ADELLE: A global testing method for trans-eQTL mapping.

IF 4 2区 生物学 Q1 GENETICS & HEREDITY
PLoS Genetics Pub Date : 2025-01-10 eCollection Date: 2025-01-01 DOI:10.1371/journal.pgen.1011563
Takintayo Akinbiyi, Mary Sara McPeek, Mark Abney
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引用次数: 0

Abstract

Understanding the genetic regulatory mechanisms of gene expression is an ongoing challenge. Genetic variants that are associated with expression levels are readily identified when they are proximal to the gene (i.e., cis-eQTLs), but SNPs distant from the gene whose expression levels they are associated with (i.e., trans-eQTLs) have been much more difficult to discover, even though they account for a majority of the heritability in gene expression levels. A major impediment to the identification of more trans-eQTLs is the lack of statistical methods that are powerful enough to overcome the obstacles of small effect sizes and large multiple testing burden of trans-eQTL mapping. Here, we propose ADELLE, a powerful statistical testing framework that requires only summary statistics and is designed to be most sensitive to SNPs that are associated with multiple gene expression levels, a characteristic of many trans-eQTLs. In simulations, we show that for detecting SNPs that are associated with 0.1%-2% of 10,000 traits, among the 8 methods we consider ADELLE is clearly the most powerful overall, with either the highest power or power not significantly different from the highest for all settings in that range. We apply ADELLE to a mouse advanced intercross line data set and show its ability to find trans-eQTLs that were not significant under a standard analysis. We also apply ADELLE to trans-eQTL mapping in the eQTLGen data, and for 1,451 previously identified trans-eQTLs, we discover trans association with additional expression traits beyond those previously identified. This demonstrates that ADELLE is a powerful tool at uncovering trans regulators of genetic expression.

阿黛尔:跨eqtl映射的全球测试方法。
了解基因表达的遗传调控机制是一个持续的挑战。与表达水平相关的遗传变异在接近基因时很容易被识别(即顺式- eqtl),但远离与其表达水平相关的基因的snp(即反式- eqtl)则很难发现,尽管它们占基因表达水平的大部分遗传能力。识别更多trans-eQTL的主要障碍是缺乏足够强大的统计方法来克服trans-eQTL定位的小效应大小和大的多重测试负担的障碍。在这里,我们提出了ADELLE,这是一个功能强大的统计测试框架,只需要汇总统计,并且被设计成对与多个基因表达水平相关的snp最敏感,这是许多反式eqtl的特征。在模拟中,我们表明,对于检测与10,000个性状中0.1%-2%相关的snp,我们认为ADELLE在8种方法中显然是最强大的,在该范围内所有设置的最高功率或功率与最高功率没有显着差异。我们将ADELLE应用于小鼠高级交叉系数据集,并显示其发现在标准分析下不显著的trans- eqtl的能力。我们还将ADELLE应用于eQTLGen数据中的trans- eqtl映射,对于先前鉴定的1451个trans- eqtl,我们发现了与先前鉴定的其他表达性状的反关联。这表明ADELLE是发现基因表达反式调控因子的有力工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Genetics
PLoS Genetics GENETICS & HEREDITY-
自引率
2.20%
发文量
438
期刊介绍: PLOS Genetics is run by an international Editorial Board, headed by the Editors-in-Chief, Greg Barsh (HudsonAlpha Institute of Biotechnology, and Stanford University School of Medicine) and Greg Copenhaver (The University of North Carolina at Chapel Hill). Articles published in PLOS Genetics are archived in PubMed Central and cited in PubMed.
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