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具有主要效应的多态基因:对拟南芥变异、选择和进化的影响

Polymorphic genes of major effect: consequences for variation, selection and evolution in Arabidopsis thaliana.

作者信息

Stinchcombe John R, Weinig Cynthia, Heath Katy D, Brock Marcus T, Schmitt Johanna

机构信息

Department of Ecology and Evolutionary Biology, Unversity of Toronto, Toronto, Ontario.

出版信息

Genetics. 2009 Jul;182(3):911-22. doi: 10.1534/genetics.108.097030. Epub 2009 May 4.

Abstract

The importance of genes of major effect for evolutionary trajectories within and among natural populations has long been the subject of intense debate. For example, if allelic variation at a major-effect locus fundamentally alters the structure of quantitative trait variation, then fixation of a single locus can have rapid and profound effects on the rate or direction of subsequent evolutionary change. Using an Arabidopsis thaliana RIL mapping population, we compare G-matrix structure between lines possessing different alleles at ERECTA, a locus known to affect ecologically relevant variation in plant architecture. We find that the allele present at ERECTA significantly alters G-matrix structure-in particular the genetic correlations between branch number and flowering time traits-and may also modulate the strength of natural selection on these traits. Despite these differences, however, when we extend our analysis to determine how evolution might differ depending on the ERECTA allele, we find that predicted responses to selection are similar. To compare responses to selection between allele classes, we developed a resampling strategy that incorporates uncertainty in estimates of selection that can also be used for statistical comparisons of G matrices.

摘要

主要效应基因对自然种群内部和种群之间进化轨迹的重要性长期以来一直是激烈争论的主题。例如,如果一个主要效应位点的等位基因变异从根本上改变了数量性状变异的结构,那么单个位点的固定就可能对随后进化变化的速率或方向产生迅速而深远的影响。利用拟南芥重组自交系作图群体,我们比较了在ERECTA位点具有不同等位基因的株系之间的G矩阵结构,该位点已知会影响植物结构中与生态相关的变异。我们发现,ERECTA位点存在的等位基因会显著改变G矩阵结构,特别是分支数与开花时间性状之间的遗传相关性,并且可能还会调节对这些性状的自然选择强度。然而,尽管存在这些差异,当我们扩展分析以确定进化如何因ERECTA等位基因而异时,我们发现对选择的预测反应是相似的。为了比较不同等位基因类别对选择的反应,我们开发了一种重抽样策略,该策略纳入了选择估计中的不确定性,也可用于G矩阵的统计比较。

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