Causes and consequences of regulatory genetic variation

项目摘要/摘要 个体之间的遗传变异决定了重要的表型，包括普通人的风险 心血管疾病、自身免疫疾病和神经疾病。特别是，调节性基因 变异会导致基因表达的个体间差异。由此产生的基因表达差异 解释了许多遗传复杂性状的很大一部分变异。 尽管监管差异至关重要，但许多根本性问题仍然悬而未决。第一, 给定基因组中的大多数DNA差异可能没有影响。特定变种的性质 产生的影响仍然知之甚少。其次，遗传变异会特别影响蛋白质。 在不改变同一基因的信使核糖核酸丰度的情况下，该基因的丰度。这个 造成这些蛋白质特异性效应的机制尚不清楚。第三，我们只有一个 对调控变异导致的基因表达差异如何影响的粗略理解 生物表型。 在接下来的五年里，我实验室的研究将集中在解决这些关键差距上 知识。具体地说，我们试图识别和表征因果DNA变异，研究 基因变异对蛋白质降解的影响，并定量检查给定的精确丰度 基因可以塑造生物体的特征。我们的工作结合了计算生物学、定量和统计学 遗传学与实验性的全基因组方法。我们使用酿酒酵母作为一种 强大和易处理的调节变异模型系统，同时在人类中追求相关方法 细胞。 我们的长期愿景是提高我们对监管差异的理解，使其成为 有可能准确预测个体基因组中DNA变异的后果。这种能力 对于改善人类健康的基础研究和个性化方法将是有价值的。

Project Summary / Abstract Genetic variation among individuals shapes important phenotypes, including the risk for common human diseases such as cardiovascular, autoimmune, and neurological disease. In particular, regulatory genetic variation causes inter-individual differences in gene expression. The resulting gene expression differences account for a substantial portion of variation in many genetically complex traits. In spite of the critical importance of regulatory variation, many fundamental questions remain open. First, most DNA differences in a given genome likely have no effect. The nature of the specific variants that do have effects remains poorly understood. Second, genetic variation can specifically affect the protein abundance of a given gene without altering the abundance of the mRNA of the same gene. The mechanisms that are responsible for these protein-specific effects remain unclear. Third, we only have a crude understanding of how the differences in gene expression that result from regulatory variation affect organismal phenotypes. Over the next five years, research in my laboratory will focus on addressing these critical gaps in knowledge. Specifically, we seek to identify and characterize causal DNA variants, study the impact of genetic variation on protein degradation, and examine quantitatively how the precise abundance of a given gene can shape organismal traits. Our work combines computational biology, quantitative and statistical genetics with experimental genome-wide approaches. We use the yeast Saccharomyces cerevisiae as a powerful and tractable model system for regulatory variation, while pursuing related approaches in human cells. Our long-term vision is to improve our understanding of regulatory variation to the point at which it becomes possible to accurately predict the consequences of the DNA variants in an individual’s genome. This ability will be valuable for fundamental research and personalized approaches for improving human health.