通过计算和 cis-eQTL 分析来描述 ER 应激反应调控中的遗传变异特征。

Characterizing genetic variation in the regulation of the ER stress response through computational and cis-eQTL analyses.

机构信息

Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112, USA.

出版信息

G3 (Bethesda). 2023 Dec 6;13(12). doi: 10.1093/g3journal/jkad229.

Abstract

Misfolded proteins in the endoplasmic reticulum (ER) elicit the ER stress response, a large transcriptional response driven by 3 well-characterized transcription factors (TFs). This transcriptional response is variable across different genetic backgrounds. One mechanism in which genetic variation can lead to transcriptional variability in the ER stress response is through altered binding and activity of the 3 main TFs: XBP1, ATF6, and ATF4. This work attempts to better understand this mechanism by first creating a computational pipeline to identify potential binding sites throughout the human genome. We utilized GTEx data sets to identify cis-eQTLs that fall within predicted TF binding sites (TFBSs). We also utilized the ClinVar database to compare the number of pathogenic vs benign variants at different positions of the binding motifs. Finally, we performed a cis-eQTL analysis on human cell lines experiencing ER stress to identify cis-eQTLs that regulate the variable ER stress response. The majority of these cis-eQTLs are unique to a given condition: control or ER stress. Some of these stress-specific cis-eQTLs fall within putative binding sites of the 3 main ER stress response TFs, providing a potential mechanism by which these cis-eQTLs might be impacting gene expression under ER stress conditions through altered TF binding. This study represents the first cis-eQTL analysis on human samples experiencing ER stress and is a vital step toward identifying the genetic components responsible for the variable ER stress response.

摘要

内质网(ER)中错误折叠的蛋白质会引发 ER 应激反应,这是一种由 3 种特征明确的转录因子(TF)驱动的大规模转录反应。这种转录反应在不同的遗传背景下是不同的。遗传变异导致 ER 应激反应转录变异性的一种机制是通过改变 3 种主要 TF 的结合和活性:XBP1、ATF6 和 ATF4。这项工作试图通过首先创建一个计算管道来识别整个人类基因组中的潜在结合位点,从而更好地理解这一机制。我们利用 GTEx 数据集来识别落在预测 TF 结合位点(TFBS)内的顺式表达数量性状基因座(cis-eQTL)。我们还利用 ClinVar 数据库来比较不同结合基序位置的致病和良性变异的数量。最后,我们对经历 ER 应激的人类细胞系进行了 cis-eQTL 分析,以识别调节可变 ER 应激反应的 cis-eQTL。这些 cis-eQTL 中的大多数都是特定于给定条件的:对照或 ER 应激。这些应激特异性 cis-eQTL 中的一些位于 3 种主要 ER 应激反应 TF 的假定结合位点内,这为这些 cis-eQTL 可能通过改变 TF 结合来影响 ER 应激条件下的基因表达提供了一种潜在机制。这项研究代表了对经历 ER 应激的人类样本进行的首次 cis-eQTL 分析,是确定导致可变 ER 应激反应的遗传成分的重要步骤。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a259/10700025/b4d1fd453685/jkad229f1.jpg

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