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Tracing the ancestry of modern bread wheats


For more than 10,000 years, the selection of plant and animal traits that are better tailored for human use has shaped the development of civilizations. During this period, bread wheat (Triticum aestivum) emerged as one of the world’s most important crops. We use exome sequencing of a worldwide panel of almost 500 genotypes selected from across the geographical range of the wheat species complex to explore how 10,000 years of hybridization, selection, adaptation and plant breeding has shaped the genetic makeup of modern bread wheats. We observe considerable genetic variation at the genic, chromosomal and subgenomic levels, and use this information to decipher the likely origins of modern day wheats, the consequences of range expansion and the allelic variants selected since its domestication. Our data support a reconciled model of wheat evolution and provide novel avenues for future breeding improvement.

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Fig. 1: Wheat genome diversity map.
Fig. 2: Geographical components of the panel structure.
Fig. 3: Temporal evolution of wheat diversity.
Fig. 4: Model of reticulated evolution.

Data Availability

All data analyzed and generated during this study are included in this published article and its supplementary information files (6 tables and 13 figures) and are available online at (the catalog of imputed and non-imputed variants as a vcf file and passport information for the 487 genotypes as an .xls file). The Whealbi SNP data are open access and can be viewed in the IWGSC reference genome browser54 at The sequence data are available at NCBI under the accession number PRJNA524104.


  1. Feldman, M. & Levy, A. A. Genome evolution due to allopolyploidization in wheat. Genetics 192, 763–774 (2012).

    Article  CAS  Google Scholar 

  2. Tanno, K. & Willcox, G. How fast was wild wheat domesticated? Science 311, 1886 (2006).

    Article  CAS  Google Scholar 

  3. Brown, T. A., Jones, M. K., Powell, W. & Allaby, R. G. The complex origins of domesticated crops in the Fertile Crescent. Trends Ecol. Evol. 24, 103–109 (2009).

    Article  Google Scholar 

  4. Bocquet-Appel, J. P., Naji, S., Vander Linden, M. & Kozlowski, J. K. Detection of diffusion and contact zones of early farming in Europe from the space-time distribution of 14C dates. J. Archaeol. Sci. 36, 807–820 (2009).

    Article  Google Scholar 

  5. Szécsényi-Nagy, A., Brandt, G., Keerl, V., Jakucs, J. & Haak, W. Tracing the genetic origin of Europe’s first farmers reveals insights into their social organization. Proc. R. Soc. B. 282, 20150339 (2015).

    Article  Google Scholar 

  6. Damania, A. B. et al. (eds) The Origin of Agriculture and Crop Domestication (ICARDA, 1997).

  7. Warr, A. et al. Exome sequencing: current and future perspectives. G3 (Bethesda) 5, 1543–1550 (2015).

    Article  Google Scholar 

  8. The International Wheat Genome Sequencing Consortium (IWGSC) et al. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361, eaar7191 (2018).

  9. Matsuoka, Y. Evolution of polyploid triticum wheats under cultivation: the role of domestication, natural hybridization and allopolyploid speciation in their diversification. Plant Cell Physiol. 52, 750–764 (2011).

    Article  CAS  Google Scholar 

  10. Gao, L., Zhao, G., Huang, D. & Jia, J. Candidate loci involved in domestication and improvement detected by a published 90K wheat SNP array. Sci. Rep. 7, 44530 (2017).

    Article  CAS  Google Scholar 

  11. Wright, S. I. et al. The effects of artificial selection on the maize genome. Science 308, 1310–1314 (2005).

    Article  CAS  Google Scholar 

  12. Luu, K., Bazin, E. & Blum, M. G. pcadapt: an R package to perform genome scans for selection based on principal component analysis. Mol. Ecol. Resour. 17, 67–77 (2017).

    Article  CAS  Google Scholar 

  13. Jordan, K. W., Wang, S., Lun, Y., Gardiner, L. J., MacLachlan, R. A haplotype map of allohexaploid wheat reveals distinct patterns of selection on homoeologous genomes. Genome Biol. 16, 48 (2015).

  14. Cavanagh, C. R. et al. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc. Natl Acad. Sci. USA 110, 8057–8062 (2013).

    Article  CAS  Google Scholar 

  15. Joukhadar, R., Daetwyler, H. D., Bansal, U. K., Gendall, A. R. & Hayden, M. J. Genetic diversity, population structure and ancestral origin of Australian wheat. Front. Plant Sci. 8, 2115 (2017).

    Article  Google Scholar 

  16. Nielsen, N. H., Backes, G., Stougaard, J., Andersen, S. U. & Jahoor, A. Genetic diversity and population structure analysis of European hexaploid bread wheat (Triticum aestivum L.) varieties. PLoS ONE 9, e94000 (2014).

    Article  Google Scholar 

  17. Devos, K. M., Dubcovsky, J., Dvorak, J., Chinoy, C. N. & Gale, M. D. Structural evolution of wheat chromosomes 4A, 5A, and 7B and its impact on recombination. Theor. Appl. Genet. 91, 282–288 (1995).

    Article  CAS  Google Scholar 

  18. Nadolska-Orczyk, A., Rajchel, I. K., Orczyk, W. & Gasparis, S. Major genes determining yield-related traits in wheat and barley. Theor. Appl. Genet. 130, 1081–1098 (2017).

    Article  CAS  Google Scholar 

  19. Gardiner, L. J. et al. Hidden variation in polyploid wheat drives local adaptation. Genome Res. 28, 1319–1332 (2018).

    Article  CAS  Google Scholar 

  20. Lischer, H. E., Excoffier, L. & Heckel, G. Ignoring heterozygous sites biases phylogenomic estimates of divergence times: implications for the evolutionary history of microtus voles. Mol. Biol. Evol. 31, 817–831 (2014).

    Article  CAS  Google Scholar 

  21. Nguyen, L. T., Schmidt, H. A., Von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).

    Article  CAS  Google Scholar 

  22. Martin, S. H., Davey, J. W., Jiggins, C. D. Evaluating the use of ABBA-BABA statistics to locate introgressed loci. Mol. Biol. Evol. 32, 244–257 (2015).

    Article  Google Scholar 

  23. Ben-David, R. et al. Dissection of powdery mildew resistance uncovers different resistance types in the T. turgidum L. gene pool. in 11th Int. Wheat Genetics Symposium (Sydney University Press, 2008).

  24. El Baidouri, M., Murat, F., Veyssiere, M., Molinier, M. & Flores, R. Reconciling the evolutionary origin of bread wheat (Triticum aestivum). New Phytol. 213, 1477–1486 (2017).

    Article  CAS  Google Scholar 

  25. Balint, A. F., Kovacs, G. & Sutka, J. Origin and taxonomy of wheat in the light of recent research. Acta Agronomica Hungarica 48, 301–313 (2000).

    Article  Google Scholar 

  26. Nesbitt, M. & Samuel, D. From staple crop to extinction: the archaeology and history of the hulled wheats. in Proc. 1st International Workshop on Hulled Wheats (International Plant Genetic Resources Institute, 1996).

  27. Civáň, P., Ivaničová, Z. & Brown, T. A. Reticulated origin of domesticated emmer wheat supports a dynamic model for the emergence of agriculture in the fertile crescent. PLoS ONE 8, e81955 (2013).

    Article  Google Scholar 

  28. Luo, M. C., Yang, Z. L., You, F. M., Kawahara, T. & Waines, J. G. The structure of wild and domesticated emmer wheat populations, gene flow between them, and the site of emmer domestication. Theor. Appl. Genet. 114, 947–959 (2007).

    Article  Google Scholar 

  29. Matsuoka, Y. & Nasuda, S. Durum wheat as a candidate for the unknown female progenitor of bread wheat: an empirical study with a highly fertile F1 hybrid with Aegilops tauschii Coss. Theor Appl Genet. 109, 1710–1717 (2004). Epub 2004 Sep 22.

    Article  Google Scholar 

  30. Wang, J., Luo, M. C., Chen, Z., You, F. M. & Wei, Y. Aegilops tauschii single nucleotide polymorphisms shed light on the origins of wheat D-genome genetic diversity and pinpoint the geographic origin of hexaploid wheat. New Phytol. 198, 925–937 (2013).

    Article  CAS  Google Scholar 

  31. Minh, B. Q., Nguyen, M. A. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol. 30, 1188–1195 (2013).

    Article  CAS  Google Scholar 

  32. Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).

    Article  Google Scholar 

  33. Kucera, M. et al. AutoAnnotate: a Cytoscape app for summarizing networks with semantic annotations. F1000 Res. 5, 1717 (2016).

    Article  Google Scholar 

  34. Korneliussen, ThorfinnSand, Albrechtsen, Anders & Nielsen, Rasmus ANGSD: analysis of next generation sequencing data. BMC Bioinformatics 15, 356 (2014).

    Article  Google Scholar 

  35. Durand, E. Y., Patterson, N., Reich, D. & Slatkin, M. Testing for ancient admixture between closely related populations. Mol. Biol. Evol. 28, 2239–2252 (2011).

    Article  CAS  Google Scholar 

  36. Lê, S. et al. FactoMineR: an R package for multivariate analysis. J. Stat. Soft. 25, 1–18 (2008).

    Article  Google Scholar 

  37. R. Core Team. R: a Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2014).

  38. Chipman, H. & Tibshirani, R. Hybrid hierarchical clustering with applications to microarray data. Biostatistics 7, 286–301 (2006).

    Article  Google Scholar 

  39. Schmidtlein, S., Tichy, L., Hannes, F. & Ulrike, F. A brute-force approach to vegetation classification. J. Veg. Sci. 21, 1162–1171 (2010).

    Article  Google Scholar 

  40. Witten, D. M. & Tibshirani, R. A framework for feature selection in clustering. J. Am. Stat. Assoc. 105, 713–726 (2010).

    Article  CAS  Google Scholar 

  41. Galili, T. dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics 31, 3718–3720 (2015).

    Article  CAS  Google Scholar 

  42. Rodríguez-Álvarez, M. X., Boer, M. P., van Eeuwijk, F. A. & Eilers, P. H. Correcting for spatial heterogeneity in plant breeding experiments with P-splines. Spatial Stat. 23, 52–71 (2017).

    Article  Google Scholar 

  43. Gu, Z., Gu, L., Eils, R., Schlesner, M. & Brors, B. irclize implements and enhances circular visualization in R. Bioinformatics 30, 2811–2812 (2014).

    Article  CAS  Google Scholar 

  44. Rincent, R. et al. Recovering power in association mapping panels with variable levels of linkage disequilibrium. Genetics 197, 375–387 (2014).

    Article  Google Scholar 

  45. Astle, W. & Balding, D. J. Population structure and cryptic relatedness in genetic association studies. Stat. Sci. 24, 451–471 (2009).

    Article  Google Scholar 

  46. Wimmer, V., Albrecht, T., Auinger, H. J. & Schön, C. C. synbreed: a framework for the analysis of genomic prediction data using R. Bioinformatics 28, 2086–2087 (2012).

    Article  CAS  Google Scholar 

  47. Millet, E. J. et al. Genome-wide analysis of yield in Europe: allelic effects vary with drought and heat scenarios. Plant Physiol. 172, 749–764 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Thoen, M. P. et al. Genetic architecture of plant stress resistance: multi‐trait genome‐wide association mapping. New Phytologist 213, 1346–1362 (2017).

    Article  CAS  Google Scholar 

  49. Patterson, N., Price, A. L. & Reich, D. D, Population Structure and Eigenanalysis. PLoS Genet. 2, e190 (2006).

    Article  Google Scholar 

  50. Welham, S. J. & Thompson, R. Likelihood Ratio Tests for Fixed Model Terms using Residual Maximum Likelihood. J. R. Statist. Soc. 59, 701–714 (1997).

    Article  Google Scholar 

  51. Boer, M. P. et al. A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize. Genetics. 177, 1801–1813 (2007).

    Article  Google Scholar 

  52. Devlin, B., Roeder, K. & Genomic, K. Control for association studies. Biometrics 55, 997–1004 (1999).

    Article  CAS  Google Scholar 

  53. Li, J. & Ji, L. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 95, 221–227 (2005).

    Article  CAS  Google Scholar 

  54. Alaux, M. et al. Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biol. 19, 111 (2018).

    Article  Google Scholar 

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The authors wish to thank the INRA Biological Resources Center on small grain cereals ( for providing seeds and passport data, and for establishing a wheat biorepository. The authors thank the Federal ex situ Genbank Gatersleben, Germany (IPK), the N. I. Vavilov All-Russian Research Institute of Plant Industry, Russia (VIR), Centre for Genetic Resources, WUR, Netherlands (CGN), Kyoto University, National Bioresource Project, Japan (NBRP), the Australian Winter Cereal Collection Tamworth, Australia (AWCC), the National Plant Germplasm System, USA (USDA-ARS), the International Center for Agriculture Research in the Dry Areas (ICARDA), the Max Planck Institute for Plant Breeding Research Cologne, Germany (MPIPZ), Germplasm Resource Unit at the John Innes Centre UK (JIC) and the Wheat and Barley Legacy for Breeding Improvement (WHEALBI) consortium for providing plant material and passport data. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/ 2007–2013) under grant agreement FP7- 613556, Whealbi project ( R.W. and J.R. also acknowledge support from the Scottish Government Research Program and R.W. from the University of Dundee. H.O. acknowledges support from Çukurova University (FUA-2016–6033). K.F.X.M. acknowledges support from the German Federal Ministry of Food and Agriculture (2819103915) and the DFG (SFB924). T.L. acknowledges supports from the Agence Nationale pour la Recherche (BirdIslandGenomic project 14-CE02-0002), European Research Council (TREEPEACE project, grant agreement 339728) and the bioinformatics platform from Toulouse Midi-Pyrénées (Bioinfo Genotoul) for providing computing and storage resources. J.S. acknowledges support from the Région Auvergne-Rhône-Alpes and FEDER Fonds Européens de Développement Régional (23000816 SRESRI 2015), the CPER contrat de plan État-région (23000892 SYMBIOSE 2016) and AgreenSkills fellowship (applicant ID 4146).

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Authors and Affiliations




F.B., B.K. and N.S. carried out panel constitution and distribution. S.D., J.R. and R.W. carried out exome sequencing. D.W., M.Se., M.Sp. and G.H. carried out variant (SNP and indel) calling. C.P., D.A., N.G., M.Se., D.L. and W.D. carried out variant analysis. D.L., W.D., M.Se., C.P., N.G. and G.H. carried out phylogenetic analyis. T.L., C.P. and D.A. carried out diversity analysis and selection footprints. A.T., D.B.K., C.P., H.O., M.M., F.E. and L.C. carried out field experiments and GWAS. B.K., J.R., K.F.X.M., R.W., N.S., L.C., G.H., G.C. and J.S. conceived and supervised the study and prepared the article.

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Correspondence to Jérôme Salse.

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Supplementary Tables 1–7 and Supplementary Figures 1–13

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Pont, C., Leroy, T., Seidel, M. et al. Tracing the ancestry of modern bread wheats. Nat Genet 51, 905–911 (2019).

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