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EPISTASIS AND THE EFFECT OF FOUNDER EVENTS ON THE ADDITIVE GENETIC VARIANCE.上位性与奠基者事件对加性遗传方差的影响。
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An Extension of the Concept of Partitioning Hereditary Variance for Analysis of Covariances among Relatives When Epistasis Is Present.存在上位性时用于分析亲属间协方差的遗传方差划分概念的扩展
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大麦数量性状上位性效应的全基因组分析。

Genomewide analysis of epistatic effects for quantitative traits in barley.

作者信息

Xu Shizhong, Jia Zhenyu

机构信息

Department of Botany and Plant Sciences, University of California, Riverside, California 92521, USA.

出版信息

Genetics. 2007 Apr;175(4):1955-63. doi: 10.1534/genetics.106.066571. Epub 2007 Feb 4.

DOI:10.1534/genetics.106.066571
PMID:17277367
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1855123/
Abstract

The doubled-haploid (DH) barley population (Harrington x TR306) developed by the North American Barley Genome Mapping Project (NABGMP) for QTL mapping consisted of 145 lines and 127 markers covering a total genome length of 1270 cM. These DH lines were evaluated in approximately 25 environments for seven quantitative traits: heading, height, kernel weight, lodging, maturity, test weight, and yield. We applied an empirical Bayes method that simultaneously estimates 127 main effects for all markers and 127(127-1)/2=8001 interaction effects for all marker pairs in a single model. We found that the largest main-effect QTL (single marker) and the largest epistatic effect (single pair of markers) explained approximately 18 and 2.6% of the phenotypic variance, respectively. On average, the sum of all significant main effects and the sum of all significant epistatic effects contributed 35 and 6% of the total phenotypic variance, respectively. Epistasis seems to be negligible for all the seven traits. We also found that whether two loci interact does not depend on whether or not the loci have individual main effects. This invalidates the common practice of epistatic analysis in which epistatic effects are estimated only for pairs of loci of which both have main effects.

摘要

由北美大麦基因组图谱计划(NABGMP)为进行数量性状基因座(QTL)定位而构建的加倍单倍体(DH)大麦群体(Harrington×TR306)由145个株系和127个标记组成,覆盖的基因组总长度为1270厘摩(cM)。这些DH株系在大约25种环境条件下针对七个数量性状进行了评估,这七个数量性状分别是:抽穗期、株高、粒重、倒伏情况、成熟度、容重和产量。我们应用了一种经验贝叶斯方法,该方法在一个单一模型中同时估计所有标记的127个主效应以及所有标记对的127×(127 - 1)/2 = 8001个互作效应。我们发现,最大的主效应QTL(单个标记)和最大的上位性效应(单个标记对)分别解释了约18%和2.6%的表型变异。平均而言,所有显著主效应的总和以及所有显著上位性效应的总和分别占总表型变异的35%和6%。对于所有这七个性状,上位性似乎可以忽略不计。我们还发现两个基因座是否相互作用并不取决于这些基因座是否具有个体主效应。这使得仅对两个都具有主效应的基因座对估计上位性效应的上位性分析的常规做法无效。