Estimating genetic variance contributed by a quantitative trait locus: removing nuisance parameters.

IF 3.3 3区生物学 Q2 GENETICS & HEREDITY

Genetics Pub Date : 2024-08-07 DOI:10.1093/genetics/iyae095

Shizhong Xu

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引用次数: 0

Abstract

The main objective of mapping quantitative trait loci (QTL) and genome-wide association studies (GWAS) is to identify and locate QTLs on the genome. Estimating the sizes of QTL is equally important as identifying the QTLs. The size of a QTL is often measured by the QTL variance, or the proportion of phenotypic variance explained by the QTL, known as the QTL heritability. The reported QTL heritability is biased upward for small-sized QTLs estimated from small samples, especially in GWAS with a very small P-value threshold accommodating to Bonferroni correction for multiple tests. The phenomenon is called the Beavis effect. Methods of correcting the Beavis effect have been developed for additive effect models. Corresponding methods are not available for QTLs with more than one effect, such as QTLs including dominance and other genetic effects. In this study, we developed explicit formulas for estimating the variances and heritability for QTL with multiple effects. We also developed a method to remove nuisance parameters via an annihilator matrix. Finally, biases in estimated QTL variances caused by the Beavis effect are investigated and corrected. The new method is demonstrated by analyzing the 1000 grain weight (KGW) trait in a hybrid rice population.

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估算数量性状基因座贡献的遗传变异：去除干扰参数

绘制数量性状基因座（QTL）图谱和全基因组关联研究（GWAS）的主要目的是识别和定位基因组上的 QTL。估计 QTL 的大小与确定 QTL 同样重要。QTL的大小通常用QTL方差或QTL解释的表型变异比例（称为QTL遗传力）来衡量。对于从小样本估计出的小尺寸 QTL，报告的 QTL 遗传率会向上偏移，特别是在 GWAS 中，p 值阈值非常小，无法进行多重检验的 Bonferroni 校正。这种现象被称为比维斯效应。纠正比维斯效应的方法是针对加法效应模型开发的。对于具有一个以上效应的 QTL，如包含显性效应和其他遗传效应的 QTL，还没有相应的方法。在这项研究中，我们开发了明确的公式来估计具有多重效应的 QTL 的方差和遗传率。我们还开发了一种通过湮灭矩阵去除干扰参数的方法。最后，我们研究并纠正了由比维斯效应引起的 QTL 方差估计偏差。新方法通过分析杂交水稻群体的千粒重（KGW）性状得到了验证。

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来源期刊

Genetics GENETICS & HEREDITY-

CiteScore

6.90

自引率

6.10%

发文量

177

审稿时长

1.5 months

期刊介绍： GENETICS is published by the Genetics Society of America, a scholarly society that seeks to deepen our understanding of the living world by advancing our understanding of genetics. Since 1916, GENETICS has published high-quality, original research presenting novel findings bearing on genetics and genomics. The journal publishes empirical studies of organisms ranging from microbes to humans, as well as theoretical work. While it has an illustrious history, GENETICS has changed along with the communities it serves: it is not your mentor''s journal. The editors make decisions quickly – in around 30 days – without sacrificing the excellence and scholarship for which the journal has long been known. GENETICS is a peer reviewed, peer-edited journal, with an international reach and increasing visibility and impact. All editorial decisions are made through collaboration of at least two editors who are practicing scientists. GENETICS is constantly innovating: expanded types of content include Reviews, Commentary (current issues of interest to geneticists), Perspectives (historical), Primers (to introduce primary literature into the classroom), Toolbox Reviews, plus YeastBook, FlyBook, and WormBook (coming spring 2016). For particularly time-sensitive results, we publish Communications. As part of our mission to serve our communities, we''ve published thematic collections, including Genomic Selection, Multiparental Populations, Mouse Collaborative Cross, and the Genetics of Sex.