Multiomic QTL mapping reveals phenotypic complexity of GWAS loci and prioritizes putative causal variants.

IF 11.1 Q1 CELL BIOLOGY

Cell genomics Pub Date : 2025-03-12 Epub Date: 2025-02-21 DOI:10.1016/j.xgen.2025.100775

Timothy D Arthur, Jennifer P Nguyen, Benjamin A Henson, Agnieszka D'Antonio-Chronowska, Jeffrey Jaureguy, Nayara Silva, Athanasia D Panopoulos, Juan Carlos Izpisua Belmonte, Matteo D'Antonio, Graham McVicker, Kelly A Frazer

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引用次数: 0

Abstract

Most GWAS loci are presumed to affect gene regulation; however, only ∼43% colocalize with expression quantitative trait loci (eQTLs). To address this colocalization gap, we map eQTLs, chromatin accessibility QTLs (caQTLs), and histone acetylation QTLs (haQTLs) using molecular samples from three early developmental-like tissues. Through colocalization, we annotate 10.4% (n = 540) of GWAS loci in 15 traits by QTL phenotype, temporal specificity, and complexity. We show that integration of chromatin QTLs results in a 2.3-fold higher annotation rate of GWAS loci because they capture distal GWAS loci missed by eQTLs, and that 5.4% (n = 13) of GWAS colocalizing eQTLs are early developmental specific. Finally, we utilize the iPSCORE multiomic QTLs to prioritize putative causal variants overlapping transcription factor motifs to elucidate the potential genetic underpinnings of 296 GWAS-QTL colocalizations.

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多组QTL定位揭示了GWAS基因座的表型复杂性，并优先考虑假定的因果变异。

大多数GWAS位点被认为影响基因调控；然而，只有43%的基因与表达数量性状位点（eqtl）共定位。为了解决这种共定位差距，我们使用来自三种早期发育样组织的分子样本绘制了eQTLs、染色质可及性QTLs （caQTLs）和组蛋白乙酰化QTLs （haQTLs）。通过共定位，我们根据QTL表型、时间特异性和复杂性对15个性状中10.4% （n = 540）的GWAS位点进行了注释。我们发现，染色质qtl的整合导致GWAS位点的注释率提高了2.3倍，因为它们捕获了被eqtl遗漏的远端GWAS位点，并且5.4% （n = 13）的GWAS共定位的eqtl是早期发育特异性的。最后，我们利用iPSCORE多组qtl对重叠转录因子基序的推定因果变异进行优先排序，以阐明296个GWAS-QTL共定位的潜在遗传基础。

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

Cell genomics

CiteScore

7.10

自引率

0.00%

发文量