Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations |
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| Authors: | Anna W Santure Jocelyn Poissant Isabelle De Cauwer Kees van Oers Matthew R Robinson John L Quinn Martien A M Groenen Marcel E Visser Ben C Sheldon Jon Slate |
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| Affiliation: | 1. School of Biological Sciences, University of Auckland, Auckland, New Zealand;2. Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK;3. Centre for Ecology and Conservation, University of Exeter, Penryn, UK;4. Unité Evolution, Ecologie et Paléontologie, UMR 8198, Université de Lille – Sciences et Technologies, Villeneuve d'Ascq, France;5. Department of Animal Ecology, Netherlands Institute of Ecology (NIOO‐KNAW), Wageningen, The Netherlands;6. Queensland Brain Institute, University of Queensland, Brisbane, Qld, Australia;7. School of Biological, Earth and Environmental Sciences, University College Cork, Distillery Fields, North Mall, Cork, Ireland;8. Department of Zoology, Edward Grey Institute, University of Oxford, Oxford, UK;9. Animal Breeding and Genomics Centre, Wageningen University, Wageningen, The Netherlands |
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| 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. |
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| Keywords: | chromosome partitioning genome‐wide association genomics
GWAS
QTL mapping quantitative genetics |
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