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Genomic footprints of local adaptation along elevation gradients associate with present phenotypic variation in teosintes

M-A. Fustier, N.E. Martínez-Ainsworth, A. Venon, H. Corti, A. Rousselet, F. Dumas, View ORCID ProfileH. Dittberner, View ORCID ProfileJ.A. Aguirre-Liguori, M.G. Camarena, View ORCID ProfileD. Grimanelli, View ORCID ProfileM. Falque, View ORCID ProfileL. Moreau, View ORCID ProfileJ. de Meaux, View ORCID ProfileS. Montes-Hernandez, View ORCID ProfileL.E. Eguiarte, View ORCID ProfileY. Vigouroux, View ORCID ProfileD. Manicacci, View ORCID ProfileM.I. Tenaillon
doi: https://doi.org/10.1101/563585
M-A. Fustier
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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N.E. Martínez-Ainsworth
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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A. Venon
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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H. Corti
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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A. Rousselet
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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F. Dumas
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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H. Dittberner
2Institute of Botany, University of Cologne Biocenter, 47b Cologne, Germany
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  • ORCID record for H. Dittberner
J.A. Aguirre-Liguori
3Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
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M.G. Camarena
4Campo Experimental Bajío, Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Celaya, Mexico
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D. Grimanelli
5Université de Montpellier, Institut de Recherche pour le développement, UMR Diversité, Adaptation et Développement des plantes, Montpellier, France
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M. Falque
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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L. Moreau
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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J. de Meaux
2Institute of Botany, University of Cologne Biocenter, 47b Cologne, Germany
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S. Montes-Hernandez
4Campo Experimental Bajío, Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Celaya, Mexico
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L.E. Eguiarte
3Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
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Y. Vigouroux
5Université de Montpellier, Institut de Recherche pour le développement, UMR Diversité, Adaptation et Développement des plantes, Montpellier, France
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D. Manicacci
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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  • For correspondence: domenica.manicacci@inra.fr maud.tenaillon@inra.fr
M.I. Tenaillon
1Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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  • For correspondence: domenica.manicacci@inra.fr maud.tenaillon@inra.fr
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Abstract

Local adaptation across species range is widespread. Yet, much has to be discovered on its environmental drivers, the underlying functional traits and their molecular determinants. Because elevation gradients display continuous environmental changes at a short geographical scale, they provide an exceptional opportunity to investigate these questions. Here, we used two common gardens to phenotype 1664 plants from 11 populations of annual teosintes. These populations were sampled across two elevation gradients in Mexico. Our results point to a syndrome of adaptation to altitude with the production of offspring that flowered earlier, produced less tillers, and larger, longer and heavier grains with increasing elevation. We genotyped these plants for 178 outlier single nucleotide polymorphisms (SNPs), which had been chosen because they displayed excess of allele differentiation and/or correlation with environmental variables in six populations with contrasted altitudes. A high proportion of outlier SNPs associated with the phenotypic variation of at least one trait. We tested phenotypic pairwise correlations between traits, and found that the higher the correlation, the greater the number of common associated SNPs. In addition, allele frequencies at 87 of the outlier SNPs correlated with an environmental component best summarized by altitudinal variation on a broad sample of 28 populations. Chromosomal inversions were enriched for both phenotypically-associated and environmentally-correlated SNPs. Altogether, our results are consistent with the set-up of an altitudinal syndrome promoted by local adaptation of teosinte populations in the face of gene flow. We showed that pleiotropy is pervasive and potentially has constrained the evolution of traits. Finally, we recovered variants underlying phenotypic variation at adaptive traits. Because elevation mimics climate change through space, these variants may be relevant for future maize breeding.

Author summary Across their native range, species encounter a diversity of habitats promoting local adaptation of geographically distributed populations. While local adaptation is widespread, much has yet to be discovered about the conditions of its emergence, the targeted traits, their molecular determinants and the underlying ecological drivers. Here we employed a reverse ecology approach, combining phenotypes and genotypes, to mine the determinants of local adaptation of teosinte populations distributed along two steep altitudinal gradients in Mexico. Evaluation of 11 populations in two common gardens located at mid-elevation pointed to the set-up of an altitudinal syndrome, in spite of gene flow. We scanned genomes to identify loci with allele frequencies shifts along elevation. Interestingly, variation at these loci was commonly associated to variation of phenotypes. Because elevation mimics climate change through space, these variants may be relevant for future maize breeding.

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Posted February 28, 2019.
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Genomic footprints of local adaptation along elevation gradients associate with present phenotypic variation in teosintes
M-A. Fustier, N.E. Martínez-Ainsworth, A. Venon, H. Corti, A. Rousselet, F. Dumas, H. Dittberner, J.A. Aguirre-Liguori, M.G. Camarena, D. Grimanelli, M. Falque, L. Moreau, J. de Meaux, S. Montes-Hernandez, L.E. Eguiarte, Y. Vigouroux, D. Manicacci, M.I. Tenaillon
bioRxiv 563585; doi: https://doi.org/10.1101/563585
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Genomic footprints of local adaptation along elevation gradients associate with present phenotypic variation in teosintes
M-A. Fustier, N.E. Martínez-Ainsworth, A. Venon, H. Corti, A. Rousselet, F. Dumas, H. Dittberner, J.A. Aguirre-Liguori, M.G. Camarena, D. Grimanelli, M. Falque, L. Moreau, J. de Meaux, S. Montes-Hernandez, L.E. Eguiarte, Y. Vigouroux, D. Manicacci, M.I. Tenaillon
bioRxiv 563585; doi: https://doi.org/10.1101/563585

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