Investigating the co-transcriptional impact of genetic variation on gene regulation and disease

摘要 调控变异在复杂性状的遗传学中扮演着核心角色；然而，它仍然 确定哪些基因和调控机制受到影响具有挑战性。虽然很大 国际合作优先考虑了解增强子和启动子区域 在控制基因表达方面，我们对外部遗传因素的理解仍然存在差距 增强子和启动子影响基因调控。我们建议使用一个由70个无关的HapMap组成的小组 约鲁巴淋巴母细胞系(LCLS)研究遗传变异影响基因的机制 独立于促进剂和促进剂的监管。我们将进一步使用IPSCs(诱导多能性 干细胞)和我们最近从这70个细胞系中建立的衍生心肌细胞来研究 同一变种在多种不同细胞类型中的影响。 最近，我们发现了一类影响基因表达的表达数量性状基因座(QTL)变体，如 通过RNA-seq检测，但没有显示任何影响增强子或启动子功能的信号。我们命名为 这些变体在转录后开始表达QTL(PiQTL)，反映了我们认为piQTL 独立于促进剂和促进剂发挥作用。我们的数据表明，piQTL可能贡献了多达三分之一的 所有eQTL，这意味着它们解释了相当大一部分对基因表达水平的遗传影响。 我们的数据还表明，绝大多数影响RNA剪接(SQTL)的遗传变异起作用 不依赖于增强剂和促进剂。因为sQTL是遗传变异和 对于复杂的性状，我们认为增强子和启动子之外的遗传变异可能起到很大作用 复杂的特征和疾病。 在该项目中，我们提出了四种不同的共转录机制，它们可能驱动piQTL和/或sQTL， 我们提出了一系列分析来量化这些机制的相对贡献。我们会 评估这些机制中的每一个在LCLS、IPSCs和心肌细胞中的作用。我们将使用 全基因组关联研究(GWAS)数据，以量化这些机制对复杂性的贡献 特征和疾病。我们将专注于心脏特征，我们在心肌细胞中的数据可以帮助我们 推定的因果分子机制分开。 在本项目结束时，我们将彻底描述一类有助于 不依赖于增强子和启动子的复杂性状的遗传。

Abstract Regulatory variation plays a central role in the genetics of complex traits; however, it remains challenging to determine which genes and regulatory mechanisms are affected. While large international collaborations have prioritized understanding how enhancer and promoter regions control gene expression, there remains a gap in our understanding of how genetic elements outside enhancers and promoters impact gene regulation. We propose to use a panel of 70 unrelated HapMap Yoruba lymphoblastoid cell lines (LCLs) to study the mechanisms by which genetic variation impact gene regulation independent of enhancers and promoters. We will further use the iPSCs (induced pluripotent stem cells) and derived cardiomyocytes that we have recently established from these 70 lines to study the effects of the same variants in multiple different cell-types. Recently, we found a class of expression quantitative trait loci (QTLs) variants that affect gene expression as measured by RNA-seq, but that do not show any signal of affecting enhancer or promoter function. We named these variants post-transcription initiation expression QTLs (piQTLs), reflecting our belief that piQTLs function independently of enhancers and promoters. Our data suggest that piQTLs may contribute up to 1/3 of all eQTLs, implying that they explain a considerable fraction of the genetic effects on gene expression levels. Our data also imply that the vast majority of genetic variants that affect RNA splicing (sQTLs) function independently of enhancers and promoters. Because sQTLs are a major link between genetic variation and complex traits, we propose that genetic variants outside enhancers and promoters may contribute substantially to complex traits and disease. In the project, we propose four distinct co-transcriptional mechanisms that may drive piQTLs and/or sQTLs, and we propose a series of analyses to quantify the relative contributions of these mechanisms. We will evaluate the role of each of these proposed mechanisms in LCLs, iPSCs and cardiomyocytes. We will use genome-wide association study (GWAS) data to quantify the contribution of these mechanisms to complex traits and disease. We will focus on cardiac traits for which our data in cardiomyocytes can help us tease putative causal molecular mechanisms apart. At the conclusion of this project we will have thoroughly characterized a class of variants that contribute to the genetic of complex traits independently of enhancers and promoters.