Literature DB >> 24443444

Genomic signature of adaptation to climate in Medicago truncatula.

Jeremy B Yoder1, John Stanton-Geddes, Peng Zhou, Roman Briskine, Nevin D Young, Peter Tiffin.   

Abstract

Local adaptation and adaptive clines are pervasive in natural plant populations, yet the effects of these types of adaptation on genomic diversity are not well understood. With a data set of 202 accessions of Medicago truncatula genotyped at almost 2 million single nucleotide polymorphisms, we used mixed linear models to identify candidate loci responsible for adaptation to three climatic gradients-annual mean temperature (AMT), precipitation in the wettest month (PWM), and isothermality (ITH)-representing the major axes of climate variation across the species' range. Loci with the strongest association to these climate gradients tagged genome regions with high sequence similarity to genes with functional roles in thermal tolerance, drought tolerance, or resistance to herbivores of pathogens. Genotypes at these candidate loci also predicted the performance of an independent sample of plant accessions grown in climate-controlled conditions. Compared to a genome-wide sample of randomly drawn reference SNPs, candidates for two climate gradients, AMT and PWM, were significantly enriched for genic regions, and genome segments flanking genic AMT and PWM candidates harbored less nucleotide diversity, elevated differentiation between haplotypes carrying alternate alleles, and an overrepresentation of the most common haplotypes. These patterns of diversity are consistent with a history of soft selective sweeps acting on loci underlying adaptation to climate, but not with a history of long-term balancing selection.

Entities:  

Keywords:  association genetics; balancing selection; environmental gradient; genome scan; landscape genomics

Mesh:

Substances:

Year:  2014        PMID: 24443444      PMCID: PMC3982686          DOI: 10.1534/genetics.113.159319

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


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