Genomic approaches for dissecting regulatory variation

项目摘要/摘要 人类常见疾病的大部分风险来自个体之间的遗传变异。我的研究 实验室的重点是调节基因变异。这种类型的变异会导致基因的差异 在个体中表达，并在人类疾病的遗传风险中贡献了相当大的比例 包括心血管疾病、自身免疫疾病和神经疾病。尽管它对人类至关重要 疾病遗传学，关于调控变异的基本问题仍然没有答案。 由于在绘制地图时通常使用小样本大小，因此统计能力较低 基因组中的调控变异，大多数调控变异的来源仍然未知。监管机构 已经被映射的基因座通常跨越数十个序列变体，而我们也不知道 实际的因果变异，也不是它们改变表达的分子机制。几乎所有的工作 对调节变异的关注集中在mRNA水平上，目前还不清楚它在多大程度上转化为蛋白质水平。 和细胞生物学。最后，我们对环境如何调节监管效果的了解 变异仍然受到严格限制。 该提案概述了解决这些关键问题的研究战略。我们计划合并 方法从数量和统计遗传学与实验方法，利用新兴的 阅读、写作和编辑基因组的技术。我们将在酵母中使用强有力的方法 酿酒酵母揭示了真核生物共有的调控变异原理，以及 在包括人类在内的其他物种中解决这些问题是具有挑战性的。 我们未来五年的目标是剖析调控变异对分子的影响。 从DNA到mRNA、蛋白质和细胞适合性的级联反应。我们计划全面确定因果关系 调控变异，了解基因对mRNA和蛋白质水平的影响，具有很高的统计能力和 跨越不同的环境，并评估调节变化对细胞健康的影响。我们的长期计划 愿景是将酵母转变为第一个真核物种，在其中我们可以准确预测 自然遗传变异。从这项工作中吸取的经验教训预计将对 解释调节变异在人类健康中的作用。

Project Summary / Abstract Much of the risk for common human disease arises from genetic variation among individuals. Research in my laboratory is focused on regulatory genetic variation. This type of variation causes differences in gene expression among individuals and contributes a substantial portion of the genetic risk for human diseases including cardiovascular, autoimmune, and neurological disease. In spite of its critical importance for human disease genetics, fundamental questions about regulatory variation remain unanswered. Because of low statistical power due to the small sample sizes commonly used when mapping regulatory variation in the genome, the source of most regulatory variation remains unknown. The regulatory loci that have been mapped typically span dozens of sequence variants, and we neither know the identity of the actual causal variants, nor the molecular mechanisms through which they alter expression. Nearly all work on regulatory variation is focused on mRNA levels, and it is unclear to what extent it translates to protein levels and cell biology. Finally, our knowledge of how the environment can modulate the effects of regulatory variation remains severely limited. This proposal outlines a research strategy to tackle these critical questions. We plan to combine methods from quantitative and statistical genetics with experimental approaches that leverage emerging techniques for reading, writing, and editing genomes. We will use powerful methods in the yeast Saccharomyces cerevisiae to reveal principles of regulatory variation that are shared among eukaryotes, and that are challenging to address in other species including humans. Our goals for the next five years are to dissect the influence of regulatory variation on the molecular cascade from DNA to mRNA, proteins and cellular fitness. We plan to comprehensively identify causal regulatory variants, understand genetic influences on mRNA and protein levels with high statistical power and across different environments, and evaluate the effects of regulatory variation on cellular fitness. Our long term vision is to turn yeast into the first eukaryotic species in which we can accurately predict the consequences of natural genetic variation. The lessons to emerge from this work are expected to be highly valuable for interpreting the role of regulatory variation in human health.