Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity.

Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity.
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DOI:
10.1016/j.ajhg.2022.01.002
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发表时间:
2022-02-03
影响因子:
9.8
通讯作者:
Battle A
Battle A
中科院分区:
生物学1区
文献类型:
--
作者:
Arvanitis M;Tayeb K;Strober BJ;Battle A

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揭示遗传变异对基因表达的功能影响对于理解组织生物学和复杂性状的发病机制非常重要。尽管我们付出了巨大的努力来绘制许多人体组织中的表达数量性状位点(eQTL),但我们将这些发现转化为理解人类疾病的能力还不完整,并且大多数疾病位点不能通过与靶基因表达的关联来解释。细胞类型特异性和许多 eQTL 存在多个独立的因果变异是导致疾病位点明显差异的潜在混杂因素。在这项研究中,我们研究了遗传效应对基因表达的组织特异性以及与疾病位点的重叠,同时考虑了组织内部和组织之间存在的多种因果变异。我们发现了 eQTL 普遍存在的组织特异性的证据,但这种特异性常常被连锁不平衡所掩盖,从而误导了传统的荟萃分析方法。我们提出 CAFEH(等位基因异质性存在下的共定位和精细映射),这是一种贝叶斯方法,整合多个性状的遗传关联数据,结合连锁不平衡来识别因果变异。 CAFEH 在共定位和精细映射方面优于以前的方法。使用 CAFEH,我们表明具有高度组织特异性遗传效应的基因受到更大的选择,在分化和发育过程中丰富,并且更有可能参与人类疾病。最后,我们证明 CAFEH 可以有效地利用基因表达遗传调控中广泛的等位基因异质性来优先考虑全基因组关联复杂性状位点中的目标组织,从而提高我们解释复杂性状遗传学的能力。
Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and the pathogenesis of complex traits. Despite large efforts to map expression quantitative trait loci (eQTLs) across many human tissues, our ability to translate those findings to understanding human disease has been incomplete, and the majority of disease loci are not explained by association with expression of a target gene. Cell-type specificity and the presence of multiple independent causal variants for many eQTLs are potential confounders contributing to the apparent discrepancy with disease loci. In this study, we investigate the tissue specificity of genetic effects on gene expression and the overlap with disease loci while considering the presence of multiple causal variants within and across tissues. We find evidence of pervasive tissue specificity of eQTLs, often masked by linkage disequilibrium that misleads traditional meta-analytic approaches. We propose CAFEH (colocalization and fine-mapping in the presence of allelic heterogeneity), a Bayesian method that integrates genetic association data across multiple traits, incorporating linkage disequilibrium to identify causal variants. CAFEH outperforms previous approaches in colocalization and fine-mapping. Using CAFEH, we show that genes with highly tissue-specific genetic effects are under greater selection, enriched in differentiation and developmental processes, and more likely to be involved in human disease. Last, we demonstrate that CAFEH can efficiently leverage the widespread allelic heterogeneity in genetic regulation of gene expression to prioritize the target tissue in genome-wide association complex trait loci, thereby improving our ability to interpret complex trait genetics.
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发表时间: 2021-01-08
影响因子: 14.9
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