Genomic signature of adaptation to climate in Medicago truncatula

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.

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

Figure 1

Collection sites for the 202 lines of M. truncatula in our sample, with the native range colored according to AMT, in degrees Celsius × 10 (scale to the right of the map).

Figure 2

Linkage among candidate SNPs compared to null expectations. The histogram illustrates the distribution of median D′ values for 30 sets of 100 randomly drawn reference SNPs; median values for the top 100 candidates for each climate variable are indicated by vertical lines.

Figure 3

Distribution of diversity (θ_W, calculated across all allelic backgrounds), divergence (F_ST between major and minor allelic backgrounds), and sweep strength (H12) statistics for 10-kb regions centered on each of the top 100 candidate SNPs for each climate variable (red, AMT; blue, PWM; orange, ITH), compared to 10-kb regions centered on each of the 10,000 randomly drawn reference SNPs (gray). To control for systematic differences between genic and intergenic regions, we compare genic candidates to genic reference SNPs (left column for each statistic) and intergenic candidates to intergenic reference SNPs (right columns); Table 1 gives the number of SNPs in each of these sets. P-values are for a Wilcoxon signed-rank test of the hypothesis that the median statistic for the candidate set is greater or less than the median for the reference set.

Figure 4

Manhattan plot of the tightly linked cluster of PWM candidate SNPs on chromosome 2. Individual points plot the –log₁₀(P) value for individual SNPs. Points representing SNPs in the top 1000 candidates (across the whole genome) are colored according to their linkage disequilibrium (D′) with the highest-associated SNP in the illustrated region (at position 8,057,576; indicated with a red star): red, higher values of D′; shading to yellow, lower values of D′.