Common gardens in teosintes reveal the establishment of a syndrome of adaptation to altitude

Autoři: Margaux-Alison Fustier aff001;  Natalia E. Martínez-Ainsworth aff001;  Jonás A. Aguirre-Liguori aff002;  Anthony Venon aff001;  Hélène Corti aff001;  Agnès Rousselet aff001;  Fabrice Dumas aff001;  Hannes Dittberner aff003;  María G. Camarena aff004;  Daniel Grimanelli aff005;  Otso Ovaskainen aff006;  Matthieu Falque aff001;  Laurence Moreau aff001;  Juliette de Meaux aff003;  Salvador Montes-Hernández aff004;  Luis E. Eguiarte aff002;  Yves Vigouroux aff005;  Domenica Manicacci aff001;  Maud I. Tenaillon aff001
Působiště autorů: Génétique Quantitative et Evolution – Le Moulon, Université Paris-Saclay, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, Centre National de la Recherche Scientifique, AgroParisTech, Gif-sur-Yvette, France aff001;  Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico aff002;  Institute of Botany, University of Cologne Biocenter, Cologne, Germany aff003;  Campo Experimental Bajío, InstitutoNacional de Investigaciones Forestales, Agrícolas y Pecuarias, Celaya, Mexico aff004;  UMR Diversité, Adaptation et Développement des plantes, Université de Montpellier, Institut de Recherche pour le développement, Montpellier, France aff005;  Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland aff006;  Centre for Biodiversity Dynamics, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway aff007
Vyšlo v časopise: Common gardens in teosintes reveal the establishment of a syndrome of adaptation to altitude. PLoS Genet 15(12): e32767. doi:10.1371/journal.pgen.1008512
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008512


In plants, local adaptation across species range is frequent. Yet, much has to be discovered on its environmental drivers, the underlying functional traits and their molecular determinants. Genome scans are popular to uncover outlier loci potentially involved in the genetic architecture of local adaptation, however links between outliers and phenotypic variation are rarely addressed. Here we focused on adaptation of teosinte populations along two elevation gradients in Mexico that display continuous environmental changes at a short geographical scale. We used two common gardens, and phenotyped 18 traits in 1664 plants from 11 populations of annual teosintes. In parallel, we genotyped these plants for 38 microsatellite markers as well as for 171 outlier single nucleotide polymorphisms (SNPs) that displayed excess of allele differentiation between pairs of lowland and highland populations and/or correlation with environmental variables. Our results revealed that phenotypic differentiation at 10 out of the 18 traits was driven by local selection. Trait covariation along the elevation gradient indicated that adaptation to altitude results from the assembly of multiple co-adapted traits into a complex syndrome: as elevation increases, plants flower earlier, produce less tillers, display lower stomata density and carry larger, longer and heavier grains. The proportion of outlier SNPs associating with phenotypic variation, however, largely depended on whether we considered a neutral structure with 5 genetic groups (73.7%) or 11 populations (13.5%), indicating that population stratification greatly affected our results. Finally, chromosomal inversions were enriched for both SNPs whose allele frequencies shifted along elevation as well as phenotypically-associated SNPs. Altogether, our results are consistent with the establishment of an altitudinal syndrome promoted by local selective forces in teosinte populations in spite of detectable gene flow. Because elevation mimics climate change through space, SNPs that we found underlying phenotypic variation at adaptive traits may be relevant for future maize breeding.

Klíčová slova:

Leaves – Maize – Molecular genetics – Phenotypes – Population genetics – principal component analysis – Stomata – Variant genotypes


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