Understanding the Genetic Architecture of Gene Expression Regulation

描述(由申请人提供)：基因表达是人类和模式生物表型变异的基本决定因素。众所周知，基因表达调控具有相当大的可遗传成分，被认为是导致疾病风险和其他表型变异的大部分遗传因素。因此，为了了解遗传变异如何影响表型变异，了解遗传变异如何影响基因表达水平是很重要的。虽然以前的研究已经确定了个别的调控变异，但对基因表达调控的整体遗传结构了解很少。基因表达的遗传控制可以包括单个顺式变体、单个反式变体，以及多个顺式和/或反式变体网络之间的上位性相互作用。在这项建议中，我们将应用种群混合、家庭结构和模式生物体的方法来了解这些成分对遗传遗传力的贡献。我们还将得出关于长期顺式效应、顺式-顺式相互作用以及跨组织类型的共同基因调控的结论。由于检测不同影响的能力有很大的差异，我们提出的方法比计算这些类别中可靠识别的关联的数量的方法更有可能产生关于基因表达的遗传结构的公正结论。我们的研究将有助于更好地理解基因变异是如何影响基因表达和疾病风险的。 与公共健康相关：基因表达调控指的是我们的遗传密码如何影响哪些基因的开启和关闭，人们普遍认为这解释了基因对疾病风险的大部分贡献。基因表达调控可能受到靠近基因开启和关闭的基因组部分的遗传变异的影响，或者受到基因组其他部分的遗传变异的影响，或者受到这些影响的组合的影响。在这项提案中，我们将分析来自多个群体和家庭队列的数据，以了解这些因素如何影响基因表达。

DESCRIPTION (provided by applicant): Gene expression is a fundamental determinant of phenotypic variation in humans and model organisms. Regulation of gene expression is known to have a substantial heritable component, and is believed to underly much of the genetic contribution to disease risk and other phenotypic variation. Thus, in order to understand how genetic variation affects phenotypic variation, it is important to understand how genetic variation affects gene expression levels. Although previous studies have identified individual regulatory variants, the overall genetic architecture of gene expression regulation is poorly understood. Genetic control of gene expression may include individual cis variants, individual trans variants, as well as epistatic interactions between networks of multiple cis and/or trans variants. In this proposal, we will apply population admixture, family structure and model organism approaches to understanding the contributions of these components to genetic heritability. We will also draw conclusions about long-range cis effects, cis-cis interactions, and shared genetic regulation across tissue types. Due to large differences in power to detect different effects, the approaches we propose have a greater chance of yielding unbiased conclusions about the genetic architecture of gene expression than the approach of counting the number of robustly identified associations in these categories. Our research will lead to a greater understanding of how genetic variation affects gene expression and disease risk. PUBLIC HEALTH RELEVANCE: Gene expression regulation refers to how our genetic code affects which genes are turned on and off, and is widely believed to explain much of the genetic contribution to disease risk. Gene expression regulation may be affected by genetic variation in the part of the genome close to the gene being turned on and off, or by genetic variation in other parts of the genome, or by combinations of these effects. In this proposal, we will analyze data from multiple populations and family cohorts to understand how these factors influence gene expression.