RESEARCH ARTICLE Open Access

A consensus linkage map for molecular markersand Quantitative Trait Loci associated witheconomically important traits in melon(Cucumis melo L.)Aurora Diaz1, Mohamed Fergany2,17, Gelsomina Formisano3, Peio Ziarsolo4, José Blanca4, Zhanjun Fei5,Jack E Staub6,7, Juan E Zalapa6, Hugo E Cuevas6,8, Gayle Dace9, Marc Oliver10, Nathalie Boissot11,Catherine Dogimont11, Michel Pitrat11, René Hofstede12, Paul van Koert12, Rotem Harel-Beja13, Galil Tzuri13,Vitaly Portnoy13, Shahar Cohen14, Arthur Schaffer14, Nurit Katzir13, Yong Xu15, Haiying Zhang15, Nobuko Fukino16,Satoru Matsumoto16, Jordi Garcia-Mas2 and Antonio J Monforte1,2*

Abstract

Background: A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) overthe last two decades. However, these maps were constructed using different marker sets, thus, makingcomparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon wasconstructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny,and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS).

Results: Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), anintegrated genetic map has been constructed by merging data from eight independent mapping experimentsusing a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkagegroups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indelsand 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of thesemarkers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industryrepresentatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acidmetabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seedswere included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reportedmapping experiments using genetically diverse parental genotypes were also integrated into the consensus map.Some QTL associated with economically important traits detected in separate studies mapped to similar genomicpositions. For example, independently identified QTL controlling fruit shape were mapped on similar genomicpositions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait ina broad array of melon germplasm.

Conclusions: Even though relatively unsaturated genetic maps in a diverse set of melon market types have beenpublished, the integrated saturated map presented herein should be considered the initial reference map formelon. Most of the mapped markers contained in the reference map are polymorphic in diverse collection of

* Correspondence: amonforte@ibmcp.upv.es1Instituto de Biología Molecular y Celular de Plantas (IBMCP). UniversidadPolitécnica de Valencia (UPV)-Consejo Superior de Investigaciones Científicas(CSIC). Ciudad Politécnica de la Innovación (CPI), Ed. 8E. C/Ingeniero FaustoElio s/n, 46022 Valencia, SpainFull list of author information is available at the end of the article

Diaz et al. BMC Plant Biology 2011, 11:111http://www.biomedcentral.com/1471-2229/11/111

© 2011 Diaz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.

germplasm, and thus are potentially transferrable to a broad array of genetic experimentation (e.g., integration ofphysical and genetic maps, colinearity analysis, map-based gene cloning, epistasis dissection, and marker-assistedselection).

BackgroundSaturated genetic linkage maps (< 1 cM between mar-kers) are required for the efficient and effective deploy-ment of markers in plant breeding and genomicanalysis. Linkage map applications include, but are notlimited to: gene mapping, positional cloning, QTL analy-sis, MAS, epistasis dissection, linkage disequilibriumanalysis, comparative genomics, physical and geneticmap integration, and genome assembly. The construc-tion of highly saturated maps is often a time-consumingprocess, especially if investigators are employing differ-ent parental stocks and markers are not easily transfer-able. Merged maps are attractive since their integrationallows for an increase in marker density without theneed of additional genotyping, increased marker port-ability (i.e., polymorphic markers can be used in morethan one population), improved marker alignment preci-sion (i.e., congruent anchor maker position), andbroader inferential capabilities (i.e., cross-populationprognostication). A number of integrated linkage mapshave been developed in numerous economically impor-tant crop plants including grapevine (Vitis vinifera L.)[1], lettuce (Lactuca sativa L.) [2], maize (Zea mays L.)[3], red clover (Trifolium pratense L.) [4], ryegrass(Lolium ssp.) [5], wheat (Triticum aestivum L.) [6],among others.The genome of melon (Cucumis melo L.; 2n = 2x =

24) is relatively small (450 Mb, [7]), consisting of 12chromosomes. The first molecular marker-based melonmap was constructed in 1996 [8] using mainly restric-tion fragment length polymorphism (RFLP) markers andmorphological traits, although the markers did notcover the predicted 12 melon chromosomes. This wascomparatively late for a major crop species like melonthat is among the most important horticultural crops interms of worldwide production (25 millions of tons in2009) and which production has been increased around40% in the last ten years [9]. Subsequently, the first link-age maps that positioned markers on 12 linkage groups(LG) were constructed few years later, using the F2 pro-geny of a cross between the Korean accession PI161375and the melon type “Pinyonet Piel de Sapo” [10] andtwo Recombinant Inbred Line (RIL) populations derivedfrom the crosses “Védrantais” × PI161375 and “Védran-tais” × PI414723 [11]. However, these maps had fewmarkers in common and different LG nomenclature,making comparative mapping intractable. More recently,dense linkage maps have been constructed using Simple

Sequence Repeat (SSR) [12-16] and Single NucleotidePolymorphism (SNP) [17,18] markers. Nevertheless,although these maps share common markers, they pos-sess large numbers of map-specific markers that makesmap-wide comparisons complicated.Melon germplasm displays an impressive variability for

fruit traits and response to diseases [19-22]. Recently,part of this variability has been genetically dissected byQTL analysis [18,23-27]. Inter-population QTL compari-sons among these maps are, however, difficult given theaforementioned technical barriers.Databases integrating genomic, genetic, and phenoty-

pic information have been well developed in some plantspecies such as the Genome Database for Rosaceae [28],SOL Genomics Network for Solanaceae [29] or Gra-mene [30], and provide powerful tools for genomic ana-lysis. In 2005, the International Cucurbit GenomicsInitiative (ICuGI) [31] was created to further genomicresearch in Cucurbitaceae species by integrating geno-mic information in a database (http://www.icugi.org).Thirteen private seed companies funded this project,which sought to construct an integrated genetic melonmap through merging existing maps using common SSRmarkers as anchor points. We present herein an inte-grated melon map, including the position of QTL con-trolling economically important traits, to facilitatecomparative mapping comparison and to create adynamic genetic backbone for the placement of addi-tional markers and QTL.

Results and discussionConstruction of the integrated mapAnchor molecular markersBased on their previously observed even map distribu-tion, polymorphism, and repeatability, 116 SSR markersand 1 SNP marker (Additional File 1) were chosen asanchor points to integrate the eight genetic maps (Table1). Anchor marker segregation varied among maps,where the greatest number of polymorphic anchor mar-kers were in IRTA (Institut de Recerca i TecnologiaAgroalimentáries, Barcelona, Spain) [15] and INRA(Institut National de la Recherche Agronomique, Mon-tfavet Cedex, France) [11] maps containing 100 and 82anchor polymorphic markers, respectively. The mini-mum number of anchor polymorphic markers wasrecorded in the NERCV (National Engineering ResearchCenter for Vegetables, Beijing, China) [32] map (35polymorphic markers). Most of the anchor markers

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were originally mapped in the IRTA population, thatshared a common parent (the Korean line PI 161375)with the INRA population, while the other parent wasan Occidental cultivar ("Piel de Sapo” and “Vedrantais”for IRTA and INRA populations, respectively), so it wasactually expected that the proportion of markers thatcan be transferred successfully from IRTA to INRApopulations is larger than to the any other studiedpopulation developed from different germplasm.Molecular marker segregation analysis among individualmapsConsiderable and significant skewed marker segregations(p < 0.005) were detected in seven genomic regions ofthe DHL-based IRTA map (Table 1). Although signifi-cant skewed segregations were also detected in a regionon LG VIII of the F2-based IRTA map [10], on LGs I,IV, and VI in NIVTS (National Institute of Vegetableand Tea Science, Mie, Japan) map [116] and on LGs V,VII, VIII and X in the ARO (Agricultural ResearchOrganization, Ramat Yishay 30095, Israel) map [18]. Nosignificant segregation distortion was detected in the

other maps used herein (data not shown). The relativelyhigh number of genomic regions with skewed segrega-tion detected in the DHL-based map reinforces thehypothesis that such distortion likely originated fromunintentional selection during the in vitro line develop-ment process [33]. The low number of genomic regionsshowing skewed segregation in most melon maps con-trasts with that reported in other crops such as lettuce[2], red clover [4], sorghum [34], and tomato [35]. Thedegree of such distortion has been correlated to theextent of taxonomic divergence between mapping par-ents [36]. The use of inter-specific hybrids in order toconstruct genetic maps is a common strategy to ensurethe availability of a high number of polymorphic mar-kers, and in such cases segregation distortion may befrequent [37]. However, depending on the relative fre-quency and intensity, segregation distortion may notinterfere on the map construction. Nevertheless, suchdistortion may hinder the transfer of economicallyimportant alleles during plant improvement. The com-paratively low frequency of segregation distortion

Table 1 Mapping populations

Map Parentallines

Subspecies Marketclass

Horticulturalgroup

Populationtype

Populationsize

Numberofmarkers

Number ofpolymorphicanchormarkers

Maximumnumber ofsharedmarkers

Maplength(cM)

Reference

INRA Védrantais melo Charentais cantalupensis RIL 154 223 82 68 1654 [11,27]

PI 161375 agrestis chinensis

ARO Dulce melo Cantaloup reticulatus RIL 94 713 56 64 1222 [18]

PI 414723 agrestis momordica

IRTA Piel desapo

melo Piel desapo

inodurus DHL 69 238 100 111 1244 [15]

DHL 14 528 [17]

PI 161375 agrestis chinensis F2 93 293 37 111 1197 [10]

NITVS AR 5 melo Cantaloup reticulatus RIL 93 228 70 70 877 [16]

Hakurei 3 melo Cantaloup reticulatus

NERCV K7-1 melo Hamimelon

cantalupensis RIL 107 237 35 41 [32]

K-7-2 melo Hamimelon

cantalupensis

USDA USDA846-1

hybrid RIL 81 245 37 64 1116 [13]

Top Mark melo Western reticulatus

Shipper

Top Mark melo Western reticulatus

Q 3-2-2 melo Shipper conomon/ F2 117 168 35 64 1095 [14]

momordica

Summary of the mapping populations used to construct the integrated map. Each map is named by the abbreviation of the collaborating institutions (INRA,Institut National de la Recherche Agronomique, France; ARO, Agricultural Research Organization, Israel; IRTA, Institut de Recerca i Tecnologia Agroalimentàries,Spain; NITVS, National Institute of Vegetable and Tea Science, Japan; NERCV, National Engineering Research Center for Vegetables, China; and USDA-ARS U. S.Department of Agriculture, Agricultural Research Service, USA). The genotypes used as mapping parents belong to the subspecies (Cucumis melo L.: ssp. melo orC. melo ssp. agrestis), and the market class and horticultural group are classified according to Pitrat et al. (2000) [49]. The DHL population of 14 genotypes isactually a selected sample for bin mapping of the 69 DHLs [12]. The number of polymorphic anchor markers segregating within each map and the maximumnumber of markers shared by each map with at least one of the other maps are also shown.

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present in melon maps may be partially explained by theuse of intra-specific crosses during population develop-ment. Given the infrequent occurrence of segregationdistortion in melon, the introgression of novel, econom-ically important alleles from exotic melon germplasminto elite modern cultivars should be relativelyunimpeded.Marker polymorphism and recombination rates amongindividual mapsThe number of polymorphic markers for individualmaps ranged from 168 (USDA-ARS, Vegetable CropsResearch Unit, Department of Horticulture, MadisonUSA) to 713 (ARO) (Table 1). INRA and IRTA mapsconsisted of 12 LGs, coinciding with the basic chromo-some number of melon, whereas the remaining mapsconsisted of more LGs (see http://www.icugi.org forfurther details). The number of common markers inpairwise individual map comparisons was quite variable,with a mean of 40 common markers among maps. Eachindividual map shared between 41 and 111 markerswith at least one of the other maps (Table 1). Markerorder and recombination rates among markers werevery consistent among maps, where significant recombi-nation rate heterogeneities (p < 0.001) were detectedbetween only a few marker pairs (CMN22_85-CMTCN66 in LGIII, CMAGN75-CMGA15 in LG VII,and TJ2-TJ3 in LG VIII). Similar results have beenfound during genetic map integration in grapevine [1],but more frequent recombination rate differences havebeen reported among integrated maps in apple (Malusdomestica Borkh) [38], Brassica ssp. [39], and lettuce [2].Differences in locus order and recombination rates maybe attributed, in part, to bands that were scored as sin-gle alleles instead of duplicated loci or to evolutionaryevents (chromosomal rearrangements). Nevertheless, itmust be concluded from the data presented that majorchromosomal rearrangements have not occurred duringthe recent evolutionary history (i.e., domestication) ofthis species.Consensus linkage mapThe construction of the integrated map described hereininvolved two stages: 1) the building of a framework mapby merging all the available maps (Table 1) using Join-map 3.0 [40]; 2) the addition of subsequent markersusing a “bin-mapping” approach [41].Given the high co-linearity among melon maps, 1565

markers from all maps were initially employed for mapintegration. However, 258 (16%) of these markers couldnot be included in the final integrated map. This pro-portion was smaller than that obtained during map inte-gration of lettuce (19.6% [2]), and larger than in thegrapevine integrated map (8%, [1]). The markers segre-gating within each individual map were quite comple-mentary, what made the inclusion of a large number of

markers into the final merged map possible. For exam-ple, the IRTA_F2 map was constructed with an impor-tant proportion of RFLP markers that were not used inmost of the other maps. However, this map had enoughRFLP markers in common with the IRTA_LDH map,which has a good proportion of common markers withINRA (68) and NIVTS (70) maps, making possible tointegrate the IRTA_F2 RFLP markers in the final map.Given the congruency detected among melon maps,

the inability to incorporate some previously mappedmarkers into the integrated map is likely due to the lackof sufficient linkage among markers in some genomicregions, especially in small LGs drawn from some indivi-dual maps where there was a paucity of common frame-work map markers.The framework integrated map contained 1307 mar-

kers (110 SNPs, 588 SSRs, 252 AFLPs, 236 RFLPs, 89RAPDs, 6 indels, 15 IMAs, and 11 morphological traits)spanning 1150 cM that were distributed across 12 LGswith a mean genetic distance between adjacent loci of0.88 cM (Figures 1 and 2, Additional Files 2 and 3).Integrated map length was similar to previously pub-lished maps (Table 1). While the largest marker gap was11 cM (on the distal ends of LG × and LG IV), theremaining gaps were less than 10 cM, and occurredmainly on the distal ends of LGs (Figures 1 and 2).These gaps are likely due to the lack of sufficient com-mon anchor markers in some maps or slight inconsis-tencies (distance and/or order) among maps.Bin-mapping subsequently resulted in the addition of

285 markers (225 SNPs, 52 SSRs, 3 RFLPs, and 5 indels)producing the final integrated map containing 1592markers (640 SSRs, 335 SNPs, 252 AFLPs, 239 RFLPs,89 RAPDs, 15 IMAs, 11 indels, and 11 morphologicaltraits) with a mean marker density of 0.72 cM/marker(Table 2 Figures 1 and 2, Additional Files 2 and 3,http://www.icugi.org). One hundred and seventy-eight ofthese markers were developed, released, or mapped forthe first time for the ICuGI Consortium. The markersaturation of this integrated map is far greater than pre-viously published maps (Table 1), increasing dramati-cally the number of easily transferable markers from 200[17] to 3353 SNPs and from 386 [18] to 640 SSRs.Noteworthy is the fact that 17 previously bin-mappedmarkers were positioned on the integrated map afterbeing genotyped in several populations. In each case,these markers mapped to their predicted positionsinferred by the bin mapping approach (Table 3), demon-strating the suitability of the bin mapping set [15] toquickly map new markers onto the melon referencemap.Marker distribution in the integrated map varied

depending on the marker type. For instance, AFLP mar-kers clustered mainly in certain regions of LGs I, II, III,

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Figure 1 Integrated melon marker map. Linkage groups I to VI. Six out of the 12 melon linkage groups (LG) are designated with Romannumerals (I-VI) according to Perin et al. (2002) [11]. Marker type is indicated by colours: SSRs (green), SNPs (black), AFLPs (blue), RFLPs (red),RAPD (grey), IMA (orange), morphological traits (purple) and indel (brown). The map distance is given in centiMorgans (cM) from the top of eachLG on the left.

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V, VI, VIII, and × (Figures 1 and 2). AFLP clustering hasbeen commonly reported (e.g., in saturated maps of let-tuce [2], potato [42] or tomato [43]), and it is usuallyassociated with heterochromatic regions near

centromeres. Even though regions showing AFLP clus-tering are likely indicative of centromeric positions,comprehensive cytogenetic analyses would be necessaryto demonstrate this association in melon. In contrast,

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Figure 2 Integrated melon marker map. Linkage groups VII to XII. The remaining six linkage groups of melon (VII-XII). Color code for markersare the same as Figure 1.

Diaz et al. BMC Plant Biology 2011, 11:111http://www.biomedcentral.com/1471-2229/11/111

Page 6 of 14

SSR, SNP and RFLP markers were generally more evenlydistributed throughout the genome. Similar conclusionscan not be reached about the remaining markers(RAPDs, IMAs, indels and morphological traits) due totheir low number. Nevertheless, SSR marker clusteringwas observed in LGs III, IV, VII, VIII, XI, and XII,involving mainly SSR markers originated from genomiclibraries (e.g., CMBR-SSRs [44]), not from ESTs. Thisresult might indicate that those SSRs are located inrepetitive DNA regions as centromeres or telomeres.However, such SSR marker clusters did not overlapthose of AFLPs, even though these clusters were in thesame LG (i.e., LGs III and VIII), suggesting that SSRmarker clustering may be due to reasons not associatedwith centromeric or telomeric regions.

Integration of QTL informationEighteen previously reported melon-mapping experi-ments identified 370 QTL for 62 traits (Table 4 andAdditional File 4), and these were aligned in the inte-grated map described herein. The distribution of theseQTL varied from 18 on LG IV to 57 on LG VIII (Fig-ures 3 and 4, Additional File 5). The number of QTLsdefined per trait ranged from 1 (e.g., CMV, ETH, andFB) to 40 (FS), with QTL for FS, FW, and SSC beingidentified in 7, 5, and 5 of the previously reported 18mapping experiments, respectively. The number of QTLexperiments in melon must be considered modest whencompared with other major species, with a significantnumber of the traits being genetically characterized in

only one or two different mapping experiments, whichthereby limits the meta-analysis of QTL in this species.Even though additional studies would be necessary todraw definitive conclusions, the position of FS QTLtend to be more consistent among experiments thanthose for FW and SSC QTL, mapping on LG I in sixout of seven works, and on LGs II, VI, VII, VIII, XI, andXII in at least three experiments. Clustering of FW andSSC QTL was, however, only observed in LGs VIII andXI, and in LGs II, III, and V, respectively. FS is a highlyheritable trait in melon, whereas FW and SSC usuallyshow a lower heritability [25]. The differences in QTLdetection among experiments might be partiallyexplained by trait heritability differences. Another possi-ble explanation is that the variability of FS among thegermplasm used in the experimental crosses might becontrolled by a low number of common QTL with largeeffects, whereas a higher number of QTL with lowereffects and/or more allelic variability among them mightbe underling SSC and FW.

Utility of the integrated molecular and QTL mapThe integrated map described herein dramaticallyenhances the development and utility of genomic tools(i.e., markers, map-based cloning and sequencing) overprevious melon maps. A large proportion of the markers

Table 2 Distribution of genetic markers in the melonintegrated map

LinkageGroup

Frameworkmarkers

Binmarkers

Total Geneticlength(cM)

Markerdensity

(cM/marker)

I 131 31 162 99 0.61

II 108 18 126 94 0.74

III 105 23 128 95 0.74

IV 104 27 131 119 0.91

V 115 25 140 110 0.79

VI 102 23 125 98 0.78

VII 108 30 138 99 0.72

VIII 147 30 177 123 0.69

IX 74 18 92 84 0.91

X 89 23 112 73 0.65

XI 131 22 153 80 0.52

XII 93 15 108 77 0.71

1307 285 1592 1150 0.72

Distribution and density of markers across the 12 linkage groups, specifyingthe number of markers that were integrated using Joinmap 3.0 (framework)and bin mapping.

Table 3 Comparison of marker positions among bin andintegrated melon map

Marker Linkagegroup

Bin position(cM)

Integrated map position(cM)

ECM58 I 38-56 58

GCM168 I 75-99 82

CMBR105 III 42-65 42

CMBR100 III 42-65 45

GCM336 IV 52-77 59

GCM255 VI 45-68 55

GCM303 VI 45-68 55

ECM132 VI 80-92 91

ECM182 VII 32-60 49

ECM204 VII 73-86 81

ECM217 VIII 30-41 19

ECM128 VIII 30-41 35

GCM241 VIII 67-90 83

ECM78 X 0-14 11

ECM228 X 26-30 29

ECM164 XI 38-59 59

ECM105 XII 20-41 22

Several markers previously mapped using the bin mapping strategy [15] wereincluded in the integrated map. The expected interval for position of themarkers in centiMorgans (cM) in the integrated map based on the markersdefining the bins according to Fernandez-Silva et al. (2008) [15] is shown inthe “Bin position” column, while the actual position in the integrated map isgiven in the “Integrated map position” column.

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Page 7 of 14

in the integrated map are SSRs and SNPs, which areeasily transferable across laboratories. Moreover, thepopulations used to construct the integrated mapinclude genotypes from the most important market classcultivars ("Charentais”, “Cantaloup”, “Hami melon”, “Pielde Sapo” and “U. S. Western Shipper”) in broad horti-cultural groups (cantalupensis, inodorus, and reticula-tus), guaranteeing the future utility of the markers in abroad range of cultivars and experimental crosses. Thehigh marker density of the map allows for the selectionof specific markers to customize mapping and molecularbreeding applications, such as fine mapping, the devel-opment of novel genetic stocks (e.g., nearly isogeniclines and inbred backcross lines), MAS, and hybrid seedproduction.The positioning of economically important QTL in the

integrated map and the standardization of trait nomen-clature will facilitate comparative QTL analyses amongpopulations of different origins to provide deeperinsights into the genetic control of the diverse phenoty-pic variability observable in melon germplasm. Forexample, QTL for SSC on LG III co-localize with QTLassociated with SUC, GLU, and SWEET, suggesting per-haps the existence of pleiotropic effects (Figures 3 and4). The search of candidate genes is also facilitated, as

Table 4 Name and abbreviations of the traits analysed inthe current report

Trait Abbreviation

Ripening rate RR

Early yield Eay

Fruit Weight FW

Fruit Shape FS

Fruit diameter FD

Fruit Length FL

Fruit Convexity FCONV

Ovary Shape OVS

Soluble Solid Content SSC

Fruit number FN

Fruit Yield FY

Primary branch number PB

Percentage of mature fruit PMF

Flesh firmmes FF

Seed cell diameter SCD

Fruit Flesh proportion FFP

Percent netting PN

beta-carotene b-car, b-carM and b-carE

Ethylene production ETH

Powdery mildew resistance PM

Aphis gossypii tolerance Ag

External Color ECOL

Flesh Color FCOL

Ring sugar content RSC

Leaf Area LA

Total losses TL

Over ripening OVR

Finger texture FT

Water -soaking WSD

Flesh browing FB

Fusarium rot FUS

Stemphylium rot ST

Fruit flavor FLV

Necrosis NEC

Vine weight VW

Primary root length PRL

Average diameter of the primary root PAD

Secondary root density SRDe

Average lenght of secondary roots ALSR

Skin netting SN

Skin thickness STH

Dry matter DM

pH pH

Titratable acidity TA

3-hydroxy-2,4,4-trimethylpentyl 2-methylpropanoate

PRO

Octanal OCT

Glucose GLU

Fructose FRU

Sucrose SUC

Table 4 Name and abbreviations of the traits analysed inthe current report (Continued)

Total sugars TSUG

Succinic SUCC

Sourness SOUR

Bitterness BITTE

Sweetness SWEET

Cucumber mosaic virus CMV

Net cover NTC

Net density NTD

Stripes STR

Sutures SUT

Softness WFF

Total carotenoids CAR

Phytoene PHY

a-carotene aCRLutein LUT

Pentamerous p

Resistance to Fusarium races 0 and 2 Fom_1

Resistance to Fusarium races 0 and 1 Fom_2

Monoecious a

Spots on the rind mt_2

Melon necrotic spot virus Nsv

Sutures s-2

Virus aphid transmision Vat

White flesh wf

Zucchini Yellow Mosaic Virus Zym

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Figure 3 Quantitative Trait Loci (QTL) positioned in the melon integrated map. Linkage groups I to VI. QTL are located in a skeleton of theintegrated map, where candidate genes for fruit ripening (green), flesh softening (blue), and carotenoid (orange), and sugar (brown) content arealso shown. QTL are designated according to additional files 4 and 5 using the same colour code given for the candidate genes.

Figure 4 Quantitative Trait Loci (QTL) positioned in the melon integrated map. Linkage groups VII to XII. Color codes are indicated inFigure 3.

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presently little correlation has been detected betweencandidate gene and trait for ethylene production [45,46],fruit flesh firmness [46], carotenoid content [13,18], orsugar accumulation [18]. These associations were stu-died in single population, which limits the possibility ofidentifying associations between candidate genes andQTL. Multi-population analysis is a more powerfulapproach for detecting QTL/candidate gene associations.For instance, two clusters of QTL involved in carotenoidaccumulation and flesh color co-localized with carote-noid-related genes: CMCRTR and BOH_1 in LG VI andCMBCYC and LYCB in LG VIII (Figures 3 and 4), andas such become candidate genes for those QTL. Similarassociations can been found between genes involved inpolysaccharide metabolism and transport and clusters ofQTL related to fruit sugar content on LGs II, III, V,VIII, and X. Likewise, associations have been detectedbetween ethylene biosynthesis genes and groups of QTLwith effects on fruit ripening on LG VIII.Preliminary synteny analyses have been conducted

between cucumber and melon based on the IRTA SNPand EST-SSR based melon map [17] and the cucumbergenome sequence [47]. A large number of EST-basedmarkers (RFLPs, EST-SSRs, and SNPs) mapped in theintegrated map will facilitate synteny studies withcucumber and other cucurbit species such as waterme-lon, squash, and pumpkins as genomic information onsuch species becomes available. Most cucurbit speciesdisplay a myriad of variability for economically impor-tant vegetative (e. g., branch number, sex expression)and fruit (e.g. morphology, carotenes, sugars) traits.Comparative QTL mapping based on syntenic relation-ships will allow the evaluation of associations betweenthe allelic constitution at the same genetic loci and thephenotypic variability among the different cucurbit spe-cies, as is the case with fruit size between pepper andtomato in Solanaceae family [48].

ConclusionEight molecular marker melon maps were integratedinto a single map containing 1592 markers, with a meanmarker density of 0.72 cM/marker, increasing dramati-cally the density over previously published maps inmelon. The integrated map contains a large proportionof easily transferable markers (i.e. SSRs and SNPs) andputative candidate genes that control fruit ripening,flesh softening, and sugar and carotenoid accumulation.Moreover, QTL information for 62 traits from 18 differ-ent mapping experiments was integrated into the melonmap that, together with the mapped candidate genes,may provide a suitable framework for QTL/candidategene analysis. In summary, the integrated map will be avaluable resource that will prompt the Cucurbitaceaeresearch community for next generation genomic and

genetic studies. All the individual maps, the integratedmap, marker and QTL information are available atICuGI web site (http://www.icugi.org). Researchersinterested in including their QTL data into the inte-grated map may contact the corresponding author.

MethodsMapping populationsEight mapping populations derived from seven indepen-dent crosses were used to develop the integrated map(Table 1). Three crosses involved genotypes from thetwo C. melo subspecies (ssp. melo and ssp. agrestis),three of them between two C. melo ssp. melo cultivarsand one cross between a C. melo ssp. melo cultivar anda breeding line derived from a cross between C. melossp. melo and C. melo ssp. agrestis cultivars. The C.melo ssp. melo genotypes represent the most importanteconomically market classes (Charentais, Cantaloup,Hami melon, Piel de Sapo, and U. S. Western Shipper)belonging to horticultural groups inodorus, cantalupen-sis, and reticulatus (Table 1) according to the classifica-tion described by Pitrat et al. (2000) [49]. Most of themapping populations were RILs, where two were F2 andone was a double haploid line (DHL) population (Table1).Development of new genomic SSR markersNew geno-

mic SSR marker (designated DE- and DM-) were devel-oped by Syngenta seeds. DNA plasmid libraries wereconstructed using approximately 1 kb fragments ofsheared total DNA. SSRs were targeted via 5’-biotiny-lated total LNA capture probes (12-16 bases long andcontaining 2, 3, or 4 base repeating units) (ProligoLLC–now IDT). These probes disrupted the doublehelix of the library DNA at the probe sequence and as aconsequence the single strand subsequently formed adouble helix with the LNA probe sequence. Streptavidincoated magnetic beads (Invitrogen M-280 Dynabeads)were then used to separate the targeted plasmids fromthe library. Beads were washed several times and theDNA was then eluted from the beads and transformedinto electrocompetent Escherichia coli DH12S cells (LifeTechnologies, California, USA) which were grown upand plated on large Qubit plates. Resultant colonieswere then picked using the Qubit, incubated in LBbroth, purified and recovered DNA was Sangersequenced. Proprietary programs selected sequenceswith SSRs and designed flanking primers.

Molecular markersA large proportion of molecular markers developed and/or mapped in previous works (Table 1) were positionedin the integrated map. Additionally, 196 unpublishedmarkers described bellow were included in the mergedmap. Additional file 2 details the major properties of

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these markers. On one hand, Syngenta Seeds kindlyreleased 822 SSR markers (see above) to the ICuGImapping project that were polymorphic in either AROand/or INRA mapping populations. Eighty-five of them(selected based on their position calculated in in-housebuilt genetic maps by Syngenta, unpublished results)were mapped in the ARO population and subsequentlyincluded in the merged map.On the other hand, new 9 SSRs, 5 indels, s and 27

SNPs were released by ARO group. These indels andSNPs were detected and genotyped according to Harel-Beja et al. (2010) [18] in genes associated with organicacid metabolism or transport (designated OAMG-organic acid melon genes) that were cloned by twomethods: (1) from melon cDNA and gDNA by PCRusing degenerate primers based on conserved proteinsequences; (2) ICuGI database mining. All of them wereincorporated to the ARO’s map [18].In contrast, MU- markers are EST-SSRs were devel-

oped from their respective EST contigs available atICuGI web page and mapped by the NERCV group.Four SNPs (AF- and AB- markers) were released byNIVTS (National Institute of Vegetable and Tea Science,Mie, Japan) group and mapped in their respective map.Finally, the unpublished indel MC264 and the SSR mar-ker TJ22 were included in the IRTA map [10,15,17].

Construction of the integrated mapVarious combinations of RFLP, RAPD, IMA, AFLP, SSR,indel and SNP markers had previously been employedto genotyped individuals in each of the eight mappingpopulations (Table 1). In order to ensure a minimumnumber of common anchor points among markers, 116SSR and 1 SNP markers evenly distributed through themelon genome according to two previous linkage maps[15,16] (Additional File 1) were selected to be genotypedin the eight mapping populations. When possible, twomarkers per anchor-point position were chosen to maxi-mize the probability of identifying polymorphisms inpopulations examined. Standard, published protocolswere employed for SSR marker genotyping [13-16,18].Marker segregation distortion was investigated

employing Joinmap 3.0 software [40] in each of themapping populations used for map merging. Given thelarge number of maps and markers evaluated, markerdistortion was considered significant at p < 0.005 andwhen adjacent linked markers also showed distortion atp < 0.01. The heterogeneity of recombination frequency(REC) between common markers among different mapswas also evaluated with Joinmap 3.0 and declared signif-icant at p < 0.001.Initially, a map was constructed for each mapping

population, where LGs were defined with the “group”command with a minimum LOD score of 4.0. Groups

were then assigned to LGs by comparing their markercomposition with the LGs defined in previous referencemaps [11,12,15,17]. Groups belonging to the same LG indifferent populations were then integrated with the“combine groups for map integration” module of Join-map 3.0 using the following parameters: Kosambi’s map-ping function LOD > 2, REC < 0.4, goodness of fit jumpthreshold for removal of loci = 5, performing rippleafter adding 1 locus and the third integration round =No. The resulting map was designated the “frameworkmap” and was used in further marker integrations. Toadd markers mapped by bin mapping [15,17], markersdefining the bins in the IRTA map were identified onthe framework map. The bins were redefined in the fra-mework map and markers were located subsequently totheir respective bins from the IRTA to the frameworkmap..

Trait and QTL definitionTraits and QTL were selected from 17 published worksand 1 unpublished work (Additional Files 4 and 5) bythe collaborating project researchers. Crosschecking andevaluation of recording methods allowed for the unifica-tion of trait descriptions and common abbreviationswere assigned accordingly (Additional File 4). QTL weredefined following the directions of the Gramene data-base [50].Nevertheless, QTL controlling the same trait expres-

sion were often defined in independent publicationsand/or in different mapping populations and, conse-quently, QTL characterized in those different popula-tions may correspond to the same genetic locus.Therefore, each QTL was treated independently, makingit possible to notice the number of times that a QTL isreported in a similar genomic location across indepen-dent experiments.A specific identifier was assigned to each QTL, where

the first letters designate the trait abbreviation, followedby a “Q” that stands for QTL, then a letter indicating areference to a mapping experiment (publication) fol-lowed by a digit representing the LG to which the QTLmaps, and then followed by a dot and a final digit thatdistinguishes different QTL from the same experimenton the same LG (Additional File 5). For example, thedesignation FDQJ2.2 stands for one of the QTL for FD(fruit diameter) reported in the experiment J and map-ping in the LG II.QTL were defined within a marker interval according

to the information presented in the original publicationfrom which it was taken or as a personal communica-tion from a project collaborator. If a flanking markerdefining a QTL was not included in the framework mapduring the merging process, then the next closely linkedmarker was chosen for representation in the integrated

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map. Where only a single marker was associated with aQTL, marker position was used as both the start andstop position of the QTL. For illustration purposes, gra-phic representation of a QTL’s position was defined inthe centre of a marker interval (Figures 3 and 4).To provide visual images of their genomic positions,

integrated markers and QTL were plotted using Map-chart 2.0 [51]. Colour codes were used to identify mar-ker types, traits, QTL, and candidate genes in order tofacilitate visualization of the co-localization of possibleQTL and candidate genes involved in similar processesacross different mapping experiments.

Additional material

Additional file 1: Markers selected as anchor points for mapintegration. PowerPoint file depicting a skeleton of the IRTA map [12]and the position of the markers distributed among the collaboratinglaboratories for use as anchor points for map integration.

Additional file 2: Source of markers. Excel spreadsheet with twosheets: “Markers in ICuGI consensus map” containing the references inwhich markers were described and where full details may be obtained,marker type (SSR, Single Sequence Repeat; SNP, Single NucleotidePolymorphism; RFLP, Restriction Fragment Length Polymorphism; IMA,Inter Microsatellite Amplification; RAPD, Random Amplified PolymorphicDNA; AFLP Amplified Fragment Length Polymorphism; indel, insertion/deletion), the forward, reverse and extension primers (for some SNPs);and “Non-mapped markers” containing the new SSR markers released bySyngenta Seeds that are polymorphic in either ARO and/or INRAmapping populations.

Additional file 3: Integrated melon map. Excel spreadsheet containingthe position of mapped marker on 12 (I-XII) melon linkage groups.

Additional file 4: Consensus vocabulary for the traits positioned onthe melon integrated map. Excel spreadsheet containing consensusdefinitions for the traits used in the different QTL mapping experiments.

Additional file 5: Quantitative Trait Loci (QTL) located on the melonintegrated map. Excel spread sheet containing the definition of the QTLlocated on the melon integrated map. QTL are designated according tothe following rules: the first letters are the trait abbreviation, followed bya “Q”, then a letter indicating the reference followed by a digitrepresenting the LG to where the QTL maps, and the last digitdistinguishes different QTL from the same publication in the same LG.The last column indicates molecular markers from the integrated mapthat flank the mapped QTL.

AcknowledgementsThis work was supported in part by SNC Laboratoire ASL, Ruiter Seeds B.V.,Enza Zaden B.V., Gautier Semences S.A., Nunhems B.V., Rijk Zwaan B.V.,Sakata Seed Inc, Semillas Fitó S.A., Seminis Vegetable Seeds Inc, SyngentaSeeds B.V., Takii and Company Ltd, Vilmorin & Cie S.A., and Zeraim GederaLtd (all of them as part of the support to the ICuGI); the grants AGL2009-12698-C02-02 from the Spanish “Ministerio de Ciencia e Innovación” to AJM.NK lab was supported in part by Research Grant Award No. IS-4223-09Cfrom BARD, the United States - Israel Binational Agricultural Research andDevelopment Fund, and in part by Israel Science Foundation Grant No. 386-06, De Ruiter Seeds, Enza Zaden, Keygene, Rijk Zwaan, Sakata SeedCorporation, Semillas Fitó, Syngenta Seeds and Vilmorin Clause & Cie. ADwas supported by a JAE-Doc contract from “Consejo Superior deInvestigaciones Científicas” (CSIC-Spain). MF was supported by a postdoctoralcontract from CRAG. The research carried out at YX’s laboratory wassupported by Chinese funds (Grant No.2008-Z42(3), 5100001,2010AA101907).

Author details1Instituto de Biología Molecular y Celular de Plantas (IBMCP). UniversidadPolitécnica de Valencia (UPV)-Consejo Superior de Investigaciones Científicas(CSIC). Ciudad Politécnica de la Innovación (CPI), Ed. 8E. C/Ingeniero FaustoElio s/n, 46022 Valencia, Spain. 2IRTA, Center for Research in AgriculturalGenomics (CSIC-IRTA-UAB), Campus UAB, Edifici CRAG, 08193 Bellaterra(Barcelona), Spain. 3Department of Soil, Plant, Environmental and AnimalProduction Sciences, Federico II University of Naples, Via Università 100,80055 Portici, Italy. 4COMAV-UPV, Institute for the Conservation and Breedingof Agricultural Biodiversity, Universidad Politécnica de Valencia, Camino deVera s/n, 46022 Valencia, Spain. 5Boyce Thompson Institute for PlantResearch, Ithaca, New York 14853, USA. 6USDA-ARS, Vegetable CropsResearch Unit, Department of Horticulture, 1575 Linden Dr, University ofWisconsin, Madison, WI 53706, USA. 7Current address: USDA-ARS, Forage andRange Research Laboratory, Utah State University, Logan, UT 84322-6300,USA. 8Current address: USDA-ARS, Tropical Agricultural Research Station,2200 Pedro Albizu Campus Ave, Mayaguez 00680-5470, Puerto Rico.9Syngenta Biotechnology, Inc. Research Triangle Park, NC 27709, USA.10Syngenta Seeds, 12 chemin de l’Hobit, F-31790 Saint-Sauveur, France.11INRA, UR 1052, Unité de Génétique et d’Amélioration des Fruits etLégumes, Domaine St Maurice, BP 94, 84143 Montfavet Cedex, France.12Keygene N.V. P.O. Box 216. 6700 AE Wageningen. The Netherlands.13Institute of Plant Science, Agricultural Research Organization (ARO), NeweYa’ar Research Center, Ramat Yishay 30095, Israel. 14Institute of Plant Science,Agricultural Research Organization, Volcani Research Center, Bet Dagan50250, Israel. 15National Engineering Research Center for Vegetables (NERCV),Beijing Academy Agricultural and Forestry Science, Beijing 100097, China.16National Institute of Vegetable and Tea Science (NIVTS), 360 Kusawa, Ano,Tsu, Mie, 514-2392, Japan. 17Agronomy Department Faculty of Agriculture,Ain Shams University, Cairo, Egypt.

Authors’ contributionsAJM coordinated the map integration study, provided the marker and QTLdata of the IRTA mapping populations, performed the map merging, anddrafted the manuscript. MF obtained additional genotype data for the IRTAmapping population. GF integrated QTL information into the merged map,AD assisted in the map merging, prepared tables, and graphicrepresentations and helped to draft the manuscript. PZ and JB formattedthe data for representation with C-maps for publication in the ICuGI website. ZF is the responsible for the ICuGI web site. JES, JZ, and HC providednew marker and QTL data of the USDA-ARS mapping populations; JESassisted with manuscript editing. NF and SM provided new marker and QTLdata of the NITVS mapping population and new SNP markers MO providednew marker mapping data for the ARO mapping population and GDdeveloped the DE and DM SSR markers. CD, NB and MP provided newmarker and QTL data of the INRA mapping population. RH and PK assistedwith map merging construction. RHB, GL, VP, SC, AS, NK, provided new SSRand OGM markers, marker and QTL data of the ARO mapping population.YX and HYZ provided new SSR markers from melon ESTs, and also markerand QTL data of the NERCV mapping population. NF and SM provided theSSR markers used as anchor points for map integration and marker and QTLdata of the NITVS mapping population. JGM was the coordinator of theICuGI project and participated in the design of the study. All authors haveread and approved the final manuscript

Received: 11 April 2011 Accepted: 28 July 2011 Published: 28 July 2011

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doi:10.1186/1471-2229-11-111Cite this article as: Diaz et al.: A consensus linkage map for molecularmarkers and Quantitative Trait Loci associated with economicallyimportant traits in melon (Cucumis melo L.). BMC Plant Biology 201111:111.

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Diaz et al. BMC Plant Biology 2011, 11:111http://www.biomedcentral.com/1471-2229/11/111

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