Evaluating the power and limitations of genome-wide association studies in Caenorhabditis elegans.
Evaluating the power and limitations of genome-wide association studies in Caenorhabditis elegans.
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DOI：
10.1093/g3journal/jkac114
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发表时间：
2022-07-06
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--
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秀丽隐杆线虫的数量遗传学旨在识别复杂性状背后的自然分离遗传变异。全基因组关联研究扫描基因组中与群体中的表型变异或数量性状基因座显著相关的个体遗传变异。全基因组关联研究是数量遗传分析的热门选择，因为所发现的数量性状基因座在自然群体中分离。尽管有许多成功的作图实验，全基因组关联研究的经验表现还没有，到目前为止，在C。优雅我们开发了一个名为NemaScan的开源全基因组关联研究管道，并使用基于模拟的方法提供野生C. elegans菌株。模拟的性状遗传力和复杂性决定了全基因组关联研究所检测到的数量性状位点谱。检测较小效应数量性状基因座的能力随着从C.自然多样性资源。种群结构是映射性能变化的主要驱动因素，最近的选择塑造的种群表现出显着较低的错误发现率比更趋分化的菌株组成的种群。我们还概括了以前的实验验证的数量性状变异的全基因组关联研究。我们基于模拟的性能评估为社区提供了关键的背景下，追求定量遗传研究使用C。elegans自然多样性资源，以阐明复杂性状的遗传基础，在C。elegans自然种群
Quantitative genetics in Caenorhabditis elegans seeks to identify naturally segregating genetic variants that underlie complex traits. Genome-wide association studies scan the genome for individual genetic variants that are significantly correlated with phenotypic variation in a population, or quantitative trait loci. Genome-wide association studies are a popular choice for quantitative genetic analyses because the quantitative trait loci that are discovered segregate in natural populations. Despite numerous successful mapping experiments, the empirical performance of genome-wide association study has not, to date, been formally evaluated in C. elegans. We developed an open-source genome-wide association study pipeline called NemaScan and used a simulation-based approach to provide benchmarks of mapping performance in collections of wild C. elegans strains. Simulated trait heritability and complexity determined the spectrum of quantitative trait loci detected by genome-wide association studies. Power to detect smaller-effect quantitative trait loci increased with the number of strains sampled from the C. elegans Natural Diversity Resource. Population structure was a major driver of variation in mapping performance, with populations shaped by recent selection exhibiting significantly lower false discovery rates than populations composed of more divergent strains. We also recapitulated previous genome-wide association studies of experimentally validated quantitative trait variants. Our simulation-based evaluation of performance provides the community with critical context to pursue quantitative genetic studies using the C. elegans Natural Diversity Resource to elucidate the genetic basis of complex traits in C. elegans natural populations.
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影响因子：
30.8
作者：
Andersen, Erik C.;Gerke, Justin P.;Shapiro, Joshua A.;Crissman, Jonathan R.;Ghosh, Rajarshi;Bloom, Joshua S.;Felix, Marie-Anne;Kruglyak, Leonid
通讯作者：
Kruglyak, Leonid
影响因子：
6.7
作者：
Evans KS;Wit J;Stevens L;Hahnel SR;Rodriguez B;Park G;Zamanian M;Brady SC;Chao E;Introcaso K;Tanny RE;Andersen EC
通讯作者：
Andersen EC
影响因子：
2.5
作者：
Churchill, Gary A.;Gatti, Daniel M.;Munger, Steven C.;Svenson, Karen L.
通讯作者：
Svenson, Karen L.
影响因子：
14.9
作者：
Cook, Daniel E.;Zdraljevic, Stefan;Andersen, Erik C.
通讯作者：
Andersen, Erik C.
影响因子：
3.3
作者：
Gimond, Clotilde;Vielle, Anne;Braendle, Christian
通讯作者：
Braendle, Christian