New York Center for Collaborative Research in Common Disease Genomics

在这项提案中，我们解决了常见复杂疾病对基因组构成的巨大挑战 分析和超越它们为推进医疗保健提供的巨大机遇。平凡的 建议在这里研究的遗传性疾病被认为具有极端的基因座异质性，需要 对大量样本进行分析，以全面确定其背后的基因组变异。我们 建议结合深入的人口研究和对SNPs、Indels和结构性的联合分析 编码区和非编码区的变异将提供对共同基因的下一层次的理解 精神错乱。全基因组测序(WGS)将是这种下一代基因组学方法的关键 一种复杂的疾病。WGS将需要伴随着生成和处理 庞大的数据集，是NYGC的一个特别关注和优势。WGS还需要有新的 统计工具和算法，将由致力于这一提议的强大核心小组开发。 这项提案的一个首要目标是利用WGS的力量，识别疾病-- 个体核苷酸水平上的相关变异。在许多情况下，致病突变属于非编码 基因组区域，只有用WGS才能卓有成效地探索这些区域。将投入大量精力建设 新的计算策略，对非编码转录序列进行功能注释，并构建新的 支持这种策略的数据集，开辟了理解与疾病相关的监管的新前沿 变种。我们将使用WGS平台探索广泛的人类变异，包括罕见的变异 从中等效应到大效应，从新变种到大效应，以及常见的小效应变种。我们会 结合可用的RNA和表观基因组数据集来预测风险的行动模式并确定保护措施 等位基因。这些结果，再加上环境和临床数据的整合，将增强我们的 了解常见疾病的遗传风险，为利用个人基因组学奠定基础 在疾病预防和治疗方面，包括描绘药物开发的路径。 许多被建议进行研究的人群来自纽约，那里是最多样化的避难所 世界上最大的人口。分析不同的人群是全面公共 疾病分析，因为个体等位基因的效应大小被认为在不同的群体中是不同的，这是由于基因- 基因相互作用。使用来自纽约和整个纽约的不同种群中存在的遗传混合物 在美国，我们将首次对这些相互作用在许多表型中的影响进行系统研究。 这些目标将通过与基因学家、内科医生和 患者，由NYGC的一个专注的团队组织。他们将从合作和支持中得到丰富 来自独立基金会。

In this proposal, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease- associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort will be put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants. We will explore a wide spectrum of human variation using the WGS platform, including rare variants of modest to large effect, de novo variants of large effect, and common variants of small effect. We will combine available RNA and epigenomic datasets to predict modes of action of risk and identify protective alleles. These results, combined with the integration of environmental and clinical data, will enhance our understanding of genetic risk for common disease and lay the groundwork for utilization of personal genomics in disease prevention and treatment, including the delineation of pathways for drug development. Many of the population cohorts proposed for study are from New York, which harbors the most diverse population in the world. Analyzing diverse populations is a critical component of comprehensive common disease analysis, as effect sizes of individual alleles are believed to vary in different populations due to gene- gene interactions. Using the genetic admixture present in different populations from NY and throughout the United States, we will conduct the first systematic study of these interaction effects in many phenotypes. These aims will be accomplished through widespread collaborations, with genomicists, physicians, and patients, organized through a focused team at NYGC. They will be enriched by the collaboration and support from independent Foundations.