Bread wheat expanded its habitat from a core area of the Fertile Crescent to global environments within ~10,000 years. The genetic mechanisms of this remarkable evolutionary success are not well understood. By whole-genome sequencing of populations from 25 subspecies within the genera Triticum and Aegilops, we identified composite introgression from wild populations contributing to a substantial portion (4–32%) of the bread wheat genome, which increased the genetic diversity of bread wheat and allowed its divergent adaptation. Meanwhile, convergent adaptation to human selection showed 2- to 16-fold enrichment relative to random expectation—a certain set of genes were repeatedly selected in Triticum species despite their drastic differences in ploidy levels and growing zones, indicating the important role of evolutionary constraints in shaping the adaptive landscape of bread wheat. These results showed the genetic necessities of wheat as a global crop and provided new perspectives on transferring adaptive success across species for crop improvement.
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The raw sequence data were deposited in the Sequence Read Archive (https://www.ncbi.nlm.nih.gov/sra) under accession numbers PRJNA439156 and PRJNA663409. The raw sequence data were also deposited in the Genome Sequence Archive (https://bigd.big.ac.cn/gsa) under accession number CRA001951. The genotype data from VMap 1.0 are publicly available at the Genome Variation Map (https://bigd.big.ac.cn/gvm) under accession number GVM000082.
The genotyping software HapScanner is available at https://github.com/PlantGeneticsLab/TIGER/wiki/HapScanner. The custom code for SNP filtering is available at https://github.com/YaoZhou89/WGSc.
Lev-Yadun, S., Gopher, A. & Abbo, S. The cradle of agriculture. Science 288, 1602–1603 (2000).
Salamini, F., Özkan, H., Brandolini, A., Schäfer-Pregl, R. & Martin, W. Genetics and geography of wild cereal domestication in the near east. Nat. Rev. Genet. 3, 429–441 (2002).
Shiferaw, B. et al. Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security. Food Secur. 5, 291–317 (2013).
Asseng, S. et al. Rising temperatures reduce global wheat production. Nat. Clim. Change 5, 143–147 (2015).
Kahiluoto, H. et al. Decline in climate resilience of European wheat. Proc. Natl Acad. Sci. USA 116, 123–128 (2019).
Lukaszewski, A. J. et al. A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome. Science 345, 1251788 (2014).
Dubcovsky, J. & Dvorak, J. Genome plasticity a key factor in the success of polyploid wheat under domestication. Science 316, 1862–1866 (2007).
Cenci, A. et al. Grinding up wheat: a massive loss of nucleotide diversity since domestication. Mol. Biol. Evol. 24, 1506–1517 (2007).
Akhunov, E. D. et al. Nucleotide diversity maps reveal variation in diversity among wheat genomes and chromosomes. BMC Genomics 11, 702 (2010).
He, F. et al. Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome. Nat. Genet. 51, 896–904 (2019).
Cheng, H. et al. Frequent intra- and inter-species introgression shapes the landscape of genetic variation in bread wheat. Genome Biol. 20, 136 (2019).
Faris, J. D. in Genomics of Plant Genetic Resources Vol. 1 (eds Tuberosa, R. et al.) 439–464 (Springer, 2014).
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).
Glémin, S. et al. Pervasive hybridizations in the history of wheat relatives. Sci. Adv. 5, eaav9188 (2019).
Maccaferri, M. et al. Durum wheat genome highlights past domestication signatures and future improvement targets. Nat. Genet. 51, 885–895 (2019).
Lu, F. et al. Switchgrass genomic diversity, ploidy, and evolution: novel insights from a network-based SNP discovery protocol. PLoS Genet. 9, e1003215 (2013).
Tsunewaki, K. Comparative gene analysis of common wheat and its ancestral species. III. Glume hairiness. Genetics 53, 303–311 (1966).
Dvorak, J. et al. The origin of spelt and free-threshing hexaploid wheat. J. Hered. 103, 426–441 (2012).
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).
Pont, C. et al. Tracing the ancestry of modern bread wheats. Nat. Genet. 51, 905–911 (2019).
Balfourier, F. et al. Worldwide phylogeography and history of wheat genetic diversity. Sci. Adv. 5, eaav0536 (2019).
Wang, J. et al. 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).
Tenaillon, M. I. et al. Patterns of DNA sequence polymorphism along chromosome 1 of maize (Zea mays ssp. mays L.). Proc. Natl Acad. Sci. USA 98, 9161–9166 (2001).
Huang, X. et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat. Genet. 42, 961–967 (2010).
Huang, L. et al. Evolution and adaptation of wild emmer wheat populations to biotic and abiotic stresses. Annu. Rev. Phytopathol. 54, 279–301 (2016).
Li, M. et al. A CNL protein in wild emmer wheat confers powdery mildew resistance. New Phytol. 3, 1027–1037 (2020).
Green, R. E. et al. A draft sequence of the Neandertal genome. Science 328, 710–722 (2010).
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).
Ling, H.-Q. et al. Genome sequence of the progenitor of wheat A subgenome Triticum urartu. Nature 557, 424–428 (2018).
Marcussen, T. et al. Ancient hybridizations among the ancestral genomes of bread wheat. Science 345, 1250092 (2014).
Singh, N. et al. Genomic analysis confirms population structure and identifies inter-lineage hybrids in Aegilops tauschii. Front. Plant Sci. 10, 9 (2019).
Guan, Y. Detecting structure of haplotypes and local ancestry. Genetics 196, 625–642 (2014).
Seixas, F. A., Boursot, P. & Melo-Ferreira, J. The genomic impact of historical hybridization with massive mitochondrial DNA introgression. Genome Biol. 19, 91 (2018).
Harris, K. & Nielsen, R. Inferring demographic history from a spectrum of shared haplotype lengths. PLoS Genet. 9, e1003521 (2013).
Chen, H., Patterson, N. & Reich, D. Population differentiation as a test for selective sweeps. Genome Res. 20, 393–402 (2010).
Huang, X. et al. A map of rice genome variation reveals the origin of cultivated rice. Nature 490, 497–501 (2012).
Hufford, M. B. et al. Comparative population genomics of maize domestication and improvement. Nat. Genet. 44, 808–811 (2012).
Wang, W. et al. Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature 557, 43–49 (2018).
Stitzer, M. C. & Ross-Ibarra, J. Maize domestication and gene interaction. New Phytol. 220, 395–408 (2018).
Milner, S. G. et al. Genebank genomics highlights the diversity of a global barley collection. Nat. Genet. 51, 319–326 (2019).
Pourkheirandish, M. et al. Evolution of the grain dispersal system in barley. Cell 162, 527–539 (2015).
Avni, R. et al. Wild emmer genome architecture and diversity elucidate wheat evolution and domestication. Science 357, 93–97 (2017).
Pourkheirandish, M. et al. On the origin of the non-brittle rachis trait of domesticated einkorn wheat. Front. Plant Sci. 8, 2031 (2017).
Ray, D. K., Mueller, N. D., West, P. C. & Foley, J. A. Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8, e66428 (2013).
Carroll, S. P. et al. Applying evolutionary biology to address global challenges. Science 346, 1245993 (2014).
Vernot, B. & Akey, J. M. Resurrecting surviving Neandertal lineages from modern human genomes. Science 343, 1017–1021 (2014).
Huang, X., Zhao, Q. & Han, B. Comparative population genomics reveals strong divergence and infrequent introgression between Asian and African rice. Mol. Plant 8, 958–960 (2015).
Zhao, K. et al. Genomic diversity and introgression in O. sativa reveal the impact of domestication and breeding on the rice genome. PLoS ONE 5, e10780 (2010).
Hufford, M. B. et al. The genomic signature of crop-wild introgression in maize. PLoS Genet. 9, e1003477 (2013).
Wang, L. et al. The interplay of demography and selection during maize domestication and expansion. Genome Biol. 18, 215 (2017).
Baduel, P., Bray, S., Vallejo-Marin, M., Kolář, F. & Yant, L. The ‘polyploid hop’: shifting challenges and opportunities over the evolutionary lifespan of genome duplications. Front. Ecol. Evol. 6, 117 (2018).
Chen, K., Wang, Y., Zhang, R., Zhang, H. & Gao, C. CRISPR/Cas genome editing and precision plant breeding in agriculture. Annu. Rev. Plant Biol. 70, 667–697 (2019).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://arxiv.org/abs/1303.3997 (2013).
Unterseer, S. et al. A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array. BMC Genomics 15, 823 (2014).
Bukowski, R. et al. Construction of the third-generation Zea mays haplotype map. Gigascience 7, 134 (2018).
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).
Hohenlohe, P. A. et al. Population genomics of parallel adaptation in threespine stickleback using sequenced RAD tags. PLoS Genet. 6, e1000862 (2010).
Mascher, M. et al. A chromosome conformation capture ordered sequence of the barley genome. Nature 544, 427–433 (2017).
Marcais, G. et al. MUMmer4: a fast and versatile genome alignment system. PLoS Comput. Biol. 14, e1005944 (2018).
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
Letunic, I. & Bork, P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 44, W242–W245 (2016).
Frichot, E., Mathieu, F., Trouillon, T., Bouchard, G. & François, O. Fast and efficient estimation of individual ancestry coefficients. Genetics 196, 973–983 (2014).
Jakobsson, M. & Rosenberg, N. A. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 1801–1806 (2007).
Nei, M. & Li, W. H. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl Acad. Sci. USA 76, 5269–5273 (1979).
International Wheat Genome Sequencing Consortium et al. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361, eaar7191 (2018).
Yeaman, S., Gerstein, A. C., Hodgins, K. A. & Whitlock, M. C. Quantifying how constraints limit the diversity of viable routes to adaptation. PLoS Genet. 14, e1007717 (2018).
Zeng, X. et al. Origin and evolution of qingke barley in Tibet. Nat. Commun. 9, 5433 (2018).
Li, L., Stoeckert, C. J. & Roos, D. S. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 13, 2178–2189 (2003).
Tian, T. et al. agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res. 45, W122–W129 (2017).
Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).
We thank Y. Guo (Institute of Botany, Chinese Academy of Sciences); Z. Liu, S. Zheng, X. Zhang and X. Fu (Institute of Genetics and Developmental Biology, Chinese Academy of Sciences); Y. Zhou (Department of Ecology and Evolutionary Biology, University of California); and P. Kear (International Potato Center–China Center for Asia and the Pacific) for their valuable suggestions and comments. This research was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA24020201) and the National Natural Science Foundation of China (31970631) to F.L., the National Natural Science Foundation of China (31921005) and Strategic Priority Research Program of the Chinese Academy of Sciences (XDA24020203) to Y.J. and the China Postdoctoral Science Foundation (2018M631614) to Y.Z.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
a, Reference genome of genome/subgenome groups. The reference genome was divided into four taxonomic group based on genome constitution of population (AA, AABB, AABBDD and DD). b, Variation calling pipeline. We built PCR free library of all samples, which were then sequenced on Illumina machines. SNPs were called using BWA and Sentieon softwares. After filtering raw SNPs, all SNPs were merged by subgenomes.
a, Definition of syntenic regions. A site whose depth passed the depth filter was defined as syntenic. Genetic variations in syntenic regions of each lineage were retained. b, Comparison of syntenic sites identified by depth and lastz methods. The gray circle represents all sites in the chromosome, the purple circle represents the syntenic sites defined by depth-based method and the yellow circle represents the syntenic sites defined by lastz. To verify syntenic sites detected by the depth approach, we also detected the syntenic sites using whole-genome alignment to examine the consistency between the two approaches. We aligned the wild emmer genome1 to the reference with lastz and the sites with unique mapping were defined as lastz-defined syntenic sites2. For example, we detected the syntenic sites on the second part of chromosome 1 A with an overall length of 122,798,051 bp, we detected 13,061,714 and 15,383,247 syntenic sites using depth-based and lastz, respectively, and 5,445,193 sites were detected as syntenic using both methods. We found that 41.69% of depth-defined syntenic sites were also lastz-defined syntenic sites. The two approaches showed consistency, but the overlapping of syntenic sites is not high. Given the prevalent structural variations in plant genomes, the depth approach based on alignment of hundreds of genomes is likely to be more sensitive and accurate on detecting syntenic sites than aligning only two single genomes. c, IBS distance between reference genome and each accession was estimated. Chinese Spring was used as a calibration accession and had the lowest IBS distance (0.0037) as indicated by the red arrow in AABBDD taxa.
a, Phylogenetic tree of AB lineage. Wild emmer from southern Levant was used as the outgroup. Species/subspecies were represented by numbers from 1 to 22. Tip colors of the phylogeny represent sampling region of each accession, while branch colors represent ploidy levels. Branches with reliable bootstrap value (> 50) are labeled with a purple pentagram at corresponding nodes. WA: West Asia; AF: Africa; EU: Europe; EA: East Asia; SCA: South and Central Asia; AM: America. b, Ancestral coefficient of AB lineage. K varied from 2 to 7. Species are labeled with their corresponding numbers and colors. c, Nucleotide diversity and population differentiation (FST) in AB lineage. d, Nucleotide diversity and population differentiation (FST) in D lineage. Values in the circle represent nucleotide diversity and numbers next to dashed lines represent FST.
a, Comparison of nucleotide diversity of bread wheat across each chromosome. b, Comparison of nucleotide diversity of landrace and Indian dwarf wheat across the genome. Green lines represent landrace, yellow lines represent cultivar and blue lines represent Yunan wheat. Grey dots are the chromosome centromeres.
Extended Data Fig. 5 The proportion of introgression in landraces estimated from different species/subspecies.
The fd statistic (left y-axis) was estimated under four-taxon topology ((P1, P2), P3, O). Landrace was used as P2, Indian dwarf wheat (a) or Yunan wheat (b) was used as P1. Each P3 group is shown in x-axis. The right y-axis shows PGI statistic from different species/subspecies.
Extended Data Fig. 6 Introgression from wild emmer, domesticated emmer, and free-threshing tetraploids to landraces across the whole genome.
Introgression from wild emmer, domesticated emmer, and free-threshing tetraploids to landraces across the whole genome. The introgression from wild emmer, domesticated emmer, and free-threshing tetraploids were represented by blue, pink, and green lines, respectively. Grey dots represent the chromosome centromeres.
a, The introgression from urartu to landrace. b, The introgression from strangulata to landrace. Grey dots represent the chromosome centromeres.
Extended Data Fig. 8 Correlation of PGI and geographic distance between landraces and donor populations.
The averaged distance within each donor group (wild emmer, domesticated emmer, free-threshing tetraploids, and strangulata) for each landrace was used for representing the correlation between geographic distance and PGI of individual landraces.
The tract size distribution from wild emmer, domesticated emmer, free-threshing tetraploids was represented in a-d, respectively.
Extended Data Fig. 10 Selective sweeps comparison between negative control and the paired domestication events.
a–c, Comparison of selected genes between negative control (from wild einkorn to wild emmer) and domestication process from wild einkorn to domesticated einkorn. d-f, Comparison of selected genes between negative control and domestication process from wild emmer to domesticated emmer. (a) and (d) show the number of genes overlapped under the threshold of top 5%, (b) and (e) shows the whole genome distribution, and (c) and (f) show the enrichment of convergence.
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Zhou, Y., Zhao, X., Li, Y. et al. Triticum population sequencing provides insights into wheat adaptation. Nat Genet (2020). https://doi.org/10.1038/s41588-020-00722-w