Heterogeneity of genetic architecture of body size traits in a free-living population

Abstract

Knowledge of the underlying genetic architecture of quantitative traits could aid in understanding how they evolve. In wild populations, it is still largely unknown whether complex traits are polygenic or influenced by few loci with major effect, due to often small sample sizes and low resolution of marker panels. Here, we examine the genetic architecture of five adult body size traits in a free-living population of Soay sheep on St Kilda using 37 037 polymorphic SNPs. Two traits (jaw and weight) show classical signs of a polygenic trait: the proportion of variance explained by a chromosome was proportional to its length, multiple chromosomes and genomic regions explained significant amounts of phenotypic variance, but no SNPs were associated with trait variance when using GWAS. In comparison, genetic variance for leg length traits (foreleg, hindleg and metacarpal) was disproportionately explained by two SNPs on chromosomes 16 (s23172.1) and 19 (s74894.1), which each explained >10% of the additive genetic variance. After controlling for environmental differences, females heterozygous for s74894.1 produced more lambs and recruits during their lifetime than females homozygous for the common allele conferring long legs. We also demonstrate that alleles conferring shorter legs have likely entered the population through a historic admixture event with the Dunface sheep. In summary, we show that different proxies for body size can have very different genetic architecture and that dense SNP helps in understanding both the mode of selection and the evolutionary history at loci underlying quantitative traits in natural populations.

Keywords: admixture; body size; genetic architecture; genome partitioning; genome-wide association; genomics.

Figure 1

(a) The proportion of phenotypic variance for the body size traits explained by each of the 26 autosomes. (b) Scatterplot showing the correlation between the physical length of a chromosome and the phenotypic variance it explains. Solid lines are shown for linear regressions which were significant.

Figure 2

Results of regional heritability analysis of body weight in Soay sheep. Asterisks indicate regions which were significant after correcting for multiple testing.

Figure 3

(a) genome‐wide association (GWAS) of body size traits in Soay sheep. All points above the solid line are genome‐wide significant after Bonferroni correction for multiple testing. (b) Q‐Q plot showing the observed distribution of P values against the expected P values under the null hypothesis of no association. The solid line indicates the one to one line. Generally the P values are below the solid line, indicating that our P values are deflated. From left to right, inflation factors (λ) were 0.76, 0.74, 0.82, 0.67 and 0.61. Test statistics as shown in the top panel have not been adjusted using genomic control.

Figure 4

Mean and standard deviation of haplotype sharing between Soay sheep and 73 HapMap breeds for core haplotypes around s23172.1 on chromosome 16 in Soay sheep. Most relevant breed/species codes: BOR = Boreray and SBF = Scottish Blackface. All other breed codes can be found in Table S2. Haplotypes are sorted in descending order based on frequencies in the Soay sheep population. Summary statistics for haplotype sharing results can be found in Table S6.

Figure 5

Mean and standard deviation of haplotype sharing between Soay sheep and 73 HapMap breeds for core haplotypes around s74894.1 on chromosome 19 in Soay sheep. Most relevant breed/species codes: BOR = Boreray and SBF = Scottish Blackface. All other breed codes can be found in Table S2. Haplotypes are sorted in descending order based on frequencies in the Soay sheep population. Summary statistics for haplotype sharing results can be found in Table S6.