Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

Abstract

Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar phenotypic variation in different populations? Great tits (Parus major) have been studied extensively in long‐term studies across Europe and consequently are considered an ecological ‘model organism’. Recently, genomic resources have been developed for the great tit, including a custom SNP chip and genetic linkage map. In this study, we used a suite of approaches to investigate the genetic architecture of eight quantitative traits in two long‐term study populations of great tits—one in the Netherlands and the other in the United Kingdom. Overall, we found little evidence for the presence of genes of large effects in either population. Instead, traits appeared to be influenced by many genes of small effect, with conservative estimates of the number of contributing loci ranging from 31 to 310. Despite concordance between population‐specific heritabilities, we found no evidence for the presence of loci having similar effects in both populations. While population‐specific genetic architectures are possible, an undetected shared architecture cannot be rejected because of limited power to map loci of small and moderate effects. This study is one of few examples of genetic architecture analysis in replicated wild populations and highlights some of the challenges and limitations researchers will face when attempting similar molecular quantitative genetic studies in free‐living populations.

Inferences of genetic architecture of bill morphology in house sparrow using a high‐density SNP array point to a polygenic basis

“…This result provides support for the general notion that bill morphology is polygenic in nature (Boag, ; Grant & Grant, ). Therefore, most complex traits in free‐living populations may be influenced by many genes of small effect (Pritchard & Di Rienzo, ; Santure et al., ). Disparity was observed between chromosomes that contributed disproportionately to a trait and whether significant SNPs for the trait were located on these chromosomes in GWA analyses (Table , Supporting Information Table ).…”

“…Is it instead possible that our study simply missed signals from variants near previously identified genes due to lack of statistical power (Cohen, )? Our 200K SNP array has higher marker density compared to nearly all similar association studies on ecologically important traits in natural vertebrate populations (e.g., Chaves et al., ; Huisman, Kruuk, Ellis, Clutton‐Brock, & Pemberton, ; Johnston et al., , ; Kawakami, Backström et al., ; Santure et al., ; but see Bosse et al., ), with average distance between markers of approximately 5,000 bp, affording high power to detect causal variants. Nearly 92% of the SNPs on our custom 200K array passed quality control, and more than 180,000 SNPs could be used to assess the genetic architecture of bill morphology.…”

Genetics of dispersal

“…In contrast to the above examples, where the small number of loci associated with dispersal variation suggests an oligogenic genetic architecture, numerous studies (outside the field of dispersal) indicate that quantitative traits generally arise via a polygenic architecture (Mackay et al, ; Husby et al, ; Santure et al, ). While the relatively few examples of genes with large effect size could arise from underpowered QTL or GWA studies, it could also indicate the absence of such loci.…”

Association mapping of morphological traits in wild and captive zebra finches: reliable within, but not between populations

“…) and a recent genome‐wide study on eight quantitative traits in two populations of great tits (Santure et al . ). Both studies failed to replicate associations across populations.…”

“…In line with this, recent large‐scale association studies in wild bird populations have generally been unsuccessful in identifying significant associations between quantitative traits and genotypes (Santure et al . ; Kardos et al . ; but see Husby et al .…”