Mapping QTLs Associated with Variation in RNA Decay Rates

描述(申请人提供)：表达数量性状基因座(EQTL)定位研究已成为识别影响基因调控的遗传变异的广泛使用的工具。在这些研究中，基因表达水平被视为数量性状，通过结合对个体间基因表达水平的估计和全基因组的基因分型数据，将表达表型映射到特定的基因组座位。最近在人类和其他物种中进行的eQTL研究揭示了种群内和种群之间基因表达水平的巨大差异，并确定了大量影响基因调控的遗传因素。然而，到目前为止，所有的eQTL定位研究，无论是什么物种，都考虑了稳态基因表达水平的差异，因此无法确定eQTL关联的确切调控机制。特别是，典型的eQTL研究，以及大多数其他全基因组的基因表达表型研究，都没有收集数据来区分转录调控的变异和RNA衰减率的变异。总的来说，也许因为转录起始率通常被认为是整个基因表达水平的主要决定因素，所以与转录调控相比，RNA衰变机制的研究还不够深入。因此，我们对RNA衰减率在基因之间或个体之间的差异知之甚少，而且这种差异在确定最终生理表型(如人类疾病)方面的潜在重要性仍不清楚。为了解决这个问题，我们建议对HapMap淋巴母细胞系(LCL)中的RNA衰减率进行全基因组eQTL定位研究，对于这些LCL，也可以获得全基因组的稳态基因表达数据和基因数据。我们建议收集的数据将使我们能够识别潜在的RNA衰减率变异的遗传因素，以及研究RNA衰减率变异对基因表达水平整体调控变异的相对重要性。 公共卫生相关性：我们建议使用基因组方法的组合来定位影响RNA衰减率变异的QTL，以增加我们对总体基因表达水平变异背后的调控机制的理解。

DESCRIPTION (provided by applicant): Expression quantitative trait loci (eQTL) mapping studies have become a widely-used tool for identifying genetic variants that affect gene regulation. In these studies, gene expression levels are viewed as quantitative traits, and expression phenotypes are mapped to particular genomic loci by combining estimates of gene expression levels across individuals with genome-wide genotyping data. Recent eQTL studies in humans, as well as in other species, have revealed substantial variation in gene expression levels within and between populations, and identified a large number of genetic factors that influence gene regulation. However, to date, all eQTL mapping studies, regardless of species, have considered variation in steady-state gene expression levels and thus could not determine the exact regulatory mechanism underlying the eQTL association. In particular, typical eQTL studies, as well as most other genome-wide studies of gene expression phenotypes, do not collect data that will allow one to distinguish between variation in transcriptional regulation and variation in RNA decay rates. In general, perhaps because transcription initiation rates are commonly assumed to be the major determinants of overall gene expression levels, RNA decay mechanisms are under-studied compared with the regulation of transcription. As a result, we know relatively little about variation in RNA decay rates across genes or between individuals, and the potential importance of such variation in determining ultimate physiological phenotypes such as human disease remains unclear. To address this issue, we propose to perform a genome-wide eQTL mapping study of RNA decay rates in HapMap lymphoblastoid cell lines (LCLs) for which genome-wide steady- state gene-expression data and genotype data are also available. The data we propose to collect will allow us to identify genetic factors underlying variation in RNA decay rates as well as to study the relative importance of variation in RNA decay rates to overall regulatory variation in gene expression levels. PUBLIC HEALTH RELEVANCE: We propose to use a combination of genomic approaches to map QTLs that affect variation in RNA decay rates in order to increase our understanding of regulatory mechanisms underlying variation in overall gene expression levels.