Systematic functional annotation of human cis-regulatory genetic variation

描述(由申请人提供) 摘要：人类遗传学研究的一个主要目标是从功能上描述人类基因组的多态。最近的两个项目--HapMap和1000基因组计划--在构建不同群体中常见变异和连锁不平衡的目录方面取得了巨大成功。事实上，HapMap数据已经促进了全基因组关联研究的发展，该研究已经发现了2000多个与多种疾病相关的基因座1。到这项提案的资助期开始时，1000基因组计划将基本上识别出人类2中所有的~107个常见(&gt；1%次要等位基因频率)多态。有了这个目录，该领域的下一个巨大挑战将是从功能上描述这一巨大的遗传变异图景。很有可能，这107个变异中的绝大多数都不会有可检测到的功能后果--尽管无论有多少有功能影响，识别确实影响表型的特定变异将是未来十年人类遗传学研究的一个重要目标。我们的目标是开发一种实验和计算工具的组合，允许高通量地将功能结果分配给数千个人类多态，包括许多被GWAS牵连的多态。通过对标准染色质免疫沉淀和测序方法(“CHIP-SEQ”)3的简单修改，涉及样本池，我们将能够将分子特征遗传定位到单核苷酸水平，与替代方法相比，在效率和成本效益方面获得约100倍的收益。将得到的功能多态图谱与ESNP和GWAS结果相结合，将允许同时精确定位和功能表征许多影响基因表达或疾病风险的多态。 公共卫生相关性：我们的项目将通过极大地加速查明各种人类疾病背后的原因多态的过程，对人类健康产生切实和广泛的影响。由于许多原因，确定因果多态是重要的，例如，研究人员进行有针对性的后续研究和功能分析，以更好地了解多态的作用机制及其对疾病的影响。此外，了解因果多态将使其在病例/对照队列中的基因分型能够揭示这种关联的真实人群归因风险和优势比，这两者对于我们理解每个多态在疾病中的重要性都是至关重要的；使用其他SNP作为替代，可能会大大低估一个多态对疾病的贡献。

DESCRIPTION (Provided by the applicant) Abstract: A major goal of human genetics research is to functionally characterize polymorphisms in the human genome. Two recent projects-the HapMap and the 1000 Genomes Project- have achieved tremendous success in constructing a catalog of common variants and linkage disequilibrium in diverse populations. Indeed, the HapMap data have allowed the development of genome-wide association studies (GWAS), which have already implicated over two thousand loci associated with a wide range of diseases1. By the beginning of this proposal's funding period, the 1000 Genomes Project will have identified essentially all ~107 common (>1% minor allele frequency) polymorphisms in humans2. With this catalog in hand, the next great challenge for the field will be to functionally characterize this vast landscape of genetic variation. It is quite possible that the vast majority of these 107 variants will have no detectable functional consequences-though regardless of what fraction have functional effects, identifying the specific variants that do affect phenotypes will be a significant goal for human genetics research in the coming decade. Our objective is to develop a combination of experimental and computational tools that will allow the high-throughput assignment of functional consequences to thousands of human polymorphisms, including many of those implicated by GWAS. With a simple modification to standard chromatin immunoprecipitation and sequencing ("ChIP-seq") methods3 involving pooling of samples, we will be able to genetically map molecular traits down to the level of single nucleotides with ~100-fold gains in efficiency and cost-effectiveness compared to alternative methods. Integrating the resulting functional polymorphism maps with eSNP and GWAS results will allow many polymorphisms affecting gene expression or disease risk to be simultaneously pinpointed and functionally characterized. Public Health Relevance: Our project will have tangible and wide-reaching effects on human health by greatly accelerating the process of pinpointing causal polymorphisms underlying diverse human diseases. Identifying causal polymorphisms is important for a number of reasons, e.g. for investigators to perform targeted follow-up studies and functional assays to better understand the polymorphism's mechanism of action, and its effects on disease. In addition, knowing the causal polymorphism will allow its genotyping in case/control cohorts to reveal the true population-attributable risk and odds ratio of the association, both of which are crucial to our understanding of each polymorphism's importance in disease; using other SNPs as proxies may substantially underestimate a polymorphism's contribution to disease.