The impact of SNP density on quantitative genetic analyses of body size traits in a wild population of Soay sheep

IF 2.3 2区 生物学 Q2 ECOLOGY Ecology and Evolution Pub Date : 2022-12-14 DOI:10.1002/ece3.9639
Caelinn James, Josephine M. Pemberton, Pau Navarro, Sara Knott
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Abstract

Understanding the genetic architecture underpinning quantitative traits in wild populations is pivotal to understanding the processes behind trait evolution. The ‘animal model’ is a popular method for estimating quantitative genetic parameters such as heritability and genetic correlation and involves fitting an estimate of relatedness between individuals in the study population. Genotypes at genome-wide markers can be used to estimate relatedness; however, relatedness estimates vary with marker density, potentially affecting results. Increasing density of markers is also expected to increase the power to detect quantitative trait loci (QTL). In order to understand how the density of genetic markers affects the results of quantitative genetic analyses, we estimated heritability and performed genome-wide association studies (GWAS) on five body size traits in an unmanaged population of Soay sheep using two different SNP densities: a dataset of 37,037 genotyped SNPs and an imputed dataset of 417,373 SNPs. Heritability estimates did not differ between the two SNP densities, but the high-density imputed SNP dataset revealed four new SNP-trait associations that were not found with the lower density dataset, as well as confirming all previously-found QTL. We also demonstrated that fitting fixed and random effects in the same step as performing GWAS is a more powerful approach than pre-correcting for covariates in a separate model.

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SNP密度对沙伊羊野生种群体型性状定量遗传分析的影响
了解野生种群数量性状的遗传结构对理解性状进化背后的过程至关重要。“动物模型”是估计定量遗传参数(如遗传性和遗传相关性)的一种流行方法,涉及拟合研究群体中个体之间的亲缘关系估计。全基因组标记上的基因型可以用来估计亲缘关系;然而,相关性估计随着标记密度的变化而变化,这可能会影响结果。标记密度的增加也有望提高检测数量性状位点(QTL)的能力。为了了解遗传标记密度如何影响定量遗传分析的结果,我们使用两种不同的SNP密度(37,037个基因型SNPs数据集和417,373个SNPs数据集)估计了遗传力,并对Soay羊的5个体型性状进行了全基因组关联研究(GWAS)。遗传力估计在两个SNP密度之间没有差异,但高密度输入的SNP数据集揭示了四个新的SNP-性状关联,这些关联在低密度数据集中没有发现,并且证实了所有先前发现的QTL。我们还证明,在执行GWAS的同一步骤中拟合固定效应和随机效应比在单独的模型中预校正协变量更有效。
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来源期刊
CiteScore
4.40
自引率
3.80%
发文量
1027
审稿时长
3-6 weeks
期刊介绍: Ecology and Evolution is the peer reviewed journal for rapid dissemination of research in all areas of ecology, evolution and conservation science. The journal gives priority to quality research reports, theoretical or empirical, that develop our understanding of organisms and their diversity, interactions between them, and the natural environment. Ecology and Evolution gives prompt and equal consideration to papers reporting theoretical, experimental, applied and descriptive work in terrestrial and aquatic environments. The journal will consider submissions across taxa in areas including but not limited to micro and macro ecological and evolutionary processes, characteristics of and interactions between individuals, populations, communities and the environment, physiological responses to environmental change, population genetics and phylogenetics, relatedness and kin selection, life histories, systematics and taxonomy, conservation genetics, extinction, speciation, adaption, behaviour, biodiversity, species abundance, macroecology, population and ecosystem dynamics, and conservation policy.
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