En esta memoria se presenta la Tesis Doctoral que lleva por

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En esta memoria se presenta la Tesis Doctoral que lleva por título:
DESARROLLO DE UNA PLATAFORMA DE
TILLING EN MELÓN (Cucumis melo L.)
Escrita por Mireia González To
Director: Jordi Garcia Mas
Tutora: Mª Carme Espunya
Esta Tesis ha sido realizada en el Programa de Genòmica i Biotecnologia del IRTA
que pertenece al Centre de Recerca en Agrigenòmica (CRAG) y dentro del programa
de doctorado del Departamento de Bioquímica de la UAB.
A Enero de 2014
T
T
A la meva mare que mha ensenyat a estimar i a mantenir lalegria
"Dijo Tennyson que si pudiéramos comprender una sola flor sabríamos quiénes somos y qué es el mundo"
Jorge L. Borges
Ara tot just intento pensar en el principi d’aquesta aventura i me n’adono que jo era una persona
totalment diferent. Els agraïments moltes vegades es queden curts, les paraules tants cops no poden
copsar tot el que ha significat un gest o la companyia d’una persona. Per això vull començar dient
que, segurament, aquestes paraules mai diguin tot el que volen dir. Aquest només és un intent de
reconèixer i sobretot, agrair-vos a tots els que m'heu acompanyat en aquesta aventura de 8 anys.
En primer lloc vull agrair a les persones que han fet possible aquest periple: a la Carme Espunya per
ser la professora que em va descobrir el meu amor científic cap a les plantes. Al Jordi Garcia-Mas per
confiar en una estudiant de pràctiques que arribava a l'IRTA de Cabrils amb moltes ganes d’aprendre
i al Pere Arús per recolzar-lo en aquesta decisió. Vull agrair als que han col.laborat en aquest
projecte perquè sense ells no s'hagués pogut dur a terme: a Fitó i al COMAV. En especial a la Belén
Picó per aconseguir publicar un article d'aquest treball amb la seva dedicació i persistència.
L'època a l’IRTA ha estat un dels períodes més feliços de la meva vida. Tots els que hi éreu hi vau
contribuir; cadascú a la seva manera i durada. Els becaris (Edu (i les guerres privades d'aigua al
laboratori quan ja no hi quedava ningú), Ibo, Iria, Juan (¡Ánimo, ya no queda nada!), Julio, Alí, Claudio,
Roger, Eudald...). A tots ells els hi agraeixo la companyia, el fet de poder compartir la mica de
desesperació que tantes vegades pateix un becari i poder riure dels nostres errors. Si un no
s'equivoca, no aprèn.
Des d’aquí, d'aquest petit espai meu i propi, vull fer un reconeixement a tots els tècnics, sense
vosaltres els laboratoris no avançarien. És d'aquestes coses que tothom sap, però que crec que a
vegades cal dir en veu alta i clara.
Ells són: Fuensi (gràcies per ensenyar-me tant i per tenir tanta paciència amb el nostre estimat LICOR), Àngel (gràcies per la teva disposició i la teva alegria incondicional) Joana, Ana, Patricia, Alicia,
Dani, Manoli... En especial a la Vane, sempre al meu costat, inseparables companyes de "poyata".
Gràcies per fer-me riure (i a vegades fer-me plorar), per fer-me ballar i treballar, per ensenyar-me les
tècniques i perquè fora de la feina m’has cuidat igual que cuides als teus. Gràcies per fer-me sentir
tan estimada.
Als companys de caseta (Montse, Francesc, Olga, Ainoha, Jonatan...) perquè allà vam ser
autodidactes, vam compartir cafès i coneixements. Potser la ciència no cal que sigui tan seria, a
vegades. A la Puri, pel “cachondeo” que m’animava les tardes com a gairebé ningú, encara que li
trepitgés els "fregaos".
A tots els investigadors (Werner, Jordi, Amparo, Momo, Montse M., Montse S., Wim, Txose, Gisela,
Torben, Toni M.) i especial al Mourad per ensenyar-me que la ciència pot ser molt creativa, plena de
colors inesperats (¡Esa eterna discusión con el salmón de los geranios!) i, sobretot, per acompanyarme en tantes tardes i nits de petita solitud a Arenys en les que em cuinaves cous-cous i peix al forn
com si fos la seva pròpia germana. Al Santi Vilanova, perquè sempre m'ha cuidat i perquè en els
moments que queia ell sempre m'oferia la mà per ajudar-me a aixecar. A la Marta Pujol, no només
per tot el que l’admiro com a professional i el que he après amb ella, sinó també com a persona.
Marta, sense tu, segur, que no hagués acabat aquest projecte. Gràcies Marta.
Un dels aventatges que té la investigació és que et permet viatjar i fer estades a laboratoris d’altres
països. A Evry vaig poder treballar al costat de l'Abdelhafid Bendahmane al qui vull agrair
l’ensenyament de la tècnica del TILLING. També a la Christelle Troadec, amb qui vam compartir hores
d'aprenentatge, llargues xerrades en franco-català-anglès i molts caramels. Merci beaucoup
Christelle. La estancia en Evry fue como un "mini Erasmus" gracias a dos latinos: Nilo y Silvia. A ellos
quiero agradecer que me acogieron en su piso como una más, me cocinaron a la italiana y me
prepararon Pisco-Sour para olvidarnos entre todos de los diseños de cebadores y de las plantas de
tomate. Nilo y Silvia siempre os recuerdo, gracias.
A pesar de haber acabado las prácticas de doctorado en Marzo de 2010 y de no haber presentado
la tesis, conseguí una beca en Italia, más concretamente en Roma para trabajar con Giovanni Giuliano
en el ENEA. Considero ese período como una ampliación del doctorado y de mi aprendizaje. Per
questo non vorrei lasciare di ringraziare a Marco, Silvia, Killy, Sara, Patrizia, Elio (DT!) e Giulia
l'incredibile esperienza di vivere e lavorare a Roma. Lavorare divertendomi così tanto: ballare e bere
la birra in laboratorio con Silvia al termine di lunghe giornate di lavoro tra i pomodori e PCR. Grazie a
Giuliano per la fiducia in me e nelle mie capacità. E a tutti per rendere questo periodo uno dei giorni
più felici della mia vita. Voglio tanto bene all'Italia e gli italiani!.
Finalment i no menys important, vull agrair als amics que m’acompanyeu des de sempre i que m'heu
vist créixer i madurar en aquest projecte. Que heu aguantat les llargues i constants (i segurament
pesades ;-) converses sobre aquest tema i sempre heu confiat en mi. Crec que si confies en algú
aquella persona també confia més amb ella mateixa per això vull dir-vos que és un regal preciós el
que m'heu fet: Club Bikini (Marta, Anna P., Anna A.), PSFs!! (Martina, Jess, Raquel B. -gràcies també
pel increïble disseny de la portada, sabia que faries alguna cosa que la sentiria pròpia, gràcies
artista!- Raquel Ll., Nayibe, Isa, Nurieta, Alba, Tere...), Claudia sempre aprop estiguis on estiguis,
Humanistes! (Marta, Eva, Laia) que m'heu acompanyat i juntes hem descobert tantes coses
fantàstiques de la vida com per exemple que el coneixement és poder. Sou totes fantàstiques, dones
increïbles. Us admiro a totes i de totes he après lliçons imprescindibles per créixer. Sou l'orgull del
gènere femení! ;-).
Al Jordi Carreras perquè sense ell probablement mai hagués iniciat aquesta aventura. Gràcies per
ajudar-me tant a creure en mi. I a tants amics que sempre em feu riure, pensar, imaginar, crear,
superar-me: Jorge, Aleix, Belén, La Peña!!!, Carme, Manolo, Chelo, Marisa, Alexis...Papa, gràcies per
ensenyar-me la disciplina, la constància i el sacrifici que han estat realment indispensables per
projectes com aquest.
Per acabar, vull agrair a la meva família tot l'esforç que han fet des de sempre i sobretot perquè sou
els meus fans incondicionals i em cuideu com ningú. Mama no tinc paraules, ets fantàstica, la meva
heroïna sense dubte. Marc, simplement t'adoro. Àvis (Eulàlia i Quimet) sou el meu exemple a seguir,
no he conegut persones més bones que vosaltres. Patrick, tempiternament, gràcies per TOT, per la
VIDA i per ensenyar-me que si un vol pot aconseguir els seus somnis. Nada por obligación, todo por
ilusión. Gràcies, Gracias, Grazie, Thanks, Merci,
Mireia González To
Barcelona, 07/01/2014
T
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Una de las recientes tecnologías descritas de mutagénesis dirigida en plantas es la
denominada tecnología TALENs (Transcription Activator-Like Effector Nucleases).
Existen patógenos bacterianos del género Xanthomonas que infectan a una amplia
gama de especies y que durante la infección, proporcionan a las células de la planta
una serie de proteínas conocidas como Transcription Activator-Like Effectors (Boch y
Bonas, 2010). Estas proteinas se unen a promotores de genes diana de la planta y de
este modo modifican el transcriptoma de la planta huésped. Para unirse al ADN de
la planta, TALE contiene un dominio de unión compuesto por varias repeticiones de
monómeros de 34 aminoácidos cada uno de los cuales sólo dos residuos, que están
localizados en las posiciones 12 y 13, son hipervariables. Cada motivo hipervariable
TALE reconoce un par de bases en una secuencia de ADN.
TALENs se ha creado mediante la fusión de un dominio de unión (TALE) con una
nucleasa FokI. De este modo el complejo puede reconocer una secuencia concreta y
producir un corte de doble cadena en un sitio específico para inducir mutagénesis
dirigida, como por ejemplo la inserción de un fragmento exógeno de doble cadena
induciendo a la represión o activación del gen dependiendo de la función del
HM
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dominio donde se ha localizado la inserción de TALENs. Esta tecnología de
mutagenesis dirigida ya se ha usado con éxito en varias especies como por ejemplo
en Arabidopsis thaliana (Cermak y col., 2011).
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Genes candidatos para el TILLINGO
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(.,)/#9(
Genes candidatos para el TILLING
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(.,)/#9(
Genes candidatos para el TILLINGO
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Genes candidatos para el TILLING
(.,)/#9(
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Genes candidatos para el TILLING
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&-(m "#m !"m 3,m "#m *1m "'#8m .*9,23*1m HZm /3#m 1#m +#8!*0-,m .0m #620#0m #*m Ym *m
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Dosis EMS
Número de frutos recogidos en las
plantas M1
Número de familias M2 incluidas
en la población de TILLING
0,50%
204
177
1%
2544
1922
1.5%
392
269
TOTAL
3140
2368
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"#m *m *>,#1m GGGm 7m Ym m 1#!3#,!'m "#m LHjGGIm 7m GGGm #,m #12m 0#%'A,m #1m '"<,2'!Ym
1>+'1+-m1#m*-!*'80-,m-20-1m.-*'+-0$'1+-1m#,20#mLHjGGIiGGGm7mm^'%30mIYIm_Ymm
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#,!-,20"-1m#,20#m*1m40'#""#1mLHjGGIm7mYm _m#*m"#mjm3,m4#8m.*'!"-m#*m+<2-"-m"#mmm
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#,m %0'1m "#2#0+',m #*m [email protected] m .02'0m "#*m !3*m #*m %#*m .#0">m 0#1-*3!'A,m ^7m .-0m *-m 2,2-m *-1m [email protected] "#m *-1m
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m+'#,201m/3#m#,m#*m%#,-2'.-mm!-,2#,>m3,mm#,m*m.-1'!'A,mNONiHMGYm#m+-"-m/3#m*m
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Posición
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1
2
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Exón 12
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Intrón 12
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2%
0.01
1226
Intrón 12
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4
1460
Intrón 12
C/T
2%
5
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Intrón 12
C/T
1%
6
C384
Exón 13
C560T
Ser540Phe
1%
0.00
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Resultados
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Resultados
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Resultados
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^HFILZm +32,2#m ,Em G_m 7m 20#1m #,m *m .- *!'A,m "#*m m ^KIm ^K_Zm HKIHm ^L_m 7m GJHFm ^M__Ym -1m
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Resultados
!+ TDMIOT32,2#1m#,!-,20"-1m#,m#*m.0'+#0m+.*'!A,m"#mKFFm. m"#*m%#,m>Ym,m0-(-Zm/3<**-1m#,!-,20"-1m
#,m*m.- *!'A,mm7m#,m4#0"#m#,m*m.- *!'A,mYmg-1'!'A,m0#1.#!2-m#*mm#,m#*m+Ym
m
Nº
Familia
Posición
CDS*
Cambio aa
%EMS
SIFT
1
F2036
Exón 1
G 74 A
Arg25Lys
1%
0.00
0.02
5
53
Exón 1
G 289 A
Glu97Lys
1%
6
2532
Exón 1
C 294 T
Phe98Phe
2%
7
1420
Intrón 1
G/A
2%
0m #*m 1#%3,"-m +.*'!A,m ^ *m IYO_m 1#m '"#,2'$'!0-,m 3,m 2-2*m "#m GJm +32,2#1m "#m *-1m
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IaYm 320-m "#m *-1m +32,2#1m /3#m 2'#,#,m *m +32!'A,m #,m *m 0#%'A,m #6A,'!Zm .0-4-!,m
3,m !+ '-m "#m +',-9!'"-m ^KMZm GHHOZm JJJZm HFLF_m 7m *m $+'*'m GNNFm !-,2'#,#m 3,m
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ijim#6!#.2-m#,mOKOZm#,m#*m/3#m#*m!+ '-m#1m3,m20,14#01'A,m"#m%3,',mm!'2-1',m
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m
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m
Nº
Familia
Posición
CDS
Cambio aa
%EMS
SIFT
2
F57
Exón 2
G 385 A
Glu129Lys
1%
0.00
3
F1880
Exón 2
G 465 A
Thr155Thr
1%
4
F959
Intrón 2
G/C
8
1229
Exón 2
C 401 T
Ala134Val
2%
0.10
9
444
Exón 2
G 407 A
Gly136Glu
2%
0.00
10
1287
Intrón 2
C/A
2%
11
1115
Intrón 2
C/T
2%
12
1667
Intrón 3
G/A primer
nucleótido del
intrón
2%
13
2646
Intrón 3
C/T
2%
14
1233
Intrón 3
C/T
15
2060
Exón 4
G 616 A
1%
2%
Glu206Lys
2%
0.09
GGKm
.#9(OO'/.#)(-O
Resultados
16
2035
Intrón 4
C/T
2%
17
1368
3’UTR
T/C
2%
18
2163
3’UTR
G/A
2%
m
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pot1
pvr2
rym
nsv
sbm1
mo1
MAAAEMERTMSFDAAEKLKAAD---GGGGEVDDELEEGEIVEES----NDTASYLGKEIT
MATAEMEKTTTFDEAEKVKLN------ANEADDEVEEGEIVEET----DDTTSYLSKEIA
MAEDTETRPASAGAEER------------------EEGEIADDG----DGSAAAAAGRVS
MVVEDSMKATSAEDLSNSIANQNPRGRGGDEDEELEEGEIVGDDD--LDSSNLSAS-LVH
MVVEETPKSIITDDQITTNPN-----RVIEDDNNLEEGEILDED----DSSATSKP-VVH
MKSEE-QKLIDVNKHRGVRSD-------GEEDEQLEEGEIVGGDADTLSSSSSSRPGTAI
*
:
*****
..:
53
50
38
57
50
52
pot1
pvr2
rym
nsv
sbm1
mo1
VKHPLEHSWTFWFDNPTTKSRQTAWGSSLRNVYTFSTVEDFWGAYNNIHHPSKLIMGADF
TKHPLEHSWTFWFDNPVEKSKQDAWGSSLRNVYTFSTVEDFWGAYNNIHHPSKLVVGADL
-AHPLENAWTFWFDNPQGKSRAVAWGSTIHPIHTFSTVEDFWSLYNNIHHPSKLNVGADF
QPHPLEHSWTFWFDNPSAKSKQATWGASIRPIYTFSTVEEFWSVYNNIHHPSKLAMRADL
QPHLLENSWTFWFDTPAAKSKQDDWGSSMRPIYTFSTVEEFWSIYNNIHHPGKLAVGADF
AQHPLEHSWTFWFDTPSAKSKQVAWGSSMRPIYTFSSVEEFWSLYNNIHRPSKLAQGADF
* **::*** **.* **:
**:::: ::***:**:**. *****:*.**
**:
113
110
97
117
110
112
pot1
pvr2
rym
nsv
sbm1
mo1
HCFKHKIEPKWEDPVCANGGTWKMSFSKGKSDTSWLYTLLAMIGHQFDHGDEICGAVVSV
HCFKHKIEPKWEDPVCANGGTWKMSFSKGKSDTSWLYTLLAMIGHQFDHEDEICGAVVSV
HCFKDKIEPKWEDPICANGGKWTISCGKGKSDTFWLHTLLALIGEQFDFGDEICGAVVSV
YCFKHKIEPKWEDPVCANGGKWTVNFPRGKSDNGWLYTLLAMIGEQFDCGDEICGAVVNV
YCFKHKIEPKWEDPICANGGKWTANYPKGKSDTSWLYTLLAMIGEQFDHGDEICGAVVKV
YCFKNKIEPKWEDPVCANGGKWTMTFTKAKSDTCWLYTLLAMIGEQFDHGDDICGAVVNV
:***.*********:*****.*. . :.***. **:****:**.*** *:******.*
173
170
157
177
170
172
pot1
pvr2
rym
nsv
sbm1
mo1
RAKGEKIALWTKNAANETAQVSIGKQWKQFLDYSDSVGFIFHDDAKRLDRNAKNRYTV
RGKGEKISLWTKNAANETAQVSIGKQWKQFLDYSGSVGFIFHDDAKRLDRNAKNRYTV
RKNQERVAIWTKNAANETAQISIGKQWKEFLDYKDSIGFVVHEDAKRSDKGAKNRYTV
RSGQDKISIWTKNASNEAAQASIGKQWKEFLDYNESIGFIFHDDAKKFDRLAKNKYMV
RGRAEKISIWTKNASNEAAQVSIGKQWKEFLDYNETMGFIFHDDARKLDRNAKNKYVV
RARQEKIALWTKNAANESAQLSIGKQWKEFIDYNDTIGFIFHEDAKTLDRSAKNKYTV
*
:::::*****:**:** *******:*:**. ::**:.*:**: *: ***:* *
231
228
215
235
228
230
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SeqAA
prH
prE
prL
SUBsec
#-/-#9(m
MVVEDSMKATSAEDLSNSIANQNPRGRGGDEDEELEEGEIVGDDDLDSSNLSASLVHQPH
000011111111112344444444322111111111111222211111221111111221
000000011111000000000000111111111233333333321111111122223333
988877777677776654554444556667776554554444456666666666655444
LLLLLLLLLLLLLLL...........LLLLLLL...........LLLLLLLL........
SeqAA PLEHSWTFWFDNPSAKSKQATWGASIRPIYTFSTVEEFWSVYNNIHHPSKLAMRADLYCF
prH
212211222222222221111100112211111112222222111112211100101011
prE
221111222211000000123443210111123334444333322111135676665543
prL
556666544556666677765445676667655443333444566666543212223344
SUBsec....LL......LLLLLLL.....LLLLLLL.............LLL.....EEE.....
SeqAA KHKIEPKWEDPVCANGGKWTVNFPRGKSDNGWLYTLLAMIGEQFDCGDEICGAVVNVRSG
prH
112222212222211111122221222222122222222111111111112111111112
prE
322233343332211123333323333333332222333333211111232333344311
prL
555444444444566655444444444444444444333445667677654444433566
SUBsec.............LLL...........................LLLLL..........LL
SeqAA
prH
prE
prL
SUBsec
QDKISIWTKNASNEAAQASIGKQWKEFLDYNESIGFIFHDDAKKFDRHAKNKYMV
1111111111222233222233334322112211111112357666553311100
1111223332111112343212112333222222355431000000000000100
7776665445665654433444543334555455433356542323346678789
LLLL...................................L..H.......LLLLL
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Amplicón
Exón
Posición
cambio AA
Familia M2
Plantas
secuenciadas
en M2
Segregación en M2
(WT/H/M)*
eIF4E-1
Exón 1
G74A
Arg25Lys
F2036
24
9/7/8
eIF4E-2
Exón 2
G385A
Glu129Lys
F57
8
5/3/0
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FSIPLELIYFVKKSAVFPYRWVLVQFGAFIVLCGATHLINLWTFT-THSRTVALVMTTAK
FSIPLELIYFVKKSAVFPYRWVLVQFGAFIVLCGATHLINLWTFT-MHSRTVAVVMTTAK
FSIPVELIYFVKKSAVFPYRWVLVQFGAFIVLCGATHLINLWTFN-MHTRNVAIVMTTAK
FSIPLELIYFVHKSACFPYRWVLMQFGAFIVLCGATHFISLWTFF-MHSKTVAVVMTISK
FSIPLELLYFISRSN-LPFKWVLVQFIAFIVLCGLTHLLNGWTYNPHPSFQLILSLTVAK
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VLTAVVSCATALMLVHIIPDLLSVKTRELFLKNKAAELDREMGLIRTQEETGRHVRMLTH
ALTALVSCITALMLVHIIPDLLSVKTRELFLKKKAAQLDREMGIIRTQEETGRHVRMLTH
MLTAAVSCITALMLVHIIPDLLSVKTRELFLKTRAEELDKEMGLIIRQEETGRHVRMLTH
ILTALVSCATAITLLTLIPLLLKIKVRELFLAQNVLELDQEVGMMKKQTEASMHVRMLTH
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EIRSTLDRHTILKTTLVELGRTLALEECALWMPTRTGLELQLSYTLHQQ---NPVGYTVP
EIRSTLDRHTILKTTLVELGRTLALEECALWMPTRTGLELQLSYTLRHQ---NPVGLTVP
EIRSTLDRHTILKTTLVELGRTLDLAECALWMPCQGGLTLQLSHNLNNL---IPLGSTVP
EIRKSLDKHTILYTTLVELSKTLKLQNCAVWMPNESRSQMNLTHELSPSSAAESHRS-LS
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IQLPVINQVFGTSRAVKISPNSPVARLRPVSGKYMLGEVVAVRVPLLHLSNFQINDWPEL
INLPVISQVFSSNRALKISPNSPVASLRPRAGRYVAGEVVAVRVPLLHLSNFQINDWPEL
IQLPVINQVFGTNHVVKISPNSPVARLRP-AGKYMPGEVVAVRVPLLHLSNFQINDWPEL
INLPIINEIFSSPEAIQIPHTNPLARMRNTVGRYIPPEVVAVRVPLLHLSNFTN-DWAEL
INDPDVLEIT-KNKGVRILRQDSVLAASSSGGSGEPCAVAAIRMPLLRASDFKG-GTPEL
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STKRYALMVLMLPSDSARQWRVHELELVEVVADQVAVALSHAAILEESMRARDLLMEQNV
STKRYALMVLMLPSDSARQWHVHELELVEVVADQVAVALSHAAILEESMRARDLLMEQNV
STRSYAVMVLVLPMNGLRKWREHELELVQVVADQVAVALSHAAILEDSMRAHDQLMEQNI
VDTRYAILVLVLSSVDERVWSYDEMEIVEVVADQVAVALSHATVLEESQTMREKLEMRNR
VPECYAILVLVLPSEQGRSWCSQEIEIVRVVADQVAVALSHAAILEESQHMRETLEEQNR
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ALDLARREAETAIRARNDFLAVMNHEMRTPMHAIIALSSLLQETELTPEQRLMVETILKS
ALDLARREAETAIRARNDFLAVMNHEMRTPMHAIIALSSLLQETELTPEQRLMVETILKS
ALDLARREAEMAVRARNDFLAVMNHEMRTPMHAIIALSSLLQETDLTPEQRLMVETILKS
ALDVARQEAEMAIRARNDFLAVMNHEMRTPMHAVIALCSLLLETDLTPEQRVMIETILKS
VLQQAQENAMKASQARTSFQKVMNNGMRRPMHSILGLLSIFQDEKASSDQRMIVDTMVKT
ALEQAKQDALRASQARNAFQMVMSHGLRRPMHSILGLLSLLQDEKLGNEQRLLVDSMVKT
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SNLLATLMNDVLDLSRLEDGSLQLELGTFNLHTLFREVLNLIKPIAVVKKLPITLNLAPD
SNLLATLINDVLDLSRLEDGSLQLDIGTFNLHAVFKEVLNLIKPVTLVKKLSLTLHLGPD
SNLLATLINDVLDLSRLEDGSLQLDIGTFNLHALFREVHSLIKPIASVKKLFVTLSLSSD
SNLLATLINDVLDLSRLEDGILELENGTFNLHGILREAVNLIKPIASLKKLSITLALALD
STVLSTLINDAMEISAKDDGRFPVEMKPFQLHLLVREASCLVKCLCVYKGFGFSTDVPTS
SNVVSTLIDDVMDTSTKDNGRFPLEMRYFQLHSMIKEAACLAKCLCAYRGYNISIEVDKS
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LPVFAVGDEKRLMQAILNVVGNAVKFSKEGSISISAIVAKSETFREIRVPDFHPVPSDSH 529
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LPNQVMGDEKRTFQVLLHMVGHLLNVSIGKGSVIFRVVLETGAETGNDKVWGTRRPSTTD 534
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RESEARCH ARTICLE
Open Access
Towards a TILLING platform for functional
genomics in Piel de Sapo melons
Mireia González1, Meihong Xu1,5, Cristina Esteras2, Cristina Roig2, Antonio J Monforte1,3, Christelle Troadec4,
Marta Pujol1, Fernando Nuez2, Abdelhafid Bendahmane4, Jordi Garcia-Mas1 and Belén Picó2*
Abstract
Background: The availability of genetic and genomic resources for melon has increased significantly, but
functional genomics resources are still limited for this crop. TILLING is a powerful reverse genetics approach that
can be utilized to generate novel mutations in candidate genes. A TILLING resource is available for cantalupensis
melons, but not for inodorus melons, the other main commercial group.
Results: A new ethyl methanesulfonate-mutagenized (EMS) melon population was generated for the first time in
an andromonoecious non-climacteric inodorus Piel de Sapo genetic background. Diverse mutant phenotypes in
seedlings, vines and fruits were observed, some of which were of possible commercial interest. The population was
first screened for mutations in three target genes involved in disease resistance and fruit quality (Cm-PDS, Cm-eIF4E
and Cm-eIFI(iso)4E). The same genes were also tilled in the available monoecious and climacteric cantalupensis EMS
melon population. The overall mutation density in this first Piel de Sapo TILLING platform was estimated to be 1
mutation/1.5 Mb by screening four additional genes (Cm-ACO1, Cm-NOR, Cm-DET1 and Cm-DHS). Thirty-three point
mutations were found for the seven gene targets, six of which were predicted to have an impact on the function
of the protein. The genotype/phenotype correlation was demonstrated for a loss-of-function mutation in the
Phytoene desaturase gene, which is involved in carotenoid biosynthesis.
Conclusions: The TILLING approach was successful at providing new mutations in the genetic background of Piel
de Sapo in most of the analyzed genes, even in genes for which natural variation is extremely low. This new
resource will facilitate reverse genetics studies in non-climacteric melons, contributing materially to future genomic
and breeding studies.
Keywords: Cucumis melo, inodorus, TILLING, mutant, disease resistance, fruit quality
Background
Melon (Cucumis melo L.) is an important vegetable
crop. Genetic and genomic information for this crop is
increasing significantly due to several national and international projects [1]. A broad range of genomic tools
are available today [2-7]. An effort is also in progress,
through a Spanish initiative, to obtain the whole genome
sequence of this crop [8]. These tools are generating a
lot of information about genes involved in various biological processes, such as plant resistance and fruit quality
[9,10]. However, the tools necessary for reverse genetic
* Correspondence: [email protected]
2
Institute for the Conservation and Breeding of Agricultural Biodiversity
(COMAV-UPV), Universitat Politècnica de València, Camino de Vera s/n, 46022
Valencia, Spain
Full list of author information is available at the end of the article
studies to conduct the functional validation of candidate
genes in melons are still limited.
The TILLING (Targeting Induced Local Lesions in
Genomes) method may represent an effective means of
addressing limitations in melon research [11]. The application of TILLING has proved to be useful in identifying
novel alleles in genes controlling traits of agronomic
interest in legumes [12-15], cereals [16-23], solanaceous
crops [24-26] and Brassica spp [27,28].
C. melo is a highly variable species divided into two
subspecies, melo and agrestis. Most of the commercial
cultivars belong to the inodorus and cantalupensis
groups of the subspecies melo [29]. Cultivars of these
two commercial groups are quite different in plant,
flowering and fruit traits. Cantalupensis cultivars are
© 2011 Picó et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
T
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early flowering, frequently monoecious, and produce climacteric fruits (aromatic, medium sugar, soft fleshed
and with a short shelf life), whereas inodorus are late
flowering, mostly andromonoecious, and non-climacteric, producing non-aromatic, high sugar, firm-fleshed
fruits with a long shelf life, and which are preferred in
certain markets. These differences make breeding strategies and objectives quite different for the two groups of
melons.
A melon TILLING platform generated from a monoecious climacteric cantalupensis genotype has recently
become available [30], and has proven to be useful for
improving the shelf life of climacteric melons. A TILLING platform generated in an inodorus background
might represent a useful resource for functional studies
and for breeding non-climacteric melons.
In this paper, we present the development of an EMSmutagenized population from an andromonoecious nonclimacteric inodorus melon type (Cucumis melo L. subspecies melo cv Piel de Sapo). In total, 2,368 M2 families
were obtained. A diversity of interesting mutant phenotypes were observed in the field. In addition, several
mutant families have been identified in several genes
that were selected based on their potential contribution
to fruit quality and disease resistance.
Methods
EMS mutagenesis of melon seeds
The double haploid line, M62-113 (from Semillas Fito
S.A.), belonging to the Piel de Sapo commercial type
(Cucumis melo subsp melo var inodorus), was used as
the starting cultivar. This is the parent of the melon
genetic map and is one of the parents of the DHL line
selected for the sequencing of the melon genome. Different batches of a total of ~12,000 M62-113 seeds
were treated with the alkylant mutagen ethyl methanesulfonate (EMS). Different EMS concentrations were
tested, and 1% was finally selected and tested on a larger batch of seeds. Seeds were first hydrated with tap
water (16h), and were then soaked in tap water containing EMS concentrations (18 h). The treated seeds
were thoroughly rinsed in tap water twice for 4 hours.
After washing, seeds were placed on trays over wet
paper, and were kept in a germination chamber overnight. ~5,000 mutant plants of this first (M1) generation were transplanted at the greenhouse. Plants were
grown in two localities, in Barcelona (by Semillas Fito
S.A. and IRTA) and in Valencia (by COMAV-UPV).
Each M1 plant was selfed (1 fruit per plant) giving rise
to the M2 seed.
TILLING procedure
Twenty seeds were sown per M2 family, and the germination percentage was scored. Finally, a total of 2,368
Page 2 of 11
mutagenized M2 families, which produced at least 10
viable seedlings in at least two plantings, were sampled
for DNA extraction. 1-cm discs of tissue from 10 individual plants per M2 were pooled, and total DNA was
extracted, quantified, diluted and organized into twentyfive 96-well plates. Using equivalent amounts of DNA
from individual M2 families, the samples were pooled
four-fold and organized into a 96-well format. Seeds of
all pooled M2 populations are maintained at the Genebank of the COMAV-UPV, coded as F (S. Fito),
I (IRTA) or C (COMAV-UPV) plus the corresponding
number.
Primer sets were designed from 3 genes that were
selected based on their potential contribution to fruit
quality and disease resistance: Cm-eIF4E (translation
initiation factor 4E) and Cm-eIF(iso)4E (translation initiation factor E, Isoform) which are involved in resistance to
viruses [31], and Cm-PDS (Phytoene Desaturase), which
is involved in carotenoid synthesis [32]. The CODDLe
program (Codons Optimized to Deliver Deleterious
Lesions) [33] was used to select the regions most likely to
harbor deleterious changes induced by EMS (Table 1).
These 3 genes were tilled in the Piel de Sapo population
as well as in a set of 2,483 available lines of the cantalupensis TILLING population reported in [30]. Four additional genes involved in fruit ripening were tilled in the
Piel de Sapo population: Cm-ACO1 (ACC oxidase 1),
involved in the conversion of ACC into ethylene [34];
Cm-NOR (non-ripening), a transcription factor related to
ethylene-sensitive/insensitive phenotypes [35]; Cm-DET1
(de-tiolated-1), a negative regulator of light-mediated
responses that affects carotenoid and flavonoid pathways
in tomato and other crops [36,37]; and Cm-DHS (Deoxyhypusine Synthase), mutations of which delay fruit softening in tomato [38]. Primer sets used for these
additional genes are the same as those used in [30].
The amplicons analyzed for each gene are indicated in
Figures 1 and 2.
Nested PCR was used to improve the specificity of
amplification. The PCR reactions were performed in a
25 μl volume consisting of dH 2O, 1× PCR buffer (Promega Corp, Madison, WI), 2.5 mM MgCl 2 , 0.2 mM
dNTPs, 1 U Taq polymerase, 0.4 mM forward and
reverse primers, unlabeled in the first reaction, and
700 nm and 800 nm 5’ labeled (MWG Biotech AG,
Germany) in the second reaction, and 10 ng DNA. The
thermocycling conditions were 95°C for two minutes for
initial denaturing, followed by 35 cycles of 95°C for
20 seconds, 63-69°C (specific for each primer pair) for
one minute, 72°C from 30 seconds to one minute and
one cycle of 72°C for five minutes. PCR products
(~0.2 μl) were separated in 1% agarose gels. The PCR
products were heated and cooled in a thermocycler (a
gradient starting at 94°C and decreasing 0.1°C per second
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Table 1 Primer pairs used to amplify the 3 target genes tilled in both EMS-mutant populations
Gene
Forward (*LabelledIRD700)
Reverse (*LabelledIRD800)
Cm-eIF4E
1st amplicon
GACTCAAACGCCTAACAGAAAATC
CTATCTCACCAAGTTTCCTAAATT
*GAGGGCGGTGCCATTCTTCTTCGG
*TCCCTAAATCGAACCAAGAAACGCC
Cm-eIF4E
2nd amplicon
TTGTTTCGTGTTGACATGTCCATC
AGCATGCATTTCACCTCATTGGCT
*TGCTTGGCTGTTAATTTATCTCTGC
*GTCAAGTACAGAACAAGAATCTGAG
Cm-eIF(iso)4E
Cm-PDS
GATCGATAATTTCCCTTTTC
TGACAGGCTTAAGCACTATG
*ACCCCAATTCATTCTAGGG
*TGTGCAAGCGCAACAAGGTAC
CAATGGGATGCTTAGATCAAC
TCCTTCCAAAATTACCCTAG
*GGATTTCTCGGAGTGACTCGG
*GCTCTCGAGCAACTAGCACT
Nested PCR was used in all cases with labeled primers in the second PCR.
to 4°C) to form the heteroduplexes. Once the heteroduplexes were formed, the products were treated with Endo
I. Digestions were performed in 30μl of final volume with
dH2O, 3μl digestion buffer, 150 ng of PCR product and
3μl of EndoI (diluted 1/5000). The products were incubated at 45°C for 20 minutes to digest mismatches in the
heteroduplex. Digestion was stopped by adding 5μl of
0.15 M EDTA and placing the reaction on ice. After the
digestion was completed, the products were filtered
through a Millipore MultiScreen filter plate that was
packed with hydrated Sephadex G-50 medium beads
(Amersham Biosciences). Samples were concentrated in
the Speed Vac at 65°C for 45 minutes. Loading dye was
added and the PCR products were denatured and loaded
onto a polyacrylamide gel attached to a LI-COR 4300
DNA Analyzer (LICOR, Lincoln, NE) for separation.
A total of 903 pools were assayed (592 four-fold pools of
the Piel the Sapo population and 311 eight-fold pools of
the cantalupensis population). Once a mutation was
revealed in a pool, the corresponding families were
1169
500
1719
Cm-eIF4E
154
299
154
166
1
2
5 6
3
8 9
7
78
126
66
51
4
12
10 11
13
14
15
16
17 18
Cm-eIF(iso)4E
19
1188
Cm-PDS
1125
169
290
46
1476
45
754
188
116
161
20
22
58
21
23 24 25
Figure 1 Gene structure of the target genes screened in both populations,inodorus and cantalupensis, (eIF4E, eIF(iso)4E and PDS).
Boxes represent exons and lines introns. White and black boxes indicate 3’UTR and 5’UTR regions. Amplicons analyzed by TILLING are indicated.
Black and white triangles indicate mutations found in the inodorus Piel de Sapo and cantalupensis Charentais populations, respectively. Numbers
correspond to the mutations described in table 3.
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933
933
107
103
150
Cm-ACO1
125
334
227
291
1272
89
Cm-NOR
184
26
182
314
564
1185
Cm-DET1
72
83
431
776
102
288
933
27
166
123
69
1232
182
28 29
198
136
57
81
30
578
Cm- DHS
624
84
166
93
96
31
754
168
803
106
219
32
87
33
Figure 2 Gene structure of the target genes screened in the inodorus population (ACO-1, NOR, DET-1 and DHS). Boxes represent exons
and lines introns. White and black boxes indicate 3’UTR and 5’UTR regions. Amplicons analyzed by TILLING are indicated. Black triangles indicate
mutations found in the Piel de Sapo population. Numbers correspond to the mutations described in table 3.
analyzed individually to select the mutant M2 family.
Mutation was confirmed by sequencing in the pooled
DNA, in the individual M2 families and in several individual plants used in the segregation studies. The effect of
the mutations was analyzed with SIFT (Sorting Intolerant
from Tolerant, http://blocks.fhcrc.org/sift/SIFT.html)
[39], which predicts whether an amino acid substitution
affects protein function. Scores below 0.05 are predicted
to affect protein function.
Phenotyping of M2 and M3 individuals
Seedling phenotypes were systematically evaluated in the
M2 generation. Additionally, in order to increase the
number of seeds in our mutagenized population, we
obtained the M3 generation. M2 populations that are
being reproduced are also being inspected for phenotypes
that are distinct from the wild type in plant, flowering
and fruit traits. To date, about 800 M2 plants have been
reproduced by S. Fito. M3 plants are also being analyzed
for ethylene-response mutants by growing seedlings in
darkness with and without an air flux containing 10
microL L-1 ethylene, and analyzing the “triple response”.
Results
Generation of an EMS mutant population in the Piel de
Sapo background
We selected 0.5%, 1 and 1.5% for generating a pilot population of ~600 lines, and studied the effect of EMS dosage
on M2 seed viability and seedling vigor. Increased EMS
concentration led to an increased percentage of M2 fruits
in which seeds were non-viable or in which the number
of viable seeds was too low to perform TILLING analysis
(13.24%, 27.75% and 31.38%, respectively). Only a slight
reduction in the average germination rate was observed
in M2 families obtained from 0.5% M1 (93.51%), whereas
higher reductions were obtained in 1% and 1.5% (82.73
and 75.94%, respectively). In addition, seedling growth
was more restricted at the 1.5% concentrations. In contrast, the progeny from the 1%-treated M1 were robust.
Based on these results, 1% EMS was used in the end to
complete the mutagenized melon population. This EMS
dose produces an acceptable level of M1 seed survival,
fertility in M1 plants to set viable M2 seeds, and vigor in
M2 seedlings. From a total of 3,140 M1 fruits finally
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obtained, 2,368 M2 families were sampled for DNA and
used for TILLING purposes.
Phenotyping of the mutagenized population
Ten plants per M2 line were scored for seedling phenotypes. A large number of the mutations affected
cotyledons, with 5% of the M2 families showing variation in their number position and shape. About 4.3%
of the M2 families segregated for “dwarf” or “semidwarf” plants. Albinism and chlorophyll deficiency
occurred in 2.1% of the M2 families. Over 2% of the
families showed alterations in leaves and shoot morphology. Gravitropic mutants and necrosis also
appeared, but were less frequent. Figure 3 shows several seedling phenotypes. M3 families were characterized for plant flowering and fruit traits. Fruit traits of
interest for melon breeding were identified: longer and
rounder fruits than the standard Piel de Sapo fruits,
with a lighter rind color, without the typical rind
spots, and with different degrees of netting. Some lines
have a subtle aroma and showed a color change and
the formation of an abscission layer near maturity,
a
traits that are more similar to climacteric cantalupensis
types than to the standard non-climacteric inodorus
Piel de Sapo. Differences in the dark-grown seedlings’
response to ethylene were also observed. Wild type
M62-113 showed the typical triple response: exaggeration of the apical hook, together with the inhibition of
hypocotyl and root growth as well as the radial swelling of the shoot [40], whereas some M3 families
showed responses of varying intensities (Figure 3).
Identification of mutations in target genes by TILLING
The TILLING approach allowed us to identify nucleotide changes in two of the three gene targets first
screened in the Piel de Sapo population (Table 2). EMSinduced changes were mostly G:C to A:T transitions
(67%) (Table 3), as was expected due to the frequent
alkylation of guanine residues by EMS, thus forcing mispairing with T [41]. Four mutations were exonic, most
of which were determined to be missense mutations,
only one being silent. A graph of the target genes marking the location of the induced polymorphisms is shown
in Figures 1 and 2.
b
Wild type
Wild type
c
+Ethylene
+Air
+Ethylene
+Air
+Ethylene
+Air
+Ethylene
+Air
Wild type
Figure 3 Images of selected mutant phenotypes observed in the melon TILLING population. a) Mutant seedlings found in M2. From left
to right and from top to bottom, variations in cotyledons number and position, alterations in leaf and shoot morphology, albinism and
chlorosis, including virus-like symptoms, dwarfing and altered gravitropism compared with seedling wild type. b) First row: Mutations found in
adult M3 plants, chlorosis, dwarfing and leaf and flower deformation. Second row: alterations in fruits in comparison with wild type, deformation,
chlorosis, rough surface, and pear-shape. Third row: fruit phenotypes of interest for melon breeding, variation in shape, longer and rounder
melons, and melons with a subtle aroma and formation of abscission layer with or without color change. c) Variation in triple response: M2
families showing a more intense response to ethylene than wild type and others segregating for the response.
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Table 2 Comparison of the mutations found by TILLING
in the gene targets screened in the two EMSmutagenized melon populations, Piel de Sapo (PS) and
Charentais (CH)
PS Population
Gene
CH population
Exon/Intron-UTR
Cm-eIF4E
3/1
CmeIF(iso)4E
0/0
5/9
1/0
Cm-PDS
1/1
1/3
TOTAL
4/2
7/12
Four new alleles were reported for Cm-eIF4E, defined
by 4 mutations. Two (in exons 1 and 2) were predicted
to affect protein function according to SIFT (p<0.05).
The segregation of the missense mutations was analyzed
in each mutant M2 family (Table 3) and homozygous
individuals for each mutation are being produced
for phenotypic analysis. Two new alleles were reported
for Cm-PDS. Mutations were detected in the first intron
and in the second exon of the amplicon (Figure 1). The
exonic mutation was predicted to affect protein
function.
The genotype/phenotype segregation was verified for
the Cm-PDS mutations in 15 plants of each M2. The
intronic mutation found in M2 family F1151 (mutation
20 in Figure 1) presented a Mendelian segregation of 4
wild type/7 heterozygous/4 homozygous mutant (fitting
to a 1:2:1 ratio) (Table 3). No associated phenotype was
observed, which agrees with the position of the mutation in an intronic region. The M2 family C384 carried
a missense mutation in exon 2 (mutation 21 in Figure
1). The segregation of M2 was 9 heterozygous/6 wild
type. In this family, we observed that some plants
showed delayed growth and even death at the cotyledon
stage, and therefore could not be sampled. M3 seeds
from a heterozygous M2 plant were used to repeat segregation analysis. Fourteen plants germinated out of the
20 seeds sown. Again, plants with delayed growth were
observed, but we also found a seedling with albino cotyledons and hypocotyl (Figure 4). This seedling was carefully grown until tissue could be sampled for DNA
extraction. The albino was the only plant homozygous
for the mutant allele; the remaining M3 plants were
wild type or heterozygous. This mutant line showed a
similar albino phenotype comparable to the previously
reported phenotypes for PDS disruption [32].
To further evaluate the mutation rate of the Piel de
Sapo population, we extended the TILLING screen to 4
additional genes involved in fruit quality. Mutations were
found for all genes, except for Cm-NOR, with Cm-DET1
being the most mutated gene. Six mutations were exonic,
most determined to be missense, only one silent, but all
were predicted to be tolerated (Figure 2, Table 3).
Mutation efficiency
We used these results to calculate the mutation rate of
the population. A total of 14 point mutations were
detected out of the total 11,534 bp analyzed. Previous
studies reported the difficulty in tracking mutations
on the ends of the fragments (~100 bp) [42]. Therefore,
200 bp was subtracted off each amplicon, and we considered the length screened in this study to be 9,134 bp. The
overall mutation density was then calculated by dividing
the total base pairs screened, which includes the sum of
the total length of the 12 amplicon sizes × the total number of individuals screened, by the total number of mutations revealed by TILLING ((9,134 × 2,368)/14 =
1,544,950). It was calculated to be ~1/1.5 Mb. The mutation frequency as determined by TILLING is coherent
with the moderate level of phenotypic mutants found in
our population.
In order to compare the inodorus and the cantalupensis
populations, the same genes were screened in a set of
2,483 lines of the Charentais population [30]. The number of mutations was higher, and new alleles were found
for the three genes (Table 2 Figure 1). The spectrum of
observed changes was similar to that found in the Piel de
Sapo population (Table 3). Only one mutation was found
for Cm-eiF(iso)4E. Cm-eIF4E was also the most mutated
gene with 14 mutations: seven intronic, two in the 3’UTR, and five exonic. Of the exonic mutations, two,
located in exons 1 and 2, were not tolerated (p<0.05).
One intronic mutation was located in the first nucleotide
of intron 3, and may affect a splicing site. TILLING analysis also revealed four mutations in Cm-PDS, one of
which was not tolerated. The 19 point mutations discovered in the 3,871 bp analyzed in the Charentais population make a mutation rate of ~1/401 Kb ((3,071 × 2,483)/
19 = 401,331). This is about 3 times higher than that
found in the Piel de Sapo population. This high mutation
rate in the cantalupensis population has also been
observed by screening additional genes in the final version of the population, which consists of 4,023 lines [30].
Discussion
The TILLING platform reported here is the first ever
developed in an andromonoecious non-climacteric inodorus melon genetic background. The mutation rate in
the Piel de Sapo population was moderate. It is less
mutated than the cantalupensis population that was
developed using a different genotype and a different protocol for treating the seeds, which resulted in increased
seed viability at higher EMS doses (1 to 3%). Our attempt
was the first with Piel de Sapo melons, and results suggest that our EMS treatment causes a high level of seed
lethality. Regarding the protocol, Charentais seeds were
not hydrated before being treated. Seed hydration has
been reported to activate cellular division and induce the
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Table 3 Details of the mutations found by TILLING in the gene targets screened in the two EMS-mutagenized melon
populations, Piel de Sapo (PS) and Charentais (CH)
Gene/
population
Amplicon size
(bp)
Identified
mutants
N° Exon/
1
Intron
Position
AA
change
M2
Family
M2 segregation (WT/
H/M)2
Cm-eIF4E/PS
500
1
1
A 74 G
R 25 K
F2036
9/7/8
0.00
1169
3
5/3/0
0.00
Cm-eIF4E/CH
500
1169
3
11
Exon 1
SIFT
score
2
Exon 2
G 385 A
E 129 K
F57
3
Exon 2
G 465 A
T 155 T
F1880
4
Intron 2
G/C
5
Exon 1
G 289 A
E 97 K
53
6
Exon 1
C 294 T
F 98 F
2532
7
Intron 1
G/A
8
Exon 2
C 401 T
A 134 V
1229
0.10
9
Exon 2
G 407 A
G 136 E
444
0.00
F959
0.02
1420
10 Intron 2
C/A
11 Intron 2
C/T
1287
12 Intron 3
G/A first nt of
intron
13 Intron 3
C/T
14 Intron 3
C/T
15 Exon 4
G 616 A
16 Intron 4
C/T
2035
17 3’UTR
T/C
1368
18 3’UTR
G/A
2163
1115
splicing
1667
2646
1233
E 206 K
2060
0.09
222 TGA
CmeIF(iso)4E/
PS
1014
0
-
CmeIF(iso)4E/
CH
1014
1
19 Exon 1
Cm-PDS/PS
1188
2
Cm-PDS/CH
1188
Cm-ACO1/PS
933
Cm-NOR/PS
Cm-DET1/PS
1185
776
Cm-DHS/PS
4
G 128 A
R 43 K
M1587
1.00
20 Intron 1
C/T
F1151
4/7/4
21 Exon 2
C 560 T
S 227 F
C384
6/9/0
22 Exon 1
C 395 T
S 172 F
1182
23 Intron 1
C/T
2495
24 Intron 1
T/C
1460
25 Intron 1
C/T
1226
0
-
933
1
26 Exon 4
C 728 T
1272
0
1
27 Exon 2
T 402 A
L 135 L
I76
2
28 Exon 4
G 760 A
V 255 I
29 Exon 4
C 848 T
S 284 L
30 Intron 6
G 2981 A
T 243 I
C142
0.00
0.01
10/6/3
1.00
F201
2/11/2
0.37
F1876
2/4/3
0.25
1232
2
F1248
31 Intron 7
C 3211 T
578
1
32 Exon 1
G 184 A
V 62 I
F 1728
754
1
33 Exon 3
G 610 A
V 204 I
C348
C487
13/20/0
0.58
2/6/0
0.27
1
Number of mutations corresponds to those represented in Figures 1 and 2
For some mutations, it was difficult to obtain homozygous MM plants as seedlings showed altered development.
2
repair of DNA damage [43]. Differences in seed structure
between genotypes, as well as an increase in the efficiency
and accuracy of the repair of the induced lesions may
explain the differences between populations. Perhaps,
HGNm
using a higher EMS dosage and/or an extended length of
mutagen application, combined with a more intense
wash length, and a more accurate seedling nursery would
have increased mutation efficiency. Other authors that
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Page 8 of 11
M/M
WT/WT
WT/M
Figure 4 Verification of genotype/phenotype relationship in the Cm-PDS gene. Chromatograms of wild type (WT), homozygous mutants
(M) and heterozygous are shown for the C 560 T transition altering codon 227 S (serine) to F (phenylalanine) and predicted to affect the protein
function. Segregation of the mutation was confirmed in M3 seeds from a heterozygous M2 plant. The albino was the only plant homozygous for
the mutant allele; the remaining M3 plants were wild type or heterozygous.
also found variable results in mutation frequency when
using EMS within a crop suggest the use of alternative
mutagens as a way for getting a higher density of mutations with less toxicity to the treated seeds [20].
Despite this higher mutation rate in the Charentais
population, the efficiency of both populations in producing mutations predicted to be damaging to the proteins
in Cm-eIF4E and Cm-PDS was similar. The new mutations found in Cm-eIF4E could be of interest, more so
when this factor is highly conserved in eukaryotes. The
natural diversity of Cm-eIF4E has been studied in
melon and related species by EcoTILLING [31] and no
variation has been reported within Cucumis melo,
except for the nsv mutation (a point mutation of
Leu228-His in exon 5), which controls resistance to
Melon necrotic spot virus [44]. Variants in exons 1 to 3
were identified using EcoTILLING in another Cucumis
species, Cucumis zeyheri, a wild relative of melon, isolated from the cultivated species by strong crossability
barriers. Therefore, our new Cm-eIF4E alleles represent
non-transgenic variants absent in nature. However it
remains to be demonstrated if these mutations will lead
to a gain of function, thereby producing new functional
phenotypes, or to a loss of function. In other crops,
recessive resistance to virus results from defective forms
of eIF4E, for example in pepper (pvr2), pea (sbm1),
tomato (pot-1), lettuce (mo1) and barley (rym) [45-47].
In most cases, resistance results from a few amino acid
changes clustered in two neighboring regions of the
eIF4E structure, located near the structural pocket
involved in CAP-binding [48]. Some of the coding
changes identified in our TILLING assay (in exons 1
and 2) are located near these two regions, close to the
conserved tryptophan residues required for CAP-binding activity (Figure 5). The other coding mutations are
found in different regions of the gene, but most affect
highly conserved aminoacids. EcoTILLING has also
shown that most natural variation in Cm-ACO1 occurs
in exons 1, 2 and 3 [49]. No variants are found in large
germplasm collections in exon 4. The effect of the identified mutation in exon 4 on ethylene production needs
to be demonstrated.
The mutants found in Cm-DET1 and Cm-DHS are the
first reported for these genes in inodorus melons. It has
been demonstrated that phenotypes of the tomato
mutants high pigment-2dg (hp-2dg) and hp-2j are
caused by lesions in the DET1 gene. Point missense
mutations and intron mutations directing alternative
splicing have been reported in both the N-terminus and
the C-terminus of the protein in Arabidopsis and
tomato, suggesting that both ends of the protein are
important for this function [50,51]. It has been reported
that suppression of DHS delays loss of tissue integrity in
senescing tomato fruit, leading to an extended shelf life.
Further analysis will indicate if melon mutants CmDET1 and Cm-DHS have alterations in fruit senescence.
Segregation studies are now being performed along with
phenotype analysis of the mutant lines.
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Page 9 of 11
Figure 5 Localization of eIF4E amino acids differing between virus-susceptible and virus-resistant genotypes of pepper (Capsicum spp.,
pvr2), tomato (Lycopersicon spp., pot1), lettuce (Lactuca spp., mo1), pea (Pisum sativum, sbm1), melon (Cucumis melo, nsv) and barley
(Hordeum vulgare, rym) in the predicted amino acid sequences (protein alignment of the susceptible genotypes). Black boxes indicate amino
acids differing between susceptible and resistant genotypes. The two protein regions with clustering of amino acid substitutions are highlighted in
pink and blue. In red are the mutations detected by TILLING in our PS population, in green, the mutations detected in the Charentais population. The
conserved tryptophan residues reported to be required for cap-binding activity are underlined in the Pisum sequence [48].
Conclusions
The TILLING approach worked in inodorus melons as a
way of identifying new heritable variants in candidate
genes that are different from those present in natural
populations. The cosegregation of a mutation predicted
to alter the functionality of PDS with the albino phenotype expected for PDS disruption suggests that this is a
promising approach for advancement in reverse melon
genetics. It is also useful to analyze TILLING populations
phenotypically, in order to use the phenotypes of interest
readily in crop improvement. The novel fruit phenotypes
could be of interest to diversify the market supply of Piel
HHFm
de Sapo melons. The information presented here will
also be useful for creating new inodorus melon populations with a higher mutation rate. Completion of the
melon genome sequence will provide many potential target genes of interest that may be functionally studied,
facilitating future genomic and breeding studies.
Acknowledgements and Funding
The authors thank Torben Jahrmann and Eulàlia Fitó (Semillas Fitó S.A.) for
selfing the M1 plants and obtaining M3 seed from the M2 families, Fatima
Dahmani for sequencing Cm-eIF4E/PS mutants, Montserrat Saladié for
providing the sequences of Cm-ACO1 and Cm-NOR from the M62-113 melon
line and Diego Bergareche for obtaining data on the M2 segregation. This
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González et al. BMC Research Notes 2011, 4:289
http://www.biomedcentral.com/1756-0500/4/289
work was supported by projects GEN2003-20237-C06-02/03, funded by the
Ministerio de Educación y Ciencia (Spain), and GEN2006-27773-C2-1/2,
funded by the ERA-PG programme.
Author details
1
IRTA, Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB, Carretera de
Cabrils Km 2, 08348 Cabrils (Barcelona), Spain. 2Institute for the Conservation
and Breeding of Agricultural Biodiversity (COMAV-UPV), Universitat
Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain. 3Instituto
de Biología Molecular y Celular de Plantas (IBMCP), Universitat Politècnica de
València (UPV)-Consejo Superior de Investigaciones Científicas (CSIC), Ciudad
Politécnica de la Innovación (CPI), Ed. 8E, C/Ingeniero Fausto Elio s/n, 46022
Valencia, Spain. 4Unité de Recherche en Génomique Végétale (INRA-URGV), 2
rue Gaston Crémieux CP 5708, 91057 Evry Cedex, France. 5Department of
Plant Science, School of Agriculture and Biology, Shanghai Jiaotong
University, 200030 Shanghai, People’s Republic of China.
Authors’ contributions
JG-M, MG and AJM performed the EMS mutagenesis. FN and BP contributed
to the development and conservation of the M2 seed. BP, CR and CE
extracted the DNA and performed the phenotypic analysis. DNA pooling,
TILLING screens and analysis, and PDS mutant phenotypic analysis were
done by MG, CT and MX. MX and MP participated in the sequencing of the
eIF4E mutants in the M2 population. JG-M, AB, BP, and FN coordinated the
study. BP, MG, CE, and JG-M were primarily responsible for drafting and
revising the manuscript with contributions from co-authors. All authors read
and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Received: 15 March 2011 Accepted: 11 August 2011
Published: 11 August 2011
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doi:10.1186/1756-0500-4-289
Cite this article as: González et al.: Towards a TILLING platform for
functional genomics in Piel de Sapo melons. BMC Research Notes 2011
4:289.
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BMC Genomics
BioMed Central
Open Access
Research article
MELOGEN: an EST database for melon functional genomics
Daniel Gonzalez-Ibeas1, José Blanca2, Cristina Roig2, Mireia González-To3,
Belén Picó2, Verónica Truniger1, Pedro Gómez1, Wim Deleu3,
Ana Caño-Delgado4, Pere Arús3, Fernando Nuez2, Jordi Garcia-Mas3,
Pere Puigdomènech4 and Miguel A Aranda*1
Address: 1Departamento de Biología del Estrés y Patología Vegetal, Centro de Edafología y Biología Aplicada del Segura (CEBAS)- CSIC, Apdo.
correos 164, 30100 Espinardo (Murcia), Spain, 2Departamento de Biotecnología, Instituto de Conservación y Mejora de la Agrodiversidad
Valenciana (COMAV-UPV), Camino de Vera s/n, 46022 Valencia, Spain, 3Departament de Genètica Vegetal, Centre de Recerca en Agrigenòmica
CSIC-IRTA, Carretera de Cabrils Km2, 08348 Cabrils (Barcelona), Spain and 4Departament de Genètica Molecular, Centre de Recerca en
Agrigenòmica CSIC-IRTA, Jordi Girona 18-26, 08034 Barcelona, Spain
Email: Daniel Gonzalez-Ibeas - [email protected]; José Blanca - [email protected]; Cristina Roig - [email protected]; Mireia GonzálezTo - [email protected]; Belén Picó - [email protected]; Verónica Truniger - [email protected]; Pedro Gómez - [email protected];
Wim Deleu - [email protected]; Ana Caño-Delgado - [email protected]; Pere Arús - [email protected]; Fernando Nuez - [email protected];
Jordi Garcia-Mas - [email protected]; Pere Puigdomènech - [email protected]; Miguel A Aranda* - [email protected]
* Corresponding author
Published: 3 September 2007
BMC Genomics 2007, 8:306
doi:10.1186/1471-2164-8-306
Received: 8 May 2007
Accepted: 3 September 2007
This article is available from: http://www.biomedcentral.com/1471-2164/8/306
© 2007 Gonzalez-Ibeas et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: Melon (Cucumis melo L.) is one of the most important fleshy fruits for fresh consumption. Despite
this, few genomic resources exist for this species. To facilitate the discovery of genes involved in essential traits,
such as fruit development, fruit maturation and disease resistance, and to speed up the process of breeding new
and better adapted melon varieties, we have produced a large collection of expressed sequence tags (ESTs) from
eight normalized cDNA libraries from different tissues in different physiological conditions.
Results: We determined over 30,000 ESTs that were clustered into 16,637 non-redundant sequences or
unigenes, comprising 6,023 tentative consensus sequences (contigs) and 10,614 unclustered sequences
(singletons). Many potential molecular markers were identified in the melon dataset: 1,052 potential simple
sequence repeats (SSRs) and 356 single nucleotide polymorphisms (SNPs) were found. Sixty-nine percent of the
melon unigenes showed a significant similarity with proteins in databases. Functional classification of the unigenes
was carried out following the Gene Ontology scheme. In total, 9,402 unigenes were mapped to one or more
ontology. Remarkably, the distributions of melon and Arabidopsis unigenes followed similar tendencies, suggesting
that the melon dataset is representative of the whole melon transcriptome. Bioinformatic analyses primarily
focused on potential precursors of melon micro RNAs (miRNAs) in the melon dataset, but many other genes
potentially controlling disease resistance and fruit quality traits were also identified. Patterns of transcript
accumulation were characterised by Real-Time-qPCR for 20 of these genes.
Conclusion: The collection of ESTs characterised here represents a substantial increase on the genetic
information available for melon. A database (MELOGEN) which contains all EST sequences, contig images and
several tools for analysis and data mining has been created. This set of sequences constitutes also the basis for an
oligo-based microarray for melon that is being used in experiments to further analyse the melon transcriptome.
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Background
Melon (Cucumis melo L.) is an important horticultural
crop grown in temperate, subtropical and tropical regions
worldwide. Melon is among the most important fleshy
fruits for fresh consumption, its total production in 2004
exceeding 874 million metric tons, of which 72.5% are
produced in Asia, 11.7% in Europe, 8.4% in America and
6.1% in Africa, being a significant component of fresh
fruit traded internationally [1]. Melon belongs to the
Cucurbitaceae family, which comprises up to 750 different
species distributed in 90 genera. Species in this family
include watermelon, cucumber, squash and marrow, all
of them cultivated essentially because of their fruits, but
this family also includes species of interest for other reasons, as, for example, their contents in potentially therapeutic compounds (e.g. Momordica charantia) [2]. Melon
is a diploid species, with a basic number of chromosomes
x = 12 (2x = 2n = 24) and an estimated genome size of 450
to 500 Mb [3], similar in size to the rice genome (419 Mb)
[4,5] and about three times the size of the Arabidopsis
genome (125 Mb) [6]. Melon has been classified into two
subspecies, C. melo ssp. agrestis and C. melo ssp. melo with
India and Africa being their centres of origin, respectively
[7,8].
Melon has a great potential for becoming a model for
understanding important traits in fruiting crops. Melon
fruits have wide morphological, physiological and biochemical diversity [7,9] which can be exploited to dissect
biological processes of great technological importance,
among them flavour development and textural changes
that occur during fruit ripening. The contemporary melon
cultivars can be divided into two groups, climacteric and
nonclimacteric, according to their ripening patterns [10].
Climacteric fruits are characterized by rapid and profound
changes during ripening associated to increased levels of
respiration and release of ethylene, whereas the nonclimacteric varieties do not produce ethylene and have long
shelf-life. Analyses of climacteric and nonclimacteric melons have illustrated the process of aroma formation [1114] and the temporal sequence of cell wall disassembly
[15-17]. Melon can be also a very useful experimental system to analyse other aspects of fundamental plant biology. For example, melon and other cucurbits have been
used to analyse the development of the plant vasculature
and the transportation of macromolecules through it [1820], and different interactions between melon and pests
and pathogens have been characterised with varying
depths [21-27].
Important genetic tools have been described for melon, as
for example linkage genetic maps [28,29] and the development of a genomic library of near isogenic lines (NILs)
from an exotic accession [30]; also, biotechnology is feasible in melon [31-33]. However, the great majority of
genes involved in the aforementioned traits are yet to be
identified in melon. Partial sequencing of cDNA inserts of
expressed sequence tags (ESTs) have been used as an effective method for gene discovery. By sequencing clones
derived from RNA from different sources, and/or by normalizing cDNA libraries, the total set of genes sampled
can be maximized. Bioinformatic analysis, annotation
and clustering of sequences could yield databases which
mining can be used to select candidate genes implicated
in traits of interest. EST collections can also serve to construct microarrays useful for identifying sets of plant genes
expressed during different developmental stages and/or
responding to environmental stimuli [34,35]. In addition,
EST collections are good sources of simple sequence
repeats (SSRs) and single-nucleotide polymorphisms
(SNPs) that can be used for creating saturated genetic
maps [36,37]. Thus, EST collections have been generated
for many plant species, being the most comprehensive
those of Arabidopsis[6] and rice [38]. Fruit crops have
been less extensively surveyed, but important collections
are publicly available for several species, including tomato
[39], apple [40], grape [41] and citrus [42].
Despite the importance of the family Cucurbitaceae, relatively little EST information is currently available: only
16,039 nucleotide sequences have been annotated from
the whole Cucurbitaceae family in the publicly accessible
GenBank database as of November 2006; out of these,
12,180 correspond to the Cucumis genus and 6,061 to
melon. These numbers are in sharp contrast with the data
available for families composed of other important food
crops like Solanaceae (1,020,102 sequences), Fabaceae
(1,466,518 sequences), Brassicaceae (1,010,148 sequences
excluding Arabidopsis), Vitaceae (449,478) and Rosaceae
(390,066 sequences). Here we describe a public EST
sequencing project in melon. We report the determination and analysis of 30,675 high-quality melon ESTs,
sequenced from eight normalized cDNA libraries corresponding to different tissues in different physiological
conditions. We have classified the sequences into functional categories and described SSRs and SNPs of potential use in genetic maps and marker-assisted breeding
programs. A database which contains all EST sequences,
contig images and several tools for analysis and data mining has been created. In addition, we have analyzed the
EST melon dataset to identify candidate genes potentially
coding microRNAs or involved in fruit maturation processes and pathogen defence. The pattern of transcript
accumulation in different physiological conditions has
been characterised by Real-Time-qPCR for 20 of these candidate genes.
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Results
EST Sequencing and Clustering
Eight cDNA libraries were constructed using material
from "Piel de Sapo" Spanish cultivars, the C-35 cantaloupe line (both belonging to Cucumis melo L. ssp. melo)
and the accession pat81 of C. melo L. ssp. agrestis (Naud.)
Pangalo. The sources of RNA to construct each library
were fruits of 15 and 46 days after pollination (dap),
leaves, photosynthetic cotyledons inoculated with Cucumber mosaic virus (CMV), healthy roots and Monosporascus
cannonballus Pollack et Uecker (the causal agent of melon
vine decline) infected roots (Table 1). Approximately
3,700 sequences were determined from each library by
single-pass 5' sequencing, except for the library prepared
from CMV infected cotyledons for which approximately
6,600 sequences were determined, yielding a total of
33,292 raw sequences. Processing to eliminate vector
sequences, low quality chromatograms and sequences of
less than 100 base pairs (bp) gave rise to 29,604 good
quality expressed sequence tags (ESTs) (Table 2) implying
a cloning success of approximately 89%. The average
edited length was 674 bp, and only a 6.4% of the
sequences had less than 350 bp.
Clustering of the sequences using default parameters of
the EST analysis pipeline EST2uni [43] yielded 6,023 tentative consensus sequences (also called contigs) and
10,614 unclustered sequences (also called singletons),
with a total of 16,637 non-redundant sequences or unigenes (Table 2). All good quality ESTs were used for clustering, independently of the melon genotype of origin,
because single nucleotide polymorphisms (SNPs) were
expected among genotypes. The number of ESTs per unigene was between 1 and 44 (1 case), with an average of 1.8
ESTs per contig, as a high proportion of contigs (4,886 out
of 6,023) contained less than 5 ESTs and contigs with
more than 8 ESTs were scarce (Fig. 1A). Therefore, redundancy values were notably low (around 16%). The unigene length varied between 101 bp and 2,664 bp,
averaging 751 bp (Fig. 1B). Library specific unigenes were
about one third of the total for each library (Table 2). A
second round of clustering yielded 14,480 unigene clusters, referred to as superunigenes. A web integrated data-
base that contains all EST sequences, contig images and
several tools for analysis and data mining has been created
and named MELOGEN [44]. Codon usage was estimated
using this EST collection. As expected, the codon usage of
melon was very similar to that of Arabidopsis and other
dicots. The preferred stop codon was UGA occurring in
the 48% of the sequences. Suppression of the CG dinucleotide in the last two codon positions is very frequent in
dicots, possibly as a consequence of methylation of C in
the CG dinucleotide, resulting in an increased mutation
rate [45]; in agreement with these data, the ratio XCG/
XCC for melon was 0.52, very similar to the corresponding figure for tomato (0.58), pea (0.51), potato (0.48) and
other dicots [45].
Libraries obtained from tissues inoculated with M. cannonballus were expected to contain sequences from the
fungus. To estimate the proportion of sequences of fungal
origin in these libraries, BLAST analyses against a database
with plant and fungal sequences were carried out [46].
Only 56 sequences from these libraries were found to
have a more significant similarity with fungal sequences
than with plant sequences (Table 3). Consequently, these
sequences were considered of fungal origin [46].
SSRs and SNPs
We have analysed the nature and frequency of microsatellites or simple sequence repeats (SSRs) in the melon
sequence dataset. A search for repeats of two, three or four
nucleotides in the dataset yielded 1,052 potential SSRs.
Approximately, 6% of the unigenes contained at least one
of the considered SSRs motifs, with repeats of three
nucleotides being prevalent (Table 4). The maximum and
minimum lengths of the repeats were 68 and 17 nucleotides, respectively, and the average length was 26 nucleotides. The most common repeat among dinucleotides was,
by far, the AG repeat, constituting the 83% (Table 4).
Repeats of AT and AC dinucleotides followed, with
approximately 9% and 7%, respectively. Among the trinucleotide repeats, the most frequent was AAG (66%, Table
4), and the least frequent was ACT (0.6%, Table 4).
Among tetranucleotide repeats, the most frequent was
AAAG (51%, Table 4). A high proportion of SSRs (29.5%)
Table 1: Description of cDNA libraries
Name
Subspecies/cultivar/accession
Tissue/physiological condition
15d
46d
A
AI
CI
HS
PS
PSI
Ssp. melo cv. "Piel de Sapo" T-111
Ssp. melo cv. "Piel de Sapo" T-111
Ssp. agrestis accession pat81
Ssp. agrestis accession pat81
Ssp. melo var. cantaloupe accession C-35
Ssp. melo var. cantaloupe accession C-35
Ssp. melo cv. "Piel de Sapo" Piñonet torpedo
Ssp. melo cv. "Piel de Sapo" Piñonet torpedo
Fruit 15 days after pollination
Fruit 46 days after pollination
Roots
Roots infected with M. cannonballus
Photosynthetic cotyledons infected with CMV
Leaves
Roots
Roots infected with M. cannonballus
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Table 2: EST statistics
Library
Raw
sequences
Good-Quality
ESTs
EST length
Singletons
Contigs
Unigenes
Redundancy (%)
Library-specific
unigenes
Novelty (%)
15d
46d
A
AI
CI
HS
PS
PSI
3,936
3,840
3,936
3,647
6,605
3,648
3,840
3,840
33,292
3,582
3,493
3,666
3,255
5,664
3,012
3,377
3,555
29,604
608.1 ± 175.2
583.0 ± 161.1
700.0 ± 185.4
756.3 ± 137.1
651.4 ± 205.7
669.3 ± 171.1
679.9 ± 198.7
749.3 ± 156.2
1,009
1,000
1,289
928
2,089
939
1,179
1,279
10,614
1,930
1,854
1,900
1,688
2,590
1,609
1,766
1,826
6,023
2,939
2,854
3,189
2,616
4,679
2,548
2,945
3,105
16,637
18
18
13
20
17
15
13
13
1,100
1,063
1,365
1,005
2,264
998
1,258
1,363
37
37
43
38
48
39
43
44
were found in open reading frames (ORFs), though an
analysis of the localization of di-, tri- and tetranucleotides
separately showed that di- and tetranucleotides localised
preferentially in untranslated regions (UTRs), whereas trinucleotides localised in both, UTRs and ORFs (Table 5).
Single nucleotide polymorphisms (SNPs) are the most
abundant variations in genomes and, therefore, constitute
a powerful tool for mapping and marker-assisted breeding. We initially identified in the melon sequence dataset
14,074 single nucleotide sequence variations and therefore potential SNPs (pSCH; Table 6) distributed in 4,663
contigs; however, these variations would include highquality SNPs (pSNP) but also sequencing errors and
mutations introduced during the cDNA synthesis step.
Using more stringent criteria, these figures were substantially reduced: Putative SNPs were annotated only when
the least represented allele was present in at least two EST
sequences from the same genotype in a given contig and
showing the same base change. Two accessions of the
same cultivar (cv. "Piel de sapo") represented 47.3% of
the sequences, but more than one half of the sequences
were from two other more distant genotypes, the C-35
cantaloupe accession (29.3%) and the pat81 agrestis
accession (23.4%). Thus, a total of 356 high-quality SNPs
were found in 292 contigs, averaging 1.2 SNPs per contig.
Table 3: ESTs showing significant similarity with fungal
sequences
Library
Number of ESTs
15d
46d
A
AI
CI
HS
PS
PSI
Total
0
0
2
26
0
1
1
30
60
Transitions were much more common than transversions.
There were 117 AG and 112 CT transitions compared with
28 AC, 37 AT and 33 GT transversions (Table 6). CG transversions were not detected. The MELOGEN database [44]
includes a tool for designing oligonucleotide primers to
amplify the region containing the polymorphism to generate the corresponding molecular marker.
Functional annotation
In order to identify melon unigenes potentially encoding
proteins with known function, we carried out a BLASTX
analysis [47] of the sequence dataset against the databases
listed in Table 7. Out of the 13,019 unigenes with a hit
with proteins in databases, 11,431 (68.7%) unigenes
showing an E value of 1e-10 were annotated. On the
other hand, 31.3% of the unigenes did not show significant similarity to any protein in the databases and, therefore, were not annotated.
Additionally, we performed a functional classification of
the unigenes following the Gene Ontology scheme. Gene
Ontology provides a structured and controlled vocabulary
to describe gene products according to three ontologies:
molecular function, biological process and cellular component [48]. To do that, we added GO terms based on the
automated annotation of each unigene using the Arabidopsis database [6]. A summary of the results with the
percentage of unigenes annotated in representative categories corresponding to the GO slim terms [48] is shown,
as well as a comparison of the distribution of melon and
Arabidopsis unigenes (Fig. 2). The distributions of melon
and Arabidopsis unigenes follow similar tendencies, suggesting that the melon dataset is representative of the
whole melon transcriptome. In total, 9,402 unigenes
could be mapped to one or more ontologies, with multiple assignments possible for a given protein within a single ontology. A high percentage of unigenes in both
species was classified as "unknown function". Out of the
9,791 assignments made to the cellular component category, 25.8% corresponded to membrane proteins and
17.8% to plastidial proteins (Fig. 2A). Under the molecu-
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!!! Table 4: Simple sequence repeats (SSRs) statistics*
Number of di-pSSR
%
AG
AT
AC
Total
205
23
18
246
83.3
9.4
7.3
100
Dinucleotide repeat
Figure 1 statistics
Unigenes
Unigenes statistics. (A) Distribution of melon ESTs among
unigenes (contigs and singletons). (B) Size distribution of
melon unigenes.
lar function category, assignments were mainly to catalytic
activity (23.0%) and to hydrolase activity (14.7%) (Fig.
2B). The distribution of unigenes under the biological
process category was more uniform, with 19.9% of assignments to cellular process and 12.7% to biosynthesis (Fig.
2C).
We have also identified 6,673 (40.1%) melon unigenes
with an ortholog in the Arabidopsis database, and a
HMMER motif has been assigned to 4,655 (28.0%) unigenes by comparisons with the Pfam database [49] (Table
7). All these results are compiled in the MELOGEN database, which also contains direct links to the databases
used to carry out analyses.
Genes potentially encoding microRNAs
Central to RNA silencing are small RNA molecules
(sRNAs) that can arise from endogenous or exogenous
sources from precursors with double-stranded RNA
(dsRNA) pairing. One class of such sRNAs are microRNAs
(miRNAs), which originate from endogenous long selfcomplementary precursors that mature in a multi-step
process involving many enzymes [50,51]. Recently, a
Trinucleotide repeat
Number of tri-pSSR
%
AAC
AAG
AAT
ACC
ACG
ACT
AGC
AGG
ATC
CCG
Total
41
471
22
18
14
4
25
54
48
17
714
5.7
66.0
3.1
2.5
2.0
0.6
3.5
7.6
6.6
2.4
100
Tetranucleotide repeat
Number of tetra-pSSR
%
AAAC
AAGG
AATC
AATG
AATT
ATCG
ACTC
AAGC
ACAT
AAAG
AAAT
Total
8
7
4
3
2
2
1
1
1
47
16
92
8.7
7.6
4.3
3.3
2.2
2.2
1.1
1.1
1.1
51.1
17.3
100
*The number of di-, tri- and tetranucleotide repeats identified in the
melon database is shown for the complete set of putative SSRs
(pSSRs).
comprehensive strategy to identify new miRNA homologs
in EST databases has been developed [52,53]. We have followed this strategy to identify potential melon miRNAs. A
total of 20 ESTs that contained homologs to miRNAs in
the microRNA Registry database [54] were identified and
grouped into 12 contigs and, after manual inspection of
secondary foldback hairpin structure, 5 unigenes were
selected (Table 8). Contig sequences varied between 536
and 840 nucleotides long, and had negative folding free
energies of -206.8 to -160.8 kcal mol-1 (Table 8) according
to MFOLD [55], which are in the range of the computational values of Arabidopsis miRNA precursors [52]. Their
predicted secondary structures showed that there were at
least 16 nucleotides paired between the sequence of the
potential mature miRNA and its opposite arm (miRNA*)
in the corresponding hairpin structure (Fig. 3). The location of the potential miRNAs varied among ESTs, 4 were
found in the sense orientation of the EST, 1 was found in
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Table 5: Localization of simple sequence repeats (SSRs) with respect to putative initiation and termination codons in the melon
sequence dataset*
5'-UTR
ORF
3'-UTR
Other†
Total
Dinucleotide repeats
Trinucleotide repeats
Tetranucleotide repeats
All SSRs analyzed
No.
%
No.
%
No.
%
No.
%
65
0
13
1
79
82.3%
0.0%
16.5%
1.3%
100.0%
121
99
13
1
234
51.7%
42.3%
5.6%
0.4%
100.0%
18
2
9
0
29
62.1%
6.9%
31.0%
0.0%
100.0%
204
101
35
2
342
59.6%
29.5%
10.2%
0.6%
100%
*Only full length melon unigenes were used for this analysis. Full length unigenes were automatically selected by checking the presence of the start
codon by comparison of the 5'-terminal region of the unigene with the corresponding Arabidopsis gene used for annotation. †Imprecise localization
of the SSR with respect to putative initiation or termination codons.
the antisense orientation. We have also searched for
potential targets of the potential miRNAs in the melon
EST dataset, identifying 3 of them (Table 8). However,
minimal folding free energy indexes (MFEIs) [53] were
below the -0.85 cut-off value proposed by Zhang et al.
[53] only for m12 (Table 8). Potential melon miRNA m12
has a precursor of 536 nt in length and codes for a melon
ortholog of the Arabidopsis miR319. miR319 targets a
transcription factor of the TCP family [56,57]; in the
melon dataset, an ortholog of this Arabidopsis gene has
been found in a unigene annotated as a TCP transcription
factor. In this case, the melon miRNA and its potential target have a pattern of paired/non-paired bases between the
target and the miRNA identical to the corresponding target-miRNA pattern in Arabidopsis (data not shown).
Genes potentially encoding pathogen resistance and fruit
quality traits
Pathogens affect severely the productivity of melon crops.
Three of the cDNA libraries sequenced here correspond to
pathogen-infected tissues and, thus, should contain transcripts from genes whose expression is induced in
response infection. We have carried out a bioinformatics
search for homologs of genes involved in pathogen resistance response (see [58] for a review) and virus susceptibility [59-61], finding among them at least one melon
ortholog to the Arabidopsis FLS2 receptor [62], several
unigenes potentially encoding disease resistance proteins
as well as mitogen-activated protein kinases, homologs to
translation initiation factors constituting potential virus
susceptibility factors, etc. [see Additional file 1].
Fruit development and ripening are the most important
processes determining the fruit quality traits of fleshy
fruits like melon. At present most of the molecular and
genetic data available about fruit development and ripening come from tomato [63,64] and Arabidopsis [65,66].
In recent years, several genes and quantitative trait loci
controlling fruit quality traits have been described in
melon [67,68]. As for developmental processes,
homologs to genes involved in melon fruit development,
ripening and quality have been found in the melon dataset. These include several MADS-box genes, homologs to
the fw2.2 and ovate QTLs [69,70], several homologs to
Table 6: Single nucleotide polymorphisms (SNPs) statistics*
Variation
Number
%
pSNP transversions:
pSNP transitions:
pSCH transversions:
pSCH transitions:
127
229
4,273
9,801
35.7
64.3
30.4
69.6
Mutation
Number of pSNP
Mutation
Number of pSCH
A<->C
A<->G
A<->T
C<->G
C<->T
G<->T
28
117
37
29
112
33
A<->C
A<->G
A<->T
C<->G
C<->T
G<->T
859
5,860
1,897
431
3,941
1,086
*Type and number of transition and transversions are shown for putative single nucleotide variations in sequence (pSCH) and for putative highquality single nucleotide polymorphism (pSNP) identified in the melon database.
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Table 7: Functional annotation statistics
A. Number of unigenes with BLAST hits
Database*
Number of unigenes
%
Arabidopsis
Cucurbitaceae
Uniref90
Any database
11,724
5,340
11,893
13,019
70.5
32.1
71.5
78.3
Database*
Number of unigenes
%
Pfam
4,655
28.0
Database*
Number of unigenes
%
Arabidopsis
6,673
40.1
B. Number of unigenes with HMMER hits
C. Number of unigenes with orthologue
* Databases searched were: Arabidopsis [6,109]; Uniref90 [110,115]; Cucurbitaceae: all cucurbitaceae sequences available in the National Center for
Biotechnology Information (NCBI); any database: results using Arabidopsis, cucurbitaceae and Uniref90 databases all together; Pfam [49,112].
members of the SBP-box gene family to which the major
tomato ripening gene COLORLESS NON-RIPENING
belongs [71], several ACC synthase and ACC oxidase
genes, unigenes from several cell wall-metabolism
enzymes, etc [see Additional file 1].
Expression analysis of selected ESTs by Real-Time-qPCR
The accumulation of transcripts for 20 selected genes was
analyzed by reverse transcription Real-Time-qPCR. ESTs
for this analysis were preferentially chosen among those
showing significant similarity with genes related to
response to infection and fruit quality characteristics in
melon and other species, and included CTL1, EIF4A-2,
EIF4E, EIN4, GA2OX1, HSP101, HSP70, IAA9, LSM1,
LUT2, NCBP, SVP, HIR, TCH4, TIP4, TOM1, TOM2A,
TOM3, UGE5 and WRKY70 (Table 9). Preliminary experiments were carried out to choose between GAPDH and
CYCLOPHILIN (CYP7) RNAs as endogenous controls;
results showed that the CYP7 RNA levels varied the least
among treatments (data not shown) and, therefore, transcript accumulation levels were expressed relative to CYP7
RNA levels.
Figure 4A illustrates the alteration of the RNA accumulation levels of selected genes that occurred in photosynthetic cotyledons after CMV infection. A significant
increase in the level of transcripts from HSP101, HSP70,
HIR, TOM2A, WRKY70 and EIN4 was observed; for
HSP101, HSP70, WRKY70 and EIN4, transcript accumulation levels in inoculated cotyledons were up to five times
greater than in uninoculated controls (Fig. 4A). All of
these genes, except TOM2A, have been shown to be
responsive to virus infection in other hosts [72-74]. Notably, the expression of EIF4E, known to be required for
MNSV multiplication [27], remained unaltered. A shutoff
of host gene expression also occurs in association with
virus infection [75]; for the set of genes analysed here,
only GA2OX1 and NCBP responded to CMV infection
with a reduction in the accumulation of their transcripts.
The response of selected genes in roots inoculated with M.
cannonballus was analysed in melon genotypes known to
be susceptible (cultivar "Piel de sapo"; Fig. 4B) and partially resistant (accession pat81 of C. melo L. ssp. agrestis;
Fig. 4C) to the infection by this fungus. The patterns of
transcript accumulation resulted clearly different for both
genotypes. For pat81 (resistant), transcription factors
WRKY70 and SVP increased their expression between 2
and 3 times after inoculation; other stress-inducible genes
(HSP101, HSP70) showed only a moderate increase (Fig.
4C). For "Piel de sapo" (susceptible), accumulation of
WRKY70 and SVP transcripts only increased about 1.5
times after inoculation whereas the expression of HSP101
showed a marked increase (Fig. 4B). It is also worth noting the differential response of the GA2OX1 gene in the
two genotypes. Expression of GA2OX1 increased about
1.5 times in pat81 roots after the M. cannonballus attack,
whereas it decreased in "Piel de sapo" roots after fungal
infection (compare Figs. 4B and 4C).
Comparison of patterns of transcript accumulation at two
stages of fruit development showed increased levels of
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products2 of melon and Arabidopsis unigenes according to the Gene Ontology scheme for functional classification of gene
Distribution
Figure
Distribution of melon and Arabidopsis unigenes according to the Gene Ontology scheme for functional classification of gene
products.
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!!! Table 8: Potential melon miRNAs
Name
Potential mature miRNA
sequence (5'->3')*
Melogen unigene†
Precursor folding free
energy (kcal mol-1)§
MFEI
(kcal mol-1)
miRNA
family
Potential target in melon
m2
m4
m7
m8
m12
ugaagcugccagcaugaucu
ugauugagccgugccaauauc
ucggaccaggcuucauucccc
uugacagaagauagagagcac
uuggacugaagggagcucccu
bCL2353Contig1
bPSI_40-F10-M13R_c
bA_31-D02-M13R_c
bCI_04-H02-M13R_c
b15d_24-H05-M13R_c
-206.8
-195.0
-160.8
-188.2
-163.6
-0.67
-0.66
-0.70
-0.74
-0.86
miR167
miR171
miR166
miR157
miR319
-bHS_39-C12-M13R_c
-bCI_30-A09-M13R_c
bCL2243Contig1
*Nucleotide sequences correspond to potential mature miRNA sequences as deduced from BLAST searches using known plant miRNA sequences
[54] and analysis of secondary structure predictions [52]. †Accession numbers (MELOGEN database) of potential precursors of melon miRNAs are
given. §Computational values of folding free energies have been calculated using MFOLD 3.1 [55]. Minimal folding free energy indexes (MFEIs) have
been calculated as described by Zhang et al. [53].
gene expression for 9 of the analysed genes. This was particularly evident for HSP70, TOM2A, TOM3, EIN4 and
IAA9. In contrast, decreased levels of transcript accumulation were observed for the other 11 genes.
genes for experiments aimed at understanding important
processes involved in fruit development and resistance to
viral and fungal pathogens. Also, data presented here provide an important tool for generating markers to saturate
melon genetic maps.
Discussion
In this paper we provide an initial platform for functional
genomics of melon by the identification of more than
16,000 unigenes assembled from almost 30,000 ESTs
sequenced from 8 melon cDNA libraries. It is probably
premature to estimate the proportion of melon genes represented in this dataset, but based on available data for
other plant species (i.e. Arabidopsis and rice), it is likely
that the melon unigene set characterised here represents
approximately between half and one-third of the number
of expressed, protein coding genes of melon. Libraries
were constructed from various tissue types, but with a bias
towards fruit development and pathogen-infected tissues.
Data from these libraries will become a useful resource of
Potential3precursors of melon microRNAs
Figure
Potential precursors of melon microRNAs. (A) Stem
loop sequence of putative precursor miRNA corresponding
to unigene bCI_04-H02-M13R_c. (B) Stem loop sequence of
putative precursor miRNA corresponding to unigene
b15d_24-H05-M13R_c. The mature miRNA sequences are
shown in bold.
In contrast to typical EST gene-sampling strategies
reported previously, we have found a low degree of redundancy in the sequences determined. The process of clustering reduced the number of sequences to 56%, from
29,604 good quality ESTs to 6,023 contigs and 10,614 singletons. Contigs with more than 8 ESTs were scarce, the
majority of them being formed by 3 or 2 ESTs. Redundancy of the sequences derived from each library ranged
from 13% to 20%, with singletons constituting approximately one third of the unigenes determined per library.
This low redundancy is probably due to the success of the
normalization process, responsible for the suppression of
superabundant transcripts specific for a given tissue or
condition. Normalization precludes in silico analysis of
gene expression, but greatly increases the number of unigenes that can be determined by reducing redundancy
[76]. Here we have used a recently described normalization protocol which is based on the cleavage of DNA or
DNA-RNA duplexes by a specific DNase [77]; this process,
in our hands, has proven simple, reproducible and efficient. Another factor that has contributed to the low
redundancy values obtained has been the sequencing of
libraries from very distinct tissues. Thus, the number of
library specific unigenes was about one half of the total
number of unigenes contributed by each library, suggesting that further sequencing of the libraries still has the
potential to provide a good number of new, non-redundant sequences.
cDNA sequences are a useful source of SSRs, which are
excellent molecular markers due to their high degree of
polymorphism. A common feature of cDNA sequences
obtained from plants is the high frequency of SSRs that
they contain [36]. We have identified more than 1,000
potential SSRs in the melon dataset, with approximately
HIGm
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Table 9: Transcripts selected from the database for gene expression analysis by Real Time qPCR
Gene
Melogen unigene
Sequence length (bp) Arabidopsis locus Aminoacid
similarity (%)
Annotation (HMMR domain)
CTL1
CYP 7
EIF4A-2
EIF4E
EIN4
GA2OX1
HSP101
HSP70
IAA9
bCL1465Contig1
1,387
AT1G05850
66.8
bCL3337Contig1
bCL2906Contig1
bCL4710Contig1
bCL1742Contig1
bCL1313Contig1
bCI_38-F11-M13R_c
bPSI_41-D06-M13R_c
bCL1341Contig1
801
1,146
815
829
1,454
726
819
1,672
AT5G58710
AT1G54270
AT4G18040
AT3G04580
AT1G78440
AT1G74310
AT5G09590
AT5G65670
78.4
92.6
77.5
55.7
59.9
73.4
86.8
51.2
LSM1
bHS_37-F11-M13R_c
766
AT3G14080
72.4
LUT2
NCBP
SVP
bCL3563Contig1
bCL183Contig1
bCL2852Contig1
1,082
1,081
826
AT5G57030
AT5G18110
AT2G22540
75.5
85.3
54.9
Chitinase-like protein 1, similar to class I chitinase
(Glyco_hydro_19)
Peptidyl-prolyl cis-trans isomerase, cyclophilin
Eukaryotic translation initiation factor 4A-2 (DEAD)
Eukaryotic translation initiation factor 4E 1 (IF4E)
Ethylene receptor (Response_reg)
Gibberellin 2-oxidase (2OG-FeII_Oxy)
Heat shock protein 101 (AAA_2)
Heat shock protein 70/HSC70-5 (HSP70)
Auxin-responsive protein/indoleacetic acid- induced
protein 9 (AUX_IAA)
Small nuclear ribonucleoprotein/snRNP, putative/Sm
protein, putative, similar to U6 snRNA-associated
Sm-like protein
Lycopene epsilon cyclase (Lycopene_cycl)
Novel cap-binding protein (IF4E)
Short vegetative phase protein, MADS box
transcription factor related cluster (SRF-TF)
Band 7 family protein, strong similarity to
hypersensitive-induced response protein (Band_7)
Xyloglucan:xyloglucosyl transferase/xyloglucan
endotransglycosylase/endo- xyloglucan transferase/
TCH4
Tonoplast intrinsic protein (MIP)
Transmembrane protein-related/TOM1 (DUF1084)
Senescence-associated family protein
Tobamovirus multiplication protein 3/THH1
(DUF1084)
UDP-glucose 4-epimerase/UDP-galactose 4epimerase/Galactowaldenase (Epimerase)
WRKY family transcription factor, DNA-binding
protein (WRKY)
HIR
bCL144Contig1
1,266
AT1G69840
89.7
TCH4
bCL1212Contig1
1,228
AT5G57560
65.9
TIP4
TOM1
TOM2A
TOM3
bA_23-B12-M13R_c
bCL4416Contig1
bCL3115Contig1
bPSI_36-E03-M13R_c
751
780
1,113
857
AT2G25810
AT4G21790
AT1G32400
AT1G14530
50.5
75.4
60.1
UGE5
bCL1153Contig1
1,313
AT4G10960
70.9
WRKY70
bA_25-B01-M13R_c
889
AT3G56400
42.1
6% of the melon unigenes containing di-, tri- or tetranucleotide repeats. A clear bias toward AG and AAG repeats
existed, that account for 67% of the SSRs. In contrast, the
GC repeat was not found in the melon dataset. A similar
bias toward AG and against CG repeats has been identified in Arabidopsis and other plant species [40,78]. As
proposed at least in one other instance [40], this may be
due to the tendency of CpG sequences to be methylated
[79], which potentially might inhibit transcription.
Another interesting feature of melon SSRs relates to their
pattern of localization with respect to putative initiation
and termination codons. It is known that the UTRs of
transcribed sequences are richer in SSRs than coding
regions, particularly at the 5'-UTRs [36,40]. However, in
the melon dataset, a high proportion of SSRs (29.5%)
were found in ORFs. An analysis of the localization of di, tri- and tetranucleotide repeats separately showed that
di- and tetranucleotides were preferentially located in
UTRs, whereas trinucleotides localised in both, UTRs and
ORFs, consistently with maintenance of the ORFs coding
capacity. Thus, the prevalence of trinucleotide repeats in
the melon dataset (71%) explains this result.
We identified in the melon sequence dataset 356 highquality SNPs. Since non-redundant sequences analysed
here encompassed 4.5 Mb, one SNP was found every
12,000 pb of sequence. This small figure is probably due
to the limited number of melon genotypes used and the
low redundancy found among libraries. In fact, when the
frequency of SNPs is computed in relation to the length
and number of contigs containing SNPs, the corresponding value (one SNP in every 616 bp of sequence) is of the
same order of magnitude as values previously calculated
for melon (441 bp; [80]) and other plant species [40].
With the advent of high-throughput detection systems,
the SSRs and SNPs identified here will constitute an
important resource for mapping and marker-assisted
breeding in melon and closely related crops.
As an approach to the function of melon unigenes, we carried out a bioinformatics analysis based on BLASTX and
matches with the Pfam database [49]. The proportion of
melon unigenes with no similar sequences in databases
was quite high, suggesting that the melon dataset may
encompass an important number of melon-specific
HIHm
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!
!
!
!
Figure 4 analyzed by Real Time qPCR
Transcripts
Transcripts analyzed by Real Time qPCR. (A) Pattern of transcripts accumulation in CMV-infected melon cotyledons (CI)
relative to that of healthy cotyledons (CS). (B) Pattern of transcripts accumulation in M. cannonballus infected roots of C. melo
L. cv. "Piel de sapo" (PSI) relative to that of healthy roots (PS). (C) Pattern of transcripts accumulation in M. cannonballus
infected roots of C. melo L. ssp. agrestis (AI) relative to that of healthy roots (A). (D) Pattern of transcripts accumulation in
fruits of 15 days after pollination of C. melo L. cv. "Piel de sapo" (15d) relative to that of fruits of 46 days after pollination (46d).
cy: cyclophilin endogenous control; see Table 9 for the rest of genes.
HIIm
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sequences. However, the proportion specific sequences
might be overestimated because blasting has been made
with unigene sequences, which in many cases do not
cover the complete length of the transcript. We performed
a functional classification of the unigenes following the
Gene Ontology scheme, which is one of the more versatile
and complete systems for functional classification [48]. A
comparison of the distributions of melon and Arabidopsis unigenes in GO categories showed that both followed
similar tendencies, suggesting that the melon dataset is
representative of the whole melon transcriptome. This is
remarkable, as the number of different libraries
sequenced has been relatively small; again, this is probably due to the success of the normalization process. We
have also carried out specific searches for genes involved
in pathways of particular relevance in melon, such are
resistance response and fruit development, identifying a
remarkable number of melon candidates. For example, an
ortholog of the flagellin receptor FLS2 from Arabidopsis
[62] has been identified, together with 163 candidate
RLKs that may have critical roles in pathogen recognition
or diverse signalling processes. Similarly, up to 8 MADSbox gene homologs with potential roles in development
have been found in the melon dataset. Moreover, a bioinformatics approach [52,53] allowed the identification of
potential precursors of melon miRNAs together with several potential targets in the melon dataset. This finding
opens the door to biotechnology approaches based on the
use of artificial miRNAs to specifically silence melon
genes [81,82].
The transcript accumulation analysis for the 20 selected
genes revealed important changes in gene expression associated with pathogen infection and fruit development. For
virus infection, the accumulation of transcripts remained
unaltered for 12 genes, but showed a significant increase
for 6 genes and a decrease for 2. Among the set of genes
analysed, TOM2A and EIF4E were known to code for virus
susceptibility factors [27,83]; the expression of TOM2A
was increased after CMV infection, consistently with its
requirement by the virus, but this was not the case for
EIF4E. Different hypotheses can explain this result: since
EIF4E is an abundant, housekeeping protein, increased
expression may not be essential for virus multiplication;
alternatively, CMV may not use EIF4E in melon or may
use a factor coded by a different member of the 4E family;
it may also be that timing of the sampling for this experiment was not appropriate to detect such an effect, as
requirement of EIF4E might occur very early during virus
multiplication. In the cases of infection of susceptible
("Piel de sapo") and resistant (pat81) melons by M. cannonballus, more extensive alterations in gene expression
seemed to occur in the susceptible than in the resistant
accession. Significantly, for the susceptible accession,
stress responsive genes (e.g. HSP101) appeared to be max-
imally induced, whereas for the resistant accession, a gene
encoding a WRKY70 transcription factor, potentially
involved in resistance response, was induced to high levels. Significantly, expression of GA2OX1 increased about
1.5 times in pat81 after the M. cannonballus attack,
whereas it decreased in "Piel de sapo". GA2ox is a major
gibberellin (GA) catabolic enzyme, with an important
role in controlling GA levels in plants. Hormones control
many plant developmental processes, and strong evidence
indicates that hormone signalling is involved in the regulation of root growth and architecture [84,85]. The differential response of the GA2OX1 gene in the two melon
genotypes is consistent with an enhanced root growth in
pat81 after infection [86]. Notably, other genes involved
in hormone-mediated signalling pathways, such as the
IAA9 gene, did not show such differential response to M.
cannonballus infection in both genotypes. In the case of
fruit development, differences in the expression of
selected genes between immature and ripening fruits
appeared to be even sharper than in the cases of healthy
and pathogen-infected tissues. Specific roles during fruit
development for HSP70, TOM2A and TOM3 have not
been identified, though an increased expression has been
shown at least in the case of TOM2A in tomato [87]. The
ethylene receptor gene EIN4 showed a two-fold increase
in expression. EIN4 is the ortholog of Arabidopsis EIN4
and tomato LeETR4 [88,89]. In tomato, LeETR4 is also
highly expressed in ripening fruit, suggesting that it
responds by modulating ethylene signalling during ripening [63]. The MADS-box gene (SVP) showed about a fourfold decrease in expression. This gene is the ortholog of
tomato JOINTLESS, which specifies the abscission zone in
tomato. In tomato fruit microarray hybridizations, the
expression of JOINTLESS also decreased from 7 to 57 DAP
[87], in agreement with our data for melon. The lycopene
epsilon cyclase (LUT2) and xyloglucan endotransglycosylase (TCH4) genes showed an approximately four-fold
decrease in expression during melon fruit development.
These findings fit with the patterns of expression of these
genes in tomato, where their transcript levels decrease to a
non-detectable level in the ripe fruits [90,91].
Conclusion
In summary, this collection of ESTs represents a substantial increase on the information available for melon. The
dataset contains SSR and SNP markers that can be used for
breeding, as well as a significant number of candidate
genes that can be experimentally tested for their roles in
various important processes. This set of genes constitutes
also the basis for a microarray for melon that is being used
in experiments to further analyse fruit development and
maturation and responses to pathogen infections.
HIJm
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Methods
Plant material
The cDNA libraries were prepared using material from
four different melon genotypes: the line T-111 (Semillas
Fitó, Barcelona, Spain), which corresponds to a Piel de
Sapo breeding line, the Piel de Sapo cultivar "Piñonet torpedo" (Semillas Batlle, Barcelona, Spain), the accession C35 of the germplasm collection of La Mayora-CSIC
(EELM-CSIC, Málaga, Spain), which corresponds to a cantaloupe-type of melon, and the accession pat81 of C. melo
L. ssp. agrestis (Naud.) Pangalo maintained at the germplasm bank of COMAV (COMAV-UPV, Valencia, Spain)
(Table 1). Seeds of line T-111 were germinated at 30°C for
two days and plants were grown in a greenhouse in peat
bags, drip irrigated, with 0.25-m spacing between plants.
Fruits of 15 and 46 days after pollination were collected
and mesocarp tissues were recovered and used for RNA
extractions. Root samples were from Piel de sapo and
pat81 plants, both healthy and inoculated with M. cannonballus. Piel de sapo is fully susceptible to the infection
by this fungus whereas pat81 has been shown to be partially resistant [92,93]. Seeds were pre-germinated in Petri
dishes. After 4 days, seedlings were transplanted to 0.5-l
pots filled with sterile soil substrate and grown in a greenhouse (20–35°C, 60–85% relative humidity). Inoculations were carried out by adding 50 colony-forming units
(CFU) of M. cannonballus per gram of sterile soil as
described by Iglesias et al. [94]. Fourteen days after inoculation, healthy and inoculated roots were collected for
RNA extraction. The presence of the fungus and the infection levels were assessed by real-time quantitative PCR as
described by Picó et al. [95]. CMV infected cotyledons
were collected from plants of the C-35 accession. In this
case, seeds were pregerminated in Petri dishes for 24 h at
28°C in the dark, planted in 0.5-l pots and maintained in
an insect-proof green house (20–28°C, 45 to 85% relative
humidity) for 6 to 7 days, until the first true leaf started
emerging. At this stage, cotyledons were mechanically
inoculated with CMV following standard procedures [96].
Inoculated cotyledons were harvested 4 days after inoculation and used for RNA extractions. Dot-blot hybridisation [97] was used to check infection by CMV. Plants of
the C-35 accession were also used for collecting healthy
leaves. Plants were maintained in the greenhouse for 21
days, and second and third leaves above cotyledons were
harvested for RNA extractions.
Construction of cDNA libraries and EST sequencing
Total RNA was prepared as described by Aranda et al. [98].
Poly(A+) RNA from total RNA was purified using MicroPoly(A+) Purist (Ambion, Austin, TX, USA), a celluloseoligo(dT)-based method. Integrity and quality of both
total and poly(A+) RNA were tested by gel electrophoresis.
cDNA libraries were constructed with the SMART cDNA
Library Construction kit (Clontech, Mountain View, CA,
USA), using a modified primer to include a Sfi I enzyme
restriction site. A normalization step was carried out with
TRIMMER kit (Evrogen, Moscow, Russia). After normalization, a cDNA fractionation step was performed with SizeSep 400 Spun Columns (Amersham Biosciences,
Buckinghamshire, England). cDNA was digested with Sfi
I, generating Sfi IA-Sfi IB cohesive ends for directional
cloning into a modified version of BlueScript SK plasmid
vector (Stratagene, La Jolla, CA, USA). Ligation products
were transformed into E. coli electrocompetent cells
DH10B (Invitrogen, Carlsbad, CA, USA) by electroporation. The titer of the libraries was evaluated by plating an
aliquot on LB agar plates with ampicillin at 100 g ml-1.
Only libraries of 105 cfu ml-1 or more were considered as
acceptable. Prior to large scale sequencing, the average
insert size was estimated by restriction analyses of 24 plasmid DNA minipreps per library from randomly picked
colonies.
Sequencing was carried out from the 5'-end of the inserts
without library amplification using the universal M13
reverse primer. An external custom service was contracted
for this task (Macrogen Inc., Seoul, Korea). Approximately
6,000 clones were sequenced from the CI library, and
3,500 clones were sequenced from each of the other
libraries (Table 2). Sequences obtained in this work can be
found in GenBank [accession numbers AM713476 to
AM743079] and MELOGEN [44].
Bioinformatics
EST sequences were automatically trimmed, clustered and
annotated using the EST2uni analysis pipeline [43].
EST2uni compromises the analysis pipeline written in
PERL [99], a database (MySQL) [100] and a web site to
browse the results coded in PHP [101]. Thus, for the EST
pre-processing step, base calling was performed with
Phred [102], low quality regions and vector sequences
were trimmed with Lucy [103], and repeats and low complexity regions were masked with RepeatMasker [104] and
Seqclean [105]. Further vector contamination was also
eliminated with Seqclean using NCBI's UniVec [106].
High-quality EST sequences were then assembled to
obtain the unigene set using Tgicl [105].
Detection of SSRs was performed using Sputnik [107].
Putative SNPs were annotated when the least represented
allele was present in two EST sequences or more. ORFs
were predicted in the ESTs with the aid of the ESTScan
software [108].
For functional annotation, comparisons against the Arabidopsis (TAIR) [109] and Uniref [110] databases were carried out using BLASTN or BLASTX for nucleotide or
protein sequences, respectively. Functional domains were
searched with HMMPFAM [111] using the Pfam database
HIKm
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[112]. The Gene Ontology (GO) classification [48] was
derived from the BLASTN results against the Arabidopsis
proteome. Also, a bi-directional BLASTN comparison was
performed in order to obtain a set of putative orthologs
with Arabidopsis. Finally, a set of superunigenes was
obtained grouping different unigenes with the same
expected mRNA target, as judged by extensive sequence
overlapping.
To assess codon usage, we generated a set of melon
sequences predicted to contain full-length coding regions.
These sequences were subjected to BLASTX and, after
manual inspection, sequences showing a high similarity
to Arabidopsis proteins were selected to ensure that no
sequences containing frame-shift errors were included in
the analysis. From this smaller dataset, which included
588 sequences, ORFs were defined and a codon usage
table was created. Codon usage was calculated from
sequences using the GCUA program [113]. All codons
were found in the dataset, with the least frequent codon
represented 134 times.
To identify potential melon miRNAs, the 33,292 melon
ESTs were subjected to a BLAST search against mature
sequences of known miRNAs from the miRNA Registry
Database (released January 2007) [54] using BLASTN
[47]. ESTs with only 0–1 mismatched nucleotides with
known miRNAs were considered. Selected ESTs were subjected to a BLAST search against protein databases in order
to remove potential protein-coding sequences. ESTs pertaining to the same melon unigene of the MELOGEN
database were grouped. The secondary structures of the
unigenes encoding potential miRNA precursors were predicted with the web-based tool MFOLD [55], using
default parameters. In each case, only the lower energy
structure was selected for visual inspection, as previously
described [52,114]. In order to select unigenes with perfect or near-perfect secondary foldback hairpin structures,
only sequences with a maximum size of 3 nucleotides for
a bulge in the miRNA sequence and with at least 16 paired
nucleotides between the mature sequence and the opposite arm were considered as potential miRNA candidates.
In addition, the minimal folding free energy index (MFEI)
for each sequence was calculated following Zhang et al.
[53].
Gene expression analyses
Real time quantitative PCR was performed with an AB
7500 System (Applied Biosystems, Foster City, CA, U.S.A)
to quantify mRNA corresponding to some transcripts of
interest, in the tissues and physiological conditions used
for library construction. Twenty ESTs representing these
transcripts were chosen from the database and used to
generate gene-specific primers (Table 10) with Primer
Express Software (Applied Biosystems). The chemistry
used for PCR product detection was the Power SYBR green
dye (Applied Biosystems) and ROX as passive reference.
CYCLOPHILIN served as endogenous control (sequence
extracted from the database), Ct was the method of calculation to perform relative quantification, and three
technical replicates were carried out and considered for
statistical analysis. Melting curves analyses at the end of
Table 10: Primer sequences for Real Time-qPCR analysis of transcript accumulation
Gene
Primer sequence (5'->3') Forward
Reverse
CTL1
CYP 7
EIF4A-2
EIF4E
EIN4
GA2OX1
HSP101
HSP70
IAA9
LSM1
LUT2
NCBP
SVP
HIR
TCH4
TIP4
TOM1
TOM2A
TOM3
UGE5
WRKY70
tgggccatgttggctctaag
cgatgtggaaattgacggaa
ttcccgaggtttcaaagatca
ttcggttccttcccttccat
tgcaacgtgactgctgtttct
tagggcaaatcggttagcga
aacgtatggtgcggattgaca
gctgaggcgtaccttggaaa
gacggaaagccaggttcaag
ctacttcgagatgggcggaa
gctggcgtggaacactcttt
cgtcggtctgcttaatttgca
cgaggcaggtcacgttctct
tgacgggctcagagacagtg
ggagggtagccttgagggaat
tccttgctggtgtcggatc
gggagaaggaagaaacttcatgag
ctcctcagcagccgaagaaa
aatggagttcgggctgttgt
gcgaaagtgtccaaaagcca
ggattgctcctggcctgac
ctcccgtgacaactccatca
cggtgcataatgctcggaa
ccaatgcttctggtggcact
ccgccgatgtagctttcatc
tctggcatgtgaagatccaaga
ccaaatgcaaaccgattgaa
tccaccttcatggtatccaacat
atcctgccagcatcctttgt
cccctccatactcactttcacaa
tcaccaacgatcaccctttca
cgaatgccttcaatgtccagt
cgcctacgaactccattgaca
agagaagacgaggagcgcaa
gttccagggacgttttcagc
ctggacattgctcgacaacaa
cgtttgccaataacgcattg
gcgtcaaaagcggataaagc
tggacccgctaaaacaccac
aaggcaaggcttggcatgt
acacaagctttttgcatccgt
tcggctgcttttcttcgatc
HILm
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the process and No Template Controls (NTC) were carried
out to ensure product-specific amplification and no
primer-dimer quantification. A control reaction as for
reverse transcription but without the enzyme was performed to evaluate genomic DNA contamination.
!!! 4.
5.
6.
Authors' contributions
Daniel Gonzalez-Ibeas prepared RNAs for two libraries,
constructed the eight libraries, carried out the gene expression analysis by Real-Time-qPCR and participated in the
bioinformatics analyses and in the drafting of the manuscript. José Blanca carried out the bioinformatics analyses,
EST database and web page, and participated in the drafting of the manuscript. Cristina Roig and Belén Picó prepared RNAs for the root libraries and participated in the
drafting of the manuscript. Mireia González-To, Wim
Deleu and Jordi Garcia-Mas prepared RNAs from melon
fruits and participated in the drafting of the manuscript.
Pere Puigdomènech is the main coordinator of The MELOGEN Project and participated in the conception of the
study together with Pere Arús, Fernando Nuez, Jordi Garcia-Mas and Miguel A. Aranda. Miguel A. Aranda is the
principal investigator or this work, supervised it and wrote
the manuscript. All authors read and approved the final
manuscript.
Additional material
7.
8.
9.
10.
11.
12.
13.
14.
Additional file 1
Genes potentially encoding pathogen resistance and fruit quality traits.
Genes were identified in the melon data set by comparison with the Arabidopsis database [6,109]. A brief description, the corresponding Arabidopsis locus and the HMMR domain identified are given for each
unigene.
Click here for file
[http://www.biomedcentral.com/content/supplementary/14712164-8-306-S1.pdf]
15.
16.
17.
18.
19.
Acknowledgements
This work was supported by grants from Ministerio de Educación y Ciencia
(Spain) (GEN2003-20237-C06) and Consejería de Educación y Cultura
(Región de Murcia, Spain) (BIO2005/04-6436). Wim Deleu, Cristina Roig
and Daniel Gonzalez-Ibeas are recipient of a postdoctoral fellowship from
the Centre de Recerca en Agrigenòmica CSIC-IRTA (Spain), a Juan de la
Cierva grant from Ministerio de Educación y Ciencia (Spain) and a predoctoral fellowship from Ministerio de Educación y Ciencia (Spain), respectively.
20.
21.
22.
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BMC Plant Biology
BioMed Central
Open Access
Research article
A set of EST-SNPs for map saturation and cultivar identification in
melon
Wim Deleu†1, Cristina Esteras†2, Cristina Roig2, Mireia González-To1,
Iria Fernández-Silva1, Daniel Gonzalez-Ibeas3, José Blanca2,
Miguel A Aranda3, Pere Arús1, Fernando Nuez2, Antonio J Monforte1,4,
Maria Belén Picó2 and Jordi Garcia-Mas*1
Address: 1IRTA, Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB, Carretera de Cabrils Km 2, 08348 Cabrils (Barcelona), Spain, 2COMAV-UPV,
Institute for the Conservation and Breeding of Agricultural Biodiversity, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022 Valencia,
Spain, 3Departamento de Biología del Estrés y Patología Vegetal, Centro de Edafología y Biología Aplicada del Segura (CEBAS)- CSIC, Apdo.
correos 164, 30100 Espinardo (Murcia), Spain and 4Instituto de Biología Molecular y Celular de Plantas (IBMCP) UPV-CSIC, Ciudad Politécnica
de la Innovación Edificio 8E, Ingeniero Fausto Elio s/n, 46022 Valencia, Spain
Email: Wim Deleu - [email protected]; Cristina Esteras - [email protected]; Cristina Roig - [email protected]; Mireia GonzálezTo - [email protected]; Iria Fernández-Silva - [email protected]; Daniel Gonzalez-Ibeas - [email protected];
José Blanca - [email protected]; Miguel A Aranda - [email protected]; Pere Arús - [email protected]; Fernando Nuez - [email protected];
Antonio J Monforte - [email protected]; Maria Belén Picó - [email protected]; Jordi Garcia-Mas* - [email protected]
* Corresponding author †Equal contributors
Published: 15 July 2009
BMC Plant Biology 2009, 9:90
doi:10.1186/1471-2229-9-90
Received: 31 March 2009
Accepted: 15 July 2009
This article is available from: http://www.biomedcentral.com/1471-2229/9/90
© 2009 Deleu et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: There are few genomic tools available in melon (Cucumis melo L.), a member of the Cucurbitaceae, despite
its importance as a crop. Among these tools, genetic maps have been constructed mainly using marker types such as
simple sequence repeats (SSR), restriction fragment length polymorphisms (RFLP) and amplified fragment length
polymorphisms (AFLP) in different mapping populations. There is a growing need for saturating the genetic map with
single nucleotide polymorphisms (SNP), more amenable for high throughput analysis, especially if these markers are
located in gene coding regions, to provide functional markers. Expressed sequence tags (ESTs) from melon are available
in public databases, and resequencing ESTs or validating SNPs detected in silico are excellent ways to discover SNPs.
Results: EST-based SNPs were discovered after resequencing ESTs between the parental lines of the PI 161375 (SC) ×
'Piel de sapo' (PS) genetic map or using in silico SNP information from EST databases. In total 200 EST-based SNPs were
mapped in the melon genetic map using a bin-mapping strategy, increasing the map density to 2.35 cM/marker. A subset
of 45 SNPs was used to study variation in a panel of 48 melon accessions covering a wide range of the genetic diversity
of the species. SNP analysis correctly reflected the genetic relationships compared with other marker systems, being able
to distinguish all the accessions and cultivars.
Conclusion: This is the first example of a genetic map in a cucurbit species that includes a major set of SNP markers
discovered using ESTs. The PI 161375 × 'Piel de sapo' melon genetic map has around 700 markers, of which more than
500 are gene-based markers (SNP, RFLP and SSR). This genetic map will be a central tool for the construction of the
melon physical map, the step prior to sequencing the complete genome. Using the set of SNP markers, it was possible
to define the genetic relationships within a collection of forty-eight melon accessions as efficiently as with SSR markers,
and these markers may also be useful for cultivar identification in Occidental melon varieties.
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BMC Plant Biology 2009, 9:90
Background
Single-nucleotide polymorphisms (SNPs) are the most
frequent type of variation found in DNA [1] and are valuable markers for high-throughput genetic mapping,
genetic variation studies and association mapping in crop
plants. Several methods have been described for SNP discovery [2]: SNP mining from expressed sequence tag (EST)
databases [3]; based on array hybridization [4] or amplicon resequencing [5]; from the complete sequence of a
genome [6] and more recently, using high-throughput
sequencing technologies [7]. The discovery of SNP markers based on transcribed regions has become a common
application in plants because of the large number of ESTs
available in databases, and EST-SNPs have been successfully mined from EST databases in non-model species
such as Atlantic salmon [8], catfish [9], tomato [10] and
white spruce [11].
Melon (Cucumis melo L.) is an important crop worldwide.
It belongs to the Cucurbitaceae family, which also includes
cucumber, watermelon, pumpkin and squash. The melon
genome has an estimated size of 450 Mb [12] and is a diploid with a basic chromosome number of x = 12. In recent
years research has been carried out to increase the genetic
and genomic resources for this species, such as the
sequencing of ESTs [13], the construction of a BAC library
[14], the development of an oligo-based microarray [15]
and the development of a collection of near isogenic lines
(NILs) [16]. Genetic maps have also been reported for
melon, but they have been constructed with different
types of molecular markers and genetic backgrounds [1721], making it difficult to transfer markers from one map
to another. The aim of the International Cucurbit Genomics Initiative (ICuGI) [22], currently in progress, is to
obtain a consensus genetic map by merging genetic maps
available using a common set of SSRs as anchor markers.
A double haploid line (DHL) population from the cross
between the Korean accession PI 161375 (SC) and the inodorus type 'Piel de sapo' T111 (PS) was the basis for the
construction of a genetic map with 221 co-dominant,
transferable RFLP and SSR markers [21]. New EST-derived
SSR markers, added to this map using a bin-mapping
strategy with only 14 mapping individuals, gave a new
map with 296 markers distributed in 122 bins and a density of 4.2 cM/marker [21]. There is a need for saturating
the SC × PS genetic map with more markers that are amenable for large-scale genotyping, as are SNPs. In a preliminary experiment with melon, amplicon resequencing of
34 ESTs in SC and PS was used for SNP discovery, obtaining a frequency of one SNP every 441 bp and one indel
every 1,666 bp [23]. The availability of more than 34,000
melon ESTs from normalized cDNA libraries from different melon genotypes and tissues [13] is a valuable
resource for the identification of SNPs to be added to the
current genetic map.
http://www.biomedcentral.com/1471-2229/9/90
Genetic markers can also be used for variability analysis
studies. In melon, there have been several attempts to elucidate intraspecific relationships among melon germplasm, using isozyme [24], RFLP [25], RAPD [26], AFLP
[27] and SSR [28] markers, with SSRs the preferred marker
for fingerprinting and genetic variability analysis in melon
[28]. Due to the absence of a known set of SNPs in the
species, this marker has not been compared with other
types for variability analysis. It would be of special interest
to have a set of these markers for a high-throughput system to identify the germplasm used in breeding programs,
mainly from inodorus and the cantalupensis melon types.
The objectives of this work were to increase the marker
resolution in the melon genetic map, discovering ESTSNPs in a melon EST database, and to study the performance of a subset of EST-SNPs for variability analysis in a
collection of melon accessions.
Results and discussion
SNP discovery
Two strategies were used to discover SNPs in melon. The
first was based on producing amplicons from randomly
selected melon ESTs and resequencing the parental lines
of the melon genetic map PI 161375 (SC) × 'Piel de sapo'
T111 (PS). Primers were designed from 223 melon ESTs
(Table 1). After discarding primers that did not amplify a
PCR product, amplicons that did not produce high quality
sequences and monomorphic amplicons, 93 ESTs
(56.3%) showed at least one polymorphism between SC
and PS.
The second strategy was the validation of in silico SNPs
from the ICuGI database [22]. Three hundred and sixty-six
in silico SNPs found in the database were selected, belonging to two types of SNPs: pSNP and pSCH (Table 1; see
methods). Primers were designed from 269 ESTs containing pSNP and 97 containing pSCHs. Putative in silico SNPs
were validated in 51.8% and 21.3% of the amplicons for
pSNPs and pSCHs, respectively. In some instances additional SNPs were detected in the sequenced regions, giving a slightly higher percentage of polymorphic
amplicons (69.7% and 31.3% for pSNP and pSCH amplicons, respectively). From the ESTs reported by GonzalezIbeas et al. [13], 47.3% were obtained from two accessions of the 'Piel de sapo' cultivar type (Pinyonet and PS),
and the remainder from two genotypes, the C-35 cantaloupe accession (29.3%) and the pat81 agrestis accession
(23.4%). The pSNPs and pSCHs were deduced from this
set of EST sequences, with a high proportion found
between pat81 and 'Piel de sapo', and SNPs experimentally validated after resequencing amplicons from PS and
SC. SC belongs to the agrestis melon type as the accession
pat81 but has a different origin, so, as expected not all the
SNPs were conserved between SC and PS, giving a pSNP
validation of 51.8%. On the other hand, only 21.3% of
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Table 1: Amplicons designed from ESTs for SNP discovery
Amplicons
Failed
Monomorphic
Polymorphic
Polymorphic amplicons*
In silico SNP validation
Random ESTs
223
58
72
93
56.3%
in silico pSNPs
269
41
69
159
69.7%
51.8%
in silico pSCHs
97
14
57
26
31.3%
21.3%
TOTAL
589
113
198
278
58.4%
ESTs were selected at random or chosen because they contained pSNPs or pSCHs in the MELOGEN database. Columns show the number of
amplicons that failed to amplify or gave bad quality sequences, and monomorphic and polymorphic amplicons between SC and PS. The percentages
of polymorphic amplicons and in silico SNPs that were validated are shown in the last two columns. (*) Polymorphic amplicons rate was calculated
without considering failed amplicons.
the pSCHs were validated, indicating that many may represent sequencing errors or mutations introduced during
the cDNA synthesis procedure. The SNPs in a subset of
amplicons containing in silico SNPs between 'Piel de Sapo'
and pat81 were validated using different genotyping
methods (see below) rather than resequencing in PS and
SC.
A total of 368 amplicons (random and containing in silico
SNPs) were resequenced in PS and SC and produced
177.5 kb of melon DNA, with 431 SNPs and 59 short
indels, at an average of one SNP every 412 bp and one
indel every 3.0 kb, (Table 2). This is in agreement with the
values obtained in a previous small-scale experiment
using the same two melon accessions, which gave one
SNP every 441 bp and one indel every 1.6 kb [23]. SC and
PS belong to the agrestis (C. melo ssp. agrestis) and inodorus
(C. melo ssp. melo) melon groups, respectively, which are
two of the more distant groups in the species [28]. This
may explain the relatively high frequency of SNPs
between the cultivars.
SNP detection
Various detection methods were used for genotyping the
SNPs in each EST. A restriction site around the SNP position, different in the parental sequences, was used to
develop a CAPS marker for 103 EST-SNPs. When more
than one SNP was discovered in one amplicon, we
selected the most suitable SNP for detection using CAPS.
When no restriction enzyme was available to produce a
CAPS marker, we used the SNaPshot SNP detection system. Seventy-seven EST-SNPs were genotyped with SNaP-
shot. For 14 ESTs, PS and SC gave a different amplicon
size, so they could be genotyped as SCAR markers. Four
EST-SNPs were genotyped using DNA sequencing and two
were converted into dCAPS. The SNP detection method
used for each mapped EST-SNP is shown in Additional file
1.
SNP variability
Forty-five SNPs (see Additional file 2) were randomly chosen to study their variability in a set of melon accessions
of worldwide cultivar and botanical types (see Additional
File 3). The inodorus cultivars were overrepresented in
order to assess whether SNPs between distant melon
accessions (SC and PS) were also variable among more
closely related genotypes.
All SNPs were polymorphic and the mean major allele frequency was 0.69 (Table 3). Only one SNP (AI_24-H05)
had a rare allele (frequency = 0.08), whereas the frequencies of the two alleles were similar in 28 SNPs (major
allele frequency < 0.65). Average gene diversity (He) was
0.4 (ranging from 0.14 to 0.5). Forty-three SNPs yielded
He > 0.20, demonstrating that most of the chosen SNPs
were highly informative, as found for SNPs in rye [29] but
contrasting with crops such as soybean [30] and wheat
[31] where SNPs yielding rare alleles are more frequent.
The mean gene diversity index for SNPs was considerably
lower than the values reported for SSRs in melon (e.g. PIC
= 0.58 [21], He = 0.66 [28]). To ensure the difference was
not due to sampling, gene diversity indexes were estimated using a subset of genotypes that had been included
Table 2: Frequency of SNPs and indels found after resequencing EST-derived amplicons
Amplicons sequenced in SC and PS
Length sequenced (bp)
SNPs
bp per SNP
indels
bp per indel
Reference
368
177,518
431
411.9
59
3,008.8
this report
34
15,000
34
441.2
9
1,666.6
[23]
Data from a previous report using the same two melon parental lines is shown as a comparison.
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Table 3: Gene diversity indexes for SNP and SSR alleles using all, inodorus or genotypes described in a previous study [28]
Genotypes
Marker type
Major allele frequency
Ho
He
He range
all
SNP
0.69
0.10
0.40
0.14–0.50
inodorus
SNP
0.85*
0.07
0.15
0–0.50
group used in [28]
SNP
0.63
0.09
0.47
0.16–0.50
group used in [28]
SSR
0.47
0.14
0.64
0.51–0.83
Ho, observed heterozygosity; He expected heterozygosity. * Major allele frequency was only calculated for polymorphic SNPs.
in a previous study with SSRs [28] (see Additional file 3).
The differences in gene diversity were confirmed, demonstrating that they were intrinsic to the different marker
type. SNPs are biallelic, implying that the He value can
not exceed 0.5, whereas SSRs are multiallelic and so it can
be higher. Haplotypes may yield higher gene diversity values than individual SNPs and provide more efficient
application of SNP markers [29].
All inodorus genotypes could be distinguished with the set
of SNPs, although polymorphism was notably reduced
(Table 3). Fourteen SNPs were monomorphic and 18 were
informative (minor allele frequency > 0.1). As most of the
SNPs were discovered between the agrestis and inodorus
cultivar and not within inodorus, we expected the SNP polymorphism within inodorus to be lower. Nevertheless,
these results demonstrate that SNPs discovered using a
germplasm sample can be successfully transferred to different germplasm samples in melon.
The genetic relationships among accessions based on SNP
polymorphism were investigated by cluster analysis. The
NJ dendrogram (Figure 1) fits very well with previous classifications using different markers [26,28,32]. Comparing
the common genotype set in [28], the average pair-wise
distances based on SNPs and SSR were 0.47 and 0.64,
respectively. The correlation between the two distance
matrices was 0.73 (P < 0.00001) according to Mantel's
test, confirming that the current SNP set is as effective as
SSRs in establishing genetic relationships among melon
accessions, as shown in species such as rye [29] and soybean [30].
The population structure was estimated using the STRUCTURE software [33]. The a posteriori probability of the data
increased rapidly from K = 1 to 4 and begun to reach a plateau for K = 5, inferring that our collection can be divided
in five populations. Genetic variability among melon
germplasm seems to be highly structured. The subdivision
of the accessions in 5 populations agrees with the botanical classification and the cluster analysis (Figure 1): group
1 included all the inodorus cultivars from Spain; group 2, a
diverse group of traditional inodorus landraces and similar
ones from the Near-East region such as elongated (chate
and flexuosus) and Asiatic ananas and chandalak types;
group 3, modern cantalupensis cultivars; group 4, mainly
traditional varieties and wild melons from India and
Africa and group 5 included conomon accessions from the
Far East. The population structure should be taken into
account when establishing a collection of genotypes for
association mapping studies in melon and models including population structure should be used [34]. Alternatively, melon collections without structure, as we found
with the inodorus melon accessions included in our studies, could be used.
These results demonstrate that SNPs discovered using a
small germplasm sample can be transferred to different
cultivar groups, being useful for depicting genetic relationships as well as for cultivar identification.
SNP mapping using a bin-mapping strategy
Two hundred and seventy-eight SNP-containing ESTs
(Table 1) plus twelve additional SNP-containing ESTs previously discovered between the two parental lines [22]
were used for mapping in the SC × PS genetic map using
14 DHLs of the melon bin-mapping population [21]. In
total, 199 EST-derived SNPs were mapped, yielding 200
new markers (Figures 2 and 3). F112 produced two SCAR
markers (F112a and F112b) that mapped to groups I and
V, respectively. Our previous melon bin-map contained
296 markers distributed in 122 bins, with a density of 4.2
cM/marker and 2.4 markers per bin [21]. With the addition of 35 candidate genes previously reported for resistance to virus and fruit ripening [23,35,36] and the SNPs
now described, the new bin-map contains 528 markers,
distributed in 145 bins, with an increased density of 2.35
cM/marker and 3.64 markers per bin. The SNP-based
markers defined 23 new bins with an average bin length
of 8.55 cM. Some of the new bins were located in regions
with poor marker density in the previous SC × PS melon
map [21], such as HS_30-B08 in group XI, AI_12-B08 in
group VII, A_38-F04 in group VI or P06.05 in group III.
Essentially the new version of the melon bin-map is a
gene-based map, with 412 markers (78%) obtained from
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K=5
SC
HER
GIN
PAT
FREE
CHT
TRI
KAK
SEN5
MOM
ZA1
ANN
INB
YC
CAR
DUL
C35
VED
VER
DOU
JPN
FLEX
ALF
KIZ
CHAN
EIN
AYN
KRK
CHA
ERI
ACD
VLV
VVG
AMD
BBL
VHC
TNI
AMC
ACA
BBE
HND
RMO
VCU
T111
AMA
PSPO
PPS
VVT
0.05
Figure
Dendogram
of
45 SNPs
1 inand
48population
melon accessions
structure based on the variability
Dendogram and population structure based on the
variability of 45 SNPs in 48 melon accessions. The
neighbor-joining (NJ) tree based on Nei genetic distances
[44] for the selected melon accessions is shown on the right.
The subdivision based on STRUCTURE is shown on the left;
each accession on the NJ is colored according to its group
assignation defined from STRUCTURE analysis.
gene sequences. Additionally, 114 RFLPs derived from
ESTs were previously mapped in an F2 population from
the cross SC × PS [37], and their approximate position can
also be plotted in the corresponding bin-map. As a large
proportion of the markers are codominant and based on
gene sequences, this makes this map a very useful tool for
melon breeding and comparative analysis in cucurbit species.
With the advent of next generation sequencing technologies, SNP discovery has become more feasible in nonmodel crop species, allowing the discovery of thousands
of SNPs in a single experiment [7]. In Eucalyptus grandis
more than 23,000 SNPs were discovered using 454
sequencing technology, with a validation rate of 83%
[38]. In melon, a preliminary analysis of 100,000 reads
obtained after 454 sequencing of leaf cDNAs from SC and
PS produced more than 1,000 SNPs (Garcia-Mas, unpublished). This indicates that the use of next generation
sequencing technologies is the next step towards saturation of the melon genetic map.
Conclusion
The set of 200 SNP markers discovered and mapped have
increased the marker resolution of the melon genetic map
by defining new bins. The genetic map contains more
than 500 gene-based codominant markers (SNPs, RFLPs
and SSRs), which can be used as anchor points with other
genetic maps in this species. This genetic map is also a useful resource for comparative mapping in the Cucurbitaceae, for the construction of the melon physical map and
for sequencing the melon genome. Additionally, the set of
SNPs has proven to be as useful as microsatellites for studying genetic relationships in melon and for varietal identification.
Methods
Plant material and DNA extraction
The parent lines of the melon double haploid line (DHL)
mapping population, PI 161375 'Songwan Charmi' (SC)
and 'Piel de sapo' line T111 (PS), were used for SNP discovery [20]. Fourteen DHLs from the SC × PS segregating
population were used to bin-map the SNP set [21]. The 48
melon genotypes selected for analysis with a subset of
SNPs (see Additional file 3) were obtained from the germplasm collection maintained at COMAV (Valencia, Spain)
and from a previous study of germplasm variability using
SSRs [28]. DNA from all genotypes was extracted using a
modified CTAB method [27]. DNA of the forty-eight
melon accessions was extracted from leaves of five individuals per accession to take into account the genetic variability within heterogeneous accessions.
SNP discovery and detection
SNPs were discovered using two different strategies.
Firstly, random ESTs were selected from the International
Cucurbit Genomics Initiative (ICuGI) webpage [22].
Primer pairs were designed from each EST using the
Primer3 software [39] with an average length of 20 nucleotides, a melting temperature around 60°C and an
expected PCR product of 500–700 bp. Genomic DNA
from the parental lines of the melon mapping population
was amplified with each primer pair as previously
described [23]. Amplified fragments were purified with
Sepharose columns and sequenced using the ABI Prism
BigDye Terminator Cycle Sequencing kit (Applied Biosystems, Foster City, CA, USA) in an ABI Prism 3130
sequencer (Applied Biosystems, Foster City, CA, USA).
Sequences were aligned and screened for polymorphism
with the Bioedit software [40]. Putative SNP positions
were visually verified on the sequence chromatogram, and
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I
0.0
II
MC216 CmPABP
0.0
ECM61
MC51 CmEIL1
FR13B20
32.0
78.0
MG1 CMCTN86
CMGAN92 CM101A
47.0
CMCT505 CMCCA145
MC309 ECM233
ECM58 ECM139 CmPG4 52.0
AI_34-A07 PSI_04-D07
AI_09-G08 AI_17-E07
PSI_07-A04 F112a P01.16
ECM199
65.0
ECM173 PSI_35-C01
CMCTN53 ECM60b
ECM60c TJ26
FR10P24 PSI_12-D08
AI_09-D03
CSWCT11
FR12I13
TJ27
ECM110 CmERS1
F116
AI_05-G01
20.0
24.0
PS_10-C09 AI_14-H05
P12.74 P05.79 P01.41
CmeIF(iso)4G-1 CmEIL3
CM24 CMAGN68 CMGA108
PSI_03-B09 GCM331
PS_02-H06 A_25-G05
CmXTH2
MC273 ECM223
AI_04-E05
GCM548
57.0
MC332
MC248
AI_14-E02
70.0
75.0
78.0
80.0
IV
AI_24-G04 HS_10-A02
AI_14-B01 P12.96
GCM190 MC127
0.0
CSWCT10
AI_18-E05
CmEIL4 CmEXP2
TJ12b CMTAN66a CMBR83
TJ30 TJ31 MC244 GCM106
14.0
CM11 CMGA128 CMBR95
AI_08-F10 A_21-C11
CSWCT16T CMBR105 MC54
CMTA170A CMBR100
25.0
AI_33-H11
P06.15 46d_37-H067
33.0
0.0
MG34A
P12.50
57.0
CMGAN94 GCM186
MC69
ECM181
MC233
20.0
25.0
MC220
ECM60a AI_06-G01
AI_14-F04
ECM205 MC365
ECM125 MC215 F028
TJ10 PS_14-A11
AI_33-E02 PS_08-G08
AI_37-A07
70.0
72.0
PSI_27-C02 CmeIF4A-3
56.0
58.0
60.0
64.0
72.0
MC211 CM131 CmeIF4A-2
81.0
90.0
91.0
95.0
CM47
CMBR89
MC344
46d_11-A08
TJ12a GCM246
AI_03-F03 AI_03-E11
98.0
108.0
MC284 CMBR35 CMAGN79
ECM53 CMAGN73 ECM185
ECM106 CM122 ECM198 86.0
ECM122 GCM336
CI_35-H04 AI_10-B10
P12.94 CmnCBP P01.11 93.0
MC219
97.0
CMTCN6
ECM134
A_23-C03
108.0
CMTC168
MC60
FR12J11
123.0
127.0
CT02B CMCTN50
PSI_28-E12
AI_37-E06
ECM137
AI_09-E07
AI_17-B12
MC294
MC212
GCM168
ECM191
ECM138
AI_11-E06
P05.27
A_03-H09
137.0
VI
PSI_10-B04
CSCCT571
ECM108
ECM97 CmXTH4
PS_34-C02 A_31-E10
PS_25-E09
40.0
MC296
ECM208
CMCTN5
ECM51 CmACS5
MC252
V
12.0
CMTCN66b GCM448
CMTCN18 MC226
AI_02-C08 CmETR2
ECM184
GCM262
26.0
CMAGN61
CMAGN52
34.0
ECM197 ECM124
PSI_20-A04
GCM101
MC376
86.0
104.0
0.0
9.0
10.0
MC134
ECM85
63.0
MC340 PS_09-H05
F216 SSH1A13
MC279
AI_09-F07
18.0
41.0
III
CM149
ECM230
12.0
http://www.biomedcentral.com/1471-2229/9/90
116.0
41.0
A_18-A08
15d_17-G01
CMATN101
TJ37 CMTCN9
50.0
CMCTN35
CMAT35
HS_11-A09 15d_14-B01
AI_08-G09 P02.22
CI_19-H12 SSH9G15
ECM129 ECM92 MC256
CmeIF(iso)4E
ECM142 CMGAN3 MC4 70.0
ECM203 GCM622 CmETR1
ECM109 GCM295 CmeIF4G
PS_15-B02 PS_03-B08
MC8 ECM52
FR11A2
MC21 GCM303 GCM255
ECM81 GCM302 ECM135
CMTCN41 CMCT123
CI_56-B01 FR14P22
AI_19-F11 PS_19-B07
AI_03-B03 15d_29-E06
MC224 AI_05-H08
HS_20-C04 HS_05-B07
A_38-F04
CMTCN2
MRGH63
F112b
CSWTA02 CSWCTT02T
AI_13-H12
CMBR15 CMBR107
CMTAA166
97.0
ECM132 ECM178
GCM112 AI_13-F02
PS_28-B07 P01.45
HS_06-D02 CmERF3
MC42
105.0
CMTAAN100
CMBR123
CMCTN38
115.0
ECM231 HS_33-D11
PSI_19-F05 PS_07-E07 CmEthInd
GCM155
135.0
CMCTN4 PSI_11-D12
141.0
Figure 2 bin map of Cucumis melo obtained by selective genotyping of fourteen DHLs
EST-SNP
EST-SNP bin map of Cucumis melo obtained by selective genotyping of fourteen DHLs. Linkage groups are represented by vertical bars, divided in bins defined by the joint genotype of the selected DHLs. The mapped SNPs in this report are
shown in bold. Underlined markers are candidate genes previously reported [23,35,36]. The other markers have been
described in [21]. Genetic distances are shown on the left, indicating the position of the last marker included in the bin according to the framework map in [21]. Markers defining new bins are shown in italics. The hypothetical position of the last marker
of these bins is indicated by a dashed horizontal line within the linkage group bar, without the genetic distance.
the genomic sequences compared with the original EST
sequence to identify any introns. In the second strategy, in
silico SNPs previously identified [13] using EST2uni [41]
were classified as i) pSNPs, corresponding to SNPs present
in at least two EST sequences from the same genotype in a
given contig and with the same base change and ii)
pSCHs, corresponding to single nucleotide variations in
sequence that did not follow the above criteria for pSNPs.
Selected pSNPs and pSCHs were verified in most cases
after resequencing the parental lines of the melon mapping population. For a small subset, the SNP was verified
with an appropriate SNP detection method.
Bioedit software was used to generate restriction maps
from sequences obtained from SC and PS. SNPs (or
indels) showing differential restriction maps were used to
develop cleaved amplified polymorphic sequence (CAPS)
markers. When no differential restriction maps were available, the ABI Prism SNaPshot ddNTP Primer Extension Kit
(Applied Biosystems) was used for SNP genotyping [23].
Markers F112, 46d_11-A08, FR12J11, 15d_17-G01,
P01.45, PSI_26-B12, F012, PS_18-F05, PS_16-C09, F088,
A_02-H11, AI_13-G03 and FR15D10 produced amplicons of different sizes in the parental lines, which were
not sequenced and were genotyped as sequence characterized amplified region markers (SCARs) after electrophoresis in agarose gels or using a LI-COR IR2 sequencer (Li-Cor
Inc, Lincoln, Nebraska, USA). Markers PSI_12-D08 and
PSI_35-F11 were converted into dCAPS markers [42].
Markers F028, F149, F080 and PSI_25-B05 were genotyped using direct sequencing.
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5.0
8.0
VIII
ECM50 F072
GCM181 MC373
ECM79 AI_05-F11
CmeIF(iso)4G-2
A_06-A03
AI_12-B08 AI_27-F07
PSI_26-B12
3.0
6.0
16.0
MC311
MC44
CMAGN75 ECM182
ECM227
AI_25-C11 F271
P06.69
39.0
47.0
48.0
51.0
55.0
60.0
IX
15d_01-B03 A_30-G06
CSGA057 CMBR24 CMBR7
ECM88 P4.35 PS_28-E01
F125 PSI_29-D11
0.0
F080 PS_18-F05
TJ3 MC301
ECM217
ECM128 PSI_23-A11
HS_25-A10 CmAco3
13.0
MC68
TJ2 CmACS3
CI_33-B09
29.0
ECM221 AI_02-A08
MC253 CMTCN30
PSI_33-F04 HS_04-F11
41.0
CSAT425B ECM84
TJ38 ECM77 CMCAN90
CMBR53 CMBR27 P06.02
AI_03-G06 CmACS2
CMAGN21 CMBR84 GCM521
54.0
F149 F012
CSWCT12T CI_08-C08
CM139 AI_08-H11
ECM204
68.0
76.0
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CMGA15 ECM172 CmERF2
PSI_37-G01 CI_37-H11
77.0
CMTC13 AI_21-G05
AI_21-D08 P01.8
35.0
MC356 MC11 MC78
ECM200
CMAT141
PSI_25-H03
94.0
0.0
10.0
17.0
ECM150 ECM177
MRGH7 CM98
ECM66
PSI_12-C05 AI_17-B03
AI_39-A12 PSI_23-G11
31.0
FR18J20 A_17-A08
F036 AI_04-D08
35.0
54.0
57.0
61.0
PSI_21-D01
TJ33
0.0
CMTCN62
MC146 ECM210 P05.50
CMTC160 ECM63
ECM183 P4.39 A_02-H01
MC17 CSWCT01
CSWCT22A
HS_30-B08
CMTCN67
MC264 CMGAN12
MC375 CMAGN45
CmXTH5
CMGA172 ECM228
MC112 MC67 CM40
CMTA134B CMCTN65
CMGA165 ECM232
GCM153 ECM49
ECM116 ECM220
ECM101 GCM344
AI_38-B09 F088
46d_21-E02 CmEXP3
CM101B
CMTCN8
31.0
34.0
42.0
HS_39-A03
CMATN56 CmEXP1
97.0
TJ29
MC330
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PSI_41-B07
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MC325
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CI_57-E03
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MC132 GCM206
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76.0
102.0
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ECM175 MC149 ECM78 0.0
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PS_33-E12 AI_36-F12
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CMCTN71 CMCTN19
69.0
ECM55
MC138
99.0
MC92 CMTC47
ECM186 P05.64
A_04-B10 FR13O21
CMACC146 GCM241
MC208 CMAG59 F013
A_32-B01 CI_58-C10
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HS_23-E06 ECM86 ECM82
PS_15-H02 PS_40-E11
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Figure 3 bin map of Cucumis melo obtained by selective genotyping of fourteen DHLs
EST-SNP
EST-SNP bin map of Cucumis melo obtained by selective genotyping of fourteen DHLs. Linkage groups are represented by vertical bars, divided in bins defined by the joint genotype of the selected DHLs. The mapped SNPs in this report are
shown in bold. Underlined markers are candidate genes previously reported [23,35,36]. The other markers have been
described in [21]. Genetic distances are shown on the left, indicating the position of the last marker included in the bin according to the framework map in [21]. Markers defining new bins are shown in italics. The hypothetical position of the last marker
of these bins is indicated by a dashed horizontal line within the linkage group bar, without the genetic distance.
SNP mapping
SNPs and indels were mapped by selective genotyping
using the bin-mapping strategy [43], adapted for the
melon mapping population [21]. Fourteen out of 72
DHLs from the melon mapping population were selected
to obtain the maximum resolution with a minimum
number of genotypes. SNPs and indels were placed in the
bin map by visual inspection of the genotypes predicted
by the markers and genotypes in the bin set.
Genetic variability analysis
Forty-five SNPs from 44 amplicons (two SNPs were
selected from F241) were chosen for genetic variability
analysis. SNPs were genotyped as CAPS or by pyrosequencing as shown in Additional file 2. Thirty SNPs,
described in Additional file 1, were used. Twelve SNPs
that were not polymorphic between SC and PS were also
included in the variability analysis, and the primers for
each amplicon are provided in Additional file 2. The SNPs
CmERF1, CmPm3 and CmXTH5 have been previously
described [36].
Eight SNPs were genotyped by minisequencing the region
surrounding the polymorphism (two SNPs were detected
for F241 in the same reaction). Pyrosequencing was performed using a PSQ™ HS 96 system (Pyrosequencing AB,
Uppsala, Sweden) following the manufacturers' instructions. Primers were designed with the Pyrosequencing™
Assay Design Software (Biotage AB, Uppsala, Sweden).
One of the amplifying primers was 5' end labeled with
biotin, allowing the immobilization of the fragment onto
M-280 streptavidin coated Sepharose™ dynabeads (Dynal
AS, Oslo, Norway). The genotyping primer was hence
designed to anneal several nucleotides upstream of the
SNP. After denaturation of the streptavidin-captured PCR
fragments, the single stranded DNA fragments were
released into the wells of the PSQ HS 96 plate. Pyrosequencing was performed using the PSQ HS SNP Reagent
kit (Pyrosequencing AB, Uppsala, Sweden), and bioluminometric quantification of pyrophosphate (Ppi) released
as a result of nucleotide incorporation during DNA synthesis was measured with the PSQ™ HS 96 system.
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Allele frequencies, major allele frequency, gene diversity
(measured as expected heterozygosity, He [44]), genetic
distances and neighbor-joining (NJ) tree were calculated
using Powermarker 3.25 [45]. The NJ tree was plotted
with MEGA 3.0 [46]. Distance matrices were compared by
the Mantel test [47].
Additional file 2
SNP markers used for genotyping the melon accessions. The EST from
where the SNPs were discovered, the genotyping method (CAPS or pyrosequencing), linkage group where the marker maps to, and source of the
marker are given. For unmapped SNP markers, the amplicon primer
sequences are given. For SNP markers genotyped using pyrosequencing,
forward, reverse and internal primers were used for genotyping. 5'bio: Forward or reverse primer was 5' labeled with biotine. ST1: Additional file 1.
Click here for file
[http://www.biomedcentral.com/content/supplementary/14712229-9-90-S2.xls]
The number of populations in our collection was deduced
with the STRUCTURE software [33]. This package uses a
Bayesian clustering approach to identify subpopulations
and to assign individuals to these populations on the
basis of their genotypes. Given a sample of individuals, K
populations are assumed (where K may be unknown) and
individuals are assigned to these populations. A posteriori
probability for each K (Pr(K)) can be calculated, which is
very small for K values lower than the appropriate value.
Usually, the researcher fixes a minimum K (for example K
= 1), recording Pr(K) after the analysis, and tests increasing Ks, plotting K against Pr(K). The final K is defined
when Pr(K) reaches a plateau for higher K values. Consequently, in the current report, several number of populations (from K = 1 to 8) were tested with the software and
the total number of populations was set when the probability reached a plateau for higher K.
Additional file 3
Forty-eight melon accessions that were examined in this study. Plant
assignation (or common name), code used in the current study, accession
number from the respective gene banks, cultivar group, origin and seed
bank donor (COMAV, Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Valencia, Spain; USDA/ARS/NCRPIS, North Central Regional Plant Introduction Station, Ames, IA, USA; IPK, Institute
of Plant Genetics and Crop Plant Research, Gatersleben, Germany;
INRA, Institute Nationale de la Recherche Agronomique, Montfavet, Avignon, France; Semillas Fitó SA, Barcelona, Spain; ARO, Agricultural
Research Organization, Ramat Yishay, Israel) are specified for each genotype. Accessions marked with (*) were previously used by Monforte et al.
(2003) for an SSR study.
Click here for file
[http://www.biomedcentral.com/content/supplementary/14712229-9-90-S3.xls]
Authors' contributions
WD discovered and mapped the SNPs and performed the
genotyping for the variability analysis. CE and MGT discovered and mapped SNPs. CR discovered SNPs. IFS
mapped SNPs. DGI identified and selected in silico SNPs.
JB carried out the bioinformatics analyses for in silico
SNPs. AJM performed the variability analysis, coordinated
the SNP mapping and participated in the drafting of the
manuscript. MBP prepared DNAs for the melon accessions and participated in the genotyping for the variability
analysis and in the drafting of the manuscript. JGM, PA,
FN, MBP and MAA were involved in the conception of the
study. JGM is the principal researcher of this work, supervised it and wrote the manuscript. All authors read and
approved the final manuscript.
Acknowledgements
This work was supported by a grant from the Ministerio de Educación y
Ciencia (Spain) (GEN2003-20237-C06). WD is recipient of a postdoctoral
fellowship from the Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB
(Spain). CR is recipient of a Juan de la Cierva grant from the Ministerio de
Educación y Ciencia (MEC) (Spain). DGI and CS are recipients of pre-doctoral fellowships from MEC (Spain). IFS is recipient of a pre-doctoral fellowship from INIA (Spain). We are grateful to Armand Sanchez and Anna
Mercader (UAB) for their help with the pyrosequencing analysis.
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Additional material
Additional file 1
SNPs markers mapped in the SC × PS genetic map. Shown here, for
each SNP marker: the EST and accession number from where it was
obtained; best BlastX hit and E-value for each EST; amplicon primer
sequences; SNP/indel position; SNP detection method; linkage group and
BIN where the marker maps to. asequence available in [22] or http://
www.melogen.upv.es without accession number. bSNPs published by
Morales et al (2004). cSNP position is provided when located in exons
and referred to EST in first column. dthird primer was used for SNaPshot
genotyping.
Click here for file
[http://www.biomedcentral.com/content/supplementary/14712229-9-90-S1.xls]
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