Theoretical and Applied Genetics

, Volume 130, Issue 5, pp 875–889 | Cite as

Use of modern tomato breeding germplasm for deciphering the genetic control of agronomical traits by Genome Wide Association study

  • Guillaume Bauchet
  • Stéphane Grenier
  • Nicolas Samson
  • Julien Bonnet
  • Laurent Grivet
  • Mathilde Causse
Original Article


Key message

A panel of 300 tomato accessions including breeding materials was built and characterized with >11,000 SNP. A population structure in six subgroups was identified. Strong heterogeneity in linkage disequilibrium and recombination landscape among groups and chromosomes was shown. GWAS identified several associations for fruit weight, earliness and plant growth.


Genome-wide association studies (GWAS) have become a method of choice in quantitative trait dissection. First limited to highly polymorphic and outcrossing species, it is now applied in horticultural crops, notably in tomato. Until now GWAS in tomato has been performed on panels of heirloom and wild accessions. Using modern breeding materials would be of direct interest for breeding purpose. To implement GWAS on a large panel of 300 tomato accessions including 168 breeding lines, this study assessed the genetic diversity and linkage disequilibrium decay and revealed the population structure and performed GWA experiment. Genetic diversity and population structure analyses were based on molecular markers (>11,000 SNP) covering the whole genome. Six genetic subgroups were revealed and associated to traits of agronomical interest, such as fruit weight and disease resistance. Estimates of linkage disequilibrium highlighted the heterogeneity of its decay among genetic subgroups. Haplotype definition allowed a fine characterization of the groups and their recombination landscape revealing the patterns of admixture along the genome. Selection footprints showed results in congruence with introgressions. Taken together, all these elements refined our knowledge of the genetic material included in this panel and allowed the identification of several associations for fruit weight, plant growth and earliness, deciphering the genetic architecture of these complex traits and identifying several new loci useful for tomato breeding.


Linkage Disequilibrium Genetic Group Fruit Weight Linkage Disequilibrium Decay Best Linear Unbiased Predictor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank the CRBLeg group in INRA for providing accessions and Stephane Deville and Sandrine Paulin for genotyping. Syngenta and Association Française pour la Recherche et la Technologie (ANRT) funded this work.

Compliance with ethical standards

Conflict of interest

Authors declared no conflict of interest in the authorship and publication of this document.

Supplementary material

122_2017_2857_MOESM1_ESM.xlsx (50 kb)
Supplementary material 1 (XLSX 50 KB)
122_2017_2857_MOESM2_ESM.pptx (20.2 mb)
Supplementary material 2 (PPTX 20643 KB)


  1. Abbo S, Pinhasi van-Oss R, Gopher A, Saranga Y, Ofner I, Peleg Z (2014) Plant domestication versus crop evolution: a conceptual framework for cereals and grain legumes. Trends Plant Sci 19:351–360PubMedCrossRefGoogle Scholar
  2. Aflitos S, Schijlen E, de Jong H, de Ridder D, Smit S, Finkers R, Wang J, Zhang G, Li N, Mao L et al (2014) Exploring genetic variation in the tomato (Solanum section Lycopersicon) clade by whole-genome sequencing. Plant J 80:136–148PubMedCrossRefGoogle Scholar
  3. Akey JM, Zhang K, Xiong M, Jin L (2003) The effect of single nucleotide polymorphism identification strategies on estimates of linkage disequilibrium. Mol Biol Evol 20(2):232–242PubMedCrossRefGoogle Scholar
  4. Albrechtsen A, Nielsen FC, Nielsen R (2010) Ascertainment biases in SNP chips affect measures of population divergence. Mol Biol Evol 27(11):2534–2547PubMedPubMedCentralCrossRefGoogle Scholar
  5. Alseekh S, Ofner I, Pleban T, Tripodi P, Di Dato F, Cammareri M, Mohammad A, Grandillo S, Fernie AR, Zamir D (2013) Resolution by recombination: breaking up Solanum pennellii introgressions. Trends Plant Sci 18:536–538PubMedCrossRefGoogle Scholar
  6. Arnold B, Corbett-Detig RB, Hartl D, Bomblies K (2013) RADseq underestimates diversity and introduces genealogical biases due to nonrandom haplotype sampling. Mol Ecol 22(11):3179–3190PubMedCrossRefGoogle Scholar
  7. Astle W, Balding DJ (2009) Population structure and cryptic relatedness in genetic association studies. Stat Sci 24(4):451–471CrossRefGoogle Scholar
  8. Barb JG, Bowers JE, Renaut S, Rey JI, Knapp SJ, Rieseberg LH, Burke JM (2014) Chromosomal evolution and patterns of introgression in Helianthus. Genetics 197(3):969–979PubMedPubMedCentralCrossRefGoogle Scholar
  9. Bastian M, Heymann S, Jacomy M (2009) Gephi: an open source software for exploring and manipulating networks. ICWSM 8:362Google Scholar
  10. Bates DM, Watts DG (2008) Nonlinear regression analysis and its applications. Wiley, HobokenGoogle Scholar
  11. Bauchet G, Causse M (2012) Genetic diversity in tomato (Solanum lycopersicum) and its wild relatives. In: Genetic diversity in plants. PMC: InTechGoogle Scholar
  12. Bauchet G, Munos S, Sauvage C, Bonnet J, Grivet L, Causse M (2014) Genes involved in floral meristem in tomato exhibit drastically reduced genetic diversity and signature of selection. BMC Plant Biol 14:279PubMedPubMedCentralCrossRefGoogle Scholar
  13. Bi K, Vanderpool D, Singhal S, Linderoth T, Moritz C, Good J (2012) Transcriptome-based exon capture enables highly cost-effective comparative genomic data collection at moderate evolutionary scales. BMC Genom 13(1):403CrossRefGoogle Scholar
  14. Blanca J, Montero-Pau J, Sauvage C, Bauchet G, Illa E, Diez MJ, Francis D, Causse M, van der Knaap E, Cañizares J (2015) Genomic variation in the tomato, from wild ancestors to contemporary breeding accessions. BMC Genom 16:257. doi: 10.1186/s12864-015-1444-1 CrossRefGoogle Scholar
  15. Breseghello F, Sorrells ME (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genet 172(2):1165–1177CrossRefGoogle Scholar
  16. Cao Y, Tang X, Giovannoni J, Xiao F, Liu Y (2012) Functional characterization of a tomato COBRA-like gene functioning in fruit development and ripening. BMC Plant Biol 12:211PubMedPubMedCentralCrossRefGoogle Scholar
  17. Casals J, Pascual L, Cañizares J, Cebolla-Cornejo J, Casañas F, Nuez F (2011) The risks of success in quality vegetable markets: possible genetic erosion in Marmande tomatoes (Solanum lycopersicum L.) and consumer dissatisfaction. Sci Hortic 130(1):78–84CrossRefGoogle Scholar
  18. Causse M, Friguet C, Coiret C, Lépicier M, Navez B, Lee M, Holthuysen N, Sinesio F, Moneta E, Grandillo S (2010) Consumer preferences for fresh tomato at the European scale: a common segmentation on taste and firmness. J Food Sci 75(9):S531–S541PubMedCrossRefGoogle Scholar
  19. Causse M, Desplat N, Pascual L, Le Paslier M-C, Sauvage C, Bauchet G, Berard A, Bounon R, Tchoumakov M, Brunel D, Bouchet JP (2013) Whole genome resequencing in tomato reveals variation associated with introgression and breeding events. BMC Genom 14(1):791CrossRefGoogle Scholar
  20. Chakrabarti M, Zhang N, Sauvage C, Munos S, Blanca J, Canizares J, Diez MJ, Schneider R, Mazurek M, McClead J, Causse M, van der Knaap E (2013) A cytochrome P450 CYP78A regulates a domestication trait in tomato (Solanum lycopersicum). Proc Natl Acad Sci USA PNAS 110(42):17125–17130PubMedCrossRefGoogle Scholar
  21. Chen A-L, Liu C-Y, Chen C-H, Wang J-F, Liao Y-C, Chang C-H, Tsai M-H, Hwu K-K, Chen K-Y (2014) Reassessment of QTLs for late blight resistance in the tomato accession L3708 using a restriction site associated DNA (RAD) linkage map and highly aggressive isolates of Phytophthora infestans. PLoS One 9(5):e96417PubMedPubMedCentralCrossRefGoogle Scholar
  22. Consortium TGP (2012) An integrated map of genetic variation from 1,092 human genomes. Nature 491(7422):56–65CrossRefGoogle Scholar
  23. Corrado G, Piffanelli P, Caramante M, Coppola M, Rao R (2013) SNP genotyping reveals genetic diversity between cultivated landraces and contemporary varieties of tomato. BMC Genom 14(1):835CrossRefGoogle Scholar
  24. Desta ZA, Ortiz R (2014) Genomic selection: genome-wide prediction in plant improvement. Trends Plant Sci 19(9):592–601PubMedCrossRefGoogle Scholar
  25. Dixon MS, Jones DA, Keddie JS, Thomas CM, Harrison K, Jones JDG (1996) The tomato Cf-2 disease resistance locus comprises two functional genes encoding Leucine-Rich repeat proteins. Cell 84:451–459PubMedCrossRefGoogle Scholar
  26. Doebley JF, Gaut BS, Smith BD (2006) The molecular genetics of crop domestication. Cell 127(7):1309–1321PubMedCrossRefGoogle Scholar
  27. Duangjit J, Causse M, Sauvage C (2016) Efficiency of genomic selection for tomato fruit quality. Mol Breed. doi: 10.1007/s11032-016-0453-3 Google Scholar
  28. Ersoz E, Yu J, Buckler E (2007) Applications of linkage disequilibrium and association mapping in crop plants. In: Varshney R, Tuberosa R (eds) Genomics-assisted crop improvement. Springer, Netherlands, p 97–119CrossRefGoogle Scholar
  29. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14(8):2611–2620PubMedCrossRefGoogle Scholar
  30. Excoffier L, Dupanloup I, Huerta-Sánchez E, Sousa VC, Foll M (2013) Robust demographic inference from genomic and SNP data. PLoS Genet 9(10):e1003905PubMedPubMedCentralCrossRefGoogle Scholar
  31. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–87PubMedPubMedCentralGoogle Scholar
  32. Fernandez-Pozo N, Menda M, Edwards JD, Saha S, Tecle IY, Strickler SR, Bombarely A, Fisher-York T, Pujar A, Foerster H, Yan A, Mueller LA (2014) The Sol Genomics Network (SGN)—from genotype to phenotype to breeding. Nucl Acids Res. doi: 10.1093/nar/gku1195 (first published online 26 Nov 2014) PubMedPubMedCentralGoogle Scholar
  33. Foll M, Gaggiotti O (2008) A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180(2):977–993PubMedPubMedCentralCrossRefGoogle Scholar
  34. Fraïsse C, Roux C, Welch JJ, Bierne N (2014) Gene-flow in a mosaic hybrid zone: is local introgression adaptive? Genetics 197(3):939–951PubMedPubMedCentralCrossRefGoogle Scholar
  35. Frary A, Nesbitt TC, Frary A, Grandillo S, Van Der Knaap E, Cong B et al (2000) fw2.2: a quantitative trait locus key to the evolution of tomato fruit size. Science 289(5476):85–88PubMedCrossRefGoogle Scholar
  36. Fridman E, Zamir D (2012) Next-generation education in crop genetics. Curr Opin Plant Biol 15(2):218–223PubMedCrossRefGoogle Scholar
  37. Gautier M, Vitalis R (2013) Inferring population histories using genome-wide allele frequency data. Mol Biol Evol 30(3):654–668PubMedCrossRefGoogle Scholar
  38. Hajjar R, Hodgkin T (2007) The use of wild relatives in crop improvement: a survey of developments over the last 20 years. Euphytica 156(1–2):1–13CrossRefGoogle Scholar
  39. Hamilton JP, Sim S-C, Stoffel K, Van Deynze A, Buell CR, Francis DM (2012) Single nucleotide polymorphism discovery in cultivated tomato via sequencing by synthesis. Plant Gen 5(1):17–29CrossRefGoogle Scholar
  40. Harlan JR (1971) Agricultural origins: centers and noncenters. Science 174(4008):468–474PubMedCrossRefGoogle Scholar
  41. Hellenthal G, Busby GBJ, Band G, Wilson JF, Capelli C, Falush D, Myers S (2014) A genetic atlas of human admixture history. Science 343(6172):747–751PubMedPubMedCentralCrossRefGoogle Scholar
  42. Hill WG, Robertson A (1968) Linkage disequilibrium in finite populations. Theor Appl Genet 38:226–231PubMedCrossRefGoogle Scholar
  43. Hill WG, Weir BS (1988) Variances and covariances of squared linkage disequilibria in finite populations. Theor Popul Biol 33(1):54–78PubMedCrossRefGoogle Scholar
  44. Hufford MB, Lubinksy P, Pyhäjärvi T, Devengenzo MT, Ellstrand NC, Ross-Ibarra J (2013) The genomic signature of crop-wild introgression in maize. PLoS Genet 9(5):e1003477PubMedPubMedCentralCrossRefGoogle Scholar
  45. Jiang K, Liberatore KL, Park SJ, Alvarez JP, Lippman ZB (2013) Tomato yield heterosis is triggered by a dosage sensitivity of the florigen pathway that fine-tunes shoot architecture. PLoS Genet 9(12):e1004043PubMedPubMedCentralCrossRefGoogle Scholar
  46. Jombart T, Devillard S, Balloux F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet 11(1):94PubMedPubMedCentralCrossRefGoogle Scholar
  47. Jonas E, de Koning DJ (2013) Does genomic selection have a future in plant breeding?. Trends Biotechnol 31: 497–504CrossRefGoogle Scholar
  48. Kaloshian I, Yaghoobi J, Liharska T, Hontelez J, Hanson D, Hogan P, Jesse T, Wijbrandi J, Simons G, Vos P et al (1998) Genetic and physical localization of the root-knot nematode resistance locus Mi in tomato. Mol Gen Genet MGG 257(3):376–385PubMedCrossRefGoogle Scholar
  49. Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E (2008) Efficient control of population structure in model organism association mapping. Genetics 178(3):1709–1723PubMedPubMedCentralCrossRefGoogle Scholar
  50. Kawchuk LM, Hachey J, Lynch DR, Kulcsar F, van Rooijen G, Waterer DR, Robertson A, Kokko E, Byers R, Howard RJ et al (2001) Tomato Ve disease resistance genes encode cell surface-like receptors. Proc Natl Acad Sci 98(11):6511–6515PubMedPubMedCentralCrossRefGoogle Scholar
  51. Koenig D, Jiménez-Gómez JM, Kimura S, Fulop D, Chitwood DH, Headland LR, Kumar R, Covington MF, Devisetty UK, Tat AV, Tohge T, Bolger A, Schneeberger K, Ossowski S, Lanz C, Xiong G, Taylor-Teeples M, Brady SM, Pauly M, Weigel D, Usadel B, Fernie AR, Peng J, Sinha NR, Maloof JN (2013) Comparative transcriptomics reveals patterns of selection in domesticated and wild tomato. Proc Natl Acad Sci 110:2655–2662CrossRefGoogle Scholar
  52. Korte A, Farlow A (2013) The advantages and limitations of trait analysis with GWAS: a review. Plant Methods 9(1):29PubMedPubMedCentralCrossRefGoogle Scholar
  53. Korte A, Vilhjalmsson BJ, Segura V, Platt A, Long Q, Nordborg M (2012) A mixed-model approach for genome-wide association studies of correlated traits in structured populations. Nat Genet 44(9):1066–1071PubMedPubMedCentralCrossRefGoogle Scholar
  54. Labate J, Robertson L (2012) Evidence of cryptic introgression in tomato (Solanum lycopersicum L.) based on wild tomato species alleles. BMC Plant Biol 12(1):133PubMedPubMedCentralCrossRefGoogle Scholar
  55. Labate J, Grandillo S, Fulton T, Muños S, Caicedo A, Peralta I, Ji Y, Chetelat R, Scott JW, Gonzalo MJ, Francis D, Yang W, van der Knaap E, Baldo AM, Smith-White B, Mueller LA, Prince JP, Blanchard NE, Storey DB, Stevens MR, Robbins MD, Fen Wang J, Liedl BE, O’Connell MA, Stommel JR, Aoki K, Iijima Y, Slade, Hurst SR, Loeffler D, Steine MN, Vafeados D, McGuire C, Freeman C, Amen A, Goodstal J, Facciotti D, Van Eck J, Causse M (2007) 1 Tomato. In: Kole C (ed) Genome mapping and molecular breeding in plants, volume 5, vegetables. Springer-Verlag, Berlin, p 11–135Google Scholar
  56. Labate JA, Robertson LD, Strickler SR, Mueller LA (2014) Genetic structure of the four wild tomato species in the Solanum peruvianum s.l. species complex. Genome 57(3):169–180PubMedCrossRefGoogle Scholar
  57. Lachance J, Tishkoff SA (2013) SNP ascertainment bias in population genetic analyses: why it is important, and how to correct it. Bioessays 35(9):780–786PubMedPubMedCentralCrossRefGoogle Scholar
  58. Lanfermeijer F, Dijkhuis J, Sturre MG, de Haan P, Hille J (2003) Cloning and characterization of the durable tomato mosaic virus resistance gene Tm-22 from Lycopersicon esculentum. Plant Mol Biol 52(5):1039–1051CrossRefGoogle Scholar
  59. Lawson DJ, Falush D (2012) Population identification using genetic data. Annu Rev Genom Hum Genet 13(1):337–361CrossRefGoogle Scholar
  60. Lawson DJ, Hellenthal G, Myers S, Falush D (2012) Inference of population structure using dense haplotype data. PLoS Genet 8(1):e1002453PubMedPubMedCentralCrossRefGoogle Scholar
  61. Li N, Stephens M (2003) Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics 165(4):2213–2233PubMedPubMedCentralGoogle Scholar
  62. Lin T, Zhu G, Zhang J, Xu X, Yu Q, Zheng Z, Zhang Z, Lun Y, Li S, Wang X et al (2014) Genomic analyses provide insights into the history of tomato breeding. Nat Genet 46:1220–1226PubMedCrossRefGoogle Scholar
  63. Martin G, Brommonschenkel S, Chunwongse J, Frary A, Ganal M, Spivey R, Wu T, Earle E, Tanksley S (1993) Map-based cloning of a protein kinase gene conferring disease resistance in tomato. Science 262(5138):1432–1436PubMedCrossRefGoogle Scholar
  64. McCouch S, Baute GJ, Bradeen J, Bramel P, Bretting PK, Buckler E, Burke JM, Charest D, Cloutier S, Cole G et al (2013) Agriculture: feeding the future. Nature 499(7456):23–24PubMedCrossRefGoogle Scholar
  65. McGill JR, Walkup EA, Kuhner MK (2013) Correcting coalescent analyses for panel-based SNP ascertainment. Genetics 193(4):1185–1196PubMedPubMedCentralCrossRefGoogle Scholar
  66. Meyer RS, Purugganan MD (2013) Evolution of crop species: genetics of domestication and diversification. Nat Rev Genet 14(12):840–852PubMedCrossRefGoogle Scholar
  67. Michalak P, Zhao K, Wright M, Kimball J, Eizenga G, McClung A, Kovach M, Tyagi W, Ali ML, Tung C-W et al (2010) Genomic Diversity and Introgression in O. sativa reveal the impact of domestication and breeding on the rice genome. PLoS One 5(5):e10780CrossRefGoogle Scholar
  68. Monforte AJ, Diaz AI, Caño-Delgado A, van der Knaap E (2014) The genetic basis of fruit morphology in horticultural crops: lessons from tomato and melon. J Exp Bot 65:4625–4637PubMedCrossRefGoogle Scholar
  69. Nielsen R, Signorovitch J (2003) Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium. Theor Popul Biol 63(3):245–255PubMedCrossRefGoogle Scholar
  70. Pfeifer B, Wittelsbürger U, Ramos Onsins SE, Lercher MJ (2014) PopGenome: an efficient swiss army knife for population genomic analyses in R. Mol Biol Evol 31:1929–1936PubMedPubMedCentralCrossRefGoogle Scholar
  71. Pritchard JK, Stephens P, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  72. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ et al (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81(3):559–575PubMedPubMedCentralCrossRefGoogle Scholar
  73. Ranc N, Muños S, Xu J, Le Paslier MC, Chauveau A, Bounon R, Rolland S, Bouchet JP, Brunel D, Causse M (2012) Genome-wide association mapping in tomato (Solanum lycopersicum) is possible using genome admixture of Solanum lycopersicum var. cerasiforme. G3 2:853–864PubMedPubMedCentralCrossRefGoogle Scholar
  74. Rincent R, Moreau L, Monod H, Kuhn E, Melchinger AE, Malvar RA, Moreno-Gonzalez J, Nicolas S, Madur D, Combes V, Dumas F, Altmann T, Brunel D, Ouzunova M, Flament P, Dubreuil P, Charcosset A, Mary-Huard T (2014) Recovering power in association mapping panels with variable levels of linkage disequilibrium. Genetics 197(1):375–387PubMedPubMedCentralCrossRefGoogle Scholar
  75. Sacco A, Ruggieri V, Parisi M, Festa G, Rigano MM, Picarella ME et al (2015) Exploring a tomato landraces collection for fruit-related traits by the aid of a high-throughput genomic platform. PLoS One 10(9):e0137139. doi: 10.1371/journalpone.0137139 PubMedPubMedCentralCrossRefGoogle Scholar
  76. Sarah G, Homa F, Pointet S, Contreras S, Sabot F, Nabholz B, Santoni S, Sauné L, Ardisson M, Chantret N, Sauvage C, Tregear J, Jourda C, Pot D, Vigouroux Y, Chair H, Scarcelli N, Billot C, Yahiaoui N, Bacilieri R, Khadari B, Boccara M, Barnaud A, Péros J-P, Labouisse J-P, Pham J-L, David J, Glémin S, Ruiz M (2016) A large set of 26 new reference transcriptomes dedicated to comparative population genomics in crops and wild relatives. Mol Ecol Resour. doi: 10.1111/1755-0998.12587 PubMedGoogle Scholar
  77. Sauvage C, Segura V, Bauchet G, Stevens R, Thi Do P, Nikoloski Z, Fernie AR, Causse M (2014) Genome Wide Association in tomato reveals 44 candidate loci for fruit metabolic traits. Plant Physiol 165(3):1120–1132PubMedPubMedCentralCrossRefGoogle Scholar
  78. Scheet P, Stephens M (2006) A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet 78(4):629–644PubMedPubMedCentralCrossRefGoogle Scholar
  79. Seeb JE, Carvalho G, Hauser L, Naish K, Roberts S, Seeb LW (2011) Single-nucleotide polymorphism (SNP) discovery and applications of SNP genotyping in nonmodel organisms. Mol Ecol Resour 11:1–8PubMedCrossRefGoogle Scholar
  80. Segura V, Vilhjalmsson BJ, Platt A, Korte A, Seren U, Long Q, Nordborg M (2012) An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nat Genet 44(7):825–830PubMedPubMedCentralCrossRefGoogle Scholar
  81. Sim S-C, Van Deynze A, Stoffel K, Douches DS, Zarka D, Ganal MW, Chetelat RT, Hutton SF, Scott JW, Gardner RG et al (2012a) High-density SNP genotyping of tomato reveals patterns of genetic variation due to breeding. PLoS One 7(9):e45520PubMedPubMedCentralCrossRefGoogle Scholar
  82. Sim S-C, Durstewitz G, Plieske J, Wieseke R, Ganal MW, Van Deynze A, Hamilton JP, Buell CR, Causse M, Wijeratne S et al (2012b) Development of a large SNP genotyping array and generation of high-density genetic maps in tomato. PLoS One 7(7):e40563PubMedPubMedCentralCrossRefGoogle Scholar
  83. Speed D, Hemani G, Johnson Michael R, Balding David J (2012) Improved heritability estimation from genome-wide SNPs. Am J Hum Genet 91(6):1011–1021PubMedPubMedCentralCrossRefGoogle Scholar
  84. Suárez-López P, Wheatley K, Robson F, Onouchi H, Valverde F, Coupland G (2001) CONSTANS mediates between the circadian clock and the control of flowering in Arabidopsis. Nature 410:1116–1120PubMedCrossRefGoogle Scholar
  85. Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123(3):585–595PubMedPubMedCentralGoogle Scholar
  86. Tanksley SD, McCouch SR (1997) Seed banks and molecular maps: unlocking genetic potential from the wild. Science 277(5329):1063–1066PubMedCrossRefGoogle Scholar
  87. Tanksley SD, Ganal MW, Prince JP, de Vicente MC, Bonierbale MW, Broun P, Fulton TM, Giovannoni JJ, Grandillo S, Martin GB et al (1992) High density molecular linkage maps of the tomato and potato genomes. Genetics 132(4):1141–1160PubMedPubMedCentralGoogle Scholar
  88. Tomato Genome Consortium (2012) The tomato genome sequence provides insights into fleshy fruit evolution. Nature 485(7400):635–641CrossRefGoogle Scholar
  89. van Berloo R (2008) GGT 2.0: versatile software for visualization and analysis of genetic data. J Hered 99(2):232–236PubMedCrossRefGoogle Scholar
  90. Van Deynze A, Stoffel K, Buell CR, Kozik A, Liu J, van der Knaap E, Francis D (2007) Diversity in conserved genes in tomato. BMC Genom 8(1):465CrossRefGoogle Scholar
  91. Varshney RK, Ribaut J-M, Buckler ES, Tuberosa R, Rafalski JA, Langridge P (2012) Can genomics boost productivity of orphan crops? Nat Biotech 30(12):1172–1176CrossRefGoogle Scholar
  92. Verlaan MG, Hutton SF, Ibrahem RM, Kormelink R, Visser RGF, Scott JW, Edwards JD, Bai Y (2013) The tomato yellow leaf curl virus resistance genes Ty-1 and Ty-3 are allelic and code for DFDGD-class RNA–dependent RNA polymerases. PLoS Genet 9(3):e1003399PubMedPubMedCentralCrossRefGoogle Scholar
  93. Viquez-Zamora M, Vosman B, van de Geest H, Bovy A, Visser R, Finkers R, van Heusden A (2013) Tomato breeding in the genomics era: insights from a SNP array. BMC Genom 14(1):354CrossRefGoogle Scholar
  94. Waugh R, Francki M, Marshall D, Thomas B, Comadran J, Russell J, Close T, Stein N, Hayes P, Muehlbauer G, Cockram J, O’Sullivan D, Mackay I, Flavell A, Ramsay L (2010) Whole-genome association mapping in elite inbred crop varieties. Genome 53(11):967–972PubMedCrossRefGoogle Scholar
  95. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evol Int J org Evol 38(6):1358–1370CrossRefGoogle Scholar
  96. Xu X, Liu X, Ge S, Jensen JD, Hu F, Li X, Dong Y, Gutenkunst RN, Fang L, Huang L et al (2012) Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes. Nat Biotechnol 30(1):105–111CrossRefGoogle Scholar
  97. Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38(2):203–208PubMedCrossRefGoogle Scholar
  98. Zamir D (2008) Plant breeders go back to nature. Nat Genet 40(3):269–270PubMedCrossRefGoogle Scholar
  99. Zamir D, Ekstein-Michelson I, Zakay Y, Navot N, Zeidan M, Sarfatti M, Eshed Y, Harel E, Pleban T, van-Oss H et al (1994) Mapping and introgression of a tomato yellow leaf curl virus tolerance gene, TY-1. Theor Appl Genet 88(2):141–146PubMedCrossRefGoogle Scholar
  100. Zhang C, Liu L, Zheng Z, Sun Y, Zhou L, Yang Y, Cheng F, Zhang Z, Wang X, Huang S et al (2013) Fine mapping of the Ph-3 gene conferring resistance to late blight (Phytophthora infestans) in tomato. Theor Appl Genet 126(10):2643–2653PubMedCrossRefGoogle Scholar
  101. Zheng X, Levine D, Shen J, Gogarten SM, Laurie C, Weir BS (2012) A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 28(24):3326–3328PubMedPubMedCentralCrossRefGoogle Scholar
  102. Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome J 1(1):5CrossRefGoogle Scholar
  103. Zuriaga E, Blanca JM, Cordero L, Sifres A, Blas-Cerdán WG, Morales R, Nuez F (2008) Genetic and bioclimatic variation in Solanum pimpinellifolium. Genet Resour Crop Evol 56(1):39–51CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Guillaume Bauchet
    • 1
    • 2
    • 3
  • Stéphane Grenier
    • 1
  • Nicolas Samson
    • 1
  • Julien Bonnet
    • 1
  • Laurent Grivet
    • 1
  • Mathilde Causse
    • 2
  1. 1.Syngenta SeedsSaint SauveurFrance
  2. 2.INRA, UR1052, Centre de Recherche PACA, GAFLMontfavet CedexFrance
  3. 3.Boyce Thompson InstituteCornell UniversityIthacaUSA

Personalised recommendations