A high‐density SNP chip for genotyping great tit (Parus major) populations and its application to studying the genetic architecture of exploration behaviour

Abstract

High-density SNP microarrays ("SNP chips") are a rapid, accurate and efficient method for genotyping several hundred thousand polymorphisms in large numbers of individuals. While SNP chips are routinely used in human genetics and in animal and plant breeding, they are less widely used in evolutionary and ecological research. In this article, we describe the development and application of a high-density Affymetrix Axiom chip with around 500,000 SNPs, designed to perform genomics studies of great tit (Parus major) populations. We demonstrate that the per-SNP genotype error rate is well below 1% and that the chip can also be used to identify structural or copy number variation. The chip is used to explore the genetic architecture of exploration behaviour (EB), a personality trait that has been widely studied in great tits and other species. No SNPs reached genomewide significance, including at DRD4, a candidate gene. However, EB is heritable and appears to have a polygenic architecture. Researchers developing similar SNP chips may note: (i) SNPs previously typed on alternative platforms are more likely to be converted to working assays; (ii) detecting SNPs by more than one pipeline, and in independent data sets, ensures a high proportion of working assays; (iii) allele frequency ascertainment bias is minimized by performing SNP discovery in individuals from multiple populations; and (iv) samples with the lowest call rates tend to also have the greatest genotyping error rates.

Genetic and phenotypic responses to genomic selection for timing of breeding in a wild songbird

“…These were used as training population. These individuals, as well as all F 1 and F 2 individuals, were genotyped on a 650K SNP chip (Kim et al, ) to predict their GEBVs. We excluded SNPs from the Z chromosome and unassigned scaffolds (32 467 SNPs).…”

“…To quantify the level of genetic differentiation between the early and late lines, we estimated F ST (Holsinger & Weir, 2009) for each SNP in every generation using a custom-made Affymetrix great tit 650K SNP chip (Kim et al, 2018). We used the same SNPs as for the estimation of GEBVs (see "Calculating the GEBV" above).…”

Response to Perrier and Charmantier: On the importance of time scales when studying adaptive evolution

“…Although regions with low recombination rates (and therefore high linkage disequilibrium) will have enhanced power to detect genuine causal variants in a GWAS (Visscher et al 2017), there is no reason why they should be more prone to false positive associations. We note that the region has not been associated with other traits studied in the Wytham population in previous GWAS studies (Santure et al 2013;Santure et al 2015;Kim et al 2018).…”

“…As part of an ongoing effort to characterize genetic variation across the species’ distribution (the Great Tit HapMap Project; (Spurgin et al., ) we have genotyped birds from >20 European populations with the same SNP chip (Kim et al. ) as the one used in Bosse et al. ().…”

“…S7 of Bosse et al (2017) we compared the breeding values of the United Kingdom and the Netherlands populations. As part of an ongoing effort to characterize genetic variation across the species' distribution (the Great Tit HapMap Project; (Spurgin et al, 2019) we have genotyped birds from >20 European populations with the same SNP chip (Kim et al 2018) as the one used in Bosse et al (2017). Based on those data, here we ask whether the loci identified as being under selection in the United Kingdom could cause UK populations to have longer bills than mainland European populations.…”