• A Corrigendum to this article was published on 26 May 2017

This article has been updated

Abstract

Landraces (traditional varieties) of domesticated species preserve useful genetic variation, yet they remain untapped due to the genetic linkage between the few useful alleles and hundreds of undesirable alleles1. We integrated two approaches to characterize the diversity of 4,471 maize landraces. First, we mapped genomic regions controlling latitudinal and altitudinal adaptation and identified 1,498 genes. Second, we used F-one association mapping (FOAM) to map the genes that control flowering time, across 22 environments, and identified 1,005 genes. In total, we found that 61.4% of the single-nucleotide polymorphisms (SNPs) associated with altitude were also associated with flowering time. More than half of the SNPs associated with altitude were within large structural variants (inversions, centromeres and pericentromeric regions). The combined mapping results indicate that although floral regulatory network genes contribute substantially to field variation, over 90% of the contributing genes probably have indirect effects. Our dual strategy can be used to harness the landrace diversity of plants and animals.

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Change history

  • 20 February 2017

    In the version of this article initially published online, the name of author Martha Willcox was misspelled as Martha Wilcox. The error has been corrected in the print, PDF and HTML versions of this article.

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Acknowledgements

J.A.R.N., M.W., J.B., S.T., E.P., A.T., H.V.D., V.V., A.O., A.E.B., N.O.G.M., I.O.-M., F.S.V., A.G.E., G.A., P.W. and S.H. were supported by La Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación (SAGARPA), Mexico under the MasAgro (Sustainable Modernization of Traditional Agriculture) initiative. J.A.R.N., C.R., K.S. and E.S.B. were supported by the US National Science Foundation (grant no. 1238014 and 0922493), and the USDA–ARS. We would like to thank ICAMEX and DuPont Pioneer Mexico for assistance in establishing the phenotypic trials.

Author information

Affiliations

  1. School of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell University, Ithaca, New York, USA.

    • J Alberto Romero Navarro
    • , Kelly Swarts
    •  & Edward S Buckler
  2. International Maize and Wheat Improvement Center (CIMMYT), Texcoco, México.

    • Martha Willcox
    • , Juan Burgueño
    • , Samuel Trachsel
    • , Ivan Ortiz-Monasterio
    • , Félix San Vicente
    • , Armando Guadarrama Espinoza
    • , Gary Atlin
    • , Peter Wenzl
    •  & Sarah Hearne
  3. Institute for Genomic Diversity, Ithaca, New York, USA.

    • Cinta Romay
    •  & Edward S Buckler
  4. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP), Campo Experimental Bajio, Celaya, México.

    • Ernesto Preciado
    •  & Arturo Terron
  5. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP), Campo Experimental Uruapan, Uruapan, México.

    • Humberto Vallejo Delgado
  6. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP), Campo Experimental Santiago Ixcuintla, Santiago Ixcuintla, México.

    • Victor Vidal
  7. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP), Campo Experimental Norman E. Borlaug, Ciudad Obregón, México.

    • Alejandro Ortega
  8. Universidad Autonoma Agraria Antonio Narro, Torreon, México.

    • Armando Espinoza Banda
  9. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP), Campo Experimental Iguala, Iguala, México.

    • Noel Orlando Gómez Montiel
  10. US Department of Agriculture–Agricultural Research Service (USDA–ARS), Ithaca, New York, USA.

    • Edward S Buckler

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Contributions

J.A.R.N. conducted the GWAS analyses; M.W. coordinated the execution of the phenotypic trials, and the collection and curation of the phenotypic data; J.B. developed the phenotypic experimental designs, formulated models and determined landrace parent–environment estimates; C.R. assisted with the GWAS analysis and data interpretation; K.S. performed genotype imputation; S.T., E.P., A.T., H.V.D.,V.V., A.O., A.E.B., N.O.G.M., I.O.-M. and A.G.E. conducted the phenotypic trials; F.S.V. and A.G.E. developed the test-cross germplasm; G.A., P.W. and E.S.B. developed the project concept; S.H. coordinated the genotypic data collection, meta-data creation and passport data curation; and J.A.R.N., S.H. and E.S.B. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Sarah Hearne or Edward S Buckler.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–14

Excel files

  1. 1.

    Supplementary Table 1

    Phenotypic evaluation information. Lists years of evaluation, trial name, location, adaptation class, number of accessions evaluated, row length in meters, number of plants per row, and broad sense heritability estimates from variance partitioning model

  2. 2.

    Supplementary Table 2

    Top genes associated with female flowering

  3. 3.

    Supplementary Table 3

    Top genes associated with male flowering

  4. 4.

    Supplementary Table 4

    Gene Ontology enrichment for flowering time candidate genes

  5. 5.

    Supplementary Table 5

    Gene Ontology enrichment for genes associated with male and female flowering time in FOAM landrace panel

  6. 6.

    Supplementary Table 6

    Top SNPs associated with altitude

  7. 7.

    Supplementary Table 7

    Top SNPs associated with latitude

  8. 8.

    Supplementary Table 8

    CIMMYT inbred lines homozygous for the chromosome 4 inversion

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DOI

https://doi.org/10.1038/ng.3784

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