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Comparative population genomics of maize domestication and improvement

Nature Genetics volume 44, pages 808–811 (2012)Cite this article

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Abstract

Domestication and plant breeding are ongoing 10,000-year-old evolutionary experiments that have radically altered wild species to meet human needs. Maize has undergone a particularly striking transformation. Researchers have sought for decades to identify the genes underlying maize evolution1,2, but these efforts have been limited in scope. Here, we report a comprehensive assessment of the evolution of modern maize based on the genome-wide resequencing of 75 wild, landrace and improved maize lines3. We find evidence of recovery of diversity after domestication, likely introgression from wild relatives, and evidence for stronger selection during domestication than improvement. We identify a number of genes with stronger signals of selection than those previously shown to underlie major morphological changes4,5. Finally, through transcriptome-wide analysis of gene expression, we find evidence both consistent with removal of cis-acting variation during maize domestication and improvement and suggestive of modern breeding having increased dominance in expression while targeting highly expressed genes.

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Figure 1: Neighbor-joining tree and changing morphology of domesticated maize and its wild relatives.
Figure 2: Genome-wide analysis of nucleotide diversity and selection.
Figure 3: Domestication and improvement candidate genes in relation to two pathways in rice.

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Acknowledgements

The authors would like to thank T. Kono, S. Watson and M. Watson for photographs of inflorescences, P. Brown for help with QTL delineation, B.S. Gaut, A.M. Gonzales and two anonymous reviewers for comments on an earlier version of the manuscript and M. Grote for statistical advice. This work was supported by funding to the maize diversity project from the US National Science Foundation (NSF; IOS-0820619 to E.S.B., J.D. and M.D.M.) and USDA-ARS (to E.S.B., M.D.M. and D.W.), as well as from USDA Hatch Funds (to P.T. and N.M.S.), the Chinese 973 program (2007CB815701 to J.W.), the Chinese Ministry of Agriculture 984 program (2010-Z13 to G.Z.), the Shenzhen Municipal Government Basic Research Program (to J.W.), the US DOE Great Lakes Bioenergy Research Center (DOE Office of Science; BER DE-FC02-07ER64494), the Office of Science of the US DOE (contract DE-AC02-05CH11231 to the US DOE Joint Genome Institute) and by grants from the US NSF (IOS-0922703 to J.R.-I.) and the USDA–National Institute of Food and Agriculture (2009-01864 to J.R.-I.).

Author information

Author notes

  1. Matthew B Hufford, Xun Xu, Joost van Heerwaarden and Tanja Pyhäjärvi: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Plant Sciences, University of California, Davis, California, USA

    Matthew B Hufford, Joost van Heerwaarden, Tanja Pyhäjärvi & Jeffrey Ross-Ibarra

  2. BGI-Shenzhen, Shenzhen, China

    Xun Xu, Chi Song, Jun Wang, Gengyun Zhang & Shuang Yang

  3. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA

    Jer-Ming Chia & Doreen Ware

  4. Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA

    Reed A Cartwright

  5. School of Life Sciences, Arizona State University, Tempe, Arizona, USA

    Reed A Cartwright

  6. Institute for Genomic Diversity, Cornell University, Ithaca, New York, USA

    Robert J Elshire, Jeffrey C Glaubitz & Edward S Buckler

  7. US Department of Agriculture–Agriculture Research Service (USDA-ARS),

    Kate E Guill, Michael D McMullen, Doreen Ware & Edward S Buckler

  8. Division of Plant Sciences, University of Missouri, Columbia, Missouri, USA

    Kate E Guill & Michael D McMullen

  9. Department of Energy (DOE) Great Lakes Bioenergy Research Center, University of Wisconsin, Madison, Wisconsin, USA

    Shawn M Kaeppler

  10. Department of Agronomy, University of Wisconsin, Madison, Wisconsin, USA

    Shawn M Kaeppler

  11. State Key Laboratory of Agrobiotechnology, China Agricultural University, Beijing, China

    Jinsheng Lai

  12. Department of Agronomy & Plant Genetics, University of Minnesota, St Paul, Minnesota, USA

    Peter L Morrell

  13. Department of Genetics, University of Wisconsin, Madison, Wisconsin, USA

    Laura M Shannon & John Doebley

  14. Department of Plant Biology, University of Minnesota, St Paul, Minnesota, USA

    Nathan M Springer, Ruth A Swanson-Wagner & Peter Tiffin

  15. The Genome Center, University of California, Davis, California, USA

    Jeffrey Ross-Ibarra

  16. The Center for Population Biology, University of California, Davis, California, USA

    Jeffrey Ross-Ibarra

Authors
  1. Matthew B Hufford
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Contributions

J.D., M.D.M., E.S.B., D.W. and J.R.-I. designed the project. M.B.H., J.v.H., T.P. and J.R.-I. performed most data analyses. J.D. developed wild and landrace inbred lines. E.S.B., S.M.K., J.L., M.D.M. and D.W. contributed sequence data for inbred maize and parviglumis. K.E.G. and R.J.E. developed libraries and managed sequencing for inbred maize and parviglumis. X.X., S.Y., J.W. and G.Z. directed sequencing for landrace maize, mexicana and Tripsacum. E.S.B., J.R.-I., D.W. and X.X. directed bioinformatics analyses. J.-M.C. and C.S. performed read mapping, SNP calling and annotation, and analysis of coding sequence. E.S.B., J.-M.C. and J.C.G. performed quality control filtering of SNPs. N.M.S., R.A.S.-W. and P.T. generated Nimblegen expression data for maize and parviglumis. S.M.K. provided early access expression data. L.M.S. reanalyzed QTL data for domestication traits. R.A.C. analyzed site frequency spectra. M.B.H., J.v.H., T.P., P.L.M. and J.R.-I. wrote the manuscript.

Corresponding authors

Correspondence to Edward S Buckler, Shuang Yang or Jeffrey Ross-Ibarra.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Tables 1–5, 8 and 9 and Supplementary Figures 1–15 (PDF 10057 kb)

Supplementary Table 6

Domestication candidates (XLSX 189 kb)

Supplementary Table 7

Improvement candidates (XLSX 163 kb)

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Hufford, M., Xu, X., van Heerwaarden, J. et al. Comparative population genomics of maize domestication and improvement. Nat Genet 44, 808–811 (2012). https://doi.org/10.1038/ng.2309

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