática.
NAC
105
Desarrollo y respuesta a estrés abiótico.
bHLH
100
Biosíntesis de antocianinas, respuesta la luz, desarrollo
floral y estrés abiótico.
bZIP
100
Expresión génica de almacenamiento de semilla,
fotomorfogénesis, desarrollo de hoja, desarrollo floral,
respuesta a ABA y biosíntesis de giberelinas.
Z-C2H2
85
Desarrollo floral, tiempo de floración, desarrollo de
semilla y desarrollo de nódulos de la raíz.
Dedo de zinc mantenido por el enlace de
coordinación entre 2 cisteínas y 2 histidinas
con un ión Zn2+.
MADS
80
Desarrollo floral, desarrollo de fruto, tiempo de floración
y desarrollo de raíz.
Motivo de 57 residuos aproximadamente
que adoptan una conformación de una α‐
hélice larga y dos láminas β.
WRKY
75
Respuesta a defensa.
MYB
180
Metabolismo secundario, respuesta a estrés biótico y
abiótico, ritmo circadiano.
29
Participan en el desarrollo de plantas, crecimiento y
maduración de semilla. Respuesta a fitohormonas,
ABA y auxinas.
GRAS
47
Desarrollo y crecimiento de la planta, señalización de
GA, formación de meristemos y transducción de
señales por luz.
TCP
21
Involucrados en el control del desarrollo de la planta,
formación órganos.
8
Involucrados en el desarrollo, formación de meristemo
apical y floral.
GATA
29
Control del desarrollo de diversos tejidos, controlan la
maduración celular, implicados en la respuesta a
cáncer.
RING finger
469
Reparación del AND y en la reorganización génica de
inmunoglobulinas.
Dedo de zinc mantenido por el enlace de
coordinación entre 7 cisteínas y una histidina
con dos iones de Zn2+.
NF‐Y
29
Involucrados en la activación de varios genes
asociados a enfermedades humanas y apoptosis.
Dominio de unión al motivo CCAAT similar a
histonas.
Homeobox
74
Reguladores del desarrollo, respuesta a estímulos
ambientales.
Familia
B3
YABBY
23
Región en el extremo N‐terminal dividido
en cinco subdominios.
Región rica en residuos básicos, próxima a
un motivo hélice-lazo-hélice.
Dos hélices básicas que interaccionan
mediante una cremallera de leucinas.
Dedo de zinc con la secuencia amino
acídica WRKYGQK conservada en el
extremo N‐terminal.
De una a cuatro repeticiones imperfectas de
52 aminoácidos que adquieren una
conformación hélice-giro-hélice.
Secuencia conservada de 120 aa en el
extremo C-terminal.
Motivo pentapartito formado por un
heptámero de leucinas, el motivo VHIID, otro
heptámero de leucinas, el motivo PFYRE y el
motivo SAW.
Región de 59 aa que adopta la estructura
hélice-lazo-hélice.
Dedo de Zinc mantenido por el enlace entre
2 cisteínas y un ión Zn2+, seguido de una
estructura hélice-lazo-hélice.
Dedo de Zinc estructurado por cuatro
cisteínas con un ión Zn2+ seguido de una
región básica.
Tres o cuatro hélices y un brazo N terminal
con 60 residuos.
Introducción General
Tabla
1.3.
Principales
familias
FTs
en
tomate.
Adaptado
de
Tomato
Transcription
Factor
Database;
http://planttfdb_v1.cbi.pku.edu.cn:9010/web/index.php?sp=le y Zhang y col., 2010.
Nº de FTs
estimados
en Tomate
Funciones de la Familia
Dominio de unión al ADN
23
Participan en la regulación de
síntesis de proteínas de reserva,
desarrollo de endospermo,
metabolismo de carbohidratos
mecanismos de defensa ,
germinación y respuesta a auxinas
Dedo de Zinc estructurado por cuatro
cisteínas con un ión Zn2+.
AP2
EREBP
84
Respuesta a varios tipos de estrés
biótico y abiótico. Procesos del
desarrollo y órganos florales.
ABI3-VP1
27
Regulación de la respuesta a ABA
durante el desarrollo de semilla,
tolerancia a la desecación.
HB
36
Involucrados en la diferenciación
celular y crcimiento.
ZF-HD
10
Involucrados en el metabolismo del
carbono, gen C4 PEPCase.
Dominio de 54 aa en la región N-terminal.
Windhovel A y col.,
2001.
AS2
13
Participan en el sistema de
vernalización de la hoja, así como
en el desarrollo de la simetría de la
lámina.
Dominio AS2 en el motivo C-terminal, un
residuo de glicina conservado y un motivo
leucine-zipper-like.
Iwakawa H y col., 2002.
Dominio de 60 aa con dos regiones
funcionales, la región básica está
localizada en el dominio N-terminal.
Región rica en residuos básicos, próxima
a un motivo hélice-lazo-hélice.
Toledo-Ortiz y col.,
2003.
Familia
DOF
Región de 70 aa con un dominio
conservado que forma una posible αhélice anfipática.
Referencia
Yanagisawa, 2002b.
Riechmann
JL
y
Meyerowitz EM, 1998.
Lazarova G y col., 2003.
Interaccionan con el ADN como
homodimeros, reconocen dos distintas
secuencias pseudopalindromicas de 9 pb.
Sessa G y col., 1997.
58
Involucrados en la respuesta la luz,
desarrollo floral y estrés abiótico.
48
Regulan el metabolismo
secundario, respuesta a estrés
biótico y abiótico, ritmo circadiano.
Dominio de 53 aa que adquieren una
conformación hélice-giro-hélice.
ZIM
20
Involucrados en el desarrollo de
flor e inflorescencias.
Contiene una estructura modular con un
único dedo de Zinc C2-C2.
Nishii A y col., 2000.
AUX-IAA
21
Involucrada en la actividad de las
proteínas Aux/IAA.
Presenta cuatro motivos de secuencias
de aa conservados I, II, III, IV que
presentan distintas funciones.
Reed JW, 2001.
47
Expresión génica de
almacenamiento de semilla,
fotomorfogénesis, desarrollo de
hoja, desarrollo floral, respuesta a
ABA y biosíntesis de giberelinas.
MYB
36
Responden en el metabolismo
secundario, respuesta a estrés
biótico y abiótico, ritmo circadiano.
NAC
41
Desarrollo y respuesta a estrés
abiótico.
Región en el extremo N-terminal dividido
en cinco subdominios.
Duval M y col., 2002.
WRKY
52
Defensa
de
patógenos,
senescencia,
desarrollo
de
tricomas.
Dedo de zinc con la secuencia amino
acídica WRKYGQK conservada en el
extremo N‐terminal.
Eulgem T y col., 2000.
bHLH
MYB
bZIP
24
Stracke R y col., 2001.
Dos hélices básicas que interaccionan
mediante una cremallera de leucinas.
Schindler U y col., 1992
De una a cuatro repeticiones imperfectas
de 52 aa que adquieren una
conformación hélice-giro-hélice.
Kirik V y Baumlein H,
1996.
Introducción General
1.6.- EXPRESIÓN GÉNICA Y REGULACIÓN BAJO ESTRÉS ABIÓTICO.
1.6.1.- Complejidad de la expresión génica y regulación.
Las plantas han desarrollado una serie de mecanismos complejos a múltiples niveles que
incrementan la adaptación a condiciones ambientales adversas. La exposición de plantas a estreses
medioambientales como, la salinidad, la sequía y las bajas temperaturas causan efectos adversos sobre
el crecimiento de la planta y la productividad de los cultivos. Cuando una planta es sometida a un estrés
abiótico, se observa que un gran número de genes cambian sus niveles de expresión como respuesta, lo
que provoca de forma general, cambios a nivel de proteínas y metabolitos (Fernie y col., 2009; Vij y Tyagi,
2007). Análisis transcriptómicos usando tecnología de microarray en plantas modelo como A. thaliana,
Brachypodium distachyon y Medicago truncata (Hirayama y Shinozaki, 2010; Seki y col., 2001; Shinozaki
y col., 2003; Bohert y col., 2006), y otras de interés agronómico como arroz (Rabbani y col 2003), cebada
(Guo y col., 2009), pimiento (Hwang y col., 2005), chopo (Brosche y col., 2005), sorgo (Pratt y col., 2005),
maíz (Hayano-Kanashiro y col., 2009), trigo (Gulick y col., 2005), patata (Vasquez-Robinet y col., 2008) y
tomate (Gong y col., 2010; Ouyang y col., 2007; Sun y col., 2010), han permitido identificar un
determinado grupo de genes inducibles por estrés, al igual que ha facilitado comprender la regulación de
la expresión génica en respuesta a estrés abiótico (Hirayama y Shinozaki, 2010; Shinozaki y col., 2003;
Yamaguchi-Shinozaki y Shinozaki, 2006).
Muchos de los genes que cambian sus niveles de expresión en respuesta a diferentes tipos de
estrés, no solo protegen a la célula frente al estrés por producción de importantes proteínas metabólicas,
también regulan genes para la transducción de señales en respuesta al estrés (Yamaguchi-Shinozaki y
Shinozaki, 2006; Seki y col., 2001). Así, los productos de estos genes han sido clasificados en dos
grupos. El primero incluye genes que codifican proteínas implicadas en el desarrollo de tolerancia a
estrés como; chaperonas, proteínas LEA (Late Embryogenesis Abundant), enzimas clave para la
biosíntesis de osmolitos como: prolina, proteínas antifreezen, proteínas de canales de agua,
25
Introducción General
transportadores de azúcares y prolina, enzimas de detoxificación, enzimas para el metabolismo de ácidos
grasos y proteínas de transferencia de lípidos (Yamaguchi-Shinozaki y Shinozaki, 2006). El segundo
grupo contiene genes que codifican proteínas con función reguladora de la expresión génica y
transducción de señales en respuesta a estrés. Estas incluyen MAP quinasas, fosfatasas, enzimas del
metabolismo de fosfolípidos, varios tipos de factores de transcripción (FTs) y otras moléculas de
señalización. Esto sugiere, que varios mecanismos de regulación transcripcional, funcionan en las vías de
transducción de señales en respuesta a estrés (Hirayama y Shinozaki, 2010; Seki y col., 2001;
Yamaguchi-Shinozaki y Shinozaki, 2006).
El grado de complejidad de la respuesta a estrés abiótico a nivel de control de la expresión génica,
se ha estudiado a partir de los distintos análisis de expresión global realizados tanto en Arabidopsis como
en arroz, en respuesta a sequía, salinidad y bajas temperaturas (Yamaguchi-Shinozaki y Shinozaki,
2006). Estos análisis han permitido identificar más de 300 genes inducibles por estrés. Entre estos más
de la mitad de los genes inducibles por sequía también son inducidos por alta salinidad y/o tratamientos
con ABA indicando un “cross-talk” entre la respuesta a sequía, salinidad y ABA (Seki y col., 2001; Seki y
col., 2002). Por el contrario, alrededor de un 10% de los genes inducidos por sequía lo son por bajas
temperaturas (Yamaguchi-Shinozaki y Shinozaki, 2003). Muchos de estos genes codifican FTs que tienen
la capacidad de controlar grandes grupos de genes implicados directamente en la respuesta a estrés, o
actúan en la biosíntesis de moléculas reguladoras como la fitohormona ácido abscísico ABA (YamaguchiShinozaki y Shinozaki, 2006; Osakabe y col., 2013).
Estos FTs inducibles por estrés incluyen miembros de las principales familias de FTs (Tabla 2), y
pueden regular varios genes inducibles por estrés de forma conjunta o separada constituyendo redes.
(Shinozaki y col., 2003). Así, estos trabajos indican que existe un alto grado de solapamiento en la
respuesta a estrés, puesto que muchos de los genes están simultáneamente controlados por uno o varios
estreses, poniendo en evidencia que existe un mecanismo regulador común, o que existe una intensa
26
Introducción General
intercomunicación entre las vías que controlan la expresión de la respuesta a deshidratación, bajas
temperaturas y ABA (Shinozaki y col., 2003).
1.6.2.- Factores de transcripción involucrados en la respuesta a estrés abiótico.
La respuesta a estrés abiótico requiere la producción de importantes proteínas metabólicas así
como la síntesis de osmoprotectores y proteínas de regulación que operan en las vías de transducción de
señales como quinasas o FTs (Saibó y col., 2009; Chaves y Oliveira, 2004). Un grupo de genes
controlado por cierto tipo de FTs se conoce como regulon, ya que controlan la respuesta a estrés abiótico
en plantas. Los elementos de regulación de algunos genes que actúan en cis que tienen un perfil de
expresión inducible por estrés y los FTs que afectan a la expresión de estos genes, se ha estudiado
recientemente para conocer más a fondo los mecanismos de regulación en respuesta a estrés abiótico.
Análisis de promotores de genes inducibles por sequía y/o frío han facilitado la identificación de cuatro
sistemas independientes de regulación para la expresión génica en respuesta a estrés (Valliyodan y
Nguyen, 2006; Shinozaki y Yamaguchi-Shinozaki, 2000; Saibo y col., 2009). Dos pertenecen a la vía
dependiente-ABA y los otros dos a la vía independiente-ABA.
1.6.2.1.- Regulon CBF/DREB.
CBF/DREB es un regulon principalmente involucrado en respuesta a bajas temperaturas. Esta
conservado en plantas a lo largo de la evolución, incluyendo plantas no aclimatadas como: tomate y
arroz) (Dobouzet y col., 2003). En Arabidopsis, los genes RD29/COR78/LT78 son inducidos por sequía,
bajas temperaturas y ABA. Análisis de los promotores de estos genes han mostrado que una secuencia
conservada de 9-pb (TACCGACAT) llamada DRE, es un elemento esencial en cis, para regular la
inducción del gen RD29A (RESPONSIVE TO DEHYDRATION 29A) de Arabidopsis en la respuesta
independiente-ABA por deshidratación y bajas temperaturas (Yamaguchi-Shinozaki y Shinozaki, 1994). El
elemento DRE también se encuentra en las regiones promotoras de algunos genes inducibles por sequía
27
Introducción General
y frío. Elementos similares que actúan en cis, llamados C-repeat (CRT) y elementos de respuesta a bajas
temperaturas (LTRE), contienen el motivo A/GCCGAC, que regula los promotores inducibles por frío
(Baker y col., 1994; Thomashow, 1999; Stockinger y col., 1997). Los cDNAs que codifican proteínas DRE/CRT-binding, CBF/DREB1 (C-repeat Binding Factor/DRE Binding protein1), y DREB2 fueron aislados
usando el sistema de un hibrido de levadura (Y1H) (Liu y col., 1998). Estas proteínas contienen un
dominio de unión al DNA conservado en las proteínas ERF (ethylene-responsive element-binding factor) y
AP2 (Apetala 2). ERF/AP2 se unen específicamente a la secuencia DRE/CRT y activan la transcripción
de genes inducidos por esta secuencia (Yamaguchi-Shinozaki y Shinozaki, 2006). La expresión de los
genes CBF/DREB1 es inducida por bajas temperaturas y la expresión de los genes DREB2 es inducida
por sequía y alta salinidad. Tanto las proteínas DREB2 y CBF/DREB1 se unen al elemento de respuesta
DRE, CBF/DREB1 a través de la expresión génica en respuesta a bajas temperaturas, mientras que
DREB2 está involucrada en la expresión génica en respuesta a sequía, lo que indica la existencia de un
entrecruzamiento entre la expresión de genes inducidos por frío y sequía a través del elemento DRE/CRT
(Yamaguchi-Shinozaki y Shinozaki, 2005). La sobre-expresión del gen CBF3/DREB1A en Arabidopsis
promueve un incremento en la tolerancia a bajas temperaturas, alta salinidad y sequía (Gilmor y col.,
2000; Kasuga y col., 1999; Liu y col., 1998). Sin embargo, plantas transgénicas de patata, tabaco, trigo y
arroz que sobre-expresan el gen CBF3/DREB1A exhiben un incremento en la tolerancia a sequía (Oh y
col., 2005, 2007; Behnam y col., 2006) (Figura 1.5).
Por otra parte, los genes RD29A y RD29B de Arabidopsis son diferencialmente inducidos bajo
condiciones de estrés y tratamientos por ABA. La región promotora de rd29A contiene como mínimo dos
elementos que actúan en cis, dos elementos DREs y uno ABRE involucrados en la expresión génica
dependiente e independiente-ABA (Yamaguchi-Shinozaki y Shinozaki, 1994). Estudios previos, han
mostrado que el elemento que actúa en cis DRE funciona en la respuesta inicial de AtRD29 a salinidad,
deshidratación y bajas temperaturas y otra región que contiene ABRE es necesaria para la inducción por
ABA (Yamaguchi-Shinozaki y Shinozaki, 1994). Muchos de los genes inducibles por bajas temperaturas
también responden a estrés inducido por ABA, sequía y altas temperaturas. Las regiones promotoras de
28
Introducción General
estos genes contienen los motivos DRE y ABRE, necesarios para la expresión de genes inducibles por
estrés abiótico (Yamaguchi-Shinozaki y Shinozaki, 1994).
1.6.2.2.- Regulon NAC y ZF-HD.
Las proteínas NAC son FTs específicos de plantas cuya función está involucrada en el desarrollo
de la planta y en la respuesta a estrés biótico y/o abiótico (Nakashima y col., 2012). Estas proteínas
regulan la expresión génica del gen ERD1 (Early Responsive to Dehydration 1) en Arabidopsis (Tran y
col., 2007; Kiyosue y col., 1993). Los genes de la familia ERD fueron identificados colectivamente como
genes que se inducen rápidamente por deshidratación (Kyosue y col., 1994). Análisis del promotor del
gen ERD1 revelan que los FTs pertenecientes a la familia NAC y ZF-HD (zinc finger homeodomain) son
activadores esenciales del gen ERD1 (Tran y col., 2007). La sobre-expresión de los genes NAC en
Arabidopsis aumenta la tolerancia a sequía sin activación del gen ERD1, sugiriendo que la interacción de
otros factores pueden ser necesarios para el control de la expresión de ERD1 bajo condiciones de estrés
(Tan y col., 2004). Estudios realizados por Hu y colaboradores (2006) han reportado que la sobreexpresión del gen de respuesta a estrés SNAC1 incrementa la tolerancia a sequía y salinidad en arroz.
SNAC1 aumenta la tolerancia a sequía en plantas transgénicas de arroz durante la etapa reproductiva
bajo condiciones severas de sequía sin afectar a la producción. Por otra parte, la sobre-expresión del gen
de respuesta a estrés SNAC2 (OsNAC6) en arroz incrementa la tolerancia a sequía y salinidad (Hu y col.,
2008). SNAC1, también induce la expresión de genes que codifican proteínas relacionadas con el ajuste
osmótico y la estabilidad de la membrana celular, regulando así la respuesta a estrés (Hu y col., 2006).
1.6.2.3.- Regulon AREB / ABF.
Los genes inducibles por ABA tienen una secuencia conservada en las regiones promotoras, un
elemento que actúa en cis llamado ABRE (ABA-responsive element; PyACGTGGC) responsable de la
expresión génica en respuesta a ABA (Yamaguchi-Shinozaki y Shinozaki, 2005; Yamaguchi-Shinozaki y
29
Introducción General
Shinozaki, 2006). El elemento de respuesta ABRE, es reconocido por los FTs AREB/ABF, considerados
los principales reguladores de la expresión de genes dependientes de ABA (Figura 1.5). Las proteínas
AREB/ABF son activadas por fosforilación gracias a dos tipos de enzimas quinasas: SnRK2 s (SNF-related
protein kinase subfamily 2) y CDPKs (calcium-dependent protein kinases) (Zhao y col., 2011). Por otra
parte, la sobre-expresión del factor ABF3 en Arabidopsis produce un aumento de la tolerancia a la
deshidratación, debido que se produce un incremento en la expresión de diferentes tipos de genes
relacionados con la ruta de respuesta a estrés mediada por ABA, como los genes que codifican
fosfatasas tipo ABI1, ABI2 y genes de tipo LEA (Kang y col., 2002). Asimismo, siguiendo una estrategia
similar, la sobre-expresión del gen ABF3 en una planta de interés agronómico como arroz, produce un
incremento significativo de la tolerancia a estrés por déficit hídrico (Oh y col., 2005).
1.6.2.4.- Regulon MYB / MYC.
Las proteínas MYC (Myelocytomatosis oncogene) y MYB (Myoblastosis oncogene) son otros
importantes reguladores transcripcionales, ya que son activadores de uno de los sistemas de regulación
de la vía dependiente-ABA (Abe y col., 2003). La expresión del gen inducible por sequía RD22
(RESPONSIVE TO DEHYDRATION 22) de Arabidopsis es mediado por ABA (Abe y col., 1997) (Figura
1.5), y su región promotora contiene los sitios de reconocimiento en cis MYC (CANNTG) y MYB
(C/TAACNA/G) (Abe y col., 1997). Los FTs, AtMYC2 (rd22BP1) y AtMYB2 se unen a los elementos en cis
del promotor AtRD22 y activan cooperativamente su expresión. Estos dos FTs son sintetizados por
acumulación endógena de ABA. Plantas transgénicas que sobre-expresan AtMYC2 y AtMYB2 presentan
alta sensibilidad a ABA y tolerancia a estrés osmótico (Abe y col., 2003). Además, la sobreexpresión de
AtMYB15 aumenta la tolerancia a estrés hídrico en Arabidopsis. Los genes MYC/MYB también han sido
sobre-expresados en especies de interés agronómico. Un ejemplo es el caso del gen StMYB1R-1 en
patata que produce un aumento en la tolerancia a sequía sin afectar su productividad (Shin y col., 2011).
Igualmente, la sobre-expresión en Solanaceas del gen MYB4 de arroz produce aumento de la tolerancia
30
Introducción General
al déficit hídrico (Vannini y col., 2007). Estudios transcriptómicos de plantas transgénicas que sobreexpresan genes de tipo MYB/MYC revelan que no solo los genes relacionados al estrés por ABA están
diferencialmente regulados, también los relacionados con el ácido jasmonico (Figura 1.5). Estos datos
indican que existe un “cross talk” entre las rutas de respuesta a estrés biótico y abiótico (Abe y col.,
2003).
Figura 1.5. Esquema que representa la red transcripcional de respuesta a estrés abiótico. Los FTs se muestran en
óvalos. Los triángulos pequeños corresponden a modificaciones post-traduccionales. Los cuadrados azules con interrogante
representan FTs MYC ICE-1 putativos que pueden activar CBF1/DREB1B y CBF2/DRE1C. Las cajas verdes representan
elementos reguladores en cis presentes en los genes de respuesta a estrés. Las cajas verdes con el interrogante
representan los elementos en cis putativos sobre los promotores de los genes de respuesta-estrés. Las líneas discontinuas
negras de SIZ1 a HOS1 representan la competición por el sitio sobre el TF ICE 1. CBF4/DREB1D es un factor que se une al
elemento-cis DRE dependiente de ABA. Adaptado de Saibo y col., 2009.
31
Introducción General
1.6.3.- Expresión génica en respuesta a estrés abiótico en tomate.
De acuerdo con lo descrito anteriormente diferentes análisis transcriptómicos en especies modelo
como Arabidopsis y en cultivos de interés agronómico como arroz, han dado a conocer los distintos
mecanismos de respuesta a estrés. El uso de aproximaciones de microarray y recientemente las nuevas
metodologías de secuenciación (NGS) han proporcionado nuevos mecanismos de regulación, que
permiten comprender más a fondo los distintos mecanismos de respuesta a estrés abiótico en el cultivo
de tomate (Duque y col., 2013; Gong y col., 2010). Estudios transcriptómicos en tomate, con LIs de una
población de Solanum pennelli tolerante a sequía y S. lycopersicum cultivar “M82” sensible, han sido
estudiados bajo condiciones de déficit hídrico. En este estudio se han identificado alrededor de 1400
genes de respuesta a sequía, la mayoría de estos pertenecen a genotipos tolerantes que codifican FTs
(Gong y col., 2010).
Figura 1.6. Vías bioquímicas afectadas por el estrés por sequía en genotipos de tomate. Las flechas marrones y negras
corresponden a las vías responsables de la biosíntesis o degradación de diversos metabolitos incluyendo: secundarios,
transporte de electrones, amino ácidos, hormonas, compuestos aromáticos, componentes de la estructura celular, azúcares,
ácidos grasos y lípidos. Adaptado de Gong y col., 2010.
32
Introducción General
Miembros de las principales familias de FTs en Arabidopsis como: AP2/EREBP, bZIP y NAC,
bHLH, HSF, MYB y reguladores GRAS (Tabla 2), también han sido identificados en tomate (Tabla 3).
Estos FTs juegan un papel importante en la tolerancia a diferentes estreses medioambientales (Zuo y
col., 2007; Zhang y col., 2009; Trujillo y col. 2008; Zheng y col., 2009) lo que evidencia la complicada red
de regulación transcripcional en respuesta al déficit hídrico en tomate (Gong y col., 2010).
Estudios de expresión en tomate, han permitido identificar un grupo de genes que aumentan sus
niveles de expresión en respuesta a salinidad. Alrededor de 201 genes no redundantes han sido
identificados en condiciones severas de salinidad en S. lycopersicum (Ouyang y col., 2007). Estos
mismos genes se han observado en análisis transcriptómicos previos realizados en Arabidopsis en
respuesta a este estrés. Diferentes FTs entre los que se encuentran miembros de la familia de proteínas
NAC, que juegan un papel importante de “cross-linking” en diferentes vías de señalización, de las familias
de FTs EREBP, zinc-finger, WRKY y HSF que son de factores asociados a la tolerancia a salinidad y han
sido observados en distintos estudios transcriptómicos tanto en tomate como Arabidopsis. Por último, se
ha descrito genes involucrados en las vías metabólicas de la reducción y fijación de nitrógeno y la
biosíntesis de metionina que son significativamente afectados por este estrés. Esto indica que, la
salinidad tiene un impacto significativo en la reducción y fijación del nitrógeno en el cultivo de tomate
(Ouyang y col., 2007).
Otros análisis de expresión entre LIs de Solanum habrochaites que es una especie tolerante a
bajas temperaturas, y el cultivar S. lycopersicum que es sensible, han permitido la identificación de
alrededor de 1500 genes que aumentan su expresión en respuesta a bajas temperaturas, en los dos
genotipos. Esto sugiere la existencia de un mecanismo de respuesta común a las bajas temperaturas
entre genotipos tolerantes y sensibles de tomate (Liu y col., 2012). Además, gran número de FTs son
regulados en respuesta a frío en al menos un genotipo de tomate. Dentro de estos FTs se encuentran
miembros de las familias MYB, NAC, WRKY, AP2/ERBP, HSF, bHLH, bZIP y Zinc finger que presentan
33
Introducción General
expresión diferencial de sus transcritos entre genotipos tolerantes y sensibles. Esto indica que la
regulación de estos FTs podría ser una respuesta común a varios estreses abióticos en tomate (Liu y col.,
2012).
1.6.4.- Factores de transcripción involucrados en la respuesta estrés abiótico en
tomate.
Durante los últimos años se han realizado diferentes estudios para identificar y caracterizar la
función que realizan los distintos tipos de FTs en respuesta a salinidad, sequía y bajas temperaturas.
Anteriormente se ha mencionado que en Arabidopsis existen distintos FTs así como elementos en cis que
participan en la respuesta a estrés abiótico. Estos, han sido divididos en dos grupos: aquellos que
participan en la vía de respuesta controlada por ABA o los que participan en rutas independientes
(Yamaguchi-Shinozaki y Shinozaki, 2006). Estudios transcriptómicos realizados en tomate bajo diferentes
tipos de estrés abiótico como: salinidad, sequía y bajas temperaturas, han permitido la identificación de
un gran número de genes inducidos o reprimidos por los mismos. Sin embargo, se desconocen muchas
de sus funciones en el control de la expresión génica en respuesta a estrés abiótico en tomate.
1.6.4.1.- Regulon CBF/DREB.
La expresión del FT DREB1A aumenta la expresión de genes inducibles por estrés. Por tanto
aumenta la tolerancia a la salinidad y al estrés hídrico en Arabidopsis y tomate (Liu y Zhu, 1998;
Nakashima y Yamaguchi-Shinozaki, 2006) (Figura 1.7). Por otra parte, la sobre-expresión del CBF1
induce la expresión del gen COR (COLD REGULATED) e incrementa la tolerancia a la congelación en
Arabidopsis (Jaglo-Ottosen y col., 1998). En tomate, plantas que sobre-expresan el gen CBF1, presentan
mayor tolerancia al déficit hídrico que plantas WT (Hsieh y col., 2002). Sin embargo, estas plantas
exhiben un retardo en el crecimiento, reducción del tamaño del fruto, número de semillas y peso fresco.
Además, contienen altos niveles de prolina en comparación con plantas WT bajo condiciones normales y
34
Introducción General
de déficit hídrico (Hsieh y col., 2002). Un efecto similar es observado cuando se sobre-expresa el gen
CBF1 de Arabidopsis bajo el control del promotor ABRC1 de cebada inducible por estrés en tomate.
Plantas que sobre-expresan el gen AtCBF1 presentan un incremento en la tolerancia al estrés por chilling,
déficit hídrico y salinidad cuando estas plantas son comparadas con plantas WT (Lee y col., 2003).
1.6.4.2.- Regulon NAC y ZF-HD.
Trabajos realizados por Hichri y col., 2014, reportaron el primer represor tipo zinc finger en tomate
SlZF2. El ortólogo en Arabidopsis aumenta la sensibilidad a salinidad, pero en tomate SlZF2 retarda la
senescencia y aumenta la tolerancia a estrés salino ya que mantiene la actividad fotosintética e
incrementa la biosíntesis de poliaminas. SlZF2 está involucrado en la biosíntesis y señalización de ABA
debido a que es rápidamente inducido y como consecuencia tomate transgénicos 35S::SlZF2 acumulan
más ABA que tomates WT. Además, análisis transcriptómicos han mostrado que SlZF2 incrementa y
reduce la expresión de involucrados en el metabolismo secundario que son cruciales para la adaptación
de la planta a condiciones medioambientales (Figura 1.7).
1.6.4.3.- Regulon AREB / ABF.
Estudios recientes han mostrado que la clase de FTs bZIP juega un rol importante en la respuesta
a estrés abiótico en el género Solanum. Las proteínas bZIP son un grupo específico de FTs que se unen
al elemento de respuesta-ABA (AREBs) (Uno y col., 2000) o ABFs (Choi y col., 2000). El cDNA que
codifica estos bZIP ha sido aislado de especies cultivadas y silvestres de tomate y se ha demostrado que
su expresión es inducida por ABA y diferentes estreses abióticos incluyendo salinidad, sequía y frío
(Yañez y col., 2009). Además, la expresión del cDNA de SlAREB1 en tabaco y tomate, ha mostrado que
regula la transcripción de genes de respuesta a estrés como: RD29A, LEA, ERD10B y TAS14, el factor de
transcripción PHI-2 y el gen que codifica la enzima trehalosa-6-fosfato fosfatasa (Yañez y col., 2009).
Recientes trabajos han mostrado la posibilidad de desarrollar especies de tomate tolerantes al déficit
35
Introducción General
hídrico usando el factor ABRE-binding, ABF4 de Arabidopsis. Plantas transgénicas de tomate que sobreexpresan el gen ABF4/AREB2 exhiben tolerancia a la sequía (Na, 2005), efecto que se atribuye a una
disminución de la pérdida de agua por unidad de área de la hoja. Otros estudios han mostrado que la
sobre-expresión de SIAREB incrementa la tolerancia a salinidad y sequía en tomate (Hsieh y col., 2010;
Orellana y col., 2010) (Figura 1.7). Plantas transgénicas de tomate que sobre-expresan el gen SIAREB
regulan la expresión de genes de respuesta a estrés como AtRD29A, AtCOR47 y SlC17 dehidrin bajo
diferentes tipos de estrés abiótico (Pandey y col., 2011).
1.6.4.4.- Regulon MYB / MYC.
En cuanto a las proteínas MYB/MYC, la sobre-expresión del gen Osmyb4 un factor transcripcional
de la familia MYB aumenta la tolerancia a déficit hídrico y a enfermedades virales en tomate (Vannini y
col., 2007) (Figura 1.7). Estudios realizados por Pan y colaboradores (2010) han mostraron que la sobreexpresión en tomate transgénico de un FTs de respuesta a etileno (ERFs) que presenta delecciones en el
dominio de represión anfifilic ERF-asociado (SlERF3ΔRD), conducen la reducción de los niveles de
peroxidación de lípidos de membrana y aumentan la tolerancia a estrés salino. El crecimiento de tomates
transgénicos SlERF3ΔRD bajo estrés salino produce un aumento en el número flores, frutos y semillas
en comparación con plantas WT.
36
Introducción General
Figura 1.7. Esquema que representa los factores de transcripción (FTs) y elementos en cis implicados en la
respuesta a la sequía, la salinidad y las bajas temperaturas en tomate. Varios FTs como AREB, MYB, NAC y bZIP en
respuesta a la sequía, la salinidad y las bajas temperaturas median la influencia sobre genes en la vía dependiente de ABA
en tomate. FTs como NAC, ZFHD y AP2 en la vía independiente de ABA permiten la expresión de genes involucrados en la
respuesta a salinidad y sequía en tomate. Los óvalos gris/lila corresponden a FTs que han sido identificados en la ruta
dependiente e independiente de ABA. Las cajas azules representan elementos reguladores en cis presentes en los genes de
respuesta a estrés. Adaptado de Gong y col., 2010.
37
Introducción General
1.7.- FACTORES DE TRANSCRIPCIÓN DE TIPO DOF.
Las proteínas DOF (DNA binding with One Finger) son una familia de FTs especifica de plantas
(Yangisawa, 2002). Se caracterizan por tener un dominio de unión al ADN altamente conservado de 52
aa en la región N-terminal. Este dominio contiene cuatro residuos cisteínas que unen un átomo de zinc
(Zn2+), estructurando un único dedo Zn2+ C2/C2 (Yanagisawa y Schmidt, 1999) (Figura 1.8).
Figura 1.8. Representación esquemática de la estructura del domino DOF. Dominio de 52 aa altamente conservado
(Rojo), cuatro residuos de cisteína coordinan un átomo de Zn 2+. Adaptado de Noguero y col., 2013.
Este dominio de unión a ADN es esencial para reconocer los motivos en cis que contienen la
secuencias 5´-(T/A) AAAG-3´ en los promotores de los genes diana (Yanagisawa y Schmidt, 1999). Las
proteínas DOF pueden unirse a promotores que contienen un único motivo 5´-AAAG-3´ ó más
frecuentemente a repeticiones del mismo motivo (Yanagisawa, 2000). Además, contienen un dominio
conservado de localización nuclear bipartito (Krebs y col., 2010), sin embargo, las regiones N- y Cterminal son muy variables y su función se desconoce. En algunos casos concretos, el dominio C-terminal
se ha visto implicado en la interacción con otras proteínas y con otros elementos regulatorios (Lijavetzky y
col., 2003; Moreno-Risueño y col., 2007; Yanagisawa, 2001).
38
Introducción General
Los FTs de tipo DOF se originaron a partir de un ancestro común en el alga unicelular
Chlamydomonas reinhardtii (CrDof1) y a través de recurrentes eventos de duplicación en el curso de la
evolución se fueron formando los diferentes grupos taxonómicos de plantas vasculares (Moreno-Risueño
y col., 2007). Los genes DOF se clasifican en familias de diferentes tamaños dentro de especies. En
gimnospermas y plantas inferiores como: Selaginella moellendorffii y P. patens se han encontrado 8 y 9
genes DOF respectivamente (Moreno-Risueño y col., 2007). Entre las angiospermas, se han identificado
36 genes DOF en A. thaliana (Yanagisawa y Schmidt, 1999), 27 genes en Brachypodium distachyon
(Hernando-Amado y col., 2012), 30 en arroz (Oryza sativa L.) (Gaur y col., 2011) y 41 en chopo (Populus
trichocarpa) (Yang y Tuskan, 2006), indicando recientes eventos de duplicación en plantas superiores
(Moreno-Risueño y col., 2007).
Figura 1.9. Árbol filogenético de los FTs de la familia DOF en Arabidopsis. El árbol fue realizado por el método neighborjoining después del alineamiento de secuencias aa de los 36 genes Arabidopsis. Los MCOGs (Major Clusters of Orthologous
Genes) deducidos se muestran en diferentes colores: A=naranja, B=azul, C=rojo, D=verde. La barra de escala corresponde a
una estimación de 0.05 sustituciones de aa por sitio (Lijavetzky y col., 2003)
39
Introducción General
Diferentes estrategias se han usado para estudiar las relaciones filogenéticas entre miembros de
la familia de genes DOF. Análisis filogenéticos realizados con los 36 FTs de Arabidopsis, han mostrado
que se organizan en cuatro grupos o subfamilias (A, B, C, D) (Lijavetzky y col., 2003) (Figura 1.9).
Los FTs de la familia DOF presentan diversidad de funciones y juegan un rol importante en
muchos procesos fisiológicos exclusivos de plantas como: asimilación del nitrógeno y fijación del carbono
fotosintético (Yanagisawa y Sheen, 1998), germinación de semilla (Papi y col., 2000), metabolismo
secundario (Skirycz y col., 2006), desarrollo vascular (Hir y Bellini, 2013; Guo y col., 2009), control de la
floración y respuesta al fotoperiodo (Imaizumi y col., 2005; Iwamoto y col., 2009) (Figura 1.10). Los genes
DOF se encuentran involucrados en la regulación/ajuste del metabolismo bajo diferentes señales
medioambientales que aún no han sido descritas. Dentro de los procesos que regulan los FTs DOF, el
desarrollo de semilla, la diferenciación de tejido y la regulación del metabolismo son considerados los
más relevantes y se describen a continuación:
1.7.1.- Diferenciación de tejido.
Anteriormente, hemos mencionado que los FTs de tipo DOF desempeñan un importante papel en
diversos procesos fisiológicos de la planta. En cuanto a la diferenciación de tejido, un ejemplo es el gen
ZmDOF1 que regula el desarrollo de polen por represión de genes que controlan este proceso (Chen y
col., 2012; Yanagisawa y col., 2000). Otro factor de tipo DOF como OBP1 (OBF- binding factor-1) de A.
thaliana, está implicado en el control de la división celular y promueve la reentrada del ciclo celular
(Skirycz y col., 2008). Además, el gen AtOBP2, juega un importante rol en la respuesta a estrés biótico,
posiblemente como parte de la vía de regulación en el metabolismo de GS en Arabidopsis (Skirycz y col.,
2006) (Figura 1.10). Así mismo, los FTs de tipo DOF juegan un papel importante en la regulación del
desarrollo del tejido vascular. AtDOF5.6/HCA2, actúa como un regulador positivo en la formación del
cambium interfascicular durante el desarrollo del tejido vascular en A.thaliana (Guo y col., 2009). El
desarrollo vascular en Arabidopsis también es susceptible a la regulación por dos FTs de tipo DOF
40
Introducción General
AtDOF2.4 y AtDOF5.8, la cual son diferencialmente expresados. El gen AtDof2.4 es detectado en las
células del procambium y AtDOF5.8 en las células de la hoja y en el tejido vascular de los capullos
florales (Konishi y col., 2007). Numerosos estudios han mostrado que los FTs de tipo DOF están
implicados en la regulación del desarrollo de células de guarda. Trabajos realizados por Cominelli y col,
(2011), han mostrado que tan solo un promotor mínimo del gen Myb60 es suficiente para conferir una
actividad específica de las células de guarda, además de ser considerado como un gen candidato para la
expresión génica de las células de guarda. StDof1 también ha sido identificado como candidato para la
activación de la expresión especifica de células de las guarda e interacciona y activa la expresión del gen
especifico de células de la guarda KST1 (Plesch y col., 2000).
1.7.2.- Desarrollo de semilla.
En relación con el desarrollo de semilla varios FTs de tipo DOF están implicados en la regulación y
síntesis de proteínas de reserva y proteínas expresadas durante el desarrollo del endospermo en
cereales (Noguero y col., 2013). El primer FT de la familia DOF implicado en la regulación de los genes
que codifican SSPs en semillas de maíz fue PBF (Prolamin Binding Factor) (Vicente-Carbajosa y col.,
1997). Los PBFs de maíz comparten un alto grado de similaridad de secuencia con los descritos en arroz
(Yamamoto y col., 2006), trigo (WPBF; Dong y col., 2007), cebada (BPBF; Mena y col., 1998) mijo
(FMPBF). Todos estos presentan perfiles similares de expresión y están restringidos para el desarrollo del
endospermo apareciendo al principio de este proceso. Otros genes DOF tienen un rol principal en el
control de la germinación de semilla (Figura 1.10). En Arabidopsis, dos genes parálogos DAG1 y DAG2
(DOF Affecting Germination) tienen papeles opuestos durante la germinación. El mutante dga1 reduce la
dormacia (Papi y col., 2000), sin embargo, el mutante dga2 incrementa el periodo de dormancia y
disminuye su respuesta a giberelinas cuando es mutado (Gualberti y col., 2002; Papi y col., 2000; 2002).
Otro regulador negativo de la germinación de Arabidopsis perteneciente a esta familia de FTs es AtDOF6.
La sobre-expresión de AtDOF6 retarda la germinación e induce genes de la ruta biosintética de ABA y
41
Introducción General
aumenta la sensibilidad de las semillas durmientes a esta hormona. Además, se ha demostrado que
interacciona con TCP14 un activador de la germinación (Rueda-Romero y col., 2012).
1.7.3.- Regulación del metabolismo.
Los FTs de la familia DOF intervienen en muchos aspectos metabólicos en respuesta a distintos
cambios medioambientales. Algunos genes DOF se encuentran involucrados en la regulación/ajuste del
metabolismo bajo diferentes señales medioambientales que aún no han sido descritas. El primer gen
DOF identificado en maíz (ZmDOF1), actúa como un regulador transcripcional en el metabolismo del
carbono del gen C4 Fosfo-Enol-Piruvato-Carboxilasa (PEPC) en repuesta a la luz (Yanagisawa y Sheen,
1998; Yanagisawa, 2002). Además, ZmDOF1 interacciona con la proteína Dof2 de maíz y con el grupo de
proteínas HMG (High Mobility Group), que pueden actuar como chaperonas que facilitan la unión del
factor DOF al ADN (Yanagisawa y col., 1997). El efecto positivo de DOF1 sobre la producción de
esqueletos de carbono se ha estado explorando para estudios de ingeniería metabólica en A.thaliana
(Yanagisawa y col., 2004). La sobre-expresión de FT, en Arabidopsis y arroz, promueve un aumento de la
expresión de genes que codifican enzimas implicadas en la biosíntesis de carbohidratos y amino ácidos
(Yanagisava et al. 2004; Kurai et al. 2011). Este hecho sugiere que este gen modifica los metabolismos
del C y del N. Por otra parte la sobre-expresión de OsDOF25 en Arabidopsis altera el metabolismo del
carbono y nitrógeno y resulta en un incremento de la concentración de aa (Santos y col., 2012). Además,
aumenta la expresión de transportadores de amonio de baja y alta afinidad (AMTs). Un incremento en los
contenidos totales de amino-N y piruvato quinasa (PK1 y PK2), fosfoenol piruvato carboxilasa (PEPC1 y
PEPC2), NADP-dependiente y NAD-dependiente de isocitrato deshidrogenasa se han observado.
Además, se ha detectado un aumento en los niveles de expresión y actividad de la enzima glutamato
deshidrogenasa (GDH) (Figura 1.10).
Los genes DOF también son importantes moduladores de las respuesta de plantas tanto a
estreses bióticos como abióticos. En este contexto muchos son inducidos por fitohormonas y/o patógenos
42
Introducción General
y participan en la regulación de fitoalexinas (Skirycz y col., 2007; Nakano y col., 2006), como es el caso
del gen OBP2, este juega un rol importante en la respuesta a estrés biótico, posiblemente como parte de
la ruta que regula el metabolismo del indol glucosinato (GS) en Arabidopsis (Skirycz y col., 2006) (Figura
1.10). Por todo lo anterior, las proteínas DOF actúan como activadores o represores en el control de la
expresión génica de numerosos genes y diferentes procesos fisiológicos de plantas (Yanagisawa y
Sheen., 1998; Díaz y col., 2002).
Figura1.10. Ejemplos de algunos procesos regulados por FTs de tipo DOF. Representación de la regulación de la expresión
génica de las proteínas DOF, durante el desarrollo de semilla, diferenciación del tejido y regulación del metabolismo. Las líneas
con un punto en el extremo (─●) conectan los procesos. El papel de los TFs en la regulación de la transcripción se indica con
flechas rojas (
) si es de activación o con flechas truncadas en rojo (
) si es de represión. Se indican las interacciones
descritas con otros TFs implicados en la regulación transcripcional en semillas con líneas negras con puntos en los extremos
(●―●). Los símbolos
y
indican regulación por luz u oscuridad. Las flechas negras con punta en diamante (
gen responsable de la señal. Las flechas negras (
) indican el
) indican los diferentes procesos. Adaptado de Noguero y col., (2013).
43
Introducción General
1.8.- CYCLING DOF FACTORS (CDFs).
De acuerdo con lo descrito anteriomente, en Arabidopsis existen 36 FTs tipo DOF que han sido
clasificados en cuatro grupos (A-D) (Lijavetzky y col., 2003). En el grupo D, se encuentra un set de
factores tipo DOF cuyos niveles de expression osicilan en condiciones de luz continua y son conocidos
como CYCLING DOF FACTORS (CDFs) (Imaizumi y col., 2005; Fornara y col., 2009). Los CDFs cumplen
un papel importante en la floración y respuesta al fotoperiodo en Arabidopsis, a través de la modulación
de la expresión de CO (CONSTANS) (Fornara y col., 2009).
El primer gen CYCLING DOF FACTOR 1 (CDF1) fue inicialmente identificado en un screening de
levadura en el que se buscaban proteínas que interaccionan con la proteína FLAVIN BIDING, KELCH
REPEAT (F-box-1, FKF1) que es considerado, además, un receptor de luz azul. CDF1 es una proteína
nuclear que se expresa principalmente en el tejido vascular (Imaizumi y col., 2005). La expresión ectópica
de CDF1 produce un desarrollo más tardío en el tiempo de floración bajo condiciones de día largo (DL),
ya que reprime la transcripción de CO (Imaizumi y col., 2005). Además, otros factores como CDF2, CDF3
y CDF5 presentan una función redundante, por lo que también retrasan la floración, mediante la
regulación negativa de CO (Fornara y col., 2009). Por otro lado, CDF1 y CDF2 juegan un papel central
como integradores de la señal de luz y participan en el ajuste metabólico apropiado a las condiciones del
luz/oscuridad del ambiente (Imaizumi y col., 2005; Fornara y col., 2009). De esta forma, los CDFs están
implicados en el control del tiempo de floración en Arabidopsis (Fornara y col., 2009).
En Arabidopsis, la floración se induce durante periodos prolongados de luz (día largo) que coincide
con las estaciónes de primavera y principios de verano, pero se retarda cuando el periodo de oscuridad
es más prolongado (día corto), que coincide con el final del otoño y el invierno. Estudios moleculares
definen que la ruta del fotoperiodo engloba importantes genes como GIGANTEA (GI), CONSTANS (CO) y
FLOWERING LOCUS T (FT) (Kobayashi y Weigel, 2007; Turck y col., 2008), cuyas funciones son
conservadas en especies lejanamente relacionadas (Hayama y col., 2003). La estimulación de la
44
Introducción General
transcripción de CO en condiciones de DL es esencial para la inducción de la floración, dado que los
largos periodos de iluminación promueven la estabilidad de la proteína CO (Jang y col., 2008; Valverde y
col., 2004), y desencadenan la transcripción de FT en hojas (An y col., 2004, Takada y Goto, 2003, Wigge
y col., 2005; Yoo y col., 2005), y una posterior traslocación de la proteína FT a los meristemos apicales
(Corbesier y col., 2007, Jaeger y Wigge, 2007, Mathieu y col., 2007).
Como se ha descrito anteriormente, múltiples FTs tipo DOF, homólogos de CDF1 están
implicados en la represión de CO en la primera parte del día (Fornara y col., 2009). En condiciones de DL
las proteínas CDF1 y CDF2 son degradas por el complejo FKF1 y GI dependiente-luz-azul que es
requerido para la medición de la duración del día (Figura 1.11). Este complejo regula directamente la
estabilidad de CDF1 en la tarde, permitiendo la activación de la transcripción de mRNA de CO, debido a
la degradación de las proteínas CDF1 y CDF2 (Figura 1.11) (Fornara y col., 2009; Imaizumi y col., 2005;
Sawa y col., 2007; Gómez, 2013; Jarillo y col., 2008). En la noche, GI es degradada vía E3 ubiquitinligasa CONSTITUTIVE PHOTOMORPHOGENESIS 1 (COP1). La interacción COP1 y GI requiere ELF3
(EARLY FLOWERING 3) un factor circadiano que actúa como un adaptador entre proteínas (Yu y col.,
2008; McWatters y col., 2000) (Figura 1.11). De esta manera, cuatro puntos de regulación durante el día,
aseguran que CO se active específicamente en condiciones de DL.
Por otro lado, recientes estudios han demostrado que los CDFs a parte de estar implicados en la
floración y respuesta al fotoperido, también juega un rol importante en el desarrollo de tuberculo. Trabajos
realizados por Kloosterman y col (2013) han demostrado que el gen CDF1 de S. tuberosum esta
implicado en la formación de tubérculo en patata. La sobre-expresión de una variante alélica de StCDF1
(StCDF1.2), produce un desarrollo temprano del tubérculo y no afecta el tiempo de floración en patata,
indicando que las vías de trasducción de señal para el desarrollo de tubérculo y tiempo de floración están
separadas. Sin embargo, la sobre-expresión de StCDF1.2 en A. thaliana causa un retardo en el tiempo de
floración, sugiriendo que el StCDF1 presenta una función similar conservada sobre la expresión de CO,
como se ha visto con el CDF1 de Arabidopsis (Imaizumi y col., 2005). Además, se ha demostrado que la
45
Introducción General
pérdida de la región C-terminal en las variantes alélicas StCDF1.2 y StCDF1.3, afecta la interacción de
estas proteínas con el complejo FKF1-GI, causando defectos en la madurez de la planta y en el desarrollo
del turberculo. Todos estos trabajos demuestran una vez más la importancia del estudiar a los CDFs
como herramienta para mejorar la producción y calidad del cultivo de tomate y otras Solanáceas
Figura 1.11. Representación esquemática de la regulación diurna de la expresión de CO. En la mañana los niveles de
expresión de los genes AtCDF1, AtCDF2, AtCDF3 y AtCDF5 son elevados. Las proteínas AtCDFs se unen al promotor de CO
reprimiendo su transcripción. La transcripción de GI y FKF1 es reprimida por CCA1 y LHY en la tarde. Además la expresión de
AtCDF1 es reducida por la participación de PRR5, PRR7 y PRR9. Una vez FKF1 percibe la luz azul, forma un complejo con GI.
Este complejo está involucrado en la degradación de AtCDF1 y AtCDF2 y posiblemente de los otros AtCDFs. En la noche GI es
degradado por el complejo COP1 que contiene ELF3. COP1 forma un complejo con GI vía ELF3 y también regula la estabilidad
de
GI.
Adaptado
de
Imaizumi
46
y
col.,
2010.
2
OBJETIVOS
Objetivos
El tomate (Solanum lycopersicum L.) es el cultivo hortícola más importante de España. Sin
embargo, su producción se ve afectada a causa de diferentes condiciones medioambientales, tales como:
salinidad, sequía y temperaturas extremas. Estudios realizados en los últimos años señalan la posibilidad
de utilizar FTs para mejorar la fotosíntesis y la producción de biomasa, así como la tolerancia al estrés
abiótico. Los FTs de tipo DOF participan en la regulación de la fisiología y metabolismo de la planta. Sin
embargo, su función exacta en el desarrollo de la tolerancia a distintos tipos de estrés abiótico y su
impacto en el desarrollo del fruto es, en gran parte, desconocida.
El objetivo general de este trabajo es la identificación y caracterización de nuevos factores
reguladores implicados en el control del ajuste metabólico en respuesta a condiciones de estrés abiótico
en tomate.
Se pretende ampliar nuestro conocimiento de los procesos de control genético de la respuesta a
condiciones ambientales adversas, y cómo se integran con procesos del desarrollo como la fructificación.
Esta información puede ser una herramienta para nuevos programas biotecnológicos de mejora de la
tolerancia a estrés en Solanaceas.
Para alcanzar este objetivo general nos planteamos los siguientes objetivos específicos:
Primero. Caracterización molecular y estudio de la función del factor de transcripción de tipo DOF, CDF3
de Arabidopsis thaliana durante el desarrollo y en condiciones de estrés abiótico.
Segundo. Estudio de la respuesta fisiológica de la sobre-expresión del gen AtCDF3 en tomate.
Tercero. Identificación y caracterización molecular y funcional de factores de transcripción de la familia
DOF de tomate (Solanum lycopersicum L.) con un papel regulador en la respuesta a estrés abiótico.
48
3
Arabidopsis CYCLING DOF FACTOR 3 CDF3
REGULATE DROUGHT AND LOW
TEMPERATURE STRESS RESPONSE
AND FLOWERING TIME IN
Arabidopsis thaliana
Arabidopsis Cycling Dof Factor 3 CDF3
3.1.- INTRODUCTION.
Abiotic stresses such as drought, cold and high salinity are among the major important
environmental factors that limit crop growth and productivity. These effects are counteracted by altered
morphology and physiology, resulting in changes in cellular processes such as, inhibition of cell division
and alterations of photosynthetic metabolism (Saibo et al., 2009; Chaves et al., 2009; Lawlor and Cornic,
2002). Transcriptome analysis has identified many genes that are inducible by abiotic stresses
(Yamaguchi-Shinozaki and Shinozaki, 2006; Seki et al., 2002; Shinozaki et al., 2003). These genes might
be classified in two major groups according to their functions. The first group includes genes encoding
proteins with function in stress tolerance, mainly downstream effectors in the stress response pathway
including osmoregulatory genes, antioxidant proteins, chaperones, detoxification enzymes and LEA (Late
embryogenesis abundant) proteins (Gong et al ., 2010; Yamaguchi-Shinozaki and Shinozaki, 2006;
Shinozaki, K. and Yamaguchi-Shinozaki, K, 2004 ). The other group controls gene expression and signal
transduction in abiotic stress response, such as protein kinases, protein phosphatases, enzymes involved
in phospholipids metabolism (Yamaguchi-Shinozaki and Shinozaki, 2006; Seki et al., 2003; Shinozaki, K.
and Yamaguchi-Shinozaki, K, 2004 ) and various transcription factors (TFs) that regulate diverse stressinducible genes cooperatively o separately, and may constitute gene networks. These stress-inducible
transcription factors are members of the DRE-binding protein (DREB) family, ethylene-responsive element
binding factor (ERF), the zinc-finger family, members WRKY family, MYB, basic helix-loop-helix (bHLH),
basic-domain lucine zipper (bZIP) and NAM, ATAF and CUC (NAC) family (Shinozaki et al., 2003).
Several transcription factors interact with cis-acting elements in the promoter regions of stress-inducible
genes (Yamaguchi-Shinozaki and Shinozaki, 2005). The dehydration-responsive element (CTR/DRE) and
ABA-responsive element (ABRE) are two major cis-elements that play an important role in the abiotic
stress response (Maruyama et al., 2012). In silico studies of the complete genome sequences of
Arabidopsis, rice (Oryza sativa) and soybean (Glycine max) have predict novel cis-acting promoter
elements involved in cold-inducible gene expression (Maruyama et al., 2012). Nevertheless new cis-acting
50
Arabidopsis Cycling Dof Factor 3 CDF3
elements and transcription factors have been identified recently, but their function in abiotic stress
tolerance is still unknown.
The DOF (DNA binding with One Finger) family of transcription factors is a group of plant-specific
TFs that contain the DNA-binding domain usually located close to the N-terminal region of the protein. The
DOF domain is a highly conserved region of 52 amino acid residues containing the string CX2 CX21
CX2C, which binds zinc (Zn2+) forming a structure called a “zinc finger” that binds specifically to cis
regulatory elements containing the common core 5´-T/AAAG-3´ (Yanagisawa and Schmidt, 1999; Noguero
et al., 2013). DOF proteins can bind to promoters containing either a unique AAAG motif o more
repetitions of this motif (Yanagisawa, 2000).
DOF genes are important modulators of plants response to both biotic and abiotic stresses and
could be induced by different phytohormones and/or pathogens (Skirycz et al., 2007; Nakano et al., 2006).
Besides, DOF TFs are involved in the regulation of plant specific processes such as carbon assimilation
(Yanagisawa, 2001), light signalling (Park et al., 2003), seed germination or development (Papi et al.,
2000; Gualberti et al., 2002; Rueda-Romero et al., 2012), flowering (Sawa et al., 2007, Fornara et al.,
2009), stomata functioning (Gardner et al ., 2009; Negi et al ., 2013), response to phytohormones (Kang et
al ., 2003; Nakano et al .,2006), carbon fixation and nitrogen assimilation (Yanagisawa and Sheen, 1998;
Rueda-Lopéz et al., 2008), secondary metabolism (Skirycz et al., 2006) and development of vascular
system (Guo et al., 2009; Konishi and Yanagisawa, 2007; Gardiner et al., 2010; Kim et al., 2010; Hir et al.,
2013).
Several reports have shown that DOF proteins can be acting both as activators or repressors in the
control of the expression of numerous plant genes (Mena et al., 1998; Yanagisawa and Sheen, 1998). In
vivo assays in Arabidopsis protoplast have shown that both AtDOF4.2 and AtDOF4.4 have transcriptional
activity and the TMD (Thr-Met-Asp) motif present in the C-terminal region of the two proteins is essential
for the transactivation ability (Zou et al., 2013). Moreover, it has been described that DOF proteins interact
with other transcription factors as basic leucine zipper bZIP (Zhang et al., 1995; Vicente-Carbajosa et al.,
51
Arabidopsis Cycling Dof Factor 3 CDF3
1997) and High Mobility Group (HMG) proteins (Yanagisawa et al., 1997). Other DOF protein from
Solanaceae, StDOF1 regulates guard cell specific gene expression (Plesch et al., 2001), while StSRF1
modulates the carbohydrate metabolism in the storage roots (Tanaka et al., 2009).
The DOF transcription factors originated from a common ancestor, likely represented by the single
Chlamydomonas reinhardtii (CrDof1) gene, and then expanded in the different taxonomic groups of
vascular plants through recurrent duplication events (Moreno-Risueño et al., 2007). The first DOF protein
has been identified in maize (ZmDOF1) and enhances transcription from C4 Phospho-Enol-Pyruvate
Carboxylase (PEPC) promoter (Yanagisawa and Sheen, 1998; Yanagisawa, 2000). Later on many
different DOF genes have been identified in plants but their number of DOF genes varies depending on
the species. Different bioinformatic analysis of Arabidopsis and rice genome predicts 36 and 30 DOF
genes, respectively (Lijavetzky et al., 2003), whereas 27 are found in Brachypodium (Hernando-Amado et
al., 2012), 30 in rice (Oryza sativa) (Gaur et al., 2011), 34 in tomato (Solanum lycopersicum) (Cai et al.,
2013; Corrales et al., 2014), 41 in poplar (Populus trichocarpa) (Yang and Tuskan, 2006), 28 in sorghum
(Sorghum bicolor) (Kushwaha et al., 2010), 31 wheat (Shaw et al., 2009) and 26 in barley (MorenoRisueño et al., 2007). Phylogenetic studies of amino acid sequences of DOF proteins using MEME
software revealed the presence of homologous motifs that are conserved among monocot and dicot
species. Analysis of the DOF gene family in Arabidopsis, rice, tomato and Brachypodium indicated that
they could be classified into four major clusters of orthologous genes or subfamilies (A, B, C and D)
(Lijavetzky et al., 2003; Hernando-Amado et al., 2012). Interestingly comparative analyses of the deduced
amino acid sequences of DOF proteins of group D of different plant species indicate the existence of 3
homologous motifs located in the C-terminal region, conserved among their sequences which are different
of the DOF binding domain and represent common signatures of type D.
In Arabidopsis, the D group contains a set of DOF factors whose transcripts oscillate under
constant light conditions and are hence known as Cycling Dof Factors (CDF1-5) (Imaizumi et al., 2005;
Fornara et al., 2009). AtCDF1 is a nuclear protein expressed mainly in vascular tissues (Imaizumi et al.,
52
Arabidopsis Cycling Dof Factor 3 CDF3
2005) and has been identified to regulate CONSTANS (CO) expression. The CDF transcription factors
have been therefore implicated in flowering-time control in Arabidopsis. The overexpression of AtCDF1-5
genes represses CO transcription causing strong delay of flowering under long-day (LD) conditions
(Fornara et al., 2009; Imaizumi et al., 2005). Moreover, characterization of the flowering time phenotype of
35S::AtCDF1-RNAi line showed a slight acceleration of flowering with unaltered diurnal pattern of CO
expression. FLAVIN-BINDING KELCH REPEAT F-BOX PROTEIN (FKF1) and GIGANTEA (GI) (Sawa et
al., 2007) complex directly regulate the CDF1 stability in the afternoon, allowing mRNA CO activation
transcription by CDF1 and CDF2 degradation mediated by FKF1 in LDs conditions (Fornara et al., 2009;
Imaizumi et al., 2005; Sawa et al., 2007; Gomez, 2013; Jarillo et al., 2008). Interestingly, the single cdf3-1
mutant did not show any alteration in the flowering phenotype under LDs and SDs conditions (Fornara et
al., 2009).
Here, we report the molecular and functional characterization of Arabidopsis CDF3 gene in
response to drought, low temperatures and osmotic stress. Subcellular localization analysis revealed that
AtCDF3 was localized in the nucleus and therefore could act as transcriptional activator. Transgenic plants
overexpressing AtCDF3 showed improved tolerance under low temperatures, oxidative and drought
stresses. Transcriptome comparison of AtCDF3 overexpressing line versus wild-type plants showed upregulation of nitrogen metabolism and stress-responsive genes (RD29, COR15 and ERD10), which might
indicate an important role of CDFs transcription factors in abiotic stress responses. Our results suggest
that CDF3 likely defines a cross-talk point of abiotic stress responses and flowering time signal
transduction pathways, and plays a multifaceted role in regulating Arabidopsis development and abiotic
stress tolerance.
53
Arabidopsis Cycling Dof Factor 3 CDF3
3.2.- MATERIAL AND METHODS.
3.2.1.- Plant material and growth conditions.
The Arabidopsis thaliana ecotype Columbia (Col-0) was used as the WT. The cdf3-1 T-DNA
insertion knockout mutant was obtained from the GABI-Kat (GK-808605; Rosso et al., 2003). Seeds were
surface-sterilized with 70% ETOH and 20% sodium hypochlorite, 20% SDS and washed with sterile water.
Stratification was performed by planting seeds on MS/2 medium (Murashige and Skoog, 1962) containing
0.5% (w/v) sucrose and 0.8% (w/v) agar and incubating them at 4 °C for 2 d. The plates were then
transferred to a growth chamber at 22 °C and 60% relative humidity (RH) under long-day growth
conditions (16/8 h light/dark). After 15 d, the seedlings were transferred to plastic pots containing a mixture
of substrate and vermiculite (3:1). Controlled environmental conditions were provided in growth chambers
at 22 °C and 60% RH under long-day growth conditions.
The tomato (Solanum lycopersicum L.) cultivar Moneymaker was used in this study. Tomato seeds
were surface sterilized in 4% sodium hypochlorite and washed with sterile purified water for 3 times. The
sterilized seeds were germinated on one-half strength MS (Murashige and Skoog, 1962) solid medium
containing 50 mg/L kanamycin under controlled conditions (25 ± 2 °C, 16/8 h light/dark cycle and 100
cultured hydroponically in aerated one-half strength Hoagland solution (Hoagland and Arnon, 1950) under
controlled conditions in growth chambers (25/18 ºC, 16/8 h light/dark cycle, 100 mol/m2 s1 light intensity
and 70%–80% relative humidity. The nutrient solution was renewed twice a week. Thirty-days-old plants
(three to four leaves) were used for stress assays. Sodium chloride was added at 75 mM in the nutrient
solution for saline stress. Plants were transferred to growth chambers at 10/5 ºC or 15/8 ºC for low
temperature stress. Control plants were maintained at 25/18 ºC in half strength nutrient solution. Gas
exchange and fluorescence measurements were performed after 14 days under stress conditions, and
biomass was assessed after 15 days (Renau-Morata et al., 2014).
54
Arabidopsis Cycling Dof Factor 3 CDF3
3.2.2.- Plasmid constructs and Arabidopsis transformation.
The open reading frame (ORF) of the AtCDF3 gene and the truncated version CDF3-stop (lacking
1035 to 1717bp of the C-terminal region) were cloned into pGWB2 binary vector under the control of the
35S promoter of Cauliflower Mosaic Virus (CaMV; Karimi et al., 2007) followed by the Nopaline synthase
gene (NOS) 3´terminator. The resultant plasmid was used to transform Arabidopsis thaliana (Col-0) plants
by the Agrobacterium tumefaciens-mediated floral dip method (Clough and Bent, 1998).Transformed
plants were selected on MS medium (Murashige and Skoog, 1962) containing 50 μg ml–1 of kanamycin.
For GUS histochemical staining experiments the promoter regions of AtCDF3 from - 1060 bp to the ATG
translation initiation codon) and CRUCIFERIN (from – 1200bp to the ATG translation initiation codon)
genes were cloned into a binary vector containing a β-glucuronidase (GUS; uidA gene) reporter gene,
producing an in-phase fusion with this reporter gene constructs pCDF3::GUS and pCRU::GUS,
respectively. The resultant plasmids were used to transform Arabidopsis plants.
3.2.3.- Tomato transformation.
The previously obtained construct 35S::AtCDF3 was used to transformed tomato plants var.
Moneymaker following the method described by Ellul et al. (2003). About 130 cotyledonary explants were
used for each construction. Explants were excise from plants were incubated 2 days in the dark on
preculture medium (CCM) and then were carefully submerged in Agrobacterium tumefaciens (LBA 4404
strain) inoculum in a Petri dish with gentle swinging. They were blotted dry on sterile filter paper and
transferred to the co-culture medium. After 72 h in the dark at 26ºC, the explants were washed twice with
liquid MS+2%sucrose medium for 15 min and after being blotted dry on sterile filter paper they were put
on shoot induction medium without selective pressure. After 48 h on 16:8h photoperiodic conditions,
explants were transferred to shoot-induction medium with 50 mg/L kanamycin. Every two weeks explants
were transferred to fresh medium. Individual shoots were excised and transferred to root-induction
medium. When the radicular system was fully developed, plants were transplanted to soil. Seeds from the
55
Arabidopsis Cycling Dof Factor 3 CDF3
transformed plants were harvested and plated on selective medium and kanamycin-resistant seedlings
were transplanted to soil.
3.2.4.- Histochemical GUS staining and subcellular localization of AtCDF3 protein.
Full length ORF of the AtCDF3 gene and the truncated version AtCDF3-stop were cloned into the
pK7WGF2.0 plasmid using the Gateway recombination system (Invitrogen) to generate C-terminal green
fluorescent protein (GFP) fusions driven by the cauliflower mosaic virus (CaMV) 35S promoter (Karimi et
al., 2007). The resultant plasmids were used in transient transformation experiments of onion cells and to
transform Arabidopsis plants by Agrobacterium tumefaciens-mediated floral dip method (Clough and Bent,
1998). Onion (Allium cepa L.) epidermal cells were transiently transform using particle bombardment with
a biolistic helium gun device (DuPont PDS-1000; Bio-Rad) as described by Diaz et al, (2002). The GFP
gene expressed under the control of 35S promoter was used as a control. Fluorescence images were
acquired after 40 h of incubation at 22 °C in the dark using a confocal microscope (LEICA Sp2 AOBS UV).
GUS histochemical staining of pCDF3::GUS and pCRU::GUS transgenic plants was performed as
described by Jefferson et al., (1987). Plant tissues were incubated in 100mM NaPO4, 2.5mM X-GlcA (5Bromo-4-Chloro-3-Indolyl-β-D-Glucuronic acid cyclohexyl-ammonium salt), 0.5mM K3Fe(CN)6, 0.5mM
K4Fe(CN)6 and 0.25% Triton X-100 at 37ªC overnight. Analyses were verified using at least eight
independent T1 lines. The images were taken using LEICA DFC 280 digital camera. For stress treatments
three-week-old transgenic pCDF3::GUS Arabidopsis plants were grown under control conditions (control)
or exposed to low (4°C) or high temperature (40ºC), for 24 h, dried on the bench (drought) for 24 h, or
treated with 100mM ABA for 24 h or 150mM NaCl for 24 h before staining.
56
Arabidopsis Cycling Dof Factor 3 CDF3
3.2.5.- Protoplast transformation and GUS assays.
Mesophyll protoplasts were isolated from rosette leaves of 3-week-old Arabidopsis plants grown in
soil (21/18 ºC, 8/16 h light/dark). Protoplast isolation and transfection was performed according to the
method described by Alonso et al. (2009). Plasmid DNA was prepared using a Genopure Plamid Maxi Kit
(Roche), and 5 µg of each pBT10-2xDOF-GUS (a dimer of the DOF binding element) and pCOR15::GUS
reporter plasmids and 14 µg of 35S::AtCDF3, 35S::AtCDF3-stop and 35S::SlCDF3 effector plasmids were
used for transfections. For normalization purposes, 1 µg of Pro35S::NAN plasmid (Kirby and Kavanagh,
2002) was added. Then, 20 µl of plasmid mixture (20 µg) and 200 µl of protoplasts were transferred to 2
ml microcentrifuge tubes following the procedure described in Weltmeier et al. (2006). GUS and NAN
enzyme assays were performed according to Kirby and Kavanagh (2002). The ratio of GUS and NAN
activities are represented as relative GUS/NAN units. For stress assays, protoplast were re-suspended in
250µl WI solution (control) or WI solution containing 25mM NaCl and ABA (100µM) or incubated in low
(4ºC) and high (37ºC) temperatures for 12h under controlled conditions (16 h/8 h light/dark cycle) in a
growth chamber except in the cold and heat treatments.
3.2.6.- RNA isolation and expression analysis by real-time RT-qPCR.
The expression of AtCDF3 gene, abiotic stress responsive genes (COR15, RD29A and ERD10),
and nitrogen metabolism genes (PEPC1, PEPC2, GS2, GLU1 and PK1) in AtCDF3 35S::AtCDF3 and
control lines (Col-0) was determined by RT-qPCR. Plants were maintained in growth chambers (21/18 ºC,
16/8 h photoperiod). Leaves of Arabidopsis of 3-week-old were collected and frozen into N2 and stored at 80°C until use for RNA extraction. Total RNA was extracted following Oñate-Sanchez and VicenteCarbajosa (2008) protocol and treated with DNase (Roche). For cDNAs synthesis, 2 µg of total RNA was
primed with oligo(dT)15 primers (Promega) using the Avian Myeloblastosis Virus Reverse Trascriptase
(AMV RT) (Promega) according to the manufacturer´s instructions. Arabidopsis UBIQUITIN10
(Czechowski et al., 2005) mRNA level (At5g25760) was used as control. A LightCycler®480 System
57
Arabidopsis Cycling Dof Factor 3 CDF3
(Roche) was used for real-time PCR (10 min at 95ºC, and 40 cycles of 95ºC for 15 s, 55ºc for 1min, 72ºC
for 10 s) using LightCycler®480 SYBR Green I Master (Roche). A final dissociation step was added to
provide the denaturing curve of the amplified products. In all treatments and conditions, three independent
samples from different extracts were used and each reaction was performed in triplicate. The primer pairs
used for amplification are described in Supplementary Table S3.1. Relative expression levels of the target
genes were calculated using the 2−ΔΔCT method (Livak and Schmittgen, 2001). Positive and negative
controls were included in the RT-qPCR analyses.
The expression levels of AtCDF3 gene in transgenic hetero- and homozygous tomato plants were
determined by RT-qPCR. Total RNA was extracted from 3 week-old plants following the protocol of OñateSanchez and Vicente-Carbajosa (2008) and treated with DNase (Roche). cDNA was synthesized from 2
μg of DNA-free RNA using the avian myeloblastosis virus reverse transcriptase and oligo(dT)15 primers
(Promega) according the manufacturer´s instructions. A LightCycler®480 System (Roche) was used for
real-time PCR (10 min at 95 °C, 40 cycles of 95 °C for 15 s, 55 °C for 1 min and 72 °C for 10 s) using
LightCycler® 480 SYBR Green I Master (Roche). In all the assays, three independent samples from
different extracts were used and each reaction was performed in triplicate. The primer pairs used for
amplification are described in Table S1. The UBIQUITIN3 gene from S. lycopersicum (Hoffman et al.,
1991) was used as reference gene. Relative expression levels of the target genes were calculated using
the 2-ΔΔCT method (Livak and Schmitten, 2001).
3.2.7.- Germination and post-germinative growth assay.
Germination, post germinative and root growth assays were carried out using control plants (Col-0),
cdf3-1 and 35S::AtCDF3 transgenic lines. Seeds were collected at the same time and obtained from
plants grown in the same conditions. For germination studies seeds were surface-sterilized as describe
above, laid on MS medium or MS containing various concentrations of Mannitol (200 and 250 mM) and
held 4ºC for 2d in dark before being transferred to 22ºC and 60% RH under long-day growth conditions.
58
Arabidopsis Cycling Dof Factor 3 CDF3
Germination was scored as radicle emergence through the endosperm and testa every 24 h; assess the
green cotyledons and true leaves. All the assays were carried out in triplicate with at least two
independent seed batches and expressed as a percentage of the total number of seeds plated. Statistical
analysis was carried out by one-way analysis of variance (ANOVA) followed by a Student Newman-Keuls
test (P<0.05). For osmotic root length assays, seeds were sterilized and plated onto Petri dishes
containing MS medium. After 6 d, the seedlings were transferred to vertical plates containing MS medium
(control) and MS medium supplemented with 200 mM mannitol (Lakhssassi et al., 2012). About 20
seedlings were used per replicate and three replicates were made for each treatment. Primary root
elongation was measured after 10 d using ImageJ software (Abràmoff et al., 2004, Corrales et al., 2014).
To evaluate growth differences between control and saline stress, data were represented as the
percentage of root growth reduction relative to standard conditions. Statistical analyses were carried out
by one-way analysis of variance (ANOVA) followed by a Student–Newman–Keuls test (P<0.01).
3.2.8.- Photosynthesis and leaf fluorescence measurement.
Net photosynthesis and related gas exchange variables, stomatal conductance and substomatal
CO2 were determined using an LI-6400 infrared gas analyser (LICOR Biosciences, Lincoln, USA).
-2
s-1), 400 ppm
CO2, ambient temperature and a vapour pressure difference (vpd) between 1 and 2 kPa. Maximum
photochemical efficiency (Fv/Fm) on dark-adapted leaves was measured using a portable pulse amplitude
modulation fluorometer (MINI PAM, Walz, Effeltrich Germany). Responses to osmotic stress were
performed using three-week-old Arabidopsis plants that were transplanted to hydroponic culture, and
photosynthesis parameters were measured after 7 days of growth by adding 5% PEG-8000 (24h). The
analyses of ABA response were performed using four-week-old plants grown in soil by spraying with 0.5
µM ABA solution in the underside of the leaves and measurements were made after 1, 2 and 3.5 hours
after treatment.
59
Arabidopsis Cycling Dof Factor 3 CDF3
For tomato analyses thirty-days-old plants (three to four leaves) were used for stress assays. Sodium
chloride was added at 75 mM in the nutrient solution for saline stress. Plants were transferred to growth
chambers at 10/5 ºC or 15/8 ºC for low temperature stress. Control plants were maintained at 25/18 ºC in
half strength nutrient solution. Gas exchange and fluorescence measurements were performed after 14
days under stress conditions, and biomass was assessed after 15 days. One measurement per plant was
taken on the third or fourth leaf from the apex. Eight to ten different plants were used. Fresh weight of
shoots and roots, stem height, number of leaves and total leaf surface were determined. Shoot and root
dry weights were measured after drying at 60 ºC for 48 h. For each genotype and treatment, eight to ten
plants were measured.
3.2.9.- Drought and cold stress tolerance assay.
Cold and drought stress assay were carried out using control plants (Col-0) and cdf3-1,
35S::AtCDF3 and 35S::AtCDF3-stop transgenic lines. Drought stress tolerance tests were performed on
plants grown in soil in individual pots. After 2 weeks, the water supply was cut off for 15 days and then
watering was resumed during 10 d. Plant survival rates were calculated afterwards and fresh weight was
measured 10 d after re-watering period. Statistical analysis was carried out by one-way analysis of
variance (ANOVA) followed by a Student Newman-Keuls test (P<0.05). Freezing tolerance was analyzed
by exposing non-acclimated or cold-acclimated (7 days at 4ºC) 2-week-old plants to -5 and -6ºC or -9 and10ºC for 6 h, respectively. Tolerance was determined as the capacity of plants to resume growth 2 weeks
after returning to control conditions.
3.2.10.- Microarray analysis.
Genome-wide expression studies with ATH1 array (Affymetrix) were performed using 3-week-old
35S::AtCDF3 and Col-0 plants, growth in chambers (21/18 ºC, 16/8 h photoperiod). Leaves of Arabidopsis
were collected and frozen into N2 and stored at -80°C until use for RNA extraction. Total RNA was
60
Arabidopsis Cycling Dof Factor 3 CDF3
extracted following Oñate-Sanchez and Vicente-Carbajosa (2008). Three arrays for the different plant
materials were hybridized according the affymetrix GeneChip Expression Analysis manual
(www.affymetrix.com). Differentially expressed Arabidopsis genes in 35S::AtCDF3 compared to WT plants
(1.5 fold; P value<0,05) were selected. They were functionally annotated by search in the TAIR
Arabidopsis
database,
classified
using
the
e-northern
expression
browser
tool
(http://bar.utoronto.ca/affydb/cgi-bin/affy_db_exprss_browser_in.cgi) (Toufighi et al., 2005) and listed in
Supplementary
Table
S3.2.
Venn
diagrams
were
performed
using
(http://bioinfogp.cnb.csic.es/tools/venny; Oliveros, 2007). Gene Ontology analyses of the
venny
tools
differentially
regulate genes (fold change > 1.5 ) in 35S::AtCDF3 transgenic plants compared to Col-0 were performed
using agriGO (http://bioinfo.cau.edu.cn/agriGO/) (Du et al., 2010) and REVIGO (http://revigo.irb.hr/)
(Supek et al., 2011) software.
3.2.11.- Metabolomic analyses.
Non-targeted and targeted metabolomics analyses were performed on 12-d-old control plants (Col0) and two independent 35S::AtCDF3 lines. Extraction, manipulation and mass spectrometric analysis of
samples followed an adapted protocol, detailed in Supplementary File 4.1, which is based on previously
described methods (Fiehn et al., 2000; Gullberg et al., 2004; Gaquerel et al., 2010).
61
Arabidopsis Cycling Dof Factor 3 CDF3
3.3.- RESULTS.
3.3.1.- Abiotic stress response and expression pattern of AtCDF3.
To identify new DOF factors that might be involved in harmonizing abiotic stress responses with the
developmental program in Arabidopsis, in silico expression analyses using the complete set of DOF genes
encoded in the Arabidopsis genome (Lijavetzky et al., 2003) were performed. Thus, we first examined the
expression patterns of all Arabidopsis DOF members using the available data on the database
(http://bar.utoronto.ca/efp/cgi-bin/efpWeb.cgi) and found that the ones of group D are differentially
expressed in response to different abiotic stresses such as drought, salinity and extreme temperatures in
vegetative tissues (Fig. 3.1). Interestingly, inside the D group the set Cycling Dof Factors (AtCDF1–5)
exhibited higher levels of induction under some of those stresses. Among the genes belonging to group D,
AtCDF3 was further characterized.
To further confirm that AtCDF3 expression is controlled by different environmental cues, we
performed a detailed RT-qPCR expression analyses using RNA isolated from 3-week-old Arabidopsis
plants that had been subjected to different abiotic stresses such as salinity, high and low temperatures,
dehydration and exogenous ABA treatments for different periods of time. As it is shown in Figure 3.2, in
leaf tissues transcripts levels of AtCDF3 are significantly increased in response to temperature stress,
dehydration, high salt, and exogenous ABA treatment although with different dynamics and extents. In
fact, AtCDF3 transcript levels increased at higher levels in response to extreme temperatures, dehydration
and ABA treatment, although an earlier induction at was observed in response to dehydration treatments
reaching maximum levels at 4h. Moreover induction of AtCDF3 was also observed in leaf tissues under
salt treatment but later reaching maximum levels at 24h.
62
Arabidopsis Cycling Dof Factor 3 CDF3
A
B
Figure 3.1. (A) Phylogenetic tree Arabidopsis DOF proteins. The tree was inferred by the neighbor-joining method after the
alignment of DOF domain amino acid sequences of the Arabidopsis DOFs. (B) Expression Profiles of the AtCDFs genes from
Arabidopsis in
shoot and root under cold, osmotic, salt, drought, oxidative, UV
and heat stress in
(http://bar.utoronto.ca/affydb/cgi-bin/affy_db_exprss_browser_in.cgi).
In order to perform a deeper analyses of the spatial expression patterns of AtCDF3 in different
plant tissues in response to abiotic stress, a promoter sequence covering 1-kb region upstream of the
AtCDF3 transcription start site was fused to a GUS-coding sequence, and the promoterAtCDF3::GUS
reporter was transformed into wild-type plants (WT). First, we studied the spatial expression patterns
during plant development. Overall It was observed low levels of GUS expression under control conditions
in all tissues of adult plants, however it was detected significantly staining in vascular systems of leafs and
stems, and guard cells (Fig. 3.3A). Moreover, flowers showed also GUS activity in pollen, petals, anthers
and stigmatic papillae with pollen (Fig. 3.3A).
63
Arabidopsis Cycling Dof Factor 3 CDF3
3.2. Transcription analysis of AtCDF3 gene by RT-qPCR in Arabidopsis plants exposed to different abiotic stress
conditions. Total RNA was isolated from leaves of 3-week-old Arabidopsis plants grown under control conditions (control),
treated with 150mM NaCl, low temperatures (4ºC), 100µM ABA (ABA), heat (40ºC) (A) or dried on the bench (drought) for the
indicated periods of time (B). Expression of the Arabidopsis UBIQUITIN10 gene (Czechowski et al., 2005) was used as a
reference gene. All data are expressed as means ± SE of three independent pools of extracts. Three technical replicates were
performed for each extract.
Interestingly, AtCDF3 promoter also provides a strong GUS staining in mature seeds, showing
maximum levels of expression in later maturation stage as compared to the GUS staining pattern
observed of the well characterized seed Cruciferin gene (pCRU::GUS, Fig. 3.3B, Suzuki et al., 2001).
When 2 weeks old transgenic plants containing the AtCDF3::GUS transgene were exposed to different
abiotic stresses such us low and high temperatures, dehydration and ABA or high salt treatments, GUS
expression increased but with very similar patterns in all cases, regardless of the treatment or the
transgenic line analyzed (Fig. 3.3D). Thus GUS staining was detected in leaves, both lateral and main
roots and stems, being especially strong in vascular bundles (Fig. 3.3C). Taken together, all these results
indicate that the expression of AtCDF3 is regulated during plant development and also in response to
different abiotic stresses and that this regulation occurs at least partially through transcriptional level.
64
Arabidopsis Cycling Dof Factor 3 CDF3
B
A
I
II
III
IV
promoAtCDF3
GUS
promoCRU
GUS
V
I
II
III
IV
V
VI
C
AtCDF3
D Control
4ºC
Drought
NaCl
ABA
40ºC
Figure 3.3. Histochemical localization of GUS activity in adult pCDF3::GUS transgenic Arabidopsis plants grown under
control conditions or exposed to different abiotic stresses. (A) GUS activity in plants grown under control conditions. I, in
flower and pollen, II, young leave and III stomata; IV, secondary root and radicle and V, stem. (B) GUS activity in pCDF3::GUS
and pCRU::GUS during seed development and germination. I and IV staining of pCDF3::GUS and pCRU::GUS in mature seeds,
respectively. II and V staining of pCDF3::GUS and pCRU::GUS seeds in phase maturation of development, respectively. III and IV
staining of pCDF3::GUS and pCRU::GUS seeds after 7 days of germination, respectively. (C) Expression analyses of CDF3 in
different organs of Arabidopsis. Northern blot analysis were performed with total RNA isolated from the indicated organs of adults
Arabidopsis plants and hybridized with a CDF3 specific probe.(D) Histochemical localization of GUS activity in three-week-old
transgenic pCDF3::GUS Arabidopsis plants grown under control conditions (control) or exposed to low (4°C) or high temperature
(40ºC), for 24 h, dried on the bench (drought) for 24 h, or treated with 100mM ABA (ABA) for 24 h or 150mM NaCl for 24h.
3.3.2.- AtCDF3 protein localize to the cell nucleus and display specific DNA-binding and
activation properties
To investigate the subcellular localization of AtCDF3 protein, translational fusions of their
corresponding ORFs to the C- terminus of GFP were made. These constructs, driven by the control of
35S promoter, were used for both transient assays of onion epidermal cells by particle bombardment and
for transformation Arabidopsis plants. Figure 3.4A, shows that the GFP-AtCDF3 fusion protein was
localized in the nuclei of onion epidermal cells, in contrast GFP control was observed in both nuclei and
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Arabidopsis Cycling Dof Factor 3 CDF3
cytoplasm of these cells. Similar results were obtained in when analyzed transgenic plants were analized
(Fig. 3.4B).
Figure 3.4. Subcellular localization and transcriptional activation properties of AtCDF3 protein. (A) Subcellular localization
of the AtCDF3 protein in onion epidermal cells. GFP alone (35S::GFP) or GFP-AtCDF3 (35S::GFP-AtCDF3) fusion proteins were
expressed transiently under the control of the CMV35S promoter in onion epidermal cells. After 36h of incubation, tissues were
observed with a confocal microscope for the emission spectrum of the GFP o by Nomaski imaging. Arrows indicate cell nuclei (B)
Confocal images of roots of transgenic Arabidopsis 35S::GFP-AtCDF3 and 35S::GFP-AtCDF3-stop plants. Arrows indicate cell
nuclei. (C) Transcriptional activation assays of AtCDF3 and AtCDF3-stop gene in transient expression experiments. Arabidopsis
protoplasts were transfect with the 35S::AtCDF3 and 35S::AtCDF3-stop effectors plasmids and reporter plasmid pBT10-2xDOFGUS. Tomato homologous gene (SlCDF3) was used as a positive control (Corrales et al., 2014). (D) Transient expression
analyses, co-transfection of protoplasts with pBT10-2xDOF-GUS reporter plasmid and empty effector plasmid and exposed to
different abiotic stresses such as NaCl (25mM), ABA (10µM), extreme temperatures (4ºC and 37ºC) for 15h. Empty pK7WGF2.0
plasmid was used as a negative control. Data are expressed as means ± standard error (SE) of three independent experiment
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Arabidopsis Cycling Dof Factor 3 CDF3
We further analyzed whether the conserved C-terminal region is important for the localization and
translational fusion to the AtCDF3 cDNA lacking the C-terminal region (amino acids 221-448; 35S::GFPAtCDF3-stop) were made and analyzed as previously indicated. The results obtained shown in Figure
3.4B, indicates that GFP-AtCDF3-stop protein change the localization pattern, and green fluorescence
was detected barely in the nucleus but also in the cytoplasm as multiple bright small spots. These results
indicate that AtCDF3 is a nuclear protein and that C-terminal domain also might play important roles in the
stability and its nuclear localization.
To gain deeper understanding of AtCDF3 function we analyzed the transcriptional activities of
AtCDF3 and transient expression analyses in Arabidopsis protoplasts were performed. Thus, effector
plasmids containing Arabidopsis CDF3 driven by the 35S promoter (35S::AtCDF3), and the previously
characterized tomato SlCDF3 (35S::SlCDF3) as positive control, were co-transfected with reporter plasmid
harboring a GUS gene under control of a minimal promoter containing a 2×DOF cis-DNA element (pBT102×DOF::GUS). The results obtained confirmed that AtCDF3 could binds to the 5′-AAAG-3′ cis-DNA
element, and also that can moderate activate the GUS reporter gene in a similar way than the tomato
homologous gene SlCDF3. We further studied whether the conserved C-terminal region is important for
transcriptional activities and effector plasmid that contains AtCDF3 cDNA lacking the C-terminus region
(35S::AtCDF3-stop) were used and analyzed as previously indicated. The results obtained shown in
Figure 3.4C, indicates that the truncated AtCDF3 was not able to promote the transcription of the reporter
plasmid. These data indicate that C-terminal domain might be also essential for its transcription
capabilities.
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Arabidopsis Cycling Dof Factor 3 CDF3
3.3.3.- Overexpression of AtCDF3 enhanced drought and low temperature tolerance in
Arabidopsis.
Our expression analyses indicated that AtCDF3 might play an important role in the plant response
to different abiotic stresses. In order to further explore the AtCDF3 role in plant, and phenotypic
characterization of gain- and loss- function plants was performed by analyzing their response under abiotic
stresses, such as dehydration and low temperatures. Thus Arabidopsis plants overexpressing full length
AtCDF3 under the control of the CaMV 35S promoter were generated, and two homozygous lines with
relatively high expression of AtCDF3 were selected for further analyses (Fig. 3.5B). Moreover a T-DNA
insertion mutant cdf3-1 (GK808G05) without cdf3 expression was also identified and the insertion site was
localized 309 bp from the ATG (Supplementary Fig S3.1). When cultured in soil under greenhouse
conditions, cdf3-1 plants do not presented significant developmental differences relative to WT plants (Col0). Nevertheless, all transgenic 35S::AtCDF3 lines (L2.1 and L5.4) exhibit several developmental
differences relative to cdf3-1 and WT (Supplementary Fig S3.2).
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Arabidopsis Cycling Dof Factor 3 CDF3
Figure 3.5. Drought and osmotic tolerance of 35S::AtCDF3, cdf3-1 and Col-0 plants. Drought stress tolerance was estimated
by scoring fresh weight (A) and survival rates (B) of 3-week-old 35S::AtCDF3 (L2.1 and L5.4), 35S::AtCDF3-stop (L1.7 and L7.2),
control (Col-0) and cdf3-1 plants, which were maintained for 15 days without irrigation and then 10 days of re-watering. Fresh
weight is expressed as means ± SE of two independent experiment with eight plants. Different letters indicate significant
differences between Col-0, cdf3-1 35S::AtCDF3 and 35S::AtCDF3-stop overexpressing lines (P<0.05; ANOVA Student-NewmanKeuls tests). C) mRNA levels of AtCDF3 gene was analyzed by RT-qPCR in different T3 independent 35S::AtCDF3 (L2.1 and
L5.4) and 35S::AtCDF3-stop (L1.7 and L7.2) transgenic lines. Letters indicate significant differences compared to Col-0 (P<0.05;
ANOVA Student-Newman-Keuls tests). Osmotic stress tolerance was estimates by scoring germination and primary root length of
reduction in 35S::AtCDF3 (L2.1), Col-0 and cdf3-1 plants under different osmotic stress conditions. (D) Germination rates of
35S::AtCDF3, Col-0 and cdf3-1 plants under osmotic stress treatment.35S::AtCDF3 (L2.1), Col-0 and cdf3-1 seed were
germinated under different a concentration of mannitol. The germination rates were calculated after 4 days after radicle
emergence and appearance of green cotyledons was also scored at 5 days. All the assays were carried out in triplicate and
expressed as a percentage of the total number of seeds plated. Statistical analysis was carried out by one-way analysis of
variance (ANOVA) followed by a Student Newman-Keuls test (P<0.05). (E) Root elongation assays. Six-day-old seedlings were
transferred MS agar plates or supplemented with 200mM mannitol and incubated vertically for 10 d before primary root length
were estimated. Results are represented as percentage of reduction relative to standard conditions Data are expressed as means
± standard errors of three independent experiments with at least 20 plants each. Letters indicate significant differences between
Col-0, cdf3-1 and 35S::AtCDF3 overexpressing lines (P<0.05; ANOVA Student-Newman-Keuls tests. Representative images of
Col-0, cdf3-1 and 35S::AtCDF3 plants after the 10 d of treatment.
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Arabidopsis Cycling Dof Factor 3 CDF3
Plants overexpressing AtCDF3 flowered slightly later than control plants under LD conditions.
Interestingly, similar results were obtained previously by Fornara et al, (2009) when overexpress AtCDF3
in companion cells using SUCROSE TRANSPORTER 2 (SUC2) promoter. However, when those lines
were subjected to water deprivation for 15 days and allowed to recover for 10 d during which they were
watered, important differences were found. Interestingly, WT and cdf3-1 plants exhibited similar severe
symptoms of water loss and significant wilting; only a little green color was visible in some leaves (Fig.
3.5B). In contrast, most of the 35S::AtCDF3 transgenic plants were less affected, keeping healthy greener
leaves. In fact after 10 d recovery period, most 35S:: AtCDF3 transgenic plants exhibited better survival
rates and fresh weight than WT and cdf3-1 plants, respectively (Fig. 3.5A,B).
To get insight and confirm the tolerance phenotypes observed in response to drought we also
further study osmotic stress tolerance, and then different germination and roots elongation studies were
conducted. First, we studied germination and the appearance of green cotyledons of 35S::AtCDF3, cdf3-1
and WT seeds when germinated on MS (control) or MS supplemented with 200 or 250mM mannitol and
scored after 4 and 5 days, respectively. When sown on control MS medium all genotypes 35S::AtCDF3,
cdf3-1 and WT seeds germinated equally well. However, when the lines where grown in 200 or 250mM
mannitol, germination and the appearance if green cotyledons rates in both treatments where clearly
higher in 35S::AtCDF3 than WT plants (Fig. 3.5D). By contrast compared to WT control, percentage of
germination of cdf3-1 seeds was significantly and consistently lowers. Similar results were obtained when
appearance of green cotyledons were scored (Fig. 3.5D). In a second experiment, primary elongation
assays were conducted and 35S::AtCDF3, cdf3-1, and WT plants were grown either on MS medium
(control) or on MS medium supplemented with 200 mM mannitol for 10 d (Fig. 3.5E). Under control
conditions, there was no difference between the gain and loss of function lines and WT plants. In contrast
on osmotic stress medium, 35S::AtCDF3 lines showed slight but significant lower values of primary growth
inhibition than the WT. In contrast, in the case of the cdf3-1 mutant exhibited lower values of root primary
growth inhibition than WT plants under similar stress conditions (Fig. 3.5E).
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Arabidopsis Cycling Dof Factor 3 CDF3
In a further step, as low temperatures rapidly induced the expression of AtCDF3 we decide studied
the freezing tolerance of AtCDF3 gain- and loss-of- function plants. Freezing tolerance was determined in
non-acclimated and cold-acclimated (7 d at 4º C) and 35S::AtCDF3, cdf3-1 and WT plants as their
capacity to resume growth after being exposed for 6 h to different freezing temperatures when returned to
control conditions. Figure 3.6A shows that while the AtCDF3 overexpressor plants exhibit higher levels of
freezing tolerance than WT plants when non-acclimated, cdf3-1 exhibited significant lower freezing
tolerance to the WT plants. Moreover, 35S::AtCDF3 lines were also significantly more freezing tolerant
than the WT line after cold acclimation (Fig. 3.6B) but the cdf3-1 plants were significantly impaired in their
capacity tolerate freezing. The freezing tolerance phenotypes of non-acclimated and cold-acclimated WT,
cdf3-1 and 335S::AtCDF3 plants are displayed in Figure 3.6, respectively, as a representative example.
Collectively, these data suggested that AtCDF3 may be involved in plant responses and tolerance to
drought, osmotic and low temperature stresses.
Figure 3.6. Freezing tolerance of 35S::AtCDF3, cdf3-1 and Col-0 plants. (A) Non acclimated two-week-old 35S::AtCDF3
transgenic, Col-0 and cdf3-1 and plants were exposed to indicated freezing temperatures for 6h. (B) Two-week-old Arabidopsis
plants were exposed to the indicated freezing temperatures for 6 h after being acclimated 7 d at 4ºC. Freezing tolerance was
estimated as the percentage of plants surviving each specific temperature after 7d of recovery under control conditions. Data are
expressed as means ±SE of the three independent experiments with 50 plants each. On each time point, different letters indicates
significant differences (P<0.05 ANOVA followed by Student-Newman Keuls test).
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3.3.4.- AtCDF3 overexpression increased photosynthesis and stomatal aperture.
To investigate the underlying mechanisms involved the response to 35S::AtCDF3 and cdf3-1 plants
to drought stress we examined different physiological parameters such as net photosynthesis and related
gas exchange variables, stomatal conductance and sub stomatal CO2 using an LI-6400 infrared gas
analyzer (LICOR Biosciences, Lincoln, USA). Thus, three-week-old 35S::AtCDF3 (L2.1), cdf3-1 and
control (Col-0) plants were transplanted to hydroponic culture, and photosynthesis parameters were
measured 24 hours after treatment with 5% PEG-8000 and represented as percentage to control
conditions. The results shown in Figure 3.7 reveal that net photosynthesis (An) of 35S::AtCDF3 plants,
under control conditions, are similar to those of WT and cdf3-1 plants. Interestingly, when the same lines
where grown in osmotic stress conditions different reduction of photosynthetic rate among genotypes was
observed when compared to control conditions (Fig. 3.7A). In fact, while AtCDF3 overexpressing plants
exhibit significant higher values that WT plants, cdf3-1 show lower values than the control (Fig. 3.7A). As
photosynthetic efficiency is correlated with the rate of stomatal conductance, a considerably higher rate of
stomatal conductance (Gs) were also observed in 35S::AtCDF3 overexpression lines compared with the
WT, by contrast cdf3-1 show lower values than WT. Furthermore, the higher increase in the substomatal
CO2 concentration in the control plants (292 to 315 µmol/mol) compared to cdf3-1 (297 to 316 µmol/mol)
under osmotic stress suggests higher biochemical limitations to photosynthesis. Accordingly, it was
observed a reduction in the maximum quantum yield of PSII (Fv/Fm) in cdf3-1 and WT plants which
indicates the existence of photo inhibition events, whereas this parameter was not affected by PEG
treatment in 35S::AtCDF3 plants (Fig. 3.7B).
Since stomatal conductance in greatly affect by ABA, we decided to investigate the possible role of
ABA in the different responses of the stomatal conductance observed in the analyzed lines. Thus, fourweek-old 35S::AtCDF3 (L2.1), cdf3-1, and control (Col-0) plants grown in soil were analyze by spraying
with 0.5 µM ABA solution in the underside of the leaves and measurements photosynthesis parameters
were made 1, 2 and 3.5 h after treatment. The results obtained revealed that there lines analyzed show
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Arabidopsis Cycling Dof Factor 3 CDF3
significant differences photosynthesis parameters with different dynamics and extents (Fig. 3.7C). While
control and cdf3-1 plants exhibit a similar significant reduction of stomatal conductance values after 1 hour
spraying with ABA (to a 60% of the non-treated values), 35S::AtCDF3 overexpressions plants exhibit a
delayed response with almost no effect after 1 hour of the treatment. However at longer times after
treatment (2-3h), 35S::AtCDF3 plants finally reach similar values of stomatal conductance than WT and
cdf3-1 plants. Correspondingly photosynthetic rate followed a similar response (Fig. 3.7D), showing an
earlier decrease (0-2 h) in control and loss- of- function plants, and delayed in 35S::AtCDF3 plants,
although equaled to the former ones after 3.5 hours. Collectively, these data suggested that AtCDF3 might
be involved in plant responses to abiotic stress by maintaining higher rates of photosynthesis under
unfavorable environmental conditions.
3.3.5.- The effect of AtCDF3 on drought tolerance is related to its transcriptional activity.
To examine whether AtCDF3 exerts effect in abiotic stress tolerance such us drought though its
transactivation activity a truncated form of AtCDF3 cDNA lacking the conserved C-terminal region, driven
by 35S promoter (35S::AtCDF3-stop), were used to transform Arabidopsis plants. Two homozygous
transgenic lines harboring the mutated gene with relatively high expression of truncated form AtCDF3-stop
were selected for further analyses (Fig. 3.5C). A phenotypic characterization 35S::AtCDF3-stop plants was
performed by analyzing their response to drought conditions as described previously. When cultured in
soil under greenhouse conditions, all overexpressing truncated 35S::AtCDF3-stop lines (L1.7 and L7.2)
plants do not presented significant developmental differences relative to WT plants. Notably recovering a
flowering time similar to the one of WT plants (Supplementary Figure S3.3). Interestingly, when those lines
were subjected to water deprivation for 15 days and allowed to recover for 10 d during which they were
watered, slight but significant differences were found. In fact all 35S::AtCDF3-stop transgenic plants were
less affected than WT, after 10 d recovery period, and exhibited better survival rates and fresh weight
values than WT, but significant lower (~2 fold) than the ones exhibited in transgenic plant overexpressing
full length AtCDF3 (Fig. 3.5A,B). All this data suggest that the AtCDF3 C-terminal domain might be
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essential for its functional capabilities, but the fact that the truncated form still promotes a significant effect
indicate that additional domain(s) in AtCDF3 protein might be also important for the function.
Figure 3.7. Effect of osmotic stress and ABA treatments on the reduction of stomatal conductance and photosynthetic
rate in 35S::AtCDF3, cdf3-1 and Col-0 plants. (A) Photosynthetic (An) rate and the maximum quantum yield (Gs) and (B)
chlorophyll florescence were estimated in three-week-old Col-0, cdf3-1 and 35S::AtCDF3 Arabidopsis plants that were
transplanted to hydroponic culture, and photosynthesis parameters were measured after 7 days of growth (control) or by adding
5% PEG-8000 (24h). Measurements were performed at steady state under saturating light (PAR 1000 mmol m-2 s-1), 400 ppm
CO2, ambient temperature and a vapour pressure difference (vpd) between 1 and 2 kPa. An and Gs were referred to the values at
control conditions. Each value is means ±SE of eight different measurements after 24 h under stress conditions. On each
parameter, different letters indicate significant differences (P<0.05). Effect of 0.5 µM ABA on the reduction of photosynthetic rate
(D) and stomatal conductance (E) in Col-0, cdf3-1 and 35S::AtCDF3 Arabidopsis plants. The analyses of ABA response were
performed using four-week-old plants grown in soil by spraying with 0.5 µM ABA solution in the underside of the leaves and
measurements were made after 1, 2 and 4 hours after treatment. For each genotype, values are referred to the parameter at t=0.
Each value is mean (±SE) of six different measurements. On each time point, different letters indicates significant differences
(P<0.05).
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Arabidopsis Cycling Dof Factor 3 CDF3
3.3.6.- Transcriptome analysis of transgenic Arabidopsis overexpressing AtCDF3.
To clarify the AtCDF3 effects in regulation of the expression of abiotic stress-responsive genes and to
further understand the molecular mechanisms involved in the higher tolerance to drought and low
temperatures, a transcriptome of 3 week-old 35S::AtCDF3 (Line 2,1) and control (Col-0) plants was
performed using the affymetrix Arabidopsis oligo microarray. The analysis of transcriptome reveals that
among ~24,000 Arabidopsis genes the transcription levels of 641 was differentially expressed (with more
than two-fold change P>0,05) in AtCDF3 overexpressing plants compared with WT plants (Supplementary
Table S3.2; Fig. 3.8). About two-thirds (409) were up-regulated, whereas 122 were down-regulated.
Moreover detailed classification of the identified genes using the e-northern expression browser tool
(Toufighi et al., 2005) indicated that among the up-regulated genes 337, 109, 147 and 76 were
significantly misregulated (>1.5 fold) in at least one time point during drought, low temperature, salinity
and osmotic stresses, respectively (Fig. 3.8A). In the other hand, among the down-regulated in the
35S::AtCDF3 plants 22, 48, 52 and 30 genes were significantly misregulated in response to those
treatments, respectively. Overall these data indicated that many drought-, low temperature-, salinity- or
osmotic- inducible genes are potentially downstream of AtCDF3, including RD29A, COR15, ERD10 and
many others. Interestingly, we observed a significant overlap between the AtCDF3 regulated genes in
response to different abiotic stresses such as osmotic, drought, cold and salinity, indicating that a common
regulatory mechanism conferred by AtCDF3 is present in response to different abiotic stresses, especially
in the regulation of biosynthesis of protective compounds and/or control of primary metabolism (Fig. 3.9).
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Arabidopsis Cycling Dof Factor 3 CDF3
Figure 3.8. Classification and Gene Ontology (GO) analyses of the genes differentially expressed in AtCDF3 overpresing
lines compared with WT plants. A-B) Venn diagrams showing overlap of up-regulated and down-regulated genes expressed in
35S::AtCDF3 transgenic plants compared with wild-type plants in response to different stresses. In silico expression analyses and
classification of 35S::AtCDF3 up-regulated (left) and down regulated (right) genes in response to cold, osmotic, salt and drought
stresses, by using e-Northern Expression Browser (http://bar.utoronto.ca). C-D) The scatter plot shows the cluster representatives
(terms remaining after reducing redundancy) in a two-dimensional space derived by applying multi-dimensional scaling to a matrix
of GO terms semantic similarities. The scatter plot was performed using http://revigo.irb.hr/revigo.jsp with list produced by the
analysis of functional categories defined by the Gene Ontology (GO) AgriGO (http://bioinfo.cau.edu.cn/agriGO/). Bubble color
indicates the p-value for the false discovery rates derived from the AgriGO analysis as well as biological processes.
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Arabidopsis Cycling Dof Factor 3 CDF3
Quantitative RT-qPCR was performed to confirm some of the identified differentially regulated genes in
the 35S::AtCDF3 plants. Thus we analyzed the expression levels different classical abiotic stressresponsive genes such as COR15A, RD29A and ERD10 in 35S::AtCDF3 lines (L2.1 and L5.4) and WT
plants under control conditions. Figure 3.9A shows the expression levels of the analyzed genes in
transgenic lines, where they exhibited higher values (from two- to fourfold) than in WT plants. These data
also confirmed the validity of the chip experiment and indicated that AtCDF3 might be upstream activator
in drought and low temperature stress pathways, acting directly or indirectly on the expression of different
stress-regulated target genes.
To elucidate whether AtCDF3 might directly regulated abiotic stress responsive genes, we first
searched for a common cis- acting elements present in the promoters of the AtCDF3 misegulated genes
using the promoter tool (Toufighi et al., 2005). We found enrichment in ABRE and DRE motifs like
(ACGTG and CCGAC, respectively) that have been identified as cis acting elements regulating gene
expression in response to drought, salt and cold stresses in Arabidopsis (Hao et al., 2002; Sakuma et al.,
2002). Interestingly we also found that many of them contain the DOF DNA-binding motifs 5´-T/AAAG-3´
in their promoter regions and among them COR15 gene was selected as a potential target of AtCDF3 for
further studies (Supplementary Figure 3.4S). In order to analyze the transcriptional activities properties of
AtCDF3, transient expression analyses in Arabidopsis protoplast were performed. Thus 35S::AtCDF3
effector plasmid was cotransfected with a reporter plasmid harboring GUS reporter gene under control of
1kb promoter region of COR15 containing 17 DOF cis-DNA binding elements (Supplementary Figure
S3.5). As shown in Figure 3.9, AtCDF3 could activate the expression of the reporter gene likely though
one of the DOF binding sites present in the COR15 promoter.
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Arabidopsis Cycling Dof Factor 3 CDF3
All the previous expression data point to DOF cis-acting element might be play a role as an abiotic
stress response element. In order to verify this idea transient expression analyses were made in
Arabidopsis and effector plasmids with reporter plasmid harboring a GUS gene under control of a minimal
promoter containing a 2×DOF cis-DNA element (pBT10 2×DOF-GUS) were used to transform Arabidopsis
protoplast and then incubated under different stress conditions such as extreme temperatures (4ºC and
37ºC) or treated with NaCl (25mM) and ABA (100µM) for 12h. The results obtained indicated all tested
conditions activated the reporter gene but to different extents (Fig. 3.4D). Notably, higher levels of GUS
activity were observed in protoplasts exposed to low and high temperatures (>1,5 fold), whereas slightly
higher levels than the control untreated were detected in those protoplasts that were treated with salt and
ABA. Overall, the data obtained indicated 5′-AAAG-3′ DNA DOF binding site is a new cis-acting abiotic
stress response element and that the CDFs might be the nuclear trans-acting factors candidates that
control its activity.
In order to better understand the regulatory mechanism of AtCDF3 mediated regulation of stress
responses
we
performed
gene
ontology
(GO)
analyses
using
agriGO
tool
(http://bioinfo.cau.edu.cn/agriGO/) (Du et al., 2010) of genes that are differentially expressed in
35S::AtCDF3 overexpressing line compared to WT plants. As shown in Figure 3.8C-D, GO terms like
response to stimulus (abiotic and biotic) and primary metabolism was overrepresented, but especially
those related to protein metabolism terms (Fig. 3.8C). Interestingly among them, some are involved in
nitrogen assimilation which could indicate that AtCDF3 might function as upstream regulators in nitrogen
assimilation pathways. Thus we decide to analyze the expression levels of several key genes involved in
nitrogen assimilation such us glutamine synthetase 2 (GS2) and glutamate synthase (GLU) in
35S::AtCDF3 lines and WT plants. Figure 3.9B shows the expression levels of the analyzed genes in
transgenic lines exhibited higher values (two- to four fold) than in WT plants. These results might indicate
that AtCDF3 might function as upstream regulator in nitrogen assimilation pathways. Since an important
amount of assimilated nitrogen should require and higher amount of carbon skeleton production we also
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Arabidopsis Cycling Dof Factor 3 CDF3
analyze the expression levels genes involved in anapleurotic pathway for the TCA cycle such as
Phosphoenolpyruvate Carboxylase 1 (PEPC1), PEPC2 and Pyruvate kinase (PK1). The data obtained
revealed that these genes were coordinately activated in the overexpression lines (Fig. 3.9B) which
indicated that AtCDF3 could be involved in the production carbon skeletons for amino acid biosynthesis as
well.
Figure 3.9. Transcription analysis abiotic stress-responsive and nitrogen assimilation genes in 35S::AtCDF3 lines. (A)
Transcription analysis by RT-qPCR of COR15, RD29 and EDR10 stress-responsive genes in 35S::AtCDF3 (L2.1 and L5.4) and
control (Col-0) plants. (B) Expression levels nitrogen assimilation genes PK1, PEC1, PEPC2, GS2 and GLU in 35S::AtCDF3 (L2.1
and L5.4) and control (Col-0) plants. (C) Transient expression analyses. Co-transfection of Arabidopsis protoplasts with the
35S::AtCDF3 effector plasmid and promCOR15::GUS reporter plasmid, arrows indicate DOF binding sites. Empty effector plasmid
was used as negative control. Data are expressed as means ± standard error (SE) of three independent experiments. Asterisks
indicate significant differences (P<0.05; ANOVA Student-Newman-Keuls tests.
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Arabidopsis Cycling Dof Factor 3 CDF3
3.3.7.- The overexpression of AtCDF3 promotes important metabolic changes in
vegetative tissues.
It is well documented that drought and extreme temperatures stresses are conditions that promote
a large impact in many features of plant metabolism and physiology (Rizhsky et al., 2004; Seki et al.,
2007, Chaves et al., 2009). Thus, we carried different metabolomic analyses to investigate the weather
AtCDF3 overexpression in Arabidopsis promotes significant changes in plant’s metabolome. In a first step,
we performed a non-targeted metabolite analyses of 35S::SCDF3 (lines L2.1 and L5.4) and WT plants.
Then, we performed a principal component analysis (PCA) to compare about 1000 molecular features per
sample with each other. The results revealed that both 35S::AtCDF3 overexpressor lines exhibit a
significant alteration of the metabolome, as indicated by split-up clustering of the datasets (Fig. 3.10A,B).
Thus, we decided to further dissect this alteration tin the metabolome and performed a targeted
metabolomic profiling by gas chromatography-mass spectrometry to study the relative levels of different
polar compounds, including proteinogenic amino acids as well as four other amino acids and distinct
sugars, extracted from 12-d-old WT and 35S::AtCDF3 (L2.1 and L5.4) transgenic plants, grown under
non-stress conditions.
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Arabidopsis Cycling Dof Factor 3 CDF3
3.10. Metabolic analyses of 35S::AtCDF3 and WT plants. A-B) PCAs of recorded, non-targeted metabolic profiles using Profile
Analysis (Bruker Daltonics, Bremen, Germany). Projection plots are shown for principal component 1 (PC1, 55.3% variance
explained) and PC2 (28%) of the L2.1line and principal component 1 (PC1, 72.7% variance explained) and PC2 (15%) of the L.4
line. Distinct grouping supports the different genotypes analyzed: WT control samples or overexpression Lines 2.1 and 5.4,
respectively. C) Relative quantities (% of WT) of selected metabolites analyzed by Gas chromatography-selected ion monitoringmass spectrometry. Results are shown as means ±SE (n=15). Similar results were obtained in five independent experiments
P>0.01; ANOVA, followed by a Student-Newman Keuls test).
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Arabidopsis Cycling Dof Factor 3 CDF3
As shown in Figure 3.10B and Supplementary Table S3.3, comparison of gas chromatography
profiles revealed a number of clear differences between the control and overexpressing lines.
Overexpression of AtCDF3 in Arabidopsis significantly induced the accumulation of sugars like sucrose
(1.1 fold) , fructose (1.68 fold) and glucose (2.0 fold) and amino acids like γ-aminobutyric acid GABA (1.3
fold), L-valine (4.0 fold), L-proline (2.2 fold), L-asparagine (1.82 fold) and L-glutamine (1.53 fold), while the
amount of glycine decrease by up to 40%, relative to the control. It is remarkable that both AtCDF3
overexpressor lines exhibited important increase in sucrose content compared with the WT while glucose
and fructose, the two monomeric building blocks of sucrose, showed no reductions. This result are
consistent with a possible role of AtCDF3 in increasing CO2 fixation rates or/and carbon partitioning
altering the balance to production of sucrose instead of starch.
3.3.8.- Overexpression of AtCDF3 in tomato enhance osmotic and low temperature
tolerance.
Considering globally all data, suggested that AtCDF3 may be involved in plant responses to
different environmental conditions. So, we decided to evaluate whether AtCDF3 could be used to improve
abiotic stress tolerance in a crop like tomato. Thus tomato plants were transformed with the previously
obtained 35S::AtCDF3 construct, and three homozygous lines with relatively high expression of AtCDF3
were selected for further analyses (Fig. 3.11A). A phenotypic characterization of tomato (T2) 35S::AtCDF3
plants was performed by analyzing their response under abiotic stresses, such as dehydration and low
temperature. Then, 30-day-old 35S::AtCDF3 and WT tomato plants were grown hydroponically under
control conditions (control) or subjected during 14 days to saline (75mM) or low temperature stress
(15/8ªC; day/night) and the biomass production and different photosynthesis parameters were evaluated.
As it shown in Figure 3.11B, when cultured in control conditions, all AtCDF3 overexpressing lines (L2, L5
and L10) presented developmental differences relative to WT tomato plants (M). In fact exhibit slight but
significant higher photosynthesis rate and total dry weight than WT plants (Fig. 3.11B). However, when the
same lines where grown in both stress conditions different photosynthetic rate and biomass among
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Arabidopsis Cycling Dof Factor 3 CDF3
genotypes was observed when compared to control conditions (Fig. 3.11C). In fact, on salt stress
conditions all transgenic lines exhibit significant higher values of An and biomass that WT plants. In
contrast under low temperature stress treatment only line L5 exhibit higher rate of photosynthesis but all
lines exhibited significant higher values of biomass. These results indicated that overexpression AtCDF3
also increase to tolerance to salt stress and improve photosynthetic rate and biomass production in crop
tomato.
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Arabidopsis Cycling Dof Factor 3 CDF3
Figure 3.11. Photosynthetic rate, biomass production and stress tolerance on 35S::AtCDF3 transgenic tomato plants
and WT exposed to salinity (75mM NaCl) and low temperatures during 14 days. A). Esquematic representation of the
construction used for tomato transformation and transcription analysis of the AtCDF3 gene in overexpressing lines. The
construction contains the ORF of the corresponding AtCDF3 gene flanked by the CaMV 35S promoter and the nopaline synthase
gene (NOS) 3´terminator. NPTII gene under the control of the NOS promoter was used as selective marker. Expression levels of
the corresponding AtCDF3 gene analyzed by RT-qPCR in heterozygous tomato lines. Expression of the UBIQUITIN3 (Hoffman et
al., 1991) gene was used as reference gene. Data are expressed as means ± SE of three independent extractions. Three
technical replicates were performed for each extraction. B). Salt and low temperatures tolerance of 35S::AtCDF3 tomato lines and
WT plants. Photosynthetic and dry weight parameters of 35S::AtCDF3 transgenic plants and WT growing under control, salt
stress (75 mM) or low temperature (10/5°C) conditions during 14 days. Biomass of plants growing under control, salt stress (75
mM) or low temperature (15/8°C) conditions. (C) Biomass production of 35S::AtCDF3 transgenic tomato plants and WT growing
under control or salt stress conditions after 14 days of treatment.
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Arabidopsis Cycling Dof Factor 3 CDF3
3.4.- DISCUSSION.
During the last decade different reports have suggested that plant DOF factors regulated various
biological processes related to plant growth and development. In this work we have identified a group of
DOF Arabidopsis genes belonging to subfamily D are regulated by different abiotic stresses like salt,
drought, and extreme temperatures but with different expression patterns suggesting that they might
participate in abiotic stress responses. Furthermore, we provide functional evidences that support that one
them, AtCDF3, display a significant role in responses to drought and low temperature stress and also may
participate as a link between flowering signaling to responses to abiotic stimuli.
3.4.1.- AtCDF3 involvement in abiotic stress responses.
We analyzed the expression patterns of the complete set of 34 genes encoding DOF proteins of
Arabidopsis (Lijavetzky et al., 2003), and found that the ones included in the group D are notably highly
expressed in response to different abiotic stress conditions such as extreme temperatures, drought or
osmotic stress (Figure 3.1). Interestingly, among them the CDFs, seem to be regulated by drought, salinity
and extreme temperatures but with diverse timing and spatial expression patterns in roots and shoots,
suggesting that CDFs might display different function in responses to changes in environmental
conditions. Further detailed expression analyses revealed that AtCDF3, responded rapidly to different
abiotic stresses such us low and high temperatures, dehydration and high salt treatments with different
timing although with similar spatial patterns in adult plants, implying that it might participate in abiotic
stress responses. Moreover the fact that AtCDF3 show similar spatial expression patterns in response to
different stress treatments indicates that their roles may be related to a common effect caused by the
treatments. However the observation that AtCDF3 is also expressed in several tissues such as vascular
systems of leafs and stems guard cells but also in pollen and seeds during Arabidopsis development
probably implies that its product should play additional roles under normal growth conditions.
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Arabidopsis Cycling Dof Factor 3 CDF3
Phenotypical analyses demonstrated that CDF3 T-DNA insertion mutant display reduced tolerance to
osmotic and low temperatures, in contrast AtCDF3 overexpressing lines were more tolerant to drought,
osmotic and low temperatures by survival rates and root length assays (Fig. 3.5). Moreover transcriptomic
analyses of 35S::AtCDF3 plants revealed that under non-stress conditions alter the expression of a large
number of genes (641) and about half of the AtCDF3 missregulated genes were responsive to osmotic,
drought or extreme temperatures (Fig. 3.8). Further transient expression analyses confirmed this
experiments and indicated that AtCDF3 could activate directly the expression of an abiotic stress
regulated genes such as COR15 (Fig. 3.9, Supplementary Figure S3.6) likely though the multiple DOF
binding sites localized in its promoter region, suggesting that CDFs might function as upstream regulators
of plant responses to abiotic stress. Moreover metabolomic analyses of AtCDF3 overexpressing plants
indicated the accumulation of amino acids like proline, GABA and sugars like sucrose and glucose which
usuallly are accumulated at higher levels in plant tissues when exposed to extreme temperatures, osmotic
stress or drought (Gill and Tuteja, 2010; Hussain et al., 2011; Rizhsky et al., 2004), displaying functions
related to osmotic adjustment, protection of membranes and ROS scavenging (Farrant et al., 2010,
Rajasekaran et al., 2000; Claussen, 2005; Munns and Tester, 2008). Thus, the increased amounts of free
aa such as proline and sugars observed in 35S::AtCDF3 plants are factors that would aid the tolerance to
low temperature and drought stresses.
Physiological studies have demonstrated that 35S::AtCDF3 plants exhibited higher rates of
photosynthesis and biomass under osmotic stress conditions than control plants. Drought, salinity and low
temperatures are environmental constrains decreasing photosynthetic efficiency and adversely affecting
plant growth and productivity. Generally theses unfavorable conditions force a water deficit that are
preceded by stomatal closure and a lower are CO2 diffusion which are the earlier responses (Tezara et al.,
1999, Flexas and Medrano 2002). Furthermore, membranes became unstable and disorganized, proteins
may undergo denaturation and loss of their activities and habitually increasing amount of reactive oxygen
species are generated, preceding oxidative stress. A general consequence of these phenomenon, it is
produced an inhibition of photosynthesis, metabolic unbalance and damage of cellular structures
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Arabidopsis Cycling Dof Factor 3 CDF3
(Krasensky and Jonak, 2012). The significantly increased photosynthetic efficiency and biomass promoted
by the overexpression of AtCDF3 in Arabidopsis, seemingly contribute to improved drought and low
temperature tolerance, as it has been correlated with growth and stress tolerance (Kerepesi and Galiba,
2000; Farrant and Moore, 2011; Pinheiro and Chaves, 2011; Less et al., 2011). Overall, our results
strongly support that AtCDF3 play a significant role in plant responses and tolerance to changing
environmental conditions.
3.4.2.- AtCDF3 as a regulatory link between carbon and nitrogen metabolism.
The analyses of the expression of AtCDF3 reveal a very complex pattern been highly expressed in
very different tissues during development. Particularly, tissues with very different sink/ source dynamics
such as vascular tissues of shouts and roots, and reproductive tissues like flowers and seeds. This data
may undercover precise tissue-specific functions for the CDFs in controlling the expression levels of
particular group of genes that might be involved in particular metabolic processes. Metabolic analyses of
35S::CDF3 plants revealed that under control conditions the transgenic lines exhibit important changes,
specifically high levels of sugars like sucrose and glucose, and the accumulation of different amino acids
such as glutamine, asparagine, proline and GABA. Interestingly the levels GABA and glutamine are
reliable indicators nitrogen utilization efficiency (Stitt and Krapp, 1999; Foyer et al., 2006; Yanagisawa et
al., 2004). Remarkably GABA has been reported to be involved among other roles in nitrogen storage and
the pathway that converts glutamate to succinate via GABA (GABA shunt), which might be a great impact
in nitrogen economy of plants (Shelp et al., 1999). Overall the observed higher amino acid content in the
overexpression plants might be related to an improvement of nitrogen assimilation or alternatively by
imbibition of protein synthesis or a higher rate of protein degradation. However the observed higher rates
of photosynthesis rate and biomass of 35S::CDF3 plants together with the close link between nitrogen and
carbon metabolism might support the hypothesis of increased nitrogen assimilation. Moreover expression
analyses of the 35S::CDF3 lines showed that expression levels of several genes encoding enzymes
involved in nitrogen assimilation such as GS2 and GLU1 are increased under non stress conditions, which
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Arabidopsis Cycling Dof Factor 3 CDF3
indicate that CDF3 might function as upstream regulators in nitrogen assimilation pathways. In the other
hand, an important amount of assimilated nitrogen should also require and higher amount of carbon
skeleton production and 2 oxogluturate is an intermediate between C and N metabolism and its levels are
important for N assimilation and it is produced though sequential reactions from photoassimilate
carbohydrates (Yuan et al., 2007; Kurai et al., 2011; Hodges, 2002). Interestingly, we also observed that
the expression of PEPC1, PEPC2 and PK1 genes involved in anapleurotic pathway for the TCA cycle was
coordinately activated in the overpression lines (Fig. 3.9B) which indicate that AtCDF3 might be involved
in the production carbon skeleton for amino acid biosynthesis. Similar results have been reported
previously with maize ZmDOF1 gene when overexpressed in Arabidopsis or rice plants (Yanagisawa et
al., 2004; Kurai et al., 2011), suggesting the participation of CDF factors and specially AtCDF3 in the
modulation of carbon a nitrogen metabolites, increase nitrogen assimilation and growth under abiotic
stress conditions and/or in particular tissues.
3.4.3.- AtCDF3 is involved in the cross-talk of abiotic stress responses and flowering
time.
Plants have conquered many diverse environments, and most species that grow at higher latitudes
synchronize their developmental program with seasonal changes in day length (or photoperiod). In
Arabidopsis, flowering is induced during long days typical of spring and early summer but is delayed
during short winter days. Molecular genetic studies defined the photoperiodic flowering pathway,
comprising at its core the GIGANTEA, CONSTANS, and FLOWERING LOCUS T genes (Kobayashi and
Weigel, 2007; Turck et al., 2008), whose functions are highly conserved in distantly related species
(Hayama et al., 2003). The stimulation of CO transcription under long days is essential for the induction of
flowering since longer periods of exposure to light promote stabilization of CO protein (Jang et al., 2008
and Valverde et al., 2004), trigger FT transcription in the leaves ( An et al., 2004, Takada and Goto, 2003,
Wigge et al., 2005; Yoo et al., 2005), and posterior translocation of the FT protein to the shoot apical
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Arabidopsis Cycling Dof Factor 3 CDF3
meristem (Corbesier et al., 2007, Jaeger and Wigge, 2007, Mathieu et al., 2007). In Arabidopsis
coordinately CDFs repress the transcript levels of CO to adjust the diurnal expression rhythm (Imauzami
et al., 2005, Fornara et al., 2009). The data obtained in this work further confirm the previously reported
aspects of CDFs function in the control of flowering time. Especially the overexpression of CDFs in phloem
companion cells in Arabidopsis promote a delay in flowering time under LD conditions but with a very
different extent (Imauzami et al., 2005, Fornara et al., 2009,). Here we could show that AtCDF3
overexpression not only promotes an impact flowering time but also in plant responses to different abiotic
stresses. Besides our results indicate that AtCDF3 functions mostly relays on a conserved C-terminal
domain. In fact though deletion experiments we have also shown that the C-terminal region of AtDF3 was
essential for its transcriptional capabilities and localization as determined by protoplast assays (Fig. 3.4B).
Moreover the role of this domain was further investigated trough transgenic analyses. Interestingly
transgenic plants that overexpresing a truncated form of AtCDF3 cDNA lacking the conserved C-terminal
region, (35S::AtCDF3-stop), not only recover a flowering time similar to the one of WT plants
(Supplemental figure S3.3), But also showed significant reduced tolerance to drought stress that one’s
exhibited in transgenic plant overexpressing full length AtCDF3 (Fig. 3.4A,B). Notably previous protein
sequence analyses of DOF proteins of group D from different plant species including Arabidopsis and
tomato reveled the existence of 3 homolog motifs of about 21, 22, and 33 aa are well conserved within
their C-terminal region (Yang et al., 2011, Hernando-Amado et al., 2012; Kloosterman et al., 2013).
Interestingly in Arabidopsis the C-terminal domain have been reported to be are essential for different
protein-protein interaction with the kelch repeat domain of the F-box proteins FKF1 and LKP2 and also
with GIGANTEA (GI) (Imauzumi et al., 2005, Sawa et al., 2007, Klossterman et al., 2013). Moreover it has
been reported that two different alleles (SlCDF1.2 and SlCDF1.3) of potato SlCDF1 gene that have lost
the C-terminal domain, are incapable to interact with the FKF1-GI complex, which results in important
alterations in tuber development and plant maturity (Klossterman et al., 2013). On this regard our data
might indicate that the C-terminal of CDFs is key domain though it exerts its action in flowering and abiotic
stress responses likely though the interaction with the signaling FKF1-GI complex. However the precise
regulatory mechanisms controlled by this complex in response to abiotic stress reposes are still unknown.
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Arabidopsis Cycling Dof Factor 3 CDF3
The timing of flowering transition has significant consequences for the reproductive success in
plants and therefore their adaptability to changing environmental conditions. Consequently plants must
check closely changes in the environmental conditions to determine the onset of flowering to ensure
reproductive success. Plasticity in flowering time in response to change environmental conditions has
been reported in several plant species (Xu et al., 2005, Lafitte et al., 2006, Sherrard and Maherali 2006,
Franks et al., 2011, Ivey and Carr, 2012). Remarkably very contrasting effects on flowering time have
been reported for a variety of external cues. For instance, warm temperatures (28ºC) considerably
accelerate flowering in contrast with the opposite effect of low temperatures (16ºC) in Arabidopsis
(Balasubramanian et al., 2006; Blázquez et al., 2003). Moreover abiotic stresses such us UV-C exposure
accelerate flowering (Martínez et al., 2004). In the other hand intermittent salt stress or cold treatments
promotes a strong effect inhibiting flowering (Kaht et al., 2011). During the last years different reports also
point out the substantial effect of nutrient availability in flowering. For example, plants flowered earlier
when grown under low NO3- compared to high NO3- conditions. In contrast, growth with low Pi delayed
flowering compared to high Pi, in Arabidopsis. Further, the interaction between these two nutrients had a
cumulative effect given that the plants grown at 3 mM NO 3 2-10 mM Pi flowered significantly earlier than
plants at 10 mM NO3 2-3 mM Pi (Kant et al., 2011). Our work shows that AtCDF3 not only play an
important role in flowering control by photoperiodic pathway but also display additional functions in plant
responses to adverse environmental conditions. It is remarkable that AtCDF3 control de expression of in
important set of genes including a number of genes that are involved in plant response to extreme temps,
drought and osmotic stress but also involved in primary metabolism. Consistently metabolomic analyses
reveal that CDFs overexpresssion promotes important changes in plant metabolome, altering the levels of
specific compounds with protective functions but also that alleviates detrimental effects of abiotic stresses
conditions. Moreover is also observed the accumulation of others such as sugars (sucrose and glucose)
and specific aa which resemble the profiles that usually are associated with specific energetic and
physiological status plant. Especially the ones involved in mobilization of nutrients from source to sink
tissues and nutrient recycling during aging and senescence programs (Jones, 2013, Bieker and Zentgraf,
2013), which would us allow to hypothesize that CDFs might be involved remobilization of valuable
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Arabidopsis Cycling Dof Factor 3 CDF3
nutrients from various organs of the plant depending on stage of plant development and environmental
cues. On this regard, the present study provide of new notions regarding of the DOF transcription factor
and contributes to our understanding of the molecular mechanisms that takes integrates plant response to
adverse environmental conditions with the developmental program involved in the transition from
vegetative to reproductive phase.
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4
CHARACTERIZATION OF TOMATO CYCLING
DOF FACTORS REVEALS CONSERVED AND
NEW FUNCTIONS IN THE CONTROL OF
FLOWERINGTIME AND ABIOTIC
STRESS RESPONSES
Characterization of tomato Cycling Dof Factors
4.1.- INTRODUCTION.
DNA binding with One Finger (DOF) proteins are a group of plant-specific transcription factors (TFs) that
contain a 50 amino acid conserved domain in the N-terminal region. This DOF domain corresponds to a
C2-C2 configured zinc finger that binds specifically to the 5'-T/AAAAG-3' sequence motif in the promoters
of direct target genes (Yanagisawa and Schmidt, 1999). In contrast, the C-terminal protein region has a
highly variable structure, containing specific protein-protein interaction domains and other regulatory
elements. For instance, the Thr-Met-Asp motif present in Arabidopsis AtDOF4.2 and AtDOF4.4, (Zou et
al., 2013) and a 48 aa C-terminal domain of maize ZmDOF1 are responsible for their activation capacity
(Yanagisawa and Sheen, 1998; Yanagisawa, 2001). Consequently, DOF TFs exhibit a complex modular
structure, which allows them to display multiple regulatory functions, acting both as activators or
repressors in the control of the expression of numerous plant genes (Mena et al., 1998; Yanagisawa and
Sheen, 1998; Diaz et al., 2002; Yamamoto et al., 2006). The regulatory activity mediated by DOF proteins
involves not only DNA binding to target sequences, but also specific protein-protein interactions with other
regulatory proteins including bZIP and MYB TFs (Zhang et al., 1995; Vicente-Carbajosa et al., 1997;
Washio, 2001; Diaz et al., 2002) and nuclear high-mobility group (HMG) proteins (Yanagisawa, 1997;
Krohn et al., 2002).
Over the last years, DOF proteins have been reported to contribute to the control of very different
biological processes, as diverse as seed maturation and germination, tissue specific gene expression,
light responses and plant hormone signalling (Yanagisawa, 2002a, 2004; Moreno-Risueño et al., 2007a,
2007b). DOFs participate in the control of genes involved in carbon fixation and nitrogen assimilation
(Yanagisawa and Sheen, 1998; Rueda-Lopez et al., 2008), secondary metabolism (Skirycz et al., 2006,
2007), vascular development (Konishi and Yanagisawa, 2007; Guo et al., 2009; Gardiner et al., 2010),
lipid metabolism in the seed (Wang et al., 2007), seed germination (Papi et al., 2000, 2002; Gualberti et
al., 2002), photoperiodic flowering (Imaizami et al., 2005; Iwamoto et al., 2009) and flower abscission (Wei
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Characterization of tomato Cycling Dof Factors
et al., 2010). Nevertheless, DOF genes involvement in the regulation/adjustment of the metabolism under
different environmental cues has not been described.
The family of DOF TFs evolved from a common ancestor in green unicellular algae such as
Chlamydomonas reinhardtii, where only one gene has been found, and rapidly expanded in mosses, ferns
and vascular plants (Moreno-Risueño et al., 2007a). DOF genes are classified into families of different
size within species. In-silico analyses of the complete genome sequences of Arabidopsis, rice and
Brachypodium predicted 36, 30 and 27 DOF genes, respectively (Lijavetzky et al., 2003; Hernando-Amado
et al., 2012), whereas 31 members have been found in wheat (Shaw et al., 2009), 26 in barley (MorenoRisueño et al., 2007a) and 28 in sorghum (Kushwaha et al., 2011). Different phylogenetic analyses using
Arabidopsis, rice, barley and Brachypodium sets of predicted DOF genes indicate that they can be
classified into four major clusters of orthologous genes or subfamilies, A-D (Lijavetzky et al., 2003;
Hernando-Amado., 2012). In Arabidopsis, the D group contains a set of DOF factors whose transcripts
oscillate under constant light conditions and are hence known as Cycling Dof Factors, CDF1-5 (Imaizumi
et al., 2005; Fornara et al., 2009). CDFs display an important role in photoperiodic flowering in Arabidopsis
through the establishment of a diurnal rhythm in CONSTANS (CO) transcript levels by repressing its
expression. When overexpressed, CDF1-5 repress CO transcription,causing a strong delay of flowering
under long-day (LD). Consistently, combining loss-of-function alleles in four ofthese genes (CDF1, 2, 3,
and 5) causes photoperiod-insensitive early flowering (Fornara et al., 2009). In vivo, CDF1 and CDF2
degradation depends of the action of a protein complex that includes FLAVIN-BINDING KELCH REPEAT
F-BOX PORTEIN (FKF1) and GIGANTEA (GI) (Sawa et al., 2007). Light is required to stabilize their
interaction, so longer photoperiods cause enhanced accumulation of GI-FKF complexes and consequently
decreased CDF protein levels (Imaizumi et al., 2005; Fornara et al., 2009).
The Solanaceae family includes several horticultural crops of major economic importance, such as
tomato, potato, tobacco, and pepper. Although wide tolerance levels to abiotic stresses can be found in
their wild relative species, only moderate tolerance is conserved among their cultured varieties (Shannon
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Characterization of tomato Cycling Dof Factors
and Grieve, 1999; Nuez and Prohens, 2008). In the case of tomato, most cultivars show negative effects
under drought and salinity, resulting in growth inhibition, decreased seed germination and reduction of fruit
quality and production (Cuartero et al., 1995; Cuartero and Fernández-Muñoz, 1999). At the molecular
level, abiotic stresses induce changes in the expression of a large number of genes leading to
physiological and biochemical alterations. Drought and salinity significantly affect photosynthesis, which
impacts the function of other important metabolic pathways such as nitrogen assimilation (Chaves et al.,
2009). Moreover, respiration is enhanced to provide energy to maintain plant growth and development
(Haupt-Herting et al., 2001). Other protection systems are also affected by drought and salt stress, such
as the antioxidant and osmoregulation pathways that reinforce plant cells by the biosynthesis of
compatible solutes and reactive oxygen species (ROS) scavengers (Blumwald et al., 2000; Apel and Hirt,
2004; Zhu 2001, 2003; Munns and Tester, 2008).
Some efforts in the identification of genes responsible for salt and drought tolerance have been
made for both wild and cultivated tomato plants. Recent global expression analyses showed that more
than 2000 and 1300 genes are induced or repressed in response to drought and salinity, respectively
(Gong et al., 2010; Sun et al., 2010), suggesting that responses to these stresses are mediated by
multiple signal transduction pathways. Moreover, a number of the identified genes are commonly affected
by both stresses and by different stress conditions like low and high temperatures (Gong et al., 2010; Sun
et al., 2010) indicating an overlap of plant responses to abiotic stress. Despite these efforts, only a small
number of transcriptional regulators have been demonstrated to participate in abiotic stress responses in
Solanaceae, like LebZIP2 (Seong et al., 2008), SlAREB1 (Yañez et al., 2009), SlAREB1 (Orellana et al.,
2010) StERBEP1 (Lee et al., 2007), AIM1 (Abuqamar et al., 2009), TERF1 (Huang et al., 2004) and
JERF1 (Wu et al., 2007).
Expression levels of certain DOF genes are regulated by several environmental conditions.
Nevertheless, especially in crop plants like tomato, their exact roles in abiotic stress tolerance are not
known. In this work, we have identified 34 DOFs in tomato and performed phylogenetic analyses and
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Characterization of tomato Cycling Dof Factors
comparisons with their Arabidopsis counterparts. Based on sequence similarity and domain analyses we
have identified five genes homologous to Arabidopsis CDFs. We explored their expression patterns during
plant development, in response to abiotic stresses and under different light conditions. Among them,
SlCDF1 and SlCDF3 were investigated in more detail, focusing particularly on their roles in photoperiodic
flowering response and abiotic stress tolerance. Arabidopsis plants overexpressing SlCDF1 and SlCDF3
genes show improved tolerance to drought and salt when compared with the wild type (WT). Combined
studies of putative downstream target genes and metabolite-profiling shed light on the molecular basis of
the uncovered new roles of CDF proteins in response to environmental stresses.
4.2.- MATERIAL AND METHODS.
4.2.1.- Database searches for the identification of DOF family members in
Solanum lycopersicum L.
The nucleotide DOF domain sequences of Arabidopsis CDF genes (Lijavetzky et al., 2003) were
used to search for potential DOF genes in the tomato genome using the BLAST program (Altschul et al.,
1997) at the Sol Genomics Network website (Bombarely et al., 2011) and Phytozome database
(Goodstein et al., 2012). The amino acid sequences of the DOF genes were deduced through the
“Translate tool” at ExPASy Proteomics Server (Artimo et al., 2012). Alignments of protein sequences were
performed by CLUSTALW (Thompson et al., 1997). Phylogenetic and molecular evolutionary analyses
were conducted using the MEGA program software version 5.0 (Guindon and Gascuel, 2003; Tamura et
al., 2011) obtaining the phylogenetic trees from Neighbour-Joining analysis. The deduced protein
sequences of CDFs proteins from tomato and Arabidopsis have been further analysed by means of the
MEME program (Bailey et al., 2009; http://meme.sdsc.edu/meme4_6_0/intro.html).
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Characterization of tomato Cycling Dof Factors
4.2.2.- Subcellular localization of tomato CDF proteins.
Open reading frames (ORFs) of the tomato SlCDF genes were cloned into the pK7WGF2.0
plasmid using the Gateway recombination system (Invitrogen) to generate C-terminal GFP fusions driven
by the cauliflower mosaic virus 35S promoter (Karimi et al., 2007). As a control, the GFP gene expressed
under the control of 35S promoter was used. Transient transformations of onion (Allium cepa L.) epidermal
cells were performed by particle bombardment with a biolistic helium gun device (DuPont PDS-1000; BioRad) as described by Diaz et al, (2002). Fluorescence images were acquired after 40 h of incubation at 22
ºC in the dark using a confocal microscope (LEICA-Sp2-AOBS-UV) with appropriate filters.
4.2.3.- DNA-binding specificity of CDF proteins using the yeast one-hybrid assay.
Two copies of the DOF cis-DNA element were produced by annealing complementary singlestranded
oligonucleotides
pTUYDOF-S
CGTGACATGTAAAGTGAATAACGTGACATGTAAAGTGAATAA-3´)
and
(5´pTUYDOF-AS
(5´-
CTAGTTATTCACTTTACATGTCACGTTATTCACTTTACATGTCACGAGCT-3´) which generate Xmal and
Xbal cohesive ends. This fragment was cloned into the Xmal and Xbal sites of the reporter plasmid
pTUY1H (Clontech) containing the HIS3 nutritional reporter gene. Entry clones containing the ORFs of the
SlCDF1-5 genes, were recombined into the pDEST22 plasmid (Invitrogen) using the LR reaction to
generate GAL4AD-ORF fusions. The resultant constructs and pTUY1H-2xDOF were co-transfected into
HF7c yeast cells. As negative control, an empty pDEST22 and pTUY1H-2xDOF vectors were used.
Transformed yeast cells were plated onto Skirtycz medium and incubated at 28 ºC. Single colonies were
then streaked on SD/-Trp-Leu selection medium with 30 mM of 3-AT (3-Amino-1, 2, 4-triazole). The plates
were subsequently incubated at 28 ºC.Single colonies were then streaked on SD/Trp-Leu-His selection
medium with 30mM 3-amino.1,2,4-triazole (3-AT). The plates were subsequently incubated at 28ºC for 2d
and yeast growth was determined.
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Characterization of tomato Cycling Dof Factors
4.2.4.- Protoplast transformation and GUS assays.
Mesophyll protoplasts were isolated from rosette leaves of 3-week-old Arabidopsis plants ecotype
Columbia (Col-0) grown in soil (21/18ºC, 8/16 h light/dark). Protoplast isolation and transfection was
performed according to the method described by Alonso et al. (2009). Plasmid DNA was prepared using a
Genopure Plamid Maxi Kit (Roche), and 5 µg of pBT10-2xDOF-GUS (a dimer of the DOF binding
element) and 14 µg of each SlCDF1-5 effector plasmid were used for transfections. For normalization
purposes, 1 µg of Pro35S::NAN plasmid (Kirby and Kavanagh, 2002) was added. Then, 20 µl of plasmid
mixture (20 µg) and 200 µl protoplast were transferred to 2 ml microcentrifuge tubes following the
procedure described in Weltmeier et al. (2006). β-Glucoronidase (GUS) and NAN enzyme assays were
performed according to Kirby and Kavanagh, (2002). The ratio of GUS and NAN activities are represented
as relative GUS/NAN units.
4.2.5.- Plant growth conditions and quantification of CDF gene expression in tomato.
Characterization of the expression of CDF genes in tomato was performed in the Marmande RAF
cultivar. Seeds were germinated on a moistened mixture of peat moss and sand in growth chambers
(25/20 ºC, 16/8 h photoperiod) and irrigated regularly alternating water and nutrient solution (Hoagland
and Arnon, 1950). To study the expression profiling of SlCDF genes during vegetative and reproductive
development we collected plant material at different developmental stages: imbibed seeds, radicles and
cotyledons from 3-d-old seedlings, roots and leaves from 30 day-old plants, roots, leaves and flowers (in
anthesis) from 60 day-old plants, and green (30 days after anthesis) and red (60 days after anthesis) fruit
mesocarp. Three different pools of each plant material were harvested at any developmental stage. To
study the effect of abiotic stress and light regulation on the expression of SlCDFs, 3-week-old uniform
plantlets, bearing three leaves, were transferred to 1 L plastic pots containing half strength Hoagland
solution. Solutions were aerated and replaced every 4 d, and plants maintained during 4 weeks in growth
chambers (25/20 ºC; 16/8 h photoperiod). Salt stress was assayed by adding NaCl at 50 mM in the
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Characterization of tomato Cycling Dof Factors
nutrient solution. Polyethylene glycol (PEG 8000; Sigma) at 5% was used for water stress. Plants were
transferred for 24 h to growth chambers at 35/30 ºC and 10/5 ºC, for high and low temperature stresses,
respectively. Three different pools of roots and leaves were harvested (four plants per pool) after 6, 12 and
24 h of initiating the stress. Control plants were maintained at 25/20 ºC in half-strength nutrient solution.
To study the diurnal changes in the expression of SlCDF genes, leaves were harvested at 6 h intervals for
a total of 24. For continuous light experiment (LL), plants were shifted to continuous light at dawn. After 24
h, leaves were harvested every 4 h during 24 h (0, 4, 8, 12, 16, 20 and 24 h). Three independent extracts,
obtained from 12 plants (two leaves per plant and four plants per extract) were assayed at the different
time points in both experiments. Plant material was collected and stored at -80 ºC until analyzed. Total
RNA was extracted and purified using the RNeasy Mini Kit (Qiagen) and treated with Turbo DNase
(Ambion) following the manufacturer’s protocol. cDNA was synthesized from 2 µg of DNA-free RNA with
the use of Superscript II reverse transcriptase (Invitrogen) and random hexamers. The ABI Prism 7000
sequence detection system (Applied Biosystems) was used for the real-time PCR with programs
recommended by the manufacturer (2 min at 50 ºC, 10 min at 95 ºC, and 40 cycles of 95 ºC for 15 s and
60 ºC for 1 min) using Power SYBR Green PCR master mix (Applied Biosystems). In all treatments and
conditions, three independent samples from different extracts were used and each reaction was performed
in triplicate. The primer pairs used for amplification are described in Supplementary Table S4.3.
UBIQUITIN3 gene from S. lycopersicum (Hoffman et al., 1991) was used as reference gene. Relative
expression levels of the target genes were calculated using the 2 −ΔΔCT method (Livak and Schmittgen,
2001). Positive and negative controls were included in the quantitative real-time PCR (RT-qPCR)
analyses.
4.2.6.- Plasmid constructs and plant transformation.
The ORF of SlCDF1 and SlCDF3 were cloned into the Gateway binary vector pGWB2 (Nakagawa
et al.,2007) under control of the 35S promoter. The resultant plasmid was used to transform Arabidopsis
thaliana plants, ecotype Columbia (Col-0) by the Agrobacterium tumefaciens-mediated floral dip method
99
Characterization of tomato Cycling Dof Factors
(Clough and Bent, 1998). Transformed plants were selected on MS medium containing 50 µg/ml
kanamycin.
4.2.7.- RNA measurements by RT-qPCR in Arabidopsis.
The expression of SlCDF genes (SlCDF1 and SlCDF3), abiotic stress responsive genes (COR15,
RD29A and ERD10), and flowering control genes (CO and FT) in overexpression (35S::SlCDF1 and
35S::SlCDF3) and control lines (Col-0) was determined by RT-qPCR. Plants were maintained in growth
chambers (21/18 ºC, 16/8 h photoperiod). Total RNA was extracted from 10 day-old seedlings to study CO
and FT expression and from leaves of 3-week-old plants to study SlCDF1-3, COR15, RD29A and ERD10
following the protocol of Onate-Sanchez and Vicente-Carbajosa, (2008). For cDNA synthesis 2 µg of total
RNA were primed with oligo dT15 primers (Promega) using the AMV Reverse Transcriptase according to
the manufacturer’s instructions. Arabidopsis UBIQUITIN mRNA level (At5g25760) was used as control.
The reaction, PCR program and the analysis of the data were performed as mentioned above to analyze
the expression of CDF genes in tomato. The primers pairs used for PCR amplification are presented in
Supplementary Table S 4.3.
4.2.8.- Salt and drought stress tolerance tests.
Salinity and drought stress assay were carried out using control plants (Col-0), 35S::SlCDF1 and
35S::SlCDF3 transgenic lines. For salinity assays, seeds were sterilized and plated onto Petri dishes
containing MS medium (Murashige and Skoog, 1962). After 6 days, seedlings were transferred to vertical
plates containing MS medium (control) and MS medium supplemented with 80 mM NaCl (Lakhssassi et
al., 2012). About 20 seedlings were used per replicate and three replicates were made for each treatment.
Primary and lateral root elongation was measured after 10 days using ImageJ software (Abramoff et al.,
2004). To evaluate growth differences between control and saline stress, data were represented as
percentage of root growth reduction relative to standard conditions and statistical analyses were carried
out by one-way ANOVA followed by Student-Newman-Keuls test (P<0.01). Drought stress tolerance tests
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Characterization of tomato Cycling Dof Factors
were performed on plants grown in soil in individual pots. After 2 weeks, the water supply was cut off for
15 days and then watering was resumed during 10 d. Plant survival rates were calculated afterwards and
fresh weight was measured 10 d after re-watering period.
4.2.9.- Metabolomic analyses.
Non-targeted and targeted metabolomics analyses were performed on 12-day-old control plants
(Col-0) and two independent 35S::SlCDF3 lines. Extraction, manipulation and mass spectrometric analysis
of samples followed an adapted protocol, detailed in Supplementary File S4.1, which is based on
previously described methods (Fiehn et al., 2000; Gullberg et al., 2004; Gaquerel et al., 2010).
4.3.- RESULTS.
4.3.1.- Identification of CDF proteins in tomato plants.
In order to identify CDF proteins encoded by the tomato genome, the amino acid sequence of the
DNA-binding domain of Arabidopsis CDF1-5 proteins (Imaizumi et al., 2005; Fornara et al., 2009) was
used to perform a BLAST survey against the tomato whole-genome database (http://solgenomics.net/;
Bombarely et al., 2011). A total of 34 predicted DOF tomato transcription factor genes were identified,
annotated and named SlDOF1-34 (S. lycopersicum DOFs, Supplementary Table S4.1). Nucleotide
sequence comparisons between genomic and cDNA clones allowed the identification of precise exonintron structures (Supplementary Table S4.2). All encoded DOF proteins contain a unique DNA binding
domain of 50 aa encompassing a C2-C2 zinc finger (DOF). In a previous study, Lijavetzky et al. (2003)
identified 36 DOF proteins in Arabidopsis and classified them into four groups: A-D. In order to evaluate
the evolutionary relationships among the tomato and Arabidopsis DOFs, specific and combined
phylogenetic analysis based on their DNA binding domain sequences were performed. The resulting trees
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Characterization of tomato Cycling Dof Factors
were obtained by the neighbour-joining algorithm and supported by comparisons with the Arabidopsis tree
(Fig. 3.1A and B, Supplementary Figure S3.1). In both species, DOFs are clustered into four mayor
groups: A, B, C and D. Three of them were further divided into subgroups based on bootstrapping values.
Arabidopsis group D1 contains the Arabidopsis CDFs, i.e At5g62430, At5g39660, At3g47500, At1g26790
and At1g69570. Interestingly, sequence analyses also identified a D-type group in tomato, containing five
genes encoding proteins with high level of sequence similarity to the Arabidopsis CDFs. These tomato
genes were considered as putative CDF orthologues from tomato and were renamed as S. lycopersicum
CDF1-5, respectively (Supplementary Table S4.1). This tentative assignation was further supported by
comparative analyses of the deduced amino acid sequences of the whole Arabidopsis and tomato CDFs
proteins by the MEME software. As shown in Fig. 4.1C the analyses revealed the existence of
homologous motifs, conserved among their sequences and different from the DOF binding domain
characteristic of this family (motif 1, Lijavetzky et al., 2003; Yanagisawa 2004a; Moreno-Risueño et al.,
2007a). Two additional conserved domains are also found in all of the proteins: motifs 2 and 4 spanning
21 and 22 aa, respectively; and another 33 aa motif (motif 3) conserved in nine of 10 sequences. These
three associated motifs seem to represent a common signature of type-D group of CDF proteins of
Arabidopsis and tomato.
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Characterization of tomato Cycling Dof Factors
A
B
C1.1
D1
C1.2
C2
D2
A
A
B
B2
C1.2
B2
C2
B1 D2
C1
C3
B2
B2
A2
B1
A
C2.1 C1
B1
A2
C2.2
C3
A1
A
C2.2
C2.1
B1
At4g21030
C3
0.05
D
0.05
At4g21030
0.05
C
C3
C1.1
D1
D
0.05
C
At5g6243
0At5g3966
0At3g4750
0At1g6957
0At1g2679
0
SlCDF1
SlCDF2
SlCDF3
SlCDF4
SlCDF5
2
1
4
3
4 2
1
2
1
1
4
3
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3
2
4
4
4
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1
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1 1
4
4
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2
1
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3
4
4
4
4
1: DOF
domain
1: DOF
domain
2, 3 and
4: CDFsdomains
2, 3 and
4: CDFs
domains
1
CPRCNS[MAl][ED]TKFCY[FY]NN[YN]N[VA][NS]QPR[HY]FC[KR][NSAK]CQRYWTAGG[TS]MRN[VL]PVG
[AS]GRRK
FYPA[PA]PYWGCT[VI]PG[PS]W[NT][VL]P[WT][LMS]
2
FYPA[PA]PYWGCT[VI]PG[PS]W[NT][VL]P[WT][LMS]
3
[GK][CS][LV][LW]VPKTLRIDDP[GN]EAAKSSIW[AT]TLGIK[HN][DE]V[VM]
4
ETS[PL][SV]LQANPAA[LM]SRSMNF[HR]E[SQ]
FYPA[PA]PYWGCT[VI]PG[PS]W[NT][VL]P[WT][LMS]
FYPA[PA]PYWGCT[VI]PG[PS]W[NT][VL]P[WT][LMS]
FYPA[PA]PYWGCT[VI]PG[PS]W[NT][VL]P[WT][LMS]
Figure 4.1. Phylogenetic trees and conserved motifs of Arabidopsis and tomato DOF protein families. (A, B) The
Arabidopsis (left) and tomato (right) trees were inferred by the neighbour-joining method after the alignment of the DOF
domain amino acid sequences of the 36 Arabidopsis (Lijavetzky et al., 2003) and 34 tomato DOF proteins (listed in
Supplementary Table S4.1), respectively. The resulting groups are shown as A, B, C or D and subscript numbers indicate
defined subgroups. The scale bar corresponds to 0.05 estimated amino acid substitutions per site. (C) Schematic distribution
of conserved motifs among Arabidopsis and tomato CDF proteins. Motifs were identified by means by MEME software using
the complete amino acid sequences of the 10 CDF proteins clustered in groups D of the phylogenetic trees. Position of the
identified motifs is relative to the DOF domain. Multilevel consensus sequences for the MEME defined motifs are listed.
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Characterization of tomato Cycling Dof Factors
MCOG D
MCOG A
MCOG B
MCOG C
Supplementary Figure S1.- Phylogenetic tree of Arabidopsis and tomato DOF proteins.The tree was inferred by the
neighbor-joining method after the alignment of DOF domain amino acid sequences of the Arabidopsis and tomato DOFs. The
resulting Major Clusters of Orthologous Genes (MCOG) A, B, C and D are indicated (Figure 4.1A and 4.1B). The scale bar
corresponds to and 0.01 estimated amino acid substitution per site. Arabidopsis and Tomato CDFs clustered in group D are
marked in blue.
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Characterization of tomato Cycling Dof Factors
4.3.2.- Tomato SlCDF1-5 proteins localize to the cell nucleus and display distinct DNAbinding and activation properties.
To investigate the subcellular localization of SlCDF proteins, translational fusions of their
corresponding ORFs to the C-terminus of GFP were made. These constructs, driven by the 35S promoter,
were used in transient assays with onion epidermal cells by particle bombardment. As shown in Fig. 4.2A,
fluorescence corresponding to the emission spectrum of GFP was restricted to the nuclei of transformed
cells that carried the 35S::GFP::SlCDF: constructs (Fig. 4.2A, panels 8-12). When cells were transiently
transformed with 35S::GFP, the GFP fluorescence spread throughout the cell, indicating a cytoplasmic
localization (Fig. 4.2A panel 7). Nomarski pictures (Fig. 4.2A, panels 1-6) and the merged pictures of those
and the fluorescence images are also shown (Fig. 4.2A, panels 13-18). We examined the capacity of the
tomato SlCDF proteins for binding to the 5’-AAAG-3’ cis-DNA element using the yeast one-hybrid system.
Fig. 4.2B shows the results of an experiment where the different SlCDFs were expressed as fusion
proteins to the GAL4 activation domain in yeast cells harbouring a HIS3 reporter gene under control of a
minimal promoter containing a 2x DOF cis-DNA element. Yeast growth on His-depleted medium results
from the activation of the HIS3 gene through binding of the SlCDF proteins to the cis-DNA element.
Addition of 3-AT as an inhibitor of the HIS3 product was used to measure the strength of the protein-DNA
mediated activation. In all cases, effective yeast growth demonstrated that SlCDF-DNA binding was
sufficiently strong to overcome 3-AT inhibition. However, yeast cells expressing SlCDF1, SlCDF2 and
SlCDF5 grew much better on medium containing 30 mM of 3-AT than those expressing SlCDF3 and
SlCDF4, indicating their higher binding affinity to the 5´-AAAG-3´ motif than the latter.
In order to test the transcriptional activation properties of SlCDFs in planta, transient expression analyses
in Arabidopsis protoplasts were performed (Fig. 4.2C). The 35S::SlCDF1-5 effector plasmids were cotransfected with reporter plasmid pBT10-GUS-2xDOF. The results confirmed that all of the tested CDFs
can bind to the 5´-AAAG-3´ cis-DNA element to different extents, and activate the reporter gene. This
showed that the previously detected DNA-binding capacity is fully functional in leaf protoplasts.
Interestingly, high levels of GUS activity were observed in protoplasts transformed with SlCDF3, 4 and 5,
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Characterization of tomato Cycling Dof Factors
whereas low levels were detected in those protoplasts that were transformed with SlCDF1 and SlCDF2.
Overall, the data obtained indicate that the identified tomato SlCDFs are functional nuclear factors that,
despite their high sequence similarity, bind the DOF element with different affinities and display distinct
transcriptional activation capacities.
A
G
M
35S::GFP
B
100 µm
H
N
35S::GFP-SlCDF1
C
100 µm
O
I
35S::GFP-SlCDF2
D
E
J
P
35S::GFP-SlCDF2
100 µm
µm
100
35S::GFP-SlCDF3
100 µm
K
Q
35S::GFP-SlCDF4
F
L
100 µm
R
35S::GFP-SlCDF5
100 µm
Figure 4.2.- Subcellular localization, transcriptional activation and DNA binding specificity of tomato SlCDF1-5
proteins. (A) Subcellular localization of the SlCDF proteins in onion epidermal cells. GFP alone (35S::GFP) or GFP-SlCDF
(35S::GFP-SlCDF1-5) fusion proteins were expressed transiently under the control of the CaMV 35S promoter in onion
epidermal cells. After 36 h of incubation tissues were observed with a confocal microscope for the emission spectrum of the
GFP (panels 7-12) or by Nomarski (1-6). Merged Nomarski and fluorescence images are also shown (panels 13-18). Arrows
point to cell nuclei.
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Characterization of tomato Cycling Dof Factors
2XDOF: 2xGCGTGACATGTAAAGTGAATAAA
SD/-L/-W/-H (3AT)
0mM
5mM
2xDOF
pTUY1H Ǿ
pTUY1H-2xDOF
30mM
AAAG
GCGTGACATGTAAAGTGAATAAA
AAAG
GUS
5mM
SlCDF
35S
pDEST22Ǿ
0
pDEST22-SlCDF1
pDEST22-SlCDF2
pmoles MU/min 0,5
1
pK7WGF2.0 Ø
35S::SlCDF1
35S::SlCDF2
pDEST22-SlCDF3
35S::SlCDF3
pDEST22-SlCDF4
35S::SlCDF4
pDEST22-SlCDF5
35S::SlCDF5
Figure 4.2.- Continued. Subcellular localization, transcriptional activation and DNA binding specificity of tomato
SlCDF1-5 proteins. (B) The DNA binding specificity of SlCDF1-5 proteins was assayed using the yeast one-hybrid
system.Yeast HF7c cells were transfected with the genes encoding SlCDF proteins and pTUY1H driving HIS3 expression
under the control of 2xDOF binding element. The transformed yeast cells were plated onto the SD/−His/−Trp/−Leu medium
including the indicated amounts 3-AT. Empty pDEST22 plasmid was used as negative control. (C) Transcriptional activation
assays of SlCDFs in Arabidopsis protoplasts. Arabidopsis protoplasts were transfected with the 35S::SlCDF1-5 effector
plasmids (pK7WGF2.0) and pBT10-2XDOF-GUS reporter plasmid, containing 2X DOF cis-DNA element. Empty pK7WGF2.0
plasmid was used as negative control. Data are expressed as means ± standard errors of three independent experiments.
4.3.3.- Expression of tomato SlCDFs follows a circadian rhythm.
To investigate whether the identified SlCDF1-5 genes from tomato are controlled by the circadian
clock like in Arabidopsis (Imaizumi et al., 2005; Fornara et al., 2009), we performed RT-qPCR analyses
using RNA from tomato plants grown under a LD diurnal cycle of 16 h light/ 8 h dark and under continuous
light (LL), respectively. The results revealed that, under LD conditions, the expression levels of tomato
SlCDF1-5 oscillated during the day, although they display quite different patterns, which could be
classified in two groups (Fig.4.3A, B). The expression levels of SlCDF1 and SlCDF3 followed a similar
pattern that consisted of upregulated levels during the second half of the night and the first part of the day,
reaching its maximum level at approximately midday. The, expression then levels rapidly decreased to
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Characterization of tomato Cycling Dof Factors
lower levels in the middle of the night (Fig. 4.3A). In contrast SlCDF2, SlCDF4 and SlCDF5 transcript
levels dropped during the first part of the light period.
Figure 4.3. Transcription analyses of tomato SlCDF1-5 genesduring development and in response to different light
conditions. (A, B) SlCDF1-5 gene expression analyzed by RT-qPCR in 7-week-old tomato plants grown under diurnal cycle
of 16h light/ 8 h dark or under continuous light. White and black bars along the horizontal axis represent light and dark
periods, respectively. (C, D) Expression profiling of SlCDFs genes. SlCDF1-5 gene expression was analyzed by RT-qPCR
using RNA extracted from vegetative and reproductive tissues of tomato: radicles (root) and cotyledons from 3-d-old
seedlings, root and leaves from 30- and 60-day-old plants imbibed seeds, flowers from 60-day-old plants, and green and red
fruit 30 and 60 days after anthesis, as indicated. Expression of tomato UBIQUITIN3 gene (Hoffman et al., 1991) was used as
reference gene. All date are expressed as means ± SE of three independent pools of extracts. Three technical replicates
were performed for each extract.
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Characterization of tomato Cycling Dof Factors
Minimum expression levels were maintained during the second half of the day and the beginning of
the night and increased to reach its maximum at the beginning of the light period (Fig. 4.3A). However,
when the analyses were performed with plants grown under continuous LL conditions, the expression of
tomato SlCDF1-5 genes exhibited a 24 h period oscillation pattern, which is similar to the one observed
under LD (Fig. 4.3B). Moreover, the expression patterns of SlCDF1-5 could still be classified into the same
two groups. Taken together, these data indicate that the expression of SlCDF1-5 is light responsive and
follows a circadian pattern, which strongly supports that the identified tomato CDF genes are true
orthologues of the Arabidopsis CDFs.
4.3.4.- Expression of tomato SlCDF1-5 genes is differentially regulated during
development.
We analysed the expression patterns of tomato SlCDF1-5 genes during plant development using
RT-qPCR (Fig. 4.3C and D) and found that SlCDF1-5 genes have distinct patterns of expression. SlCDF1
and SlCDF2 show higher expression levels in vegetative compared to reproductive organs, while SlCDF4
and SlCDF5 are expressed at significant levels in both types. In addition, SlCDF3 exhibited low expression
in all organs analysed. The difference in expression patterns became more evident when the expression
was analysed in closer detail during plant development (Fig. 4.3C). SlCDF1, SlCDF2, SlCDF4 and
SlCDF5 transcripts accumulated at high levels in cotyledons, but all of them showed minor levels of
expression in mature leaves of 4-week-old plants. In contrast, a significant increment of SlCDF1, SlCDF2
and SlCDF4 transcripts was detected in leaves of 8-week-old plants, while SlCDF3 and SlCDF5 showed a
slight reduction. In addition, a progressive enhancement of SlCDF1 expression was observed in roots
during plant development. SlCDF2, SlCDF4 and SlCDF5 expression was, however, reduced in roots of
older plants, and no changes were detected for SlCDF3. In the reproductive tissues analysed, the
expression of SlCDF1 and SlCDF3 was negligible when compared with the other SlCDFs (Fig. 4.3D).
Higher levels of SlCDF2, SlCDF4 and SlCDF5 transcripts were detected in flowers, fruits and seeds. It is
109
Characterization of tomato Cycling Dof Factors
noteworthy that, during fruit ripening a considerable increment of SlCDF4 was detected, whereas SlCDF5
transcripts were abundant only in green fruit and SlCDF2 showed similar expression in green and red fruit.
4.3.5.- SlCDF1-5 genes are differentially induced in response to abiotic stress conditions.
To address the question whether the expression of SlCDFs is also regulated by environmental
cues other than light/photoperiod, SlCDF1-5 mRNAs levels were measured in leaves and roots of threeweek-old tomato plants that had been subjected to different abiotic stresses: salinity (50Mm NaCl),
osmotic (5% PEG), heat (35/30 ºC) and cold (10/5 ºC) treatments for 6, 12 and 24 h. In leaf tissues,
transcript levels of all SlCDFs increased under salt and osmotic stress, in particular those of SlCDF2 and
SlCDF4 after 24 h (Fig. 3.4A and B). In response to high temperatures, an earlier induction at 12 h was
observed for SlCDF4 and SlCDF5 with higher increases at 24 h together with SlCDF2 (Fig. 4.4C).
However, maximum induction was observed under cold treatment at 12 h for SlCDF1, SlCDF3, SlCDF4
and SlCDF5, with decay at 24 h (Fig. 4.4D). Induction of SlCDFs was also observed in root tissues
following different patterns. All SlCDF genes were regulated by salt and drought. Most importantly,
SlCDF4 and SlCDF5 showed induction after 24 h of salt treatment, whereas SlCDF1, SlCDF2 and SlCDF3
increased at early times (6 h) after osmotic treatment (Fig. 4.4A and B). Regarding to temperature
treatments, maximum increase was observed for SlCDF3 and SlCDF5 at 24 h after heat treatment (Fig.
4.4C), and for SlCDF1, SlCDF3 and SlCDF4 at 12 h after the exposure to low temperatures (Fig. 4.4D).
4.3.6.- Overexpression of tomato SlCDF3 promotes late flowering in transgenic
Arabidopsis plants.
Tomato SlCDF1 and SlCDF3 were selected for further characterization because they responded to
various abiotic stresses and encode proteins that show highest sequence similarity to the functionally wellcharacterized Arabidopsis CDF1 (Imazumi et al., 2005; Fornara et al., 2009). Transgenic Arabidopsis
plants overexpressing SlCDF1 and SlCDF3 under the control of CaMV 35S promoter were generated and
three homozygous lines with relatively high expression of SlCDF1 and SlCDF3 were selected for further
analyses (see Fig. 4.7A). When cultured in soil under greenhouse conditions, all the overexpressing
110
Characterization of tomato Cycling Dof Factors
SlCDF3 lines (L2.10, L10.4, and L10.7) presented several developmental differences relative to WT plants
(Col-0). Plants overexpressing SlCDF3 flowered later than control plants under LD conditions but not in
short day (Fig. 4.5A, B, C and J), suggesting that these plants are impaired in the photoperiodic flowering
pathway. In addition, transgenic lines also displayed other pleiotropic alterations that became more
evident in adult plants both during vegetative and reproductive development. Fig. 4.5D-H shows
representative pictures of 4-week-old WT and 35S::SlCDF3 (line 10.7 as an example) plants showing that
leaves were bigger and petals and carpels of the mature flowers were larger than those of the WT.
Furthermore, the siliques of the overexpressing lines were bigger than WT (Fig.4.5I). In contrast, we did
not observe significantly different phenotypes in the SlCDF1 overexpressing plants (data not shown). To
assess whether the late flowering phenotype observed in the SlCDF3 overexpressing plants is due to
changes in the expression of reported key regulatory genes like CO and FT, we tested diurnal expression
profiles of these genes by RT-qPCR, comparing 35S::SlCDF3 (L2.10 and L10.7) and WT plants. Fig. 4.6A
shows that CO transcript levels decreased in the transgenic plants compared to the Col-0 and the
rhythmic cycling of the mRNA was dampened. Moreover, a reduction in the levels of FT expression was
detected in 35S::SlCDF3 plants (Fig. 4.6A). Altogether, these data support the assumption that the tomato
SlCDF3 exerts a similar mode of action as the Arabidopsis CDFs in the control of flowering time.
111
Characterization of tomato Cycling Dof Factors
Figure 4.4. Transcription analysis of tomato SlCDF1-5 genes analyzed by RT-qPCR in plants exposed to different
abiotic stress conditions. Total RNA was extracted from 7-week-old tomato plants grown in nutrient solution (control) or
supplemented with 50 mM NaCl for salt stress (A), 5% PEG 8000 for drought stress (B) exposed to 35/30 °C for high
temperature stress (C) or exposed 10/5 °C for low temperatures stress, for the indicated times (D). Expression of tomato
UBIQUITIN3 gene (Hoffman et al., 1991) was used as reference gene. Results are presented as relative expression of
SlCDF1-5 under stress conditions compared to the expression under control conditions All data are expressed as means ±
SE of three independent pools of extracts. Three technical replicates were performed for each extract.
112
Characterization of tomato Cycling Dof Factors
LD
B
Col-0
35S::SlCDF3
SD
C
Rosette Leaf Number
A
J
18
16
14
12
10
8
6
4
2
0
*
2.10
Col-0
Col-0
35S::SlCDF3
Col-0
*
*
10.4
35S::AtCDF3
10.7
35S::SlCDF3
E
D
Col-0
Col-0
F
35S::SlCDF3
G
H
Col-0
35S::SlCDF3
Col-0
35S::SlCDF3
Col-0
35S::SlCDF3
35S::SlCDF3
I
Col-0
35S::SlCDF3
Figure 4.5. Phenotypic differences of Col-0 and 35S::SlCDF3 plants during vegetative and reproductive
development.(A) Representative images of four-week-old plants WT and 35S::SlCDF3 (L 10.7 as an example) grown under
LD. (B, C) Flowering-time phenotype under LD and short day (SD) conditions, respectively. (D) Rossete leaves of Col-0 and
35::SlCDF3 plants grown under LD conditions. All leaves, including cotyledons, are shown in order of production from the first
true leaf. (E) Cauline leaves of Col-0 and 35S::SlCDF3 plants grown under LD conditions. (F, G) Detached flowers and
detached petals of Col-0 and 35S::SlCDF3 plants grown under LD conditions. (H) WT and 35S::SlCDF3 flower gynoecium. (I)
Col-0 and 35S::SlCDF3 siliques.(J) Flowering-time analyses of Col-0 and 35S::SlCDF3 (L2.10, L10.4, L10.7) lines estimated
as rosette leaf number formed under LD conditions. Data are expressed as means ± SE of 20 homozygous plants. Asterisks
indicate significant differences (P<0.05; one-way ANOVA followed by Student-Newman-Keuls test).
4.3.7.- Overexpression of SlCDF1 and SlCDF3 has an impact in drought and salt
tolerance in transgenic Arabidopsis plants.
As our expression analyses indicated that tomato SlCDF1 and SlCDF3 might play an important role
in the plant response to different abiotic stresses, we decided to further explore the function of SlCDF1
and SlCDF3. A phenotypic characterization of 35S::SlCDF1 and 35S::SlCDF3 plants was performed by
analysing their response under abiotic stresses, such as dehydration and high-salt treatment
113
Characterization of tomato Cycling Dof Factors
First, we studied the capacity of soil-grown 35S::SlCDF1 and 35S::SlCDF3 transgenic plants to
tolerate water deprivation compared to WT plants. After 15 d of drought, plants were allowed to recover for
10 d during which they were watered. As shown in Fig. 4.7B and C, when cultured in soil under non-stress
(control) conditions, both WT and transgenic lines performed equally well. After the drought treatment, all
WT plants exhibited severe symptoms of water loss and substantial wilting. In contrast, most of the
35S::SlCDF1 and 35S::SlCDF3 transgenic plants were less affected, retaining greener leaves. Only slight
wilting was observed in some of the 35S::SlCDF1 transgenic leaves. After the 10-days recovery period,
the 35S::SlCDF1 and 35S::SlCDF3 transgenic plants exhibited better survival and growth than the WT, as
judged by their survival rates and fresh weight (Fig. 4.7B and 4.7C). To assess tolerance to salt stress,
primary (PR) and lateral (LR) root elongation assays were conducted. 35S::SlCDF1, 35S::SlCDF3 and WT
plants were grown either on control medium (no NaCl) or salt stress medium, containing 80 mM NaCl for
10 days (Fig. 7D and E). Under control conditions there was no difference between the transgenic and the
WT plants. Only two transgenic 35S::SlCDF3 lines (10.4 and 10.7) did exhibit slightly longer roots. On salt
stress medium, 35S::SlCDF1 and 35S::SlCDF3 lines showed slight but significant lower values of root
primary growth inhibition than the WT. Moreover the effect was more evident on root lateral growth, as all
35S::SlCDF1 and 35S::SlCDF3 transgenic plants exhibited much lower values of root lateral growth
inhibition than WT plants under similar stress conditions (Fig. 4.7D and E). Collectively, these data
suggest that SlCDF1 and SlCDF3 may be involved in plant responses to drought and salt stress.
To investigate the molecular mechanisms underlying the enhanced tolerance to drought and salt
tolerance by SlCDF1 and SlCDF3, we tested the expression levels of different abiotic stress-responsive
genes such as COR15A, RD29A and ERD10 in 35S::SlCDF1 and35S::SlCDF3 and WT plants under
control conditions. Fig. 4.6B shows the expression levels of the analysed genes in transgenic lines, where
they exhibited higher values (from two to fourfold) than in WT plants. These data indicate that SlCDF1 and
SlCDF3 might be upstream activators in drought and salt stress pathways, acting directly or indirectly on
the expression of different stress-regulated target genes.
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Characterization of tomato Cycling Dof Factors
A
Col-0
35S::SlCDF3 (L2.10)
35S::SlCDF3 (L10.7)
1.4
1.2
Col-0
35S::SlCDF3 (L2.10)
35S::SlCDF3 (L10.7)
0.5
0.4
CO/UBI
1.0
FT/UBI
0.8
0.6
0.3
0.2
0.4
0.2
0.1
0
0
0
4
8
12
16
20
24
0
4
8
Hours
12
16
20
24
Hours
12
12
10
10
Relative expression
Relative expression
B
8
6
4
8
6
4
2
2
0
0
COR15
Col-0
RD29
L1.2
COR15
ERD10
L1.4
L2.6
RD29A
Col-0
35S::SlCDF1
L2.10
ERD10
L10.4
L10.7
35S::SlCDF3
Figure 4.6. Transcription analysis of flowering time and abiotic stress-responsive genes in 35S::SlCDF1 and
35S::SlCDF3 lines. (A) mRNA levels of CO and FT genes were analyzed by RT-qPCR in 35S::SlCDF3 (L2.10, L10.7) and
control plants (Col-0). Total RNA was extracted from 10-day-old seedlings and harvested, at the indicated times, throughout a
LD. White and black bars along the horizontal axis represent light and dark period, respectively. (B) The expression of
COR15, RD29A and ERD10 genes was analyzed by RT-qPCR on three-week-old 35S::SlCDF1 (L1.2, L1.4, L2.6),
35S::SlCDF3 (L2.10, L10.4, L10.7) and control (Col-0) plants. Expression of Arabidopsis UBIQUITIN10 gene (Czechowski et
al., 2005) was used as reference gene. All data are expressed as means ± SE of three independent pools of extracts. Three
technical replicates were performed for each extract.
115
Characterization of tomato Cycling Dof Factors
A
1
Relative Expression
Relative Expression
1
0,8
0,6
0,4
0,2
0
Col-0
B
L1.2
L1.4
35S::SlCDF1
0,8
0,6
0,4
0,2
0
L2.6
L2.10
Col-0
L10.4
L10.7
35S::SlCDF3
Control
Drought
stress
Survival
rate (%)
C
34%
100%
92%
50%
52%
93%
3
*
2
*
Fresh weight (g)
Fresh weight (g)
3
100%
*
1
86%
*
*
2
1
0
0
Col-0
L1.2
L1.4
L2.6
35S::SlCDF1
Col-0
L2.10
L10.4
L10.7
35S::SlCDF3
Figure 4.7. Drought stress tolerance of 35S::SlCDF1 and 35S::SlCDF3 plants.(A) Transcription analysis of tomato
SlCDF1 and SlCDF3 genes in different T3 independent 35S::SlCDF1 (L1.2, L1.4, L2.6) and 35S::SlCDF3 (L2.10, L10.4,
L10.7) transgenic lines. SlCDF1-3 expression was analysed by RT-qPCR in Arabidopsis plants. Expression of Arabidopsis
UBIQUITIN10 gene (Czechowski et al., 2005) was used as reference gene. Data are expressed as means ± SE of three
independent extractions. Three technical replicates were performed for each extraction. (B) Drought stress tolerance was
estimated by scoring fresh weight and survival rates of two-week-old 35S::SlCDF1 (L1.2, L1.4, L2.6), 35S::SlCDF3 (L2.10,
L10.4, L10.7), and control (Col-0) plants, that were maintained 15 days without irrigation and then 10 days of re-watering.
Representative images of plants before and after the treatment. Survival rates are indicated under the photographs. (C) Fresh
weight data are expressed as means ± SE of three independent experiments with five plants each. Asterisks indicate
significant differences between Col-0 and 35S::SlCDF1 or 35S::SlCDF3 overexpressing lines (P<0.01; ANOVA StudentNewman-Keul
116
D
Relative Inhibition of rootlength (%)
Characterization of tomato Cycling Dof Factors
70
40
60
35
50
30
*
*
*
*
*
20
*
15
*
20
*
25
40
30
Primary root
Lateral root
*
10
*
10
5
0
Col-0
1.2
1.4
0
2.6
2.10
Col-0
35S::SlCDF1
80mM NaCl
10.4
10.7
35S::SlCDF3
80mM NaCl
E
Col-0
35S::SlCDF1 (2.6)
Col-0
80 mM NaCl
35S::SlCDF3 (2.10)
80 mM NaCl
Figure 4.7 Continued. Salt stress tolerance of 35S::SlCDF1 and 35S::SlCDF3 plants. (D) Salt stress tolerance estimated
by determining the reduction of primary and lateral growth of 35S::SlCDF1 (L1.2, L1.4, L2.6), 35S::SlCDF3 (L2.10, L10.4,
L10.7) and control (Col-0) plants after 10d in MS supplemented with 80mM NaCl and represented as percentage of reduction
relative to standard conditions. Data are expressed as means ± SE of three independent experiments with at least 20 plants
each. Asterisks indicate significant differences between Col-0 and 35S::SlCDF1 or 35S::SlCDF3 overexpressing lines
(P<0.05; ANOVA Student-Newman-Keuls test). (E) Representative images of Col-0,35S::SlCDF1 (L2.6) and 35S::SlCDF3
(L2.10) after the treatments.
4.3.8.- Overexpression of SlCDF3 in transgenic Arabidopsis plants induces metabolic
changes and accumulation of specific compounds.
As drought and salt stress are known determinants that promote substantial physiological and
metabolic rearrangements in plants (Rizhsky et al., 2004; Seki et al., 2007), we carried out non-targeted
metabolite profiling to address the question whether the ectopic expression of SlCDF3 in Arabidopsis
translates into a detectable alteration of the plant´s metabolome. Principal component analysis (PCA) of
117
Characterization of tomato Cycling Dof Factors
the retention time, intensity, and accurate mass identity matrices, carried to compare approximately 1000
molecular features per sample with each other, revealed that the overexpression of SlCDF3 results in a
distinguishable alteration of the metabolome, as indicated by the clear clustering of the datasets (Fig.
4.8A). When we tried to identify the differentially abundant components causing the grouping in the PCA,
we discovered that a great part of the differences were found among the group of small and polar
compounds, containing for example sugars, amino acids, and small acids. As an example, the increased
abundance of glutamine in the overexpressing lines compared to the WT is shown in Fig. 4.8B and C.
Hence, we focused our analyses on those polar compounds and performed a targeted metabolomic
profiling by gas chromatography-mass spectrometry (GC-MS) to study the relative levels of different polar
compounds, including proteinogenic amino acids as well as four other amino acids, eight distinct sugars
plus two sugar alcohols, and eight small acids, extracted from 12-day-old WT and 35S::SlCDF3 (L2.10
and L10.7 lines) transgenic plants, grown under non-stress conditions. As shown in Fig. 4.8 D and
Supplementary Table S4.4, the comparison of GC profiles revealed a number of clear differences between
control and overexpressing lines. Overexpression of SlCDF3 in Arabidopsis significantly induced the
accumulation of sugars like sucrose (2.5-fold), and amino acids like GABA (2-fold), L-proline (2.2-fold) and
L-glutamine (1.8-fold), and succinate (1.3-fold), while the amount of malate and gluconate decrease by up
to 24 and 34.9.%, respectively, relative to the control. Consistent with the expected similar effects in both
SlCDF3 overexpressing lines, most sugars appeared at comparable levels. Interestingly, these lines
showed an important increase in sucrose compared to the WT. Since glucose and fructose, the two
monomeric building blocks of sucrose, showed no considerable reductions, it may be concluded that
SlCDF3 overexpression either causes a change in carbon partitioning favoring the production of sucrose
over that of starch, or that CO2 fixation rates are generally increased. Finally, overexpression of SlCDF3
did not trigger the accumulation of organic acids, except succinate, as reflected by its increased
concentration in both transgenic lines grown under control conditions (Fig. 4.8D).
118
Characterization of tomato Cycling Dof Factors
Figure. 4.8. Metabolic analyses of 35S::SlCDF3 and WT plants. (A) PCA of recorded, non-targeted metabolic profiles using
Profile Analysis (Bruker Daltonics, Bremen, Germany). Projection plots obtained for principal component 1 (PC1, 19%
variance explained) and PC2 (15%). Distinct grouping supports the different genotypes analysed: WT control samples or
overexpression lines 2.10 and 10.7, respectively. (B) Extracted ion chromatograms (EICs) for mass m/z 130.05 at 0.81 min
reveal induction of the compound in the overexpression lines. (C) The accurate mass of the parent ion and its isotopic pattern
led to the identification of L-glutamine. (D) Relative quantities (% of WT) of selected metabolites analysed by Gas
chromatography-selected ion monitoring-mass spectrometry. Results are shown as means ± SE (n = 15). Similar results were
obtained in five independent experiments. [Student’s t test; * P < 0.05, ** P < 0.01, *** P < 0.001].
119
Characterization of tomato Cycling Dof Factors
4.4.- DISCUSSION.
DOF proteins are plant-specific FTs that participate in different developmental and physiological
processes (Lijavetsky et al., 2003; Moreno-Risueño et al., 2007a). In this work we have identified and
characterized tomato DOF genes, homologous to Arabidopsis CDFs, and found that the encoded proteins
possessed transcriptional activation ability. Furthermore, we provide evidence for their participation in the
control of flowering time and abiotic stress responses.
4.4.1.- SlCDFs share a high degree of sequence similarity but display different DNAbinding affinities and diverse transcriptional activation capabilities.
We searched the complete tomato genome sequence and identified 34 genes encoding DOF
proteins. In accordance with previous studies in Arabidopsis (Lijavetzky et al., 2003), these 34 genes
were divided into four groups (A-D) on the basis of similarities in their DNA binding domains. Within group
D, we found five tomato genes with high level of sequence similarity to Arabidopsis CDFs. The encoded
proteins showed conservation not only in their DNA-binding domain but also in their C-terminal region,
which contained three conserved motifs of 21, 22 and 33 aa, respectively, which were reported to be
essential for the protein-protein interaction with the C-terminal kelch repeat domain of the F-box proteins
FKF1 and LKP2 (Imaizumi, 2005; Sawa et al., 2007). In addition, these three motifs are also conserved in
homologous proteins from other species, such as Jatropha curcas (JcDOF3; Yang et al., 2011a),
Brachypodium distachyon (BdDOF4, -11, -16, -20 and -22; Hernando-Amado et al., 2012) and Solanum
tuberosum (StCDF1, Kloosterman et al., 2013). Interestingly, two allelic variants of potato StCDF1
(StCDF1.2 and StCDF1.3) lacking the C-terminal end have been reported to be impaired in their
interaction with the FKF1-GI complex. As a consequence, this results in major defects in plant maturity
and tuber development (Kloosterman et al., 2013). Consistent with these data, it may be concluded that
the three identified C-terminal motifs are common features of CDF proteins, through which the regulatory
mechanisms controlled by CDFs are determined.
120
Characterization of tomato Cycling Dof Factors
Subcellular localization and yeast one-hybrid assays conducted in this study showed that the identified
tomato SlCDFs are nuclear factors that bind to the core 5’-TAAAG-3’ DOF cis-DNA element (Yanagisawa
and Schmidt, 1999) with different binding affinities. Transactivation assays confirmed these results and
indicated that SlCDFs can act as transcriptional activators, again to different extents. While SlCDF1 and
SlCDF2 exhibit only little transcriptional activation capabilities, SlCDF3, SlCDF4, and SlCDF5 display
higher transcriptional activation capacity. Consistent with these data, the overexpression of SlCDF1 and
SlCDF3 in Arabidopsis promote the expression of COR15, RD29A and ERD10. Whether they act directly
or indirectly as upstream activators remain to be elucidated. In contrast, we found that the overexpression
of SlCDF3 results in reduced expression of both CO and FT genes, most likely acting as a target
repressor, as reported for the Arabidopsis CDF1 protein (Imauzumi et al., 2005; Fornara et al., 2009). It
should be noted that the DOF domain was at first identified as a DNA-binding domain, but also reported as
a bifunctional domain for DNA-binding and protein-protein interactions (Mackay and Crossley, 1998).
Differences in the activities of DOF TFs have been associated to the core DOF domain (Yanagisawa,
2004) as well as their protein-protein interactions with other TFs. In fact, the DOF domain participates in
the interaction with other classes of TFs like bZIP proteins or HMG proteins, which in turn modify their
transcription capabilities (Vicente-Carbajosa et al., 1997; Yanagisawa, 1997; Zhang et al., 1995; Krohn et
al., 2002). For example, the Arabidopsis DOF protein OBP1 was identified as a protein interacting with
bZIP proteins OBF4 and OBF5 associated with stress responses (Zhang et al., 1995). Altogether, these
data suggest that the identified SlCDFs could display different transcription activities depending on target
gene promoters and the combinatorial interactions with other transcription factors present in a particular
tissue or under different environmental conditions.
4.4.2.- Expression of SlCDFs follows a circadian rhythm with two different patterns.
Diurnal oscillation of transcript levels of CDFs has been reported for Arabidopsis and other species
under day/night and constant light conditions (Imaizumi et al., 2005; Fornara et al., 2009; Iwamoto et al.,
121
Characterization of tomato Cycling Dof Factors
2009; Yang et al., 2011). CDFs exhibit different diurnal expression patterns that can be classified in two
different groups: CDF1, CDF2, CDF3 and CDF5 show maximum expression at the beginning of the light
period, decreasing progressively thereafter to a minimum between 16-20h, then rising again during dawn;
and the group comprising CDF4, whose transcript levels rise progressively from dawn and decrease at the
end of the night (Fornara et al., 2009). In the present study, the identified tomato SlCDFs that exhibit
similar diurnal expression patterns under LD and LL conditions, supporting the assumption that they are
true homologues of the Arabidopsis CDFs. Interestingly, their gene expression patterns could be also
classified in two groups, the group of SlCDF1 and SlCDF3 exhibit a maximum at the beginning of the day
and SlCDF2, SlCDF4 and SlCDF5 that exhibit maximum levels during the night period, suggesting that the
family of CDFs might display different function (at least two conserved functions) and regulate specific
target genes at different periods of the day.
4.4.3.- Expression of tomato SICDF genes in Arabidopsis unveils a conserved function
in the control of flowering time.
It is well established that regulation of the temporal expression of the transcription factor CO is
crucial to control the photoperiodic flowering in Arabidopsis and other photoperiod-sensitive species
(Suarez-López et al., 2001; Mizoguchi et al., 2005). The induction of CO mRNA by light under LD
conditions, but not in short-day conditions, is a key element for the triggering of flowering, as light
treatment is necessary for the stabilization of CO protein (Valverde et al., 2004; Jang et al., 2008) and the
subsequent activation of FT transcription (Takada and Goto, 2003; An et al., 2004; Wigge et al., 2005; Yoo
et al., 2005). In addition, the Arabidopsis CDFs act redundantly in repressing CO transcription to modulate
the diurnal expression rhythm (Imazumi et al., 2005; Fornara et al., 2009). Our results show that the
overexpression of tomato SlCDF3, in analogy to Arabidopsis CDF1, promoted late flowering in
Arabidopsis. Interestingly, SlCDF3 overexpression also leads to a reduction in the mRNA levels of CO and
FT, the natural direct targets of the Arabidopsis counterpart (Fig. 4.6), which is in support of a conserved
functionality. Nevertheless, it should be noted that tomato plants are photoperiod-insensitive in their native
habitats and there is no single environmental factor known to be critical for flower induction in this species
122
Characterization of tomato Cycling Dof Factors
(Heuvelink and Dorais, 2005). Several factors such as light intensity, temperature and number of leaves
affect the time of flowering in tomato (Calvert, 1959; Hussey, 1963; Kinet, 1977; Uzun, 2006), a process
considered to be controlled by intraplant competition for assimilates (Sachs and Hackett, 1969; Atherton
and Harris, 1986; Dieleman and Heuvelink, 1992). Notably, key regulatory genes like CO and the CDFs,
implicated in the photoperiodic flowering pathway are also present in tomato (Pnueli et al., 1998, 2001;
Carmel-Goren et al., 2003; Ben-Naim et al., 2006). Our results suggest that some of the identified tomato
SlCDFs, like SlCDF3, might retain some functions in the control of flowering time through similar molecular
mechanisms to those observed when expressed in Arabidopsis, but also that they might have additional
functions in tomato.
4.4.4.-SlCDFs involvement in abiotic stress responses.
As revealed by RT-qPCR expression analyses all SlCDFs respond to different abiotic stresses like
salt, drought and extreme temperatures with different timing and spatial expression patterns in roots and
shoots, suggesting that they might participate in abiotic stress responses. This observation led us to the
generation and analyses of 35S::SlCDF1 and 35S::SlCDF3 transgenic Arabidopsis plants. We could
confirm that the overexpression of SlCDF1 and SlCDF3 resulted in increased tolerance to both salt and
drought stress, as shown by survival rates and root length assays. Moreover, both overexpressing lines
exhibit higher expression levels of abiotic stress-responsive genes, like COR15, RD29A and ERD10,
under non-stress conditions, which indicate that SlCDFs might function as upstream regulators in drought
and salt stress response pathways. Metabolic profiling of 35S::SlCDF3 plants showed increased levels of
proline, glutamine, GABA and sucrose. These compounds are normally accumulated under water stress
and salinity (Hoekstra et al., 2001; Rizhsky et al., 2004) aiding stress tolerance through osmotic
adjustment, detoxification of reactive oxygen species and intracellular pH regulation (Rajasekaran et al.,
2000; Claussen, 2005; Munns and Tester, 2008; Bressan et al., 2009; Chaves et al., 2009). Their
significant increased levels, promoted by the overexpression of SlCDF3 in Arabidopsis, seemingly
contribute to improved drought and salt tolerance since its content has been correlated with the stress
123
Characterization of tomato Cycling Dof Factors
tolerance (Kerepesi and Galiba, 2000; Farrant and Moore, 2011; Pinheiro and Chaves, 2011). Altogether,
our results strongly support the participation of SlCDFs in plant responses and tolerance to abiotic stress
conditions.
4.4.5.- Impact of SlCDFs expression on C/N metabolism.
SlCDFs exhibit different expression patterns during development. However, with the exception of
SlCDF3, all of them are expressed during vegetative development at high levels, especially in young
tissues like cotyledons. In organs with contrasting sink and source activities like mature vegetative tissues
of shoots and roots, and reproductive tissues, such as flowers and fruits, they are also differentially
expressed. This may highlight precise tissue-specific functions for the SlCDFs in controlling the expression
levels of particular subsets of genes and consequently specific metabolic processes.In this regard, the
metabolic analyses of 35S::SlCDF3 plants show that the overexpression of SlCDF3 transcription factor in
Arabidopsis results in significant metabolic alterations. Specifically, we observed higher levels of sucrose
and of certain amino acids, indicative of increased nitrogen assimilation, as previously reported for other
DOF TFs (Yanagisawa et al., 2004b). In this line, our studies also revealed a higher content of succinate
and GABA. The hypothesis that GABA acts as a temporary nitrogen storage pool could explain the
increased concentration of this non-proteinogenic amino acid (Beuve et al., 2004). On the other hand, upregulation of the pathway that converts glutamate to succinate via GABA would explain the rise in
succinate content (Rhodes et al., 1999). Glutamic acid metabolism via the GABA shunt could be of
considerable importance in the nitrogen economy of plants (Shelp et al., 1999; 2006). As carbon and
nitrogen metabolites mutually influence each other in a fine balance between carbon and nitrogen
metabolism (Yanagisawa et al., 2004b; Kurai et al., 2011), the higher content of sucrose in 35S::SlCDF3
transgenic plants suggests that CO2 fixation could be also stimulated to maintain the carbon/nitrogen
balance. Hence, we hypothesize that SlCDFs genes could be involved in the regulation of the primary
metabolism in different tissues and under precise developmental and stress conditions.
124
Characterization of tomato Cycling Dof Factors
4.4.6.- CDFs at the interplay between environmental conditions and flowering time.
The results of our study confirmed a previously reported and salient feature of CDFs in the control
of flowering time. Specifically, the overexpression of AtCDFs in phloem companion cells leads to a delay
in flowering in LDs although with a different impact in Arabidopsis (Imazumi et al., 2005; Fornara et al.,
2009). Here, we could demonstrate conservation in this function for specific tomato CDFs, which are able
to reproduce the same phenotype when expressed in Arabidopsis. Flowering time is critical in the plant life
cycle, yet plants must closely monitor the environmental state to determine the onset of flowering for
reproductive success. Intriguingly, data presented here reveal that, besides the participation of some
SlCDF genes in the control of flowering in photoperiod-sensitive species, they also display additional
functions. Notably, SlCDFs regulate the expression of genes involved in abiotic stress responses.
Moreover, metabolic analyses of SlCDF-overexpressing plants showed accumulation of precise
compounds that mitigate abiotic stress conditions. They also showed important changes in particular
metabolites, like increased levels of sucrose and certain amino acids, typically associated to physiological
states like the nutrient salvage and recycling under senescence programs (Jones, 2013) or the
mobilization and relocation of resources from source to sink organs. This information opens the possibility
of further investigating the links of CDF function in the adaptation to environmental conditions and the
progression from vegetative to reproductive phases. Additional research and in-depth physiological
characterization of transgenic plants for the different SlCDF genes, currently underway, will clarify the
precise role of these genes.
125
5
CONCLUSIONES
Conclusiones
El estudio de la implicación de diferentes factores de transcripción de la familia DOF en el
desarrollo y la tolerancia a estreses abióticos nos ha permitido obtener las siguientes conclusiones:
1. El análisis de expresión “in silico” de los genes que codifican factores de tipo DOF de
Arabidopsis indica que los pertenecientes al grupo D, y especialmente los AtCDFs, cambian su
niveles de expresión en respuesta a distintos tipos de estrés abiótico en tejidos vegetativos.
2. El gen CDF3 de Arabidopsis thaliana codifica un factor de transcripción de tipo DOF cuya
expresión aumenta en respuesta a salinidad, temperaturas extremas, deshidratación y
tratamientos con la fitohormona ABA en tejidos vegetativos.
3. El factor de transcripción AtCDF3 se localiza en el núcleo y se une al elemento cis-DNA 5´AAAG-3´. Además funciona como un activador transcripcional. El dominio C - terminal del factor
AtCDF3 es esencial para su localización nuclear y actividad transcripcional.
4. La sobre-expresión del gen AtCDF3 en Arabidopsis provoca un aumento de la tolerancia a las
bajas temperaturas y a la sequía, mientras que el mutante knock-out cdf3-1 es más sensible a
estos estreses. Además, la sobre-expresión de una forma truncada de AtCDF3 sin el dominio Cterminal, limita el incremento de la tolerancia a sequía, lo que sugiere un papel importante de
este dominio en la función de la respuesta a estrés abiotico.
5. Análisis de expresión global de líneas transgénicas 35S::AtCDF3 indica que AtCDF3 regula la
expresión de un número importante de genes, implicados en la respuesta a estrés abiótico y en
la asimilación de nitrógeno. Además, análisis metabolómicos señalan la acumulación de
distintos metabolitos, como azúcares y aminoácidos. Estos datos confirman que los AtCDFs
desempeñan un papel importante en la regulación del metabolismo primario durante el
desarrollo y bajos distintas condiciones de estrés.
127
Conclusiones
6. La sobre-expresión del gen AtCDF3 en tomate promueve un aumento de la fotosíntesis y la
biomasa, tanto en condiciones habituales de cultivo, como bajo estrés salino y bajas
temperaturas.
7. El análisis filogenético comparado entre las proteínas SlDOF y sus ortólogas en Arabidopsis
establece cuatro grupos principales de genes ortólogos (MCOG: Major Clusters of Orthologous
Genes).
8. Se han identificado los ortólogos putativos de los genes “Cycling Dof Factors” CDF1-5 de
Arabidopsis en tomate. Estos genes presentan características estructurales similares a los del
grupo D de Arabidopsis y han sido denominados S. lycopersicum CDF1-5. Los SlCDF1-5 son
proteínas nucleares que se unen al motivo cis-DNA 5´-AAAG-3´ con diferentes afinidades y
actúan como activadores transcripcionales.
9. Los genes SlCDF1-5 exhiben distintos patrones de expresión en los órganos de la planta y
están regulados por ritmo circadiano. Además, sus niveles de expresión aumentan en respuesta
a estrés osmótico, salino y por temperaturas extremas.
10. La sobre-expresión del gen SlCDF3, pero no del SlCDF1, en Arabidopsis promueve un retardo
en el tiempo de floración a través de la modulación de la expresión de genes como AtCO y
AtFT. Estos datos indican que el gen SlCDF3 actúa de forma similar a los AtCDFs en el control
de la floración.
11. Líneas transgénicas de Arabidopsis que sobre-expresan los genes de tomate SlCDF1 y SlCDF3
muestran un aumento de la tolerancia a sequía y salinidad, asociado de un incremento en la
expresión de varios genes de respuesta a estrés como AtCOR15, AtRD29A y AtERD10.
128
Conclusiones
12. Análisis metabolomico de las líneas transgénicas de Arabidopsis 35S::SlCDF3 muestran una
acumulación de azúcares como sacarosa y determinados aminoácidos, sugiriendo que los
SlCDFs pueden estar involucrados en la regulación del metabolismo primario.
129
6
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154
SUPPLEMENTARY
Supplementary
3.-. Arabidopsis Cycling Dof Factor 3 CDF3 regulate drought and low temperature stress response
and flowering time in Arabidopsis thaliana
ATG
STOP
GK-808605
Col-0
C
cdf3-1
4ºC
C
4ºC
AtCDF3
UBQ
Supplementary Figure S3.1.- Characterization of cdf3-1 mutant. A) Scheme of the T-DNA insertion
mutant cdf3-1 GABI-Kat (GK-808605). The insertion T-DNA is located to 400 pb from ATG. B) AtCDF3
gene expression analysis. Expression of AtCDF3 gene was analysed by RT-PCR in Col-0 and cdf3-1
mutant plants. Total RNA was extracted from 3-week-old plants grown under control conditions (20ºC)
and exposed to low temperatures (4ºC at 24h) stress. Expression of Arabidopsis UBIQUITIN10 gene
(Czechowski
et
al.,
2005)
was
156
used
as
control.
Supplementary
E
B
A
Col-0
35S::AtCDF3
C
Col-0
35S::AtCDF3
Col-0
35S::AtCDF3
D
Col-0
F
G
Col-0
35S::AtCDF3
Col-0
H
Col-0
Col-0
35S::AtCDF3
35S::AtCDF3
Supplementary Figure S3.2. Phenotypic differences of Col-0 and 35S::AtCDF3 plants during vegetative
and reproductive development. A) Representative images of four-week-old plants WT and 35S::AtCDF3 (L
2.1) grown under LD. B) Flowering-time phenotype under long day (LD). C) Cauline leaves of Col-0 and
35S::AtCDF3 plants grown under LD conditions. D) Rossete leaves of Col-0 and 35S::AtCDF3 plants
grown under LD conditions. All leaves, including cotyledons, are shown in order of production from the first
true leaf. (E, F) Detached flowers and detached petals of Col-0 and 35S::AtCDF3 plants grown under LD
conditions. G) Wild type and 35S::AtCDF3 flower gynoecium. H) Col-0 and 35S::AtCDF3 siliques.
157
Supplementary
B
A
E
Col-0
35S::AtCDF3-stop
F
C
Col-0
35S::AtCDF3-stop
Col-0
Col-0
35S::AtCDF3stop
Col-0
35S::AtCDF3-stop
35S::AtCDF3-stop
G
Col-0
35S::AtCDF3-stop
H
D
Col-0
Col-0
35S::AtCDF3-stop
35S::AtCDF3-stop
Supplementary Figure S3.3. Phenotypic differences of Col-0 and 35S::AtCDF3-stop plants during
vegetative and reproductive development. A) Representative images of four-week-old plants WT and
35S::AtCDF3-stop grown under LD. B) Flowering-time phenotype under long day (LD). C) Cauline leaves
of Col-0 and 35S::AtCDF3-stop plants grown under LD conditions. D) Rossete leaves of Col-0 and
35::CDF3-stop plants grown under LD conditions. All leaves, including cotyledons, are shown in order of
production from the first true leaf. (E, F) Detached flowers and detached petals of Col-0 and 35S::AtCDF3
plants grown under LD conditions. G) Wild type and 35S::AtCDF3-stop flower gynoecium. H) Col-0 and
35S::AtCDF3-stop siliques.
158
Supplementary
Supplementary Figure S3.4. Identification of 5´- AAAG-3´ cis-DNA binding elements statiscally overrepresented in
the
promotor
regions
of
responsive-genes
stress
http://bar.utoronto.ca/ntools/cgi-bin/BAR_Promomer.cgi (Toufighi et al., 2005).
159
using
tool
Promoter
Supplementary
1100bp
AAACTTTGGTAGCTTTAGGGTTTTTTCAAGTCTGTGACTTATAAACGTCGAGAGAGTGTAAGCACGCT
CCATAATCTACCGCTGTTCACAAGTAATAATAGATCTTGTCCGTTGAATTTATTTTAGACTTTTTTTTTA
ATGGACTTCATTTTAAATTTTTACAAAATTAAATTATTGCATTTTCTATTTCATATTGAATTAGGAGATGT
TACTGTCCGTCAGATTCTCTAGACTTTTTTTTTTAAAGACTGATCTATGATCAGAATTCCAATTTTTTTT
TTCTTTAAGGAAATACATCAGAGAGAAAAATTATTACGAAACGATTCTATTACAAGTAATGATTTTAACC
TTTTTTTTTTTACAATTGACAATCTTTTCACAACAAAAATCCACAAGAAACGTTAGACAATGGCATAAAT
TTATTTAAATTAATCCGTATATATTCGCCTTCTATGAGAATTGAATTCTATACCACTGTAAAATTCTTAAA
CGAGATAAGATTATTTTCAGCATGTAAAAAATGGTTTGTGGTTTCAACTCATTTGGGCTATTAGTTTTA
CATTTAGGCTTGCAACCTTGTCGGTTTATTTTGTGTAGGCTTTTGGTAGATTTGGGCTTGCAAACCCAA
ATTAACTTGTTGGCCGACATACATTTGTTTCTATTACAAATTTAACAACAAACGTCAATAAATACACGTG
AAGGAAATGAGAACGACCCTCTTAAGTAGTACTGGAAATTGAAAAAAAGAAATCTAGAAATGCTAACA
TGTAAGTTTTTGTTACCAAAAATGCAATTTGTATGTAGCCACAATTTCATGGCCGACCTGCTTTTTTTTT
CTTCTTCTTTCTGAAAACCACAAATATGATTACACGTGGCCTGAAAAGAACGAACAGAAACTCGGTAA
TGTGCAAAAAATATCTTACTCTTAATACGTGTAATTTTGGAGTGTAATAGGTCTATCGATCTATAAAAC
GATACTATTGGAGATTAGATTCTTCTCATCTCACTTTGTTCATCTAAAAACTCCTCCTTTCATTTCCAAA
CAAAAACTTCTTTTTATTCTCACATCTTAAAGATCTCTCTCATGGCGATGTCTTTCTATG
Supplementary Figure S3.5. Sequence analysis of COR15 promoter. Identification of the DOF cis-DNA
binding
elements
in
COR15
promoter
(underline)
and
ATG
(red)
(http://atpan.itps.ncku.edu.tw/promoter_analysis.php?sequence) (Chen et al., 2012)
160
using
AtPAN
tool
Supplementary
Supplementary Table. S3.1.- Primers designed for Real-time PCR, expected size, and concentration
used.
Gene
AtCDF3
AtCDF3-stop
PEPC1
PEPC2
PK1
GLU1
GS2
AtCOR15
AtRD29A
AtERD10
AtUBQ10
Primer sequence
5’-AGAAGGCCGGGTGCGTTCTG-3’
5’-ACCGGCTTTGCACATCGCCT-3’
5’-TTGGTCTCGAAGCTCAGCAG-3’
5’- TCAACAACACTGCCGCTTTG -3’
5’-CTTTGAATCTCTCTTTCTCTCTC-3’
5’- CTCGAAGTACTCGTACACG -3’
5’-CCATTCCCTAAATCTACGC-3’
5’-GGTAACATAACAACAATAG-3’
5’-CGTCAGGCCTCCTCCTTCATTC-3’
5’-GTTCATGTGTCAGAAGG-3’
5’-CTATGGAGAGCAGATTAATGG-3’
5’-GTACAGTTATAGCAACCATGG-3’
5´-GAATCTGATGAACACACGTGTC-3
5´-GGACATGCTCTAACAGTC-3´
5’-CAGCGGAGCCAAGCAGAGCAG-3’
5’-CATCGAGGATGTTGCCGTCACC-3’
5’-GGTTCGGTGGTGGTGCGACT-3’
5’-TGGCTTCACCTCCTCCGTCG-3’
5’-CGTTTGTGGCCAAGCACGAAG -3’
5’-AGAGCTGTTGGATCGGTGGAGT-3’
5’-GCTCTTATCAAAGGACCTTCG -3’
5’-CGAACTTGAGGAGGTTGCAAA-3’
161
Amplicon
Concentration
length (pb)
(µM)
93
0.200
0.300
0.200
0.300
0.300
0.300
0.200
0.200
0.300
0.200
0.375
0.125
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.150
67
66
72
80
72
90
125
113
128
61
Supplementary
Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or down- regulated in
35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
1
At3g47500
2,16
0,000
Dof type zinc finger domain containing protein
2
At5g45650
1,85
0,000
subtilase family protein
3
At5g11070
1,9
0,000
expressed protein
4
At2g25735
3,32
0,000
expressed protein
5
At2g04240
1,84
0,000
zinc finger (C3HC4 type RING finger) family protein
6
At4g23200
2,76
0,000
protein kinase family protein
7
At2g21650
1,98
0,000
myb family transcription factor
8
At1g56150
2,7
0,000
auxin responsive family protein
9
At5g15160
1,65
0,000
bHLH family protein
10
At1g74940
1,87
0,000
senescence associated protein related
11
At4g32030
1,64
0,000
expressed protein
12
At5g60680
2,31
0,000
expressed protein
13
At4g37610
2,3
0,000
14
At1g66090
2,42
0,000
disease resistance protein (TIR NBS class), putative
15
At1g69490
2,35
0,000
no apical meristem (NAM) family protein
16
At2g18660
3,48
0,000
17
At4g30110
1,86
0,000
expansin family protein (EXPR3)
ATPase E1 E2 type family protein / haloacid dehalogenase like
family protein
18
At2g17040
3
0,000
no apical meristem (NAM) family protein
19
At2g42760
2,01
0,000
expressed protein
20
At1g24140
3,14
0,000
matrixin family protein
21
At4g23180
2,46
0,000
receptor like protein kinase 4, putative (RLK4)
22
At3g63210
1,91
0,001
expressed protein
23
At1g28370
3,03
0,001
ERF11 ERF domain protein 11 (ERF11)
24
At1g63840
1,64
0,001
zinc finger (C3HC4 type RING finger) family protein
25
At1g80920
1,89
0,001
DNAJ heat shock N terminal domain containing protein
26
At3g16530
1,96
0,001
legume lectin family protein
27
At5g02230
1,77
0,001
haloacid dehalogenase like hydrolase family protein
28
At1g75040
2,64
0,001
29
At4g21850
2,12
0,001
PR 5 pathogenesis related protein 5 (PR 5)
methionine sulfoxide reductase domain containing protein / SeIR
containing protein
30
At3g04640
2,38
0,001
31
At2g43010
1,68
0,001
glycine rich protein
PIF4/SRL2/bHLH9 phytochrome interacting factor 4 (PIF4) / basic helix loop
helix protein 9 (bHLH9) /
32
At1g56010
1,58
0,001
transcription activator NAC1 (NAC1)
33
At1g20450
2,08
0,001
dehydrin (ERD10)
34
At4g34150
1,85
0,001
C2 domain containing protein
35
At1g58420
3,78
0,001
expressed protein
36
At5g01870
1,87
0,001
lipid transfer protein, putative
37
At2g23120
1,78
0,001
expressed protein
38
At1g12160
1,75
0,001
flavin containing monooxygenase family protein / FMO family protein
39
At2g17840
2,45
0,001
senescence/dehydration associated protein related (ERD7)
40
At5g23020
2,39
0,001
IMS2 2 isopropylmalate synthase 2 (IMS2)
41
At1g14370
1,88
0,001
protein kinase (APK2a)
42
At1g25560
2,44
0,001
AP2 domain containing transcription factor, putative
43
At1g68840
2,69
0,001
DNA binding protein RAV2 (RAV2) / AP2 domain containing protein RAP2.8
44
45
At2g32150
At5g45340
2,35
2,7
0,001
0,001
haloacid dehalogenase like hydrolase family protein
cytochrome P450 family protein
p-value
Description
TAZ zinc finger family protein / BTB/POZ domain containing protein
162
hydrolase
domain
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
46
At4g12720
1,73
0,001
MutT/nudix family protein
47
At4g16780
2,16
0,001
homeobox leucine zipper protein 4 (HAT4) / HD ZIP protein 4
48
At4g18880
2,81
0,001
heat shock transcription factor 21 (HSF21)
49
At2g32030
1,82
0,001
GCN5 related N acetyltransferase (GNAT) family protein
50
At2g41430
1,71
0,001
dehydration induced protein (ERD15)
51
At3g03520
1,87
0,001
phosphoesterase family protein
52
At3g25290
1,74
0,001
auxin responsive family protein
53
At2g27830
1,75
0,001
expressed protein
54
At2g38470
2,58
0,001
WRKY family transcription factor
55
At4g17460
1,53
0,001
homeobox leucine zipper protein 1 (HAT1) / HD ZIP protein 1
56
At2g06530
1,53
0,001
SNF7 family protein
57
At4g16260
1,59
0,001
glycosyl hydrolase family 17 protein
58
At3g55430
1,62
0,001
glycosyl hydrolase family 17 protein / beta 1,3 glucanase, putative
59
At3g19580
2,47
0,001
zinc finger (C2H2 type) protein 2 (AZF2)
60
At2g42540
2,35
0,001
61
At4g14365
2,89
0,002
cor15a cold responsive protein / cold regulated protein (cor15a)
zinc finger (C3HC4 type RING finger) family protein / ankyrin repeat family
protein
62
At2g31880
2
0,002
leucine rich repeat transmembrane protein kinase, putative
63
At1g51090
2,24
0,002
heavy metal associated domain containing protein
64
At1g76020
1,53
0,002
expressed protein
65
At5g10380
1,84
0,002
66
At5g15960
1,6
0,002
zinc finger (C3HC4 type RING finger) family protein
stress responsive protein (KIN1) / stress induced protein (KIN1) /// stress
responsive protein (KIN1) /
67
At1g33560
1,81
0,002
disease resistance protein (CC NBS LRR class), putative
68
At1g05575
2,69
0,002
expressed protein
69
At2g18210
2,28
0,002
expressed protein
70
At3g50770
2,2
0,002
calmodulin related protein, putative
71
At3g16860
2,22
0,002
phytochelatin synthetase related
72
At4g34410
4,16
0,002
AP2 domain containing transcription factor, putative
73
At4g29780
2,92
0,002
expressed protein
74
At3g10980
1,57
0,002
wound responsive protein related
75
At4g01080
1,58
0,002
expressed protein
76
At2g41100
1,61
0,002
touch responsive protein / calmodulin related protein 3, touch induced (TCH3)
77
At1g73330
3,39
0,002
Dr4 protease inhibitor, putative (DR4)
78
At1g74950
1,55
0,002
expressed protein
79
At1g76600
1,95
0,002
expressed protein
80
At1g19020
2,27
0,002
expressed protein
81
At4g22710
1,64
0,002
cytochrome P450 family protein /// cytochrome P450 family protein
82
At5g51190
1,93
0,002
AP2 domain containing transcription factor, putative
83
At4g17670
1,72
0,002
senescence associated protein related
84
At4g23810
3,23
0,002
WRKY family transcription factor
85
At1g51700
1,51
0,002
86
At1g20510
2,11
0,002
Dof type zinc finger domain containing protein (ADOF1)
4 coumarate CoA ligase family protein / 4 coumaroyl CoA synthase family
protein
87
At1g80840
2,8
0,002
WRKY family transcription factor
88
89
At3g56880
At3g50950
1,8
1,95
0,003
0,003
VQ motif containing protein
disease resistance protein (CC NBS LRR class), putative
p-value
Description
163
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
90
At5g46780
1,65
0,003
VQ motif containing protein
91
At1g65400
2,16
0,003
disease resistance protein (TIR class), putative
92
At2g26020
1,9
0,003
plant defensin fusion protein, putative (PDF1.2b)
93
At1g67360
1,95
0,003
rubber elongation factor (REF) family protein
94
At4g28240
1,77
0,003
wound responsive protein related
95
At5g47220
2,25
0,003
ethylene responsive element binding factor 2 (ERF2)
96
At1g73540
2,23
0,003
MutT/nudix family protein
97
At2g01180
2,06
0,003
phosphatidic acid phosphatase family protein / PAP2 family protein
98
At5g44070
1,65
0,003
phytochelatin synthase 1 (PCS1)
99
At1g64280
1,65
0,003
regulatory protein (NPR1)
100
At3g26200
1,55
0,003
cytochrome P450 71B22, putative (CYP71B22)
101
At1g09070
1,66
0,003
102
At1g64710
1,57
0,003
103
At5g06320
1,72
0,003
104
At3g44260
1,84
0,003
CCR4 NOT transcription complex protein, putative
105
At2g24160
1,95
0,003
pseudogene, leucine rich repeat protein family
106
At5g57220
1,89
0,003
cytochrome P450, putative
107
At3g45860
2,13
0,003
receptor like protein kinase, putative
108
At5g52760
3,02
0,003
heavy metal associated domain containing protein
109
At5g62520
2,85
0,003
expressed protein
110
At2g25250
1,55
0,003
expressed protein
111
At5g10760
2,65
0,003
aspartyl protease family protein
112
At2g24600
2,21
0,003
ankyrin repeat family protein
113
At4g01700
1,57
0,003
chitinase, putative
114
At3g11820
1,65
0,003
115
At4g25490
3,04
0,003
SYP121 syntaxin 121 (SYP121) / syntaxin related protein (SYR1)
DRE binding protein (DREB1B) / CRT/CRE binding factor 1 (CBF1) /
transcriptional activator CBF1
116
At5g57340
1,82
0,003
expressed protein
117
At2g29670
1,64
0,003
expressed protein
118
At3g50930
2,97
0,003
AAA type ATPase family protein
119
At5g61160
2,7
0,004
transferase family protein
120
At3g17130
1,68
0,004
121
At5g52640
2,49
0,004
invertase/pectin methylesterase inhibitor family protein
HSP81 1 heat shock protein 81 1 (HSP81 1) / heat shock protein 83
(HSP83)
122
At1g64360
2,66
0,004
expressed protein
123
At1g73600
1,52
0,004
NMT3 phosphoethanolamine N methyltransferase 3, putative (NMT3)
124
At3g50760
1,61
0,004
glycosyl transferase family 8 protein
125
At3g25010
1,87
0,004
disease resistance family protein
126
At4g30140
1,55
0,004
GDSL motif lipase/hydrolase family protein
127
At4g17770
1,52
0,004
128
At1g27730
2,07
0,004
glycosyl transferase family 20 protein / trehalose phosphatase family protein
zinc finger (C2H2 type) family protein (ZAT10) / salt tolerance zinc finger
protein (STZ)
129
At5g42050
1,56
0,004
expressed protein
130
At5g64870
1,58
0,004
expressed protein
131
At1g01140
1,51
0,004
CBL interacting protein kinase 9 (CIPK9)
132
133
134
At5g13190
At4g36040
At1g09740
1,68
1,51
1,77
0,004
0,004
0,004
expressed protein
DNAJ heat shock N terminal domain containing protein (J11)
ethylene responsive protein, putative
p-value
Description
C2 domain containing protein / src2 like protein, putative
ADH alcohol dehydrogenase, putative
harpin induced family protein / HIN1 family protein / harpin responsive
family protein / NDR1/HIN1 like protein 3
164
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
135
At5g59550
1,87
0,004
zinc finger (C3HC4 type RING finger) family protein
136
At5g54940
1,59
0,004
eukaryotic translation initiation factor SUI1, putative
137
At4g23140
3,05
0,004
receptor like protein kinase 5 (RLK5) /// receptor like protein kinase 5 (RLK5)
138
At4g21760
1,7
0,004
glycosyl hydrolase family 1 protein
139
At2g38790
2,19
0,004
expressed protein
140
At1g22190
1,84
0,004
141
At1g27770
1,75
0,004
AP2 domain containing transcription factor, putative
ACA1/PEA1 calcium transporting ATPase 1, plasma membrane type / Ca(2+)
ATPase isoform 1
142
At1g74930
2,6
0,004
AP2 domain containing transcription factor, putative
143
At5g13200
2,25
0,005
GRAM domain containing protein / ABA responsive protein related
144
At3g05030
1,57
0,005
sodium proton exchanger, putative (NHX2)
145
At4g34390
1,64
0,005
extra large guanine nucleotide binding protein, putative / G protein, putative
146
At2g20560
1,88
0,005
DNAJ heat shock family protein
147
At1g17420
2,04
0,005
lipoxygenase, putative
148
At1g80440
1,92
0,005
kelch repeat containing F box family protein
149
At1g19380
1,93
0,005
expressed protein
150
At3g57260
3,64
0,005
glycosyl hydrolase family 17 protein
151
At4g09760
1,55
0,005
152
At5g12200
1,51
0,005
153
At1g71030
1,87
0,005
myb family transcription factor
154
At1g67920
1,76
0,005
expressed protein
155
At1g17340
1,54
0,005
phosphoinositide phosphatase family protein
156
At1g15010
2,19
0,005
157
At4g01390
2,96
0,005
expressed protein
meprin and TRAF homology domain containing protein / MATH domain
containing protein
158
At1g25400
1,71
0,005
expressed protein
159
At3g23110
2,23
0,005
disease resistance family protein /// disease resistance family protein
160
At3g55980
1,99
0,005
zinc finger (CCCH type) family protein
161
At2g32140
1,93
0,005
disease resistance protein (TIR class), putative
162
At1g01360
1,61
0,006
expressed protein
163
At3g16150
1,52
0,006
L asparaginase, putative / L asparagine amidohydrolase, putative
164
At5g03230
1,58
0,006
165
At5g47230
1,79
0,006
166
At4g00700
2,14
0,006
C2 domain containing protein
167
At5g27420
2,86
0,006
zinc finger (C3HC4 type RING finger) family protein
168
At4g25470
2,1
0,006
DRE binding protein (DREB1C) / CRT/DRE binding factor 2 (CBF2)
169
At1g54130
1,57
0,006
RelA/SpoT protein, putative (RSH3)
170
At5g54610
1,77
0,006
ankyrin repeat family protein
171
At1g35230
1,82
0,006
172
At1g35710
2,55
0,006
leucine rich repeat transmembrane protein kinase, putative
173
At5g11670
2,15
0,006
malate oxidoreductase, putative
174
At4g17500
2,12
0,006
ethylene responsive element binding protein 1 (ERF1) / EREBP 2 protein
175
176
At5g22570
At1g72520
1,76
2,82
0,006
0,006
WRKY family transcription factor
LOX lipoxygenase, putative
177
178
At1g74210
At2g40435
1,59
1,84
0,007
0,007
glycerophosphoryl diester phosphodiesterase family protein
expressed protein
p-value
Description
choline kinase, putative
PYD2
dihydropyrimidinase / DHPase / dihydropyrimidine amidohydrolase /
hydantoinase (PYD2)
expressed protein
AtERF5 ethylene responsive element binding factor 5 (ERF5)
AGP5 arabinogalactan protein (AGP5)
165
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
179
At3g12580
2,13
0,007
heat shock protein 70, putative / HSP70, putative
180
At4g31550
1,52
0,007
WRKY family transcription factor
181
At1g73480
1,6
0,007
hydrolase, alpha/beta fold family protein
182
At1g01560
2,23
0,007
mitogen activated protein kinase, putative / MAPK, putative (MPK11)
183
At1g24575
1,62
0,007
184
At5g52310
1,8
0,007
expressed protein
low temperature responsive protein 78 (LTI78) / desiccation responsive protein
29A (RD29A)
185
At5g55450
2,26
0,007
protease inhibitor/seed storage/lipid transfer protein (LTP) family protein
186
At2g41180
1,57
0,007
sigA binding protein related
187
At2g42750
1,51
0,007
DNAJ heat shock N terminal domain containing protein
188
At3g21230
1,51
0,007
4 coumarate CoA ligase, putative / 4 coumaroyl CoA synthase, putative (4CL)
189
At1g74430
1,64
0,007
myb family transcription factor (MYB95)
190
At5g18470
2,78
0,007
191
At3g25760
2,51
0,008
curculin like (mannose binding) lectin family protein
ERD12
early responsive to dehydration stress protein (ERD12) /// early
responsive to dehydration stress protein (ERD12)
192
At1g22160
2,29
0,008
senescence associated protein related
193
At2g44500
1,81
0,008
expressed protein
194
At5g16200
1,64
0,008
50S ribosomal protein related
195
At1g56600
1,79
0,008
galactinol synthase, putative
196
At3g52400
2,16
0,008
SYP122 syntaxin, putative (SYP122)
197
At1g12200
1,62
0,008
flavin containing monooxygenase family protein / FMO family protein
198
At5g47240
1,78
0,008
MutT/nudix family protein
199
At3g50480
1,94
0,008
broad spectrum mildew resistance RPW8 family protein
200
At2g26440
1,55
0,008
pectinesterase family protein
201
At4g12470
1,68
0,008
protease inhibitor/seed storage/lipid transfer protein (LTP) family protein
202
At5g45630
1,65
0,008
expressed protein
203
At2g32680
2,04
0,008
disease resistance family protein
204
At5g20230
2,16
0,008
plastocyanin like domain containing protein
205
At5g47070
2,05
0,009
protein kinase, putative
206
At2g30870
1,69
0,009
glutathione S transferase, putative
207
At2g26190
1,56
0,009
calmodulin binding family protein
208
At2g41640
2,64
0,009
expressed protein
209
At3g52710
1,62
0,009
expressed protein
210
At2g27080
1,96
0,009
harpin induced protein related / HIN1 related / harpin responsive protein related
211
At1g10340
2,28
0,009
ankyrin repeat family protein
212
At3g50260
1,57
0,009
AP2 domain containing transcription factor, putative
213
At4g02410
1,83
0,009
lectin protein kinase family protein
214
At1g13260
1,79
0,009
DNA binding protein RAV1 (RAV1)
215
At5g59820
2,15
0,009
zinc finger (C2H2 type) family protein (ZAT12)
216
At1g30160
1,56
0,009
expressed protein
217
At1g70300
1,64
0,009
potassium transporter, putative
218
At4g38340
1,95
0,009
RWP RK domain containing protein
219
220
221
At4g24380
At3g12500
At4g33050
1,87
2,04
1,82
0,010
0,010
0,010
expressed protein
basic endochitinase
calmodulin binding family protein
p-value
Description
166
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
222
At5g61600
1,94
0,010
ethylene responsive element binding family protein
223
At4g27652
1,65
0,010
expressed protein
224
At3g59940
1,63
0,010
kelch repeat containing F box family protein
225
At1g76650
2,23
0,010
calcium binding EF hand family protein
226
At1g33760
2,27
0,010
AP2 domain containing transcription factor, putative
227
At1g20823
1,54
0,010
zinc finger (C3HC4 type RING finger) family protein
228
At5g52050
2,82
0,011
MATE efflux protein related
229
At5g61590
1,78
0,011
AP2 domain containing transcription factor family protein
230
At1g12520
1,59
0,011
superoxide dismutase copper chaperone, putative
231
At5g66210
1,58
0,011
calcium dependent protein kinase family protein / CDPK family protein
232
At5g05410
1,7
0,011
DRE binding protein (DREB2A)
233
At4g11360
1,74
0,011
zinc finger (C3HC4 type RING finger) family protein (RHA1b)
234
At1g50740
1,8
0,011
expressed protein
235
At4g29190
1,73
0,011
236
At2g22240
1,68
0,011
zinc finger (CCCH type) family protein
inositol 3 phosphate synthase isozyme 2 / myo inositol 1 phosphate
synthase 2 / MI 1 P synthase 2 / IPS 2
237
At5g01540
2,35
0,011
lectin protein kinase, putative
238
At3g46600
1,65
0,011
scarecrow transcription factor family protein
239
At5g59050
1,62
0,011
expressed protein
240
At3g04720
2,01
0,011
HEL hevein like protein (HEL)
241
At3g14050
1,83
0,011
RSH2 RelA/SpoT protein, putative (RSH2)
242
At2g41010
1,6
0,011
243
At4g38460
1,56
0,012
VQ motif containing protein
GGPS geranylgeranyl pyrophosphate synthase, putative / GGPP synthetase,
putative
244
At5g05300
1,85
0,012
245
At2g33580
1,95
0,012
expressed protein
protein kinase family protein / peptidoglycan binding LysM domain containing
protein
246
At4g26090
1,51
0,012
disease resistance protein RPS2 (CC NBS LRR class), putative
247
At5g22380
3,15
0,012
no apical meristem (NAM) family protein
248
At5g11930
2,29
0,012
249
At5g41740
3,43
0,012
glutaredoxin family protein
disease resistance protein (TIR NBS LRR class), putative /// disease resistance
protein (TIR NBS LRR class), putative
250
At5g61010
1,66
0,012
exocyst subunit EXO70 family protein
251
At2g46400
2,44
0,012
WRKY family transcription factor
252
At5g20830
1,77
0,012
SUS1 sucrose synthase / sucrose UDP glucosyltransferase (SUS1)
253
At1g02400
1,76
0,012
gibberellin 2 oxidase, putative / GA2 oxidase, putative
254
At5g49520
1,54
0,012
WRKY family transcription factor
255
At3g44350
1,51
0,013
no apical meristem (NAM) family protein
256
At1g73800
2,13
0,013
calmodulin binding protein
257
258
At5g49890
At1g02660
1,52
1,9
0,013
0,013
chloride channel protein (CLC c)
lipase class 3 family protein
259
At5g47910
1,65
0,013
RbohD respiratory burst oxidase protein D (RbohD) / NADPH oxidase
260
At2g04450
2,16
0,013
MutT/nudix family protein
261
262
At2g24850
At1g59590
3,85
2,11
0,013
0,013
aminotransferase, putative
expressed protein
263
At5g45110
1,62
0,013
ankyrin repeat family protein / BTB/POZ domain containing protein
264
265
At4g21960
At3g03870
1,55
1,53
0,013
0,014
peroxidase 42 (PER42) (P42) (PRXR1)
expressed protein
p-value
Description
167
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
266
At4g35480
1,62
0,014
zinc finger (C3HC4 type RING finger) family protein
267
At1g57630
2,01
0,014
disease resistance protein (TIR class), putative
268
At2g39650
1,67
0,014
expressed protein
269
At5g62070
1,63
0,014
calmodulin binding family protein
270
At1g60190
2,23
0,014
armadillo/beta catenin repeat family protein / U box domain containing protein
271
At2g35930
2,43
0,014
U box domain containing protein
272
At5g26920
2,29
0,015
calmodulin binding protein
273
At5g10695
2,13
0,015
expressed protein
274
At3g60420
2,11
0,015
expressed protein
275
At1g51140
1,65
0,015
basic helix loop helix (bHLH) family protein
276
At3g50740
1,82
0,015
UDP glucoronosyl/UDP glucosyl transferase family protein
277
At2g17880
1,54
0,015
DNAJ heat shock protein, putative
278
At3g02840
3,33
0,015
immediate early fungal elicitor family protein
279
At3g27210
1,86
0,015
expressed protein
280
At2g34600
1,78
0,015
expressed protein
281
At2g40000
2,26
0,015
expressed protein
282
At1g70740
1,56
0,016
protein kinase family protein
283
At5g22250
2,95
0,016
CCR4 NOT transcription complex protein, putative
284
At4g23220
2,12
0,016
protein kinase family protein
285
At1g75020
1,51
0,016
phospholipid/glycerol acyltransferase family protein
286
At3g48650
3,14
0,016
pseudogene, At14a related protein
287
At2g40140
1,73
0,016
zinc finger (CCCH type) family protein
288
At3g16360
2,69
0,016
phosphotransfer family protein
289
At1g02930
2,26
0,017
glutathione S transferase, putative /// glutathione S transferase, putative
290
At5g52750
2,33
0,017
heavy metal associated domain containing protein
291
At4g27654
2,73
0,017
expressed protein
292
At4g15620
1,53
0,017
293
At3g14440
1,51
0,017
integral membrane family protein
NC1
9 cis epoxycarotenoid dioxygenase, putative / neoxanthin cleavage
enzyme, putative /
294
At5g60950
1,55
0,017
phytochelatin synthetase related
295
At3g53230
1,53
0,017
cell division cycle protein 48, putative / CDC48, putative
296
At5g64510
1,77
0,017
expressed protein
297
At5g53870
1,52
0,017
plastocyanin like domain containing protein
298
At1g49500
1,55
0,018
expressed protein
299
At4g17490
2,01
0,018
ethylene responsive element binding protein, putative
300
At1g19960
2,23
0,018
expressed protein
301
At3g45640
1,66
0,018
302
At1g33960
1,91
0,018
avirulence responsive protein / avirulence induced gene (AIG1)
303
At4g35985
1,8
0,018
304
At4g39210
2,62
0,018
senescence/dehydration associated protein related
APL3 glucose 1 phosphate adenylyltransferase large subunit 3 (APL3) / ADP
glucose pyrophosphorylase
305
At5g07460
1,76
0,019
peptide methionine sulfoxide reductase, putative
306
307
At3g15350
At5g60900
1,51
1,87
0,019
0,019
glycosyltransferase family 14 protein / core 2/I branching enzyme family protein
lectin protein kinase family protein
308
309
At5g44420
At2g23810
1,8
1,55
0,019
0,019
plant defensin protein, putative (PDF1.2a)
senescence associated family protein
p-value
Description
mitogen activated protein kinase, putative / MAPK, putative (MPK3)
168
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
310
311
At5g26030
At5g35735
1,68
2,02
0,020
0,020
ferrochelatase I
auxin responsive family protein
312
At4g33040
1,6
0,021
glutaredoxin family protein
313
At2g40750
2,08
0,021
WRKY family transcription factor
314
At3g51450
1,56
0,021
strictosidine synthase family protein
315
At3g52430
1,72
0,022
pad4 phytoalexin deficient 4 protein (PAD4)
316
At2g14560
3,06
0,022
expressed protein
317
At1g29395
2
0,022
stress responsive protein, putative
318
At2g14080
1,59
0,022
disease resistance protein (TIR NBS LRR class), putative
319
At1g09080
1,7
0,022
BiP 3/BP3 luminal binding protein 3 (BiP 3) (BP3)
320
At2g28400
2,1
0,023
321
At1g72930
1,68
0,023
expressed protein
disease resistance protein (TIR NBS class), putative /// disease resistance
protein (TIR NBS class), putative
322
At1g61340
1,73
0,023
F box family protein
323
At2g37130
1,74
0,024
324
At4g11280
1,78
0,024
325
At1g62290
1,56
0,024
aspartyl protease family protein
326
At4g01250
1,59
0,024
WRKY family transcription factor
327
At4g23150
2,08
0,024
protein kinase family protein
328
At5g45380
2,09
0,024
329
At3g09020
2,02
0,024
sodium:solute symporter family protein
alpha 1,4 glycosyltransferase family protein / glycosyltransferase sugar binding
DXD motif containing protein
330
At4g32980
1,58
0,024
homeobox protein (ATH1)
331
At3g16720
1,72
0,025
zinc finger (C3HC4 type RING finger) family protein
332
At2g39420
1,66
0,025
esterase/lipase/thioesterase family protein
333
At1g18740
1,65
0,025
expressed protein
334
At4g17230
1,67
0,026
scarecrow like transcription factor 13 (SCL13)
335
At1g02390
2,07
0,026
phospholipid/glycerol acyltransferase family protein
336
At3g48520
1,72
0,026
cytochrome P450 family protein
337
At3g08870
1,58
0,026
lectin protein kinase, putative
338
At3g56710
1,83
0,027
sigA binding protein
339
At1g01470
1,55
0,027
late embryogenesis abundant protein, putative / LEA protein, putative
340
At1g19210
1,57
0,027
AP2 domain containing transcription factor, putative
341
At5g18130
2,02
0,027
expressed protein
342
At3g48640
1,86
0,028
expressed protein
343
At3g51860
2,25
0,028
cation exchanger, putative (CAX3)
344
At4g27410
2,15
0,028
no apical meristem (NAM) family protein (RD26)
345
At3g57540
2,05
0,028
remorin family protein
346
At5g39670
1,99
0,028
calcium binding EF hand family protein
347
At1g21270
1,53
0,028
WAK2 wall associated kinase 2 (WAK2)
348
At3g12830
1,55
0,029
auxin responsive family protein
349
At4g15530
1,63
0,029
350
At4g39030
1,85
0,029
pyruvate phosphate dikinase family protein
EDS5/SID1 enhanced disease susceptibility 5 (EDS5) / salicylic acid induction
deficient 1 (SID1)
351
At1g63750
1,55
0,029
disease resistance protein (TIR NBS LRR class), putative
352
At3g15210
1,62
0,029
AtERF4 ethylene responsive element binding factor 4 (ERF4)
353
354
At5g13320
At4g04500
1,78
1,9
0,029
0,030
auxin responsive GH3 family protein
protein kinase family protein
p-value
Description
(ATP2a) peroxidase 21 (PER21) (P21) (PRXR5)
ACS6 1 aminocyclopropane 1 carboxylate synthase 6 / ACC synthase 6
(ACS6)
169
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
355
At1g23710
2,17
0,030
expressed protein
356
At2g17710
2,17
0,030
expressed protein
357
At3g56400
1,65
0,030
WRKY family transcription factor
358
At4g10500
2,19
0,031
oxidoreductase, 2OG Fe(II) oxygenase family protein
359
At5g24110
1,58
0,031
WRKY family transcription factor
360
At3g47480
1,55
0,032
calcium binding EF hand family protein
361
At2g18690
2,09
0,033
expressed protein
362
At5g03630
1,53
0,033
monodehydroascorbate reductase, putative
363
At5g62570
1,51
0,034
calmodulin binding protein
364
At1g07870
1,53
0,034
protein kinase family protein
365
At1g21250
1,84
0,034
WAK1 wall associated kinase 1 (WAK1)
366
At2g43570
2,32
0,034
chitinase, putative
367
At4g24570
1,94
0,034
mitochondrial substrate carrier family protein
368
At1g78460
1,64
0,035
SOUL heme binding family protein
369
At1g70810
1,58
0,035
C2 domain containing protein
370
At1g35210
1,86
0,035
expressed protein
371
At1g22770
1,71
0,035
gigantea protein (GI)
372
373
At2g29990
At4g23600
1,54
2,26
0,036
0,036
374
At4g21830
1,77
0,036
375
At3g52180
1,81
0,036
376
At1g68600
3,01
0,036
377
At1g30900
1,84
0,036
378
At5g47850
1,55
0,038
protein kinase, putative
379
At5g19120
1,6
0,038
expressed protein
380
At1g12610
1,7
0,038
DRE binding protein, putative / CRT/DRE binding factor, putative
381
At2g18680
2,37
0,038
expressed protein
382
At1g76960
2,19
0,039
expressed protein
383
At1g07440
1,72
0,039
tropinone reductase, putative / tropine dehydrogenase, putative
384
At5g04340
1,88
0,039
zinc finger (C2H2 type) family protein
385
At1g19180
1,58
0,040
expressed protein
386
At3g10930
1,82
0,040
expressed protein
387
At3g25610
1,53
0,041
haloacid dehalogenase like hydrolase family protein
388
At2g06050
1,62
0,041
OPR3 12 oxophytodienoate reductase (OPR3) / delayed dehiscence1 (DDE1)
389
At4g03450
1,85
0,041
ankyrin repeat family protein
390
At1g14870
2,25
0,041
expressed protein /// expressed protein
391
At5g53420
1,63
0,041
expressed protein
392
At1g04770
1,54
0,041
male sterility MS5 family protein
393
At2g29350
1,74
0,041
tropinone reductase, putative / tropine dehydrogenase, putative
394
At3g28340
1,58
0,042
galactinol synthase, putative
395
At3g13672
1,53
0,042
seven in absentia (SINA) family protein
396
At1g17380
1,8
0,042
expressed protein
397
At5g17350
1,91
0,042
expressed protein
398
399
At5g59680
At5g12050
1,71
1,69
0,043
0,043
leucine rich repeat protein kinase, putative
expressed protein
p-value
Description
pyridine nucleotide disulphide oxidoreductase family protein
coronatine responsive tyrosine aminotransferase / tyrosine transaminase
methionine sulfoxide reductase domain containing protein / SeIR domain
containing protein
PTPKIS1
protein tyrosine phosphatase/kinase interaction sequence protein
(PTPKIS1)
expressed protein
AtELP6 vacuolar sorting receptor, putative
170
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or
down- regulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold
Change
400
At3g09940
1,57
0,043
monodehydroascorbate reductase, putative
401
At3g23550
1,51
0,044
MATE efflux family protein
402
At1g17430
1,54
0,045
hydrolase, alpha/beta fold family protein
403
At4g14020
2,13
0,045
rapid alkalinization factor (RALF) family protein
404
At1g74450
1,66
0,048
expressed protein
405
At3g09830
1,51
0,048
protein kinase, putative
406
At3g25600
1,66
0,048
calmodulin, putative
407
At1g11210
1,57
0,049
expressed protein
408
At1g78410
1,54
0,049
VQ motif containing protein
409
At1g11050
1,59
0,050
protein kinase family protein
p-value
Description
171
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or downregulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold Change
p-value
Description
1
At1g06350
-1,96
0,000
fatty acid desaturase family protein /// fatty acid desaturase family protein
2
At5g10140
-2,34
0,000
MADS-box protein flowering locus F (FLF)
3
At5g62430
-1,65
0,000
4
At4g25100
-3,8
0,000
Dof-type zinc finger domain-containing protein
SODB/FSD1 superoxide dismutase (Fe), chloroplast (SODB) / iron superoxide
dismutase (FSD1)
5
At5g15310
-1,82
0,000
6
At3g47340
-2,23
0,000
myb family transcription factor
ASN1 asparagine synthetase 1 (glutamine-hydrolyzing) / glutamine-dependent
asparagine synthetase 1 (ASN1)
7
At5g49100
-1,88
0,000
expressed protein
8
rpoA
-1,55
0,000
9
At1g12860
-1,59
0,000
basic helix-loop-helix (bHLH) family protein / F-box family protein
10
At4g26150
-2,06
0,000
zinc finger (GATA type) family protein
11
At4g28780
-1,74
0,000
GDSL-motif lipase/hydrolase family protein
12
At1g74670
-1,97
0,001
gibberellin-responsive protein, putative
13
At1g32540
-1,56
0,001
zinc finger protein, putative
14
At3g15310
-1,65
0,001
expressed protein
15
At4g26110
-1,6
0,001
nucleosome assembly protein (NAP), putative
16
At5g28060
-1,53
0,001
17
At5g23820
-1,79
0,001
40S ribosomal protein S24 (RPS24B)
MD-2-related lipid recognition domain-containing protein / ML domain-containing
protein
18
At5g02450
-1,55
0,001
60S ribosomal protein L36 (RPL36C)
19
At1g10470
-1,54
0,001
two-component responsive regulator / response regulator 4 (ARR4)
20
At2g39390
-1,64
0,001
60S ribosomal protein L35 (RPL35B)
21
At5g57120
-1,85
0,001
expressed protein
22
At5g08180
-1,6
0,001
ribosomal protein L7Ae/L30e/S12e/Gadd45 family protein
23
rpoC2
-2,09
0,001
24
At2g40670
-2,35
0,001
25
At1g57660
-1,55
0,001
60S ribosomal protein L21 (RPL21E) /// 60S ribosomal protein L21 (RPL21E)
26
At5g35490
-1,71
0,001
expressed protein (MRU1)
27
At5g20150
-2,16
0,001
SPX (SYG1/Pho81/XPR1) domain-containing protein
28
At5g04790
-1,76
0,002
hypothetical protein
29
At3g11120
-2,15
0,002
60S ribosomal protein L41 (RPL41C) /// 60S ribosomal protein L41 (RPL41C) /
30
At3g47380
-1,59
0,002
invertase/pectin methylesterase inhibitor family protein
31
At5g42950
-1,61
0,002
GYF domain-containing protein
32
At2g22980
-1,63
0,002
serine carboxypeptidase S10 family protein
33
At5g56860
-1,52
0,002
zinc finger (GATA type) family protein
34
At3g02040
-1,71
0,002
glycerophosphoryl diester phosphodiesterase family protein
35
At5g67240
-1,69
0,002
exonuclease family protein
36
At2g17300
-1,75
0,002
expressed protein
37
At1g11260
-1,61
0,002
STP1 glucose transporter (STP1)
38
39
At5g49700
At2g46310
-1,53
-1,89
0,002
0,002
DNA-binding protein-related
AP2 domain-containing transcription factor, putative
40
41
At5g24380
At5g37260
-1,59
-1,79
0,003
0,003
transporter, putative
myb family transcription factor
two-component responsive regulator / response regulator 16 (ARR16)
172
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or downregulated in 35S::AtCDF3 Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold Change
p-value
Description
42
At5g63140
-1,51
0,003
calcineurin-like phosphoesterase family protein
43
At3g24080
-1,57
0,003
KRR1 family protein
44
At2g16660
-1,65
0,003
nodulin family protein
45
At3g16870
-1,6
0,003
zinc finger (GATA type) family protein
46
At1g68560
-1,75
0,003
47
At2g18740
-1,72
0,003
alpha-xylosidase (XYL1)
small nuclear ribonucleoprotein E, putative / snRNP-E, putative / Sm
protein E, putative
48
At3g13750
-1,7
0,004
beta-galactosidase, putative / lactase, putative
49
At3g16670
-1,58
0,004
expressed protein
50
At5g35480
-1,78
0,004
expressed protein
51
At4g12970
-1,53
0,004
expressed protein
52
At5g04530
-1,52
0,004
beta-ketoacyl-CoA synthase family protein
53
At5g49360
-1,61
0,004
glycosyl hydrolase family 3 protein
54
At2g36590
-1,84
0,004
proline transporter, putative
55
At5g22430
-1,55
0,005
expressed protein
56
At1g79410
-1,52
0,005
transporter-related
57
At1g26790
-1,56
0,005
Dof-type zinc finger domain-containing protein
58
At5g18600
-1,79
0,006
glutaredoxin family protein
59
At3g44735
-1,62
0,006
phytosulfokines-related
60
atpH
-1,57
0,006
61
atpF
-1,53
0,006
62
At1g69530
-1,67
0,007
expansin, putative (EXP1)
63
At1g02640
-1,59
0,007
glycosyl hydrolase family 3 protein
64
At4g15660
-2,02
0,007
glutaredoxin family protein
65
At5g44530
-1,53
0,007
subtilase family protein
66
At3g07050
-1,75
0,007
GTP-binding family protein
67
At1g80280
-1,89
0,007
hydrolase, alpha/beta fold family protein
68
At3g30720
-1,54
0,007
expressed protein
69
At5g24420
-1,68
0,007
glucosamine/galactosamine-6-phosphate isomerase-related
70
petG
-1,56
0,007
71
At2g18440
-1,62
0,008
expressed protein
72
At5g57180
-1,77
0,008
expressed protein
73
At1g05560
-1,72
0,008
UDP-glucose transferase (UGT75B2)
74
At3g28500
-1,56
0,008
60S acidic ribosomal protein P2 (RPP2C)
75
At3g58120
-1,69
0,009
bZIP transcription factor family protein
76
At5g45950
-1,55
0,009
GDSL-motif lipase/hydrolase family protein
77
At3g45930
-1,53
0,009
histone H4 /// histone H4
78
ndhJ
-1,77
0,009
79
psbG
-1,64
0,010
80
At1g30820
-1,59
0,010
CTP synthase, putative / UTP--ammonia ligase, putative
81
At2g29420
-1,88
0,011
glutathione S-transferase, putative
82
83
At2g47880
At2g30540
-1,53
-1,83
0,012
0,012
glutaredoxin family protein
glutaredoxin family protein
173
Supplementary
Continued Supplementay Table S3.2. Genes significantly (adjusted P-value ≤0.05) up- or downregulated in 35S::AtCDF3 plants Arabidopsis plants compared with wild-type (Col-0) plants.
Order
Gene
Fold Change
p-value
Description
84
At4g00950
-1,58
0,012
expressed protein
85
At1g68780
-1,69
0,013
86
At4g37530
-1,52
0,013
87
At3g14990
-1,71
0,013
leucine-rich repeat family protein
peroxidase 50 (PER50) (P50) (PRXR2) /// peroxidase 50 (PER50) (P50)
(PRXR2)
4-methyl-5(b-hydroxyethyl)-thiazole monophosphate biosynthesis protein,
putative
88
At4g38330
-2,17
0,014
expressed protein /// expressed protein
89
At5g53880
-1,52
0,015
expressed protein
90
At4g23750
-1,71
0,015
AP2 domain-containing transcription factor, putative
91
At1g13740
-1,74
0,016
expressed protein
92
psbL
-1,54
0,017
93
At5g48240
-1,54
0,017
hypothetical protein
94
-1,63
0,017
myb family transcription factor
95
At1g06180
rps3
chloroplast
-1,73
0,018
96
rpl14
-1,52
0,019
97
At5g25980
-1,7
0,019
glycosyl hydrolase family 1 protein /// glycosyl hydrolase family 1 protein
98
At5g65080
-1,6
0,019
MADS-box family protein
99
At3g08730
-1,6
0,020
serine/threonine protein kinase (PK1) (PK6)
100
At1g06830
-1,69
0,022
glutaredoxin family protein
101
At4g16380
-1,52
0,022
102
At4g15550
-1,53
0,022
IAGLU UDP-glucose:indole-3-acetate beta-D-glucosyltransferase (IAGLU)
103
At4g38620
-1,55
0,023
myb family transcription factor (MYB4)
104
-2,34
0,025
105
atpI
rps7
1_chloroplast
-1,61
0,026
106
At2g30610
-1,55
0,027
BTB/POZ domain-containing protein
107
At3g04770
-1,77
0,028
40S ribosomal protein SA (RPSaB)
108
At4g16140
-1,52
0,028
proline-rich family protein
109
At4g18590
-1,73
0,028
expressed protein
110
At1g76810
-1,52
0,030
eukaryotic translation initiation factor 2 family protein / eIF-2 family protein
111
At5g40340
-1,53
0,030
PWWP domain-containing protein
112
At5g54470
-1,53
0,030
zinc finger (B-box type) family protein
113
At1g30880
-1,53
0,031
expressed protein
114
At3g48720
-1,52
0,033
transferase family protein
115
At2g36410
-1,55
0,034
expressed protein
116
At3g28740
-1,57
0,035
cytochrome P450 family protein
117
rps18
-1,91
0,035
118
At4g30350
-1,56
0,036
heat shock protein-related
119
At3g09610
-1,91
0,037
myb family transcription factor
120
At3g53460
-1,53
0,040
29 kDa ribonucleoprotein, chloroplast / RNA-binding protein cp 29
121
rpl32
-1,96
0,041
122
At1g09250
-1,53
0,041
expressed protein
174
Supplementary
SupplementaryTable S3.3 Metabolite analyses of WT and 35S::AtCDF3 plants. Given are means ± SE
(n=15).
Similar
results
Col-0
Meatabolite
Glucose
Fructose
Sucrose
were
obtained
in
35S::AtCDF3 (L2.1)
three
independent
experiments
35S::AtCDF3 (5.4)
Relative
amount
compound
(%WT)
Relative amount
compound (%WT)
P-value
Relative amount
compound (%WT)
P-value
100 ± 1.84
199,93 ±19,58
0,0254
186,49 ± 20,37
0,0013
168,72 ± 23
0,6527
100 ± 5.92
100 ± 0,35
GABA
100 ± 56
L- Leucine
100 ± 66.6
L- Valine
100 ± 10.11
L- Asparagine
100 ± 36.2
L- Alanine
100 ± 17.6
L- Glycine
100 ± 16.6
L-Proline
100 ± 16.8
L- Glutamine
100 ± 53.6
111,67 ± 2.30
0,00005914
135,65 ± 43.0
116,27 ± 32.87
79,07 ± 6,16
109,58 ± 40.09
0,0287085
101,14 ± 53.0
0,00305188
116,79 ± 39,29
0,0888665
414,78 ± 142,80
182,20 ± 39,42
275,20 ± 208,31
0,0224
0,0853736
0,02870888
0,00305187
0,0888665
153,63 ± 75,89
0,0991184
89,58 ± 26,56
0,0609482
57,74 ± 17,90
0,0991181
134,90 ± 119,13
44,27 ± 45,04
0,0835558
219,03 ± 40,49
109,24 ± 7,62
0,0119931
153,17 ± 59,77
0,115238
175
119,53 ± 45
0,138921064
0,08355702
0,01199322
0,1153
Supplementary
4. Characterization of tomato Cycling Dof Factors reveals conserved and new functions in the control of
flowering time and abiotic stress responses.
Table S4.1.- S. lycopersicum DOF transcription factors sequence. DOF domain is underlined.
>SlDOF-1
MQDIHPIGGGGGRFLGGAGDRRLRPNNHQNHQALKCPRCDSLNTKFCYYNNYNLSQPRHFCKSCRRYWTKG
GVLRNVPVGGGCRKSKRSKPKSTTADDTPEEPKSDTNSSSESSSLTATTTAAAAATANTPGAATTEDVSATSS
NSASTYLNFPDSNFFIPHSTNQTFDDQPLMENSVEDQFQDIGNFTNMMTSSNDPFNMVDIPAYRLPENQNSNE
QWNTETKMVETLPTSGEMKMEQMSTDFLNQTGRVDEYPGLHQSNSELTPLNWQTGGDHGLYDLTGTVDHQS
YWSQTQWGENDNSLNFLP*
>SlDOF-2
MQDPSIYSQIKPQFPEQEHLKCPRCDSPNTKFCYYNNYNLSQPRHYCKSCRRYWTKGGTLRNIPVGGGSRKST
KRSSSSSSSSKKSSSTSTTSPATPPLTSSSSSTNPKPEPFGIPAIPSFDVMTTSTGPFSSLLASTEPQFGNFLEAL
NPNNNNGSTLQLGNPVSSSGHQNGNTSYLGVQNGGESNNCWNGGNNGWPDLAIFTPGSNFQ*
>SlDOF-3
MQDPSSIYSQINPQFPDQQVLKCPRCDSINTKFCYYNNYNLSQPRHFCKNCKRYWTKGGILRNIPVGGSSRKNT
KRSSSNSCKRSSTMTISSSTSSEQNSKTEHFDTPVVRNSPIVDANGPFGSLLASNGPEIGNFLNVLNPNGPDSG
SDAAAAQSGNSNNNHEFLGEDSNCWNGTNGWADLAIYTPGNVQLFQTKLKLPSSDLKLSSLQELHLEESFLDE
QLLQYLRTTCNHLQVLSFKRFLLLNTMKISCDCLERLAIVACDNLDVDAPNLMLFTYHVHYGTTLKLKGSHSLEA
HLTLIPETIESHWYSKLTKSLGFRCFVVYIQITEMHQIRMRDLVVHAYLYLLSVGKHKLERVKFQNFTSALLEKLKN
YIYIFTNADDLEIIEVPPECRL*
>SlDOF-4
MAFSSIPFYQDPPNWHHEQGNHHQQQQHLGITNENSSELSPTVLPPPGAAPGGGGGPVGSTRSGSITERARL
PKITQPDVALKCPRCESTNTKFCYFNNYNLSQPRHFCKTCRRYWTIGGTLRNVPVGGGCRRNNKRSSSKRSRK
SPIRSERSRNVPISTSNSTNTITTPSHFPPSSTHLSFFNTPFHNFNNFNSTQNCLNFGEIQPHEGDPTFVDQFRH
QQMEKFSFFSPLEQPSNLYPIYSEFRINHHDLENVKVEENKSSTNSTQGMNLQRNNNLGVNQFWTNYNISSTST
SQLL*
>SlDOF-5
MAFSSFPIYLDHPNLHHLQQQPDHHQQGNPGLDNPQLLPPPTQVGGGPGSIRPGSMVNRARIAKLPLPEAGLK
CPRCDSSNTKFCYFNNYSLSQPRHFCKNCRRYWTRGGALRNVPVGGGCRRNKRNKSSSNNNSAKSGGGGG
LMGNSNNASTSGIPSINCSMEMIGHHFSQSSTQFTSLMGAFQNLNNYGGGLIQPPTHQLVGEMGFQIGSNNLLP
SLVASNNFEHPTNLYPNFQNEGTTTTTTTTIEASNGVTQQVKMEDNNRQGMNSSTKQFLGTLENNNQYWDVA
NANANANVNSWIGFSSDLNNNSLSTTNHLL*
176
Supplementary
>SlDOF-6
MVFSSIQAYLDSSNWQQAPPSNYNHDGTGASANGGHVLRPQLQPQQQPHPNGSGGGGGGGGGSIRAGSMV
DRARQANVALPEAALKCPRCESTNTKFCYFNNYSLTQPRHFCKTCRRYWTRGGALRNVPVGGGCRR
>SlDOF-7
MVFSSFPVYLDHPNLHQLQQADGHQQGNTGLELPTVQPPPPMQVGASPGSIRPGSMVDRARLAKIPLPEAGLK
CPRCDSTNTKFCYFNNYNLSQPRHFCKTCRRYWTRGGALRSVPVGGGCRRNKRSKSSSNNNNNNSSKSTGG
SNVNTNKTIASGTSTSASPSSCSTEIMNGRHHFPHEQPTQLTPLMAAFQNLNHHYGGFQPNLVSTHHGNGSAL
SSHHHEMGFQIGNSTNTNNTNNLPVPSGGGSDHQWRLPSLAANTNLYPFQHGSDQGIHESSAGNNNNINGHH
DEQGLNSTKQFLGTMENNSNQYWGGNAWTGGFSGLNSSSSASHLL*
>SlDOF-8
MVFSSISAYLDPSNWQQQVGYSIPNPQLPSGLSQPTPPRPLASTPPPPPPPPPPPQPHHVGGGGSIRPGSMAD
RARLANIPMSEATQKCPRCESTNTKFCYFNNYSLSQPRHFCKTCRRYWTRGGALRSVPVGGGCRRNKRSSTS
NSSTSAKSSNNNTKSQGSSQTTNSGSTSNNNSSPSSAASLLGLMNPPIHPLRFMSPLGPLTDQHFTPNEMNYT
SISSPSPAPIVMGTNENMNFQLGMGSNLEQWRLHQQLVNQFPYNLYGGLDSSPASGSGSASASGLYPFHQAH
YDASGGGVISQIRPKVSNPMLTQLALMKMEDDQDHVASMPRQFLGNENWTSNANWNELSASFSSSSTSNNVL
*
>SlDOF-9
MNFSSIPAYLDPANWQQQSGSTIQNHHHHQQQQLTSAPPPPVLPPGPPVVAPLQPHGGGGAGSIRPGSMADR
ARMANITMPETALKCPRCDSTNTKFCYFNNYSLSQPRHFCKACKRYWTRGGALRSVPVGGGCRRNKRSNNNN
KNSTNNNNNNNSSKSPASSTSTDGRQGTNNSGSSTTISSHSNSFSGPTSAASLLGLMSPQIPPLRFMSPLGQF
SSDHHHHHHFTPSNHMNLNFSTSSCGNILGGTTEGMMVSNNNLLGTGTGAGVGGHVASLLSSGNLEHWRMQ
QQFPNFLGGFDPSNSPSSYPFQGGVHEAVQYLGGESTSQISRPKISTSMLNQMASVKMEDNNNNNSNQDQSA
LSRQLLGIQGNNENWNTSASAWSDLSASFSSSSTSNAL*
>SlDOF-10
MIQELFAGNTTLIGDDNISNITPSSSPISCTTSNSNIAPASANANSENLRCPRCDSPNTKFCYYNNYNLTQPRHFC
KTCRRYWTKGGALRNVPIGGGCRKNKSIATSKSTAAKFKNSLPFEFIGKSGIFGGFEQEIIPSNYDNNNPFLFSS
PHQNHNPILSLLKGNLHKSIGVNQFPSNNGIWKNNYEENVGEVQNSRGFQELYQRLKASTNRCYTDNMHGPSS
SSMILDSAPVTGGELGCWNPTLSTWLDLPTANGAYL*
>SlDOF-11
MSQDNKGESQSSGGGDDGGGGPMGARPKEQALNCPRCDSPNTKFCYYNNYSLSQPRHFCKTCRRYWTKG
GALRNVPIGGGCRKNKKMKTSSSSTRFSGDSKDTISGSSDIGGLKFFHGLSPAMDFQLGGLNFPRLSNNSSTST
177
Supplementary
VGGNIFNQFSSFGENSTPNIGSTSCFSLDPSGSSSLLGFNNNFPFSSSMLKQGNEGVQEMGSMGVHHGTMAS
SIESLSSINQDLHWKLQQQRLSMLFGGENQKENIISSSIPLHDDQNQNQNQIQIQKPQPILFQNLEISSSKQQEDH
QETFGNNNVDSRKDCSTTIGNHHGNNLSTEWFFDNSFGLNSNSTHSNNNNNNGNGNANDDQNVNNWNSTIQ
AWSNLNQYSTLP*
>SlDOF-12
MMDSNGTNAATSNNMEKPIQDPSQQQQQQPPPHLKCPRCDSSNTKFCYYNNYSLSQPRHFCKACKRYWTRG
GTLRNVPVGGGCRKNKRIKRPSVNSSSSTTTTSHDIITTSTPNIVNPSHHHQLHHGVVHNNIDHLSTTNSQNHLN
PLFYGLTHERSDLNIPFARLFNSRVSSHAGGVDPEGQVYSLTDNIPGLMDRRMGLGFSNSSGGVVNMGHENN
NNNNNSSSSNYGHGGFNPIKQIQDVHVMSTSNCTTSTTSLLSSYPNMFGSSSSTSTMASLIASSLQQQKFMSNI
NGNSFHSLLTPNNYEELQMSRGENNNTNINNVHEGGGNGITMLKEEKMDLSNHQIHEQIINSSDPSLSWNGAW
LDPSNMGSNSVPSLI*
>SlDOF-13
MEDQLGGRSSGENDRNQQQRRMKMPENNSASPAQPPPQKCPRCDSNNTKFCYYNNYSLTQPRYFCKTCRR
YWTQGGTLRNVPVGGGCRKGKRTMKGGGSSSSAGESSSSRSHHQVLYPPQIPNLSAAAAAFFSGNNSRSQP
PPLPSMSSLYTGAAGGGGFLSSLAAMQSMSQLSQGINNQSQLGVISGTNNNNNQFGNFNIPTPPPKVQIDQQM
ESTGFYQKPNLESSFFPSDQTLQFQPARPLGSWTQRFINNNNNNIWPNNSASNTSSGAASSSAANASLGPNDH
QWPDLPGFGPSP*
>SlDOF-14
MDPSSAQHQHHQELSSQTLESMLVSTKPQQQDPKKPKPPEQAINCPRCDSSNTKFCYYNNYSLSQPRYFCKS
CRRYWTKGGTLRNVPVGGGCRKNKRSSSSRSSSISSQDQHSIVNTPNNPFPYDSSDLSLAFARLQKQGNGQL
GFENHGNLSMMCNENPSGIFLDALRGNTGFLENNNPMNGLIHQQNLYYGVGNIINGDIGLHNVENGGLGVNNN
DQEVGLMHNYDQEISSGVTTSTTMTTVKQEMCNMAKDQGDHNRVLWGFPWQINGEGINMADFDSTRRMWN
GVGGSSWHGLLNSPLM*
>SlDOF-15
MCIMDHHQQEMTSQTLESMLVCAKPDQDQKKPRPAAAEQQPQKCPRCDSANTKFCYYNNYSLTQPRYFCKS
CRRYWTKGGTLRNVPVGGGCRKNRKLSSAKRSSQDNISPNSSNSSTDLSLAFARLQKQTNAIDQEQDTNNNM
SMMYNTNNDNTSTTFLDALRGGFLENHHGLFQHNMYNYANMGQLVENGEMGLSYDQDQMSIGTMMTTTMKQ
EMCNVARSTEGHDLNDNNKVLWGFPWQQMSGDHHVNNNMNTNDFEYSTNKQSWNGFGGSSNWHGLINSPL
M*
>SlDOF-16
MSSQTLESMLACTKPQQEKKPRPQDEVQKCPRCDSSNTKFCYYNNYSLTQPRYFCKSCRRYWTKGGTLRNV
PVGGGCRKKQRSSSKRSSPDNQSLMTTTTYPNNQISPLTQFSYDPNDLSLAFSRLQNQESGQLVCPKLQRTVR
178
Supplementary
TESIFSDSLYLTNFGNSVCHDVFENRDMCTSSSEAFSRAGFLDTLSDGLLDASNGFLHHNLYYYGSNGNNGNN
MGHVESASGEMITNFDQEVRSGALKEEIMCSDNKILLGYPWQINGDGNVADFEYSNRQNWNGLGVPSGHGLL
NSPLM*
>SlDOF-17
MGITSLQVCMDSSNWLQDTIPEENEFDSSSSPSGGDIFTCSRPLMERKLRPQHDKPINCPRCDSTHTKFCYYNN
YSLSQPRYFCKSCRRYWTKGGTLRNIPVGGGCRKNKKVSSKNSKLPNDNITTPHVESSNNYPEMSFSHFGNF
MGNNNMNHNFMHHAPIDFMDSSKYQALVGTTSTRNQDFFGNVNVGTTGLINGYGEMDISRIGPHYCSSAFGLP
NMDGNIINYEGQNITMDVKPNPKILSLEWHDQGYFNGGLGTWSGLMNNGYGSTATTNSLV*
>SlDOF-18
MGITSLQVCMDSSDWLQGTIHEDCAGGMDSSSSPSGGDHINNLMTCSRPIIVDQRRLRPPHDHSIKCPRCDST
HTKFCYYNNYSLTQPRYFCKTCRRYWTKGGTLRNIPVGGGCRKNKKVSSKKSSTNTNESIPLSTTTTTNNNNIP
EMPFPHHFMSSTNFGHHGNFMLENQAPIIDFMESKYEALVGSSSSTTTNSRLLNQDLFLGNGDNNNNIGMMMM
SGSTSTNGFGHDHDNIVATNYPFGITSIMDSSNNGNSFGMLLPYENHHEEVQNINAVEMKPNPKILSLEWHDDQ
LGSNKESSFGYYSGNGGLGSWTGLMNGNCYGSSATNPLV*
>SlDOF-19
MLPYHPRPMIMMERTRKSNIEQAPNCPRCASTNTKFCYYNNYSLSQPRYFCKACRRYWTKGGSLRNVPVGGG
CRKSRRSRSTRKDDNTLQTSSPALEGAPGAHDIDLADVFAKYLNQGTNNDHDDNIIIQESQDYSSIGASLSNSPS
SDSLVNNPTSFENESLLDNFQDYPCGNFLQEEQGAQINQDFLDFNASFLEMQAILGQEEDQFDHYNTSNFEWQ
PMMQFQDFGSILELDDHQLTKNSTTNLASHDNNNNNNYSSFDLSNYI*
>SlDOF-20
MESTQWSTHEEIGVVKSSMGAEIMNKKVRPVKDGAINCPRCNSINTKFCYYNNYSLTQPRYFCKTCRRYWTEG
GTLRNVPVGGGSRKNKRLSSSSSSSQKLPDLNPNPTSHHQNPNNIVIGSNQDLTLGFRTVPQDHHTSFHGVIP
QFLEFPKMDGSNNHLGSRTGIASRGFTSFISSASTPDLNALYNSGFPFQEIKPSAGNADHAASLSNSNYSSGGP
GGLENGSGARIMFPLGGLKQLSSTNQVDHLTKGQENNNSTAGLYWSGMISGTGGSW*
>SlDOF-21
MATQIAPPNVTCSRTSTTMEKKVRPQKDQVVNCPRCNSTNTKFCYYNNYSLTQPRYFCKTCRRYWTEGGTLR
NVPVGGGSRKNRRCSISSSSLSSISSSQKLLDLNPNPSLSSLQNPNYNLNLGSNQDLNLGFPSFNIHNHNNYFR
GMPQFLDFPKMDKGNNGINHFSTSTSNTSPVSALDLLQKGIASRGLTASISSSSSPSTPDLNALYTSSEVQENG
AKMMLPFGCLNNHNNSESKGQENSSSVGFWNDGMLGGGGTW*
>SlDOF-22
179
Supplementary
MDTSQWPQEIVMKPMEDIIGNTSKPTNCVERKLVRPQKDQVVNCPRCNSTNTKFCYYNNYSLSQPRYFCKTCR
RYWTEGGSLRNIPVGGGSRKNKKSSSPYNHHVIVNNKKLPDLVVPPPQPDNIEEYPERHFGNRPHDQNPSKIIL
EGSQDLNLGFSSDFKTITDLIQVPNYDGSNKDNNNISTILPPPSSSSSASSPSQLSVMELINGITNNNNNNNNNSF
MTMPNSVYNSSGFSLMPSLNFSLDHGIGNDVHHSSSYGNNNNNLQDTNANGRFLFPFVGLKQVSNNTSDGGA
NEPSLGDQSTNGYWNGMLGGGSW*
>SlDOF-23
MDTSPQWPQGIGIVKGVDEAKLDQRKPRPQKEQAVNCPRCNSTNTKFCYYNNYSLTQPRYFCKTCRRYWTEG
GSLRNVPVGGGSRKNKRSNSISISSSSTTSSLSLSSSSKKLFTDLANPNDLNLTYNPIPSGGTTTTTATNFSNFSD
FMALPLLHPSANSASTFMTSSNLYPSSTTGISNLHDLKSSNGINFSLDGFENGYGSLPSHQEAKLFFPMDDLKIN
VSTVGDEQFEENRGQAADQSNGFWNGMLGGGGTSW*
>SlDOF-24
MDTSQWPQGIVVKTMEEMKIPKNTNTRKIRPQQQQNDEALKNCPRCNSTNTKFCYYNNYSLSQPRFFCKNCR
RYWTDGGSLRNIPIGGVSRKSKKSSSINIMKNNIISPKVQDIINNNNNKGVNQDLNLDFSSDFKIISELIQVPNNNS
FMPIMPNISDPNSIYLFSSNLDHGLIGSSSISDGGYECNNIIQDLQVCTSTTTSGGILFPFEDLKQVSNTSEQSRDG
ESSTNGYWDVILGGN*
>SlDOF-25 (SlCDF1)
MREVKEPEIKLFGKKIVLPENGMILPVIVTGEDSDVGKSMSASEVVTADESSTGSDRDPCLVDKEGNSSQQDES
DDGSEYEKDEADKDRMTRELSEAKLEEKDQNLMMEESENLKSPSENKTKTHTIDDDSPTVKSSKTEDDQNDAS
NSQQKTLKKPDKILPCPRCNSMDTKFCYYNNYNVNQPRHFCKSCQRYWTAGGTMRNVPVGAGRRKNKNSAS
HCRHIMISEALEAARIDPPNGFSHPVFKPNGTVLSFGPDLPLCDSMASVLNLAENKTPNGIRNGLYRPENPSGIG
GENGDDCSSGSSVTTSNSMAEGVKNCPPEAVMQTINAFPSPVPCLPGVPWPIPYAAVPFPAISPAGYPMPFCP
PPYWNCNVPGPWSLPWLTPPSPTANQKGSVSAPNSPLGKHSRDGELLKPNNPEGQKNSEGSVLVPKTLRIDD
PDEAAKSSIWSTLGIKYDSVSRGGLFKSLQPKNSEKDHPTTTSPSLQANPAAFSRSLSFQERV*
>SlDOF-26 (SlCDF3)
MTCDSEIKLFGKILPVVVSGVGRGLSGSDGVIYDGNRNGSDLDRCLEGSKASSVEKDEGSEYEKQEAEKDNITG
ELSEAKSEEGDQNQMIEESENPKTPSESESSPKSSTEEDPQAVKSSKTENEPTNVTNSEQNNLKKPDKILPCPR
CNSLDTKFCYYNNNNVNQPRHFCRSCQRYWTAGGTMRNLPVGAGRRKNKNLASQYRNISIPEGLLAAGIESPN
GLIHHPLFKPNGTILSFGPDLPLCEPMASALNQAEKRVSTGIQNGSHKSEVKNSSCKGGDSGDECCRGINIPTPN
MMVEEGKGEPHKAVMHSINGIPSPVPCLHGVPWPFPWNAAVPVSAICPIPFPMPFFPTPYWNCSVPPWSNPW
LSPPLRAANEKTSGSDPTSSLGKHSREGDLLKPSNPGGKEQSEQKYSEGSILVPKTLRIDDPDEAAKSSIWSTL
GIKYDSTNRGEFFKALQPKSNDKHNKANTFPVLHTNPAALSRSITFQQGA*
180
Supplementary
>SlDOF-27 (SLCDF4)
MTDPAIKLFGRTIQLPDIPDSSGAQGDDSLPGDNNGEEDEEADKDDFGGNLDDDEEEMEILTGKELQDQNSEPT
KTDSIKELPVDNDCSTRPSKSEEEQGEASNSQEKILKKPDKIIPCPRCNSMETKFCYFNNYNVNQPRHFCKSCQ
RYWTAGGTMRNVPVGAGRRKNKNSIPHYRQISVSETLSNAQTDYPNGIQQPILAFGSPTPLCESMASVLNIADK
TMHNCSQNGFHKPQEPGVPVSYVVGDNGDDHSRRSSVTSANSEDEVNKTVPDLLKKNCHNFPPYMTYYPGA
PWPYPCSPVPWNSAIPPPGYCPPGFPMPFYPAASYWGYTVAGSWNVPWMSPATVSLIQTPTTSGPISPALGK
HSRDENIQKPLSSMEEPSNESNPEKCLWVPKTLRIDDPGEAAKSSIWATLGIKHDTVDSVGGSPFSAFQPKNDD
NNRVSENSTVLQANPAALSRSVNFNESL*
>SlDOF-28 (SlCDF5)
MSEAIAIKDPAIKLFGWTIQLPDFPAPAPEDSSFLAGEVEQELKGLYDDCIDDNEHLTTEDSQDQNPIQQRCDIIN
YYESSTAKTSKSKEEHGETSNSHERNLKKPEKTLPCPRCNSMETKFCYFNNYNASQPRHFCKNCQRYWTAGG
TMRNVPVGAGRRKHKNSVLHYSHVSVSEALSNVRTNFPTETQHPPLTLNGTILSFDTDKPVSESMVSVLNVADK
GMQNCSGNGFQKYKELRIQAGDNGDDHSDGSSVTAISSKDSDNGLPNTPRKNYNSFPTHLPCFTGAPWPYIW
SSVHCRNAVPPPGYSLPGIPMSFIPATTYWGCTIPGSWNVPWMSPPTASHNQMPLTPDPNSPTSRKHSRDEN
VLKSTGTEEEQRKESDPGKRLWFPKTLRIDDPGEAAKSPIWATLGIKHEVVNSVGGGLLSDFLPKNDERSCVSE
NSTLLQVNPAAMSRSLNFNESS*
>SlDOF-29 (SlCDF2)
MSEVRDPSIKLFGKTIGMTQQETNCVYLHDDHTTSSPLSIDDEKINLEGEVTQSKQVDELVDPAADSSIEPETSS
GISDDIKMQDADKETLSSKSVEEEDSSEEKALKKPDKLIPCPRCNSMETKFCYYNNYNVNQPRYFCKNCQRYW
TAGGTMRNVPVGSGRRKNKSSSISNYPLQAGRVEAAAHGMHLPASRTNGTVLTFGSDKPLCDSMVSALNLAE
NSHNMHRNEYHGSEQRMPTIGNDQSNGSCSTASSVTDKESSAGTHDLANWSNFQPFPPQVPYFQGAPWPYS
GFPVSFYPAAPYWGCTVSNPWNVPWLSSNQSVHNNSPTSPTLGKHSRDESKLDPSQSRRRDTTLQDREGER
CVLIPKTLRIHDPNEAAKSSIWSTLGIRNEKIDSTRGTMLFSAFNPKADHRNRELDTSFALQANPAALSRSLHFRE
STR*
>SlDOF-30
MAEVQESPISQGIKLFGATIEIQEKQAKATHQPTNKVVVDDDDDNDQEKRPDKIIPCPRCKSMETKFCYFNNYNV
NQPRHFCKGCQRYWTAGGALRNVPVGAGRRKAKPPCGPGPHGDLADGCNLFDVANQLDFDGSVVAHEDQW
HLFPAAKRRRSTSDSQSY*
>SlDOF-31
MGLSTKLVSIDDDGLDNWTTTTHNTRPEPPSIRRQLPSKSESLKCPRCDSINTKFCYYNNYNKSQPRHYCKGCK
RHWTEGGTLRNVPVGGGRKNKRVRPTDPVDHINGRKHVRLEVNDQRCPLITTTSMTNSIITSSILPSVTLIRGNS
TITSAIDEDIKNLTSSSLPYDIFSNISQDHGNTHFSLIPNSSTNTQLSSNVYYNYEHMGKFDSTILEESTITTIMPITS
NNDLHSYEPWKVPETSNNDLIIDENMSNNYWNWNEFETLSNAADLNISWDDLEIKP*
181
Supplementary
>SlDOF-32
MSSEIGDRRPARLPAPVNGTRPSEPENLPCPRCDSTNTKFCYYNNYNLSQPRHFCKSCRRYWTRGGTLRNVP
VGGGTRKNSSHKRPRINSGAGTVQEQTNPITMMGSGSGHVSGSGSMSLMGCEVNLNESVHEGGNGTSSFTS
LLTAPVGVGVGGFVPLGGFGLGLGGFGLGNLDWPMEQVSGGGNGGDGGENDKWQLSGGEMEGGGGGGGS
GGGGIGGDDDCFGWPDLAISAPGTSLK*
>SlDOF-33
MTLESSEKLVTKQQTGGVQAPPTQEPDHHLPCPRCDSINTKFCYYNNYNLSQPRHFCKSCRRYWTQGGTLRDI
PIGGGSRKNAKRSRIYTNTPFSSTIASVSSHAVPGNSPFMLPLPAANQLLFGTDVKPINNFTSLLSSHGPGVLAL
GGIEDMGFGIGRGNVWPFTGAPDSYSRNYNNGGGAGMWQFSGGEGGFVGSGDYFN*
>SlDOF-34
MPSDVRATKQQQGGAPAPEPEHLPCPRCDSTNTKFCYYNNYNFSQPRHFCKSCRRYWTHGGTLRDIPIGGGS
RKNAKRSRTITTNSMNSSCLSSTLSPRDYHHAPHPSHVSPFLVPLTADHGGSLPFDVKPSVNMCGSFTSLLSSA
QGPGGLLALGGFGLGVEDMGFGLGRPIWPFPGVSHNTSVDNNSNGAGASMYGSTWQLASGGEGGFVGAGG
EIFNFPDLAISTHGNVFNCTFLASGVLALEFRTAVPSIDHQL*
182
Supplementary
Table S4.2.- S. lycopersicum DOF transcription factors structure.
Sequence
namea
SlDOF-1
SlDOF-2
SlDOF-3
SlDOF-4
SlDOF-5
SlDOF-6
SlDOF-7
SlDOF-8
SlDOF-9
SlDOF-10
SlDOF-11
SlDOF-12
SlDOF-13
SlDOF-14
SlDOF-15
SlDOF-16
SlDOF-17
SlDOF-18
SlDOF-19
SlDOF-20
SlDOF-21
SlDOF-22
SlDOF-23
SlDOF-24
SlDOF-25
SlDOF-26
SlDOF-27
SlDOF-28
SlDOF-29
SlDOF-30
SlDOF-31
SlDOF-32
SlDOF-33
SlDOF-34
Gen model nameb
Solyc numberc
SL1.00sc02597_315.1.1
SL1.00sc04007_502.1.1
SL1.00sc05575_495.1.1
SL1.00sc04337_438.1.1
SL1.00sc04765_101.1.1
SL1.00sc01795_2.1.1
SL1.00sc03759_1.1.1
SL1.00sc01435_36.1.1
SL1.00sc06070_132.1.1
SL1.00sc01656_196.1.1
SL1.00sc07184_188.1.1
SL1.00sc00226_375.1.1
SL1.00sc00226_376.1.1
SL1.00sc06019_225.1.1
SL1.00sc06004_311.1.1
SL1.00sc05805_285.1.1
SL1.00sc06255_2.1.1
SL1.00sc02749_314.1.1
SL1.00sc03736_1.1.1
SL1.00sc05858_346.1.1
SL1.00sc02642_1.1.1
SL1.00sc00777_49.1.1
SL1.00sc06118_114.1.1
SL1.00sc02257_183.1.1
SL1.00sc02749_33.1.1
SL1.00sc02597_358.1.1
SL1.00sc03187_39.1.1
SL1.00sc00530_73.1.1
SL1.00sc00395_292.1.1
SL1.00sc00226_263.1.1
SL1.00sc00226_436.1.1
SL1.00sc02164_222.1.1
SL1.00sc02606_70.1.1
SL1.00sc01656_203.1.1
Solyc03g121400.1
Solyc06g062520.1
Solyc05g054510.1
Solyc11g066050.1
Solyc00g024680.1
Solyc06g076030.2
Solyc10g086440.1
Solyc09g010680.2
Solyc02g090310.1
Solyc11g010940.1
Solyc02g077950.1
Solyc02g077960.1
Solyc06g075370.2
Solyc11g072500.1
Solyc06g005130.2
Solyc06g071480.2
Solyc03g112930.2
Solyc04g070960.1
Solyc01g096120.2
Solyc10g009360.2
Solyc08g082910.1
Solyc03g082840.2
Solyc08g008500.2
Solyc03g115940.2
Solyc06g069760.2
Solyc02g067230.2
Solyc02g088070.2
Solyc05g007880.2
Solyc02g076850.1
Solyc02g078620.1
Solyc04g079570.1
Solyc02g065290.1
Solyc02g090220.2
aSequence
Predicted gene
structurec
___Dof ___
_▼_Dof ___
__Dof _▼3_
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_D▼of ___
___Dof ___
__D▼of _▼_
___Dof ___
___Dof ___
_▼_Dof ___
___Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
___Dof ___
_▼_Dof _▼_
_▼_D▼of ___
_▼_Dof _▼_
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
_▼_Dof ___
___Dof ___
___Dof ___
___Dof ___
___Dof ___
___Dof _▼_
Groupd
A
A
A
B
B
B
B
B
B
B
B
A
C
C
C
C
C
C
C
C
C
C
C
C
D
D
D
D
D
D
A
A
A
A
name designation is arbitrary. bS. lycopersicum gen model name and
Solycnumber at SolGenomics.net. cIntron (▼) relative position respect to the DOF domain.
Sub-index indicates number of introns. dGroup designation after the phylogenetic analysis
displayed in Fig. S1.
183
Supplementary
Table S4.3.- Primers designed for Real-time PCR, expected size, and concentration used.
Gene
SlCDF1
SlCDF2
SlCDF3
SlCDF4
SlCDF5
SlUBI3
AtCOR15
AtRD29A
AtERD10
AtCO
AtFT
AtUBQ10
Primer sequence
5’-ACAGTTCACAGCAGGATGAATCA-3’
5’-GCTTCACTGAGCTCTCTTGTCATTC-3’
5’-AAAATCCTAAGACTCCATCAGAATCAG-3’
5’- GCTTGAGGGTCTTCCTCAGTTGA -3’
5’-AAAATCCTAAGACTCCATCAGAATCAG-3’
5’- GCTTGAGGGTCTTCCTCAGTTGA -3’
5’-CCGGGAGACAATAACGGAGA-3’
5’-ATCCAGGTTTCCTCCAAAGTCA-3’
5’-CTGGAGCTCCTTGGCCATAC-3’
5’-CCAGGTGGAGGTACTGCATTTC-3’
5’-AAGCAATGGATGCTGAGGCT-3’
5’-GAAGGTGCCGTTGAATGACA-3’
5’-CAGCGGAGCCAAGCAGAGCAG-3’
5’-CATCGAGGATGTTGCCGTCACC-3’
5’-GGTTCGGTGGTGGTGCGACT-3’
5’-TGGCTTCACCTCCTCCGTCG-3’
5’-CGTTTGTGGCCAAGCACGAAG -3’
5’-AGAGCTGTTGGATCGGTGGAGT-3’
5’-GAGAAATCGAAGCCCGAGGAGCA -3’
5’-TCAGAATGAAGGAACAATCCCATA-3’
5’-CTGGAACAACCTTTGGCAAT -3’
5’-AGCCACTCTCCCTCTGACAA -3’
5’-GCTCTTATCAAAGGACCTTCG -3’
5’-CGAACTTGAGGAGGTTGCAAA-3’
184
Amplicon length
Concentration
(pb)
(µM)
93
67
66
72
80
72
125
113
128
80
219
61
0.200
0.300
0.200
0.300
0.300
0.300
0.200
0.200
0.300
0.200
0.375
0.125
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.150
0.150
Supplementary
Table. S4.4.- Metabolite analyses of WT and 35S::SlCDF3 plants.
Col-0
Relative amountof
compound(%WT)
35S::SlCDF3 (10.7)
Relative amountof
compound(%WT)
35S::SlCDF3 (2.10)
Relative amountof
compound(%WT)
Glucose
100 3.2
108.1 4.0
130.9 4.9
Fructose
100 3.2
79.1 4.0
103.3 2.9
Threalose
100 5.3
102.3 7.0
64.3 3.1
Sucrose
100 8.3
279.8 22.3
264.5 8.4
GABA
100 32.5
190.3 46.3
200.7 47.0
L-Proline
100 19.0
191.2 32.8
233.8 47.7
100 13.6
164.2 22.2
183.3 24.4
100 12.1
106.0 15.2
89.1 9.2
100 4.6
128.8 9.2
122.2 7.2
100 4.7
124.9 5.7
81.6 5.6
100 3.6
74.1 3.3
84.3 5.9
100 5.1
83.7 5.0
73.6 6.2
L-Glutamine
L-Asparagine
Succinate
Fumarate
Malate
Gluconate
185
Supplementary
Supplementary File 4.1. Methods for metabolite analyses.
Reagents and solvents. Most of the stand ard compounds used for this study and the oxidation reagent
methoxy amine hydrochloride were obtained from Sigma(St. Louis, USA).N,O-bis (trimethylsilyl) trifluoro
acetamide (BSTFA) containing 1% trimethyl chlorosilane(TMCS) was purchased from Supelco
13
13
2
(Bellefonte,USA).The six stable isotope reference compounds[ C6]-glucose,[ C12]-sucrose,[ H3]-proline,
13
13
[ C5]-glutamic acid, and [ C4]-succinic acid were purchased from Campro (Veenendaal, The
2
Netherlands),[ H4]-2-hydroxybenzoicacid from C/D/N Isotopes (Pointe-Claire, Canada).
Plant extraction. A total of 100 mg of pooled seedlings from A. thaliana (Col-0, 35S::SlCDF3 and
3S::AtCDF3 overexpressing lines) sterilely grown under long-day conditions on plates were harvested
12days after germination, immediately froze in liquid nitrogen, and thenstoredat-80ºC until further use.
When we were ready to commence the extraction, the frozen plant material was transferred into 2mL
screw-cap tubes filled with
ceramic
beads
(Mag NALyser Green
Beads), 1ml of
13
a chloroform:
13
2
methanol: H2O(20:60:20)mixture including the internal standards([ C6]-glucose, [ C12]-sucrose, [ H3]13
13
2
proline, [ C5]-glutamic acid,[ C4]-succinic, [ H4]-2- hydroxy benzoic acid) was added, and the plant
material crushedina MagNALyser Instrument(Roche, Mannheim, Germany)at6,500rpmfor1min. The final
-1
concentration of each reference compound in the solvent mixturewas15ngmL . Next, the samples were
centrifuged (10 min, 14,000rpm), and 200 µL aliquots of the supernatant transfer red to fresh tubes.
Samples were either directly analyzed by LC- MS or taken to dryness in a speed-vac concentrator for
subsequent derivatization.
UHPLC/ESI-qTOF-MS. Five microliters of the extract were separate dusing an Ultimate 3000 RSLC
system(Dionex, Sunnyvale, USA).The column used was a 50mm x 2.1mm i.d.,1.7 µm, Acquity UPLC
BEH C18 column with a 5mmx2.1mm i.d. Acquity UPLCBEHC 18 Van Guardpre-column and a 0.2µm x
2.1mm i.d.in-line filter (Waters, Milford, USA). The following binary gradient was applied: 0 to 2min
isocratic
98%
solvent
A(water
with
0.1%[v/v]
186
formica
cid),
2%
B
(acetonitrile
with
Supplementary
0.1%[v/v] formic acid); 2 to 25 min linear gradient to 5% A, 95% B; at 25 min step gradient to 100% B;
isocratic for 1 min. Thereafter, the column was set to 98% A, 2% Band conditioned for 2min before the
next injection. The flow ratewas400µL/min. All solvents were of LC-MS grade.
Eluted compounds were detected by a micro TOF-QII mass spectrometer (Bruker Daltonics, Bremen,
Germany)
operated
in
electro
spray
positive
mode.
Typical
settings
were
as
follows:capillaryvoltage,4500V;dry gastemperature,200°C;dry gasflow,10L/min; funnel, RF200Vpp.Ions
were detected from m/z 50 to 1000 at a repetition rate of 5Hz.The instrument was operate deitherin MS
orauto MS/MS mode. Mass calibration was performed using sodium for mate clusters (10 mM solution of
NaOH in 50/50% v/v isopropanol/water containing 0.2%formic acid).
For data processing the Data Analysis 4.0 software (Bruker Daltonics, Bremen, Germany) was used.
Principle component analysis was conducted using Profile Analysis 2.0 (Bruker Daltonik, Bremen,
Germany).Data sets were evaluated from 0.25 to1500 sin the mass range between m/z 50 to1000.
Compound finding was performed prior to data processing using the find molecular feature (FMF)
algorithm (Krug et al., 2008 Anal Chim Acta). On the basisofline mass spectra, mass peak clusters,
which consist of a minimum number of 8 consecutive scans, were generated. From these clusters, local
extracted ion chromatograms (EIC) traces were calculated. Finally, chromatographic peak
detection(S/N= 3,no smoothing)was performed on these EIC traces allowing the subsequent correlation
analysis of neighboring isotopes(correlation coefficient threshold=0.7,maximumvalue=1.0). To correct for
anon-constant signal variance, the data set was scaled using the PARETO method. The two first
principal components (PCs) extracted accounted for approx. 34% of the total variance existing in the
sample population.
Derivatization. Prior to GC-MS analysis, samples were derivatized according to the two-step protocol
given in the following: At first, carbonyl moieties were protected by methoximation, using
-1
30µLofa15mgmL solution of methoxy amine hydrochloride in pyridin eat 22°C (room temperature) for
16h. Afterwards, acidic protons were derivatized by the addition of 30 µL of N, O-bis (trimethylsilyl)
trifluoro acetamide (BSTFA+1%TMCS) for 1h at room temperature (22°C). All samples were analyze in
randomized order and the first sample was analyzed by GC-MS 30 min after the silylation regents were
added.
GC-MS. One µL of the derivatized sample is injected split less by an Combi Palau to sampler (CTC,
Zwingen, Switzerland) into a BRUKER Daltonics 451 gas chromatograph equipped with a 30m x0.25 mm
i.d. fused silica capillary column with a chemically bonded 0.25µm DB5-MS stationary phase (BRUKER
Daltonics). The injector temperature is set to 270°C. After1 min, the split is opened (1:100). During the
first 1.10 min a pressure pulse (30psi) supports sample application onto the column. The gas flow rate
-1
through the column is adjusted to 1mL min , the column temperature is held at 70°C for 2min, then
187
Supplementary
increased by 20°C min-1 to 325°C, and held there for 5min. The column effluent is introduced into the
ion source of a Scion-TQ triple quadrupole mass spectrometer, GC-QQQ-MS (BRUKER Daltonics).
The transfer line and the ion source temperatures are maintained at 250°C. Ion sare generated by a 70e
-1
Velectron beam at an ionization current of 80 µA, and 30spectra s are recorded in the mass range 50 to
600m/z. The acceleration voltage was turned on after a solvent delay of 390s.
All data were processed by MS Workstation8 (rev2) software (Bruker Daltonics, Bremen, Germany).
Automatic peak detection and mass spectrum deconvolution was performed with a peak width setto 1.0s.
Peak areas were calculated using selected quantification masses for each metabolite and internal
standard. Mass spectra of all detected compounds were compared with spectra in the NIST11 mass
spectral library (as of May, 2011), and an in-house reference database
188
189