Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches

Abstract

The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long-term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation-derived maternal links and microsatellite-derived paternal links; (ii) Pedigree 2, using SNP-derived assignment of both maternity and paternity; and (iii) whole-genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.

Keywords: SNP genotyping; body size; genetic architecture; genomic relatedness; heritability; maternal genetic effect.

Fig. 1

Summary of SNP characteristics. Shown are (A) the distribution of spacing between adjacent SNP markers, (B) the distribution of minor allele frequencies at SNP markers and (C) the decay of LD against physical distance between SNPs. Each closed circle shows the mean LD within a 10 Kb window. The dashed vertical line indicates the median spacing between adjacent SNP markers.

Fig. 2

Comparison of variance components from univariate animal models of body size using Model 1. Results are shown from top to bottom for neonates, lambs, yearlings and adults. Variance components differed between models, and shown are maternal effect (V_M), additive genetic effect (V_A), birth year effect (V_BY), measurement year effect (V_CY), permanent environment effect (V_PE) and the residual variance (V_R). Error bars indicate the standard error of the estimates.

Fig. 3

Comparison of variance components from univariate animal models of body size using Model 2. Results are shown from top to bottom for neonates, lambs, yearlings and adults. Variance components differed between models, and shown are maternal genetic effect (V_MA), maternal environment effect (V_ME), additive genetic effect (V_A), birth year effect (V_BY), measurement year effect (V_CY), permanent environment effect (V_PE) and the residual variance (V_R). Error bars indicate the standard error of the estimates.

Fig. 4

Estimates of genetic correlations from bivariate animal models of adult body size using Model 1. Error bars indicate the standard error of the estimates.

Fig. 5

Estimated heritability of adult body size as a function of increasing marker number. Box and whiskers show the median and spread of 50 replicate sampled sets of SNPs. The solid and dashed lines represent Pedigree 2 heritability and genomic heritability estimates using all available markers, respectively.