Genomic approaches for dissecting regulatory variation

项目总结/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。研究在我 该实验室专注于调节遗传变异。这种类型的变异导致基因的差异， 基因在个体间的表达，并对人类疾病的遗传风险有很大的贡献 包括心血管、自身免疫和神经疾病。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。 由于标测时通常使用的样本量较小，统计功效较低 尽管基因组中的调控变异存在，但大多数调控变异的来源仍然未知。监管 已经定位的基因座通常跨越几十个序列变体，我们也不知道它们的身份。 实际的致病变异，也不是它们改变表达的分子机制。几乎所有工作 关于调控变异的研究主要集中在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认识 变化仍然非常有限。 该提案概述了解决这些关键问题的研究战略。我们计划将联合收割机 方法从定量和统计遗传学与实验方法，利用新兴的 阅读、写入和编辑基因组的技术。我们将使用强大的方法在酵母 酿酒酵母揭示了真核生物之间共享的调节变异的原则， 这在包括人类在内的其他物种中是具有挑战性的。 我们未来五年的目标是剖析调控变异对分子生物学的影响。 从DNA到mRNA、蛋白质和细胞适应性的级联。我们计划全面查明 调节变体，了解基因对mRNA和蛋白质水平的影响，具有较高的统计能力， 在不同的环境中，并评估调节变化对细胞适应性的影响。我们的长期 我们的愿景是把酵母变成第一个真核生物物种，我们可以准确地预测 自然遗传变异预计从这项工作中得出的经验教训对以下方面非常有价值： 解释监管变化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.