UW Center for Mendelian Genomics

项目摘要/摘要(来自受资助的家长奖) 到目前为止，已经发现了2937个基因，这些基因与4163个孟德尔条件(MC)有关。然而， 3,000多种MC的遗传学基础尚不清楚，每年都有数百种新的MC被描述。在……里面 2011年，NHGRI和NHLBI成立了孟德尔基因组学中心(CMG)，以促进大规模 发现与MC有关的基因。在CMG计划的第一阶段，并与182 来自27个国家的117个机构的调查人员，华盛顿大学CMG(UW-CMG)评估 来自2,404个家族的6,598个样本，迄今已产生4,116个外显子组和97个全基因组序列。 这种广泛的合作努力导致了基因识别方面无与伦比的发现速度。 237个MC，包括123个新发现。这些发现的翻译及其对诊断学的影响 临床护理是直接和实质性的--结合遗传学的发现 在整个社区，自2012年以来被确认为潜在MC的基因变异约占阳性总数的25% 临床诊断工作的结果。此外，UW-CMG还开发了多种新的分析工具 包括CADD、Primus、SimRare、STAR、RV-TDT、CHP、VAT和Spliceosaurus以及方法学 创新包括MIP、SMMIP以及低投入外显子组和基因组测序方法。UW- CMG继续致力于开放数据共享，滚动提交符合条件的外显子组和基因组 向DBGaP提交数据(614份已交和1748份待交)，并开发一个新的数据浏览器 (http://geno2mp.gs.washington.edu)首次公开提供匿名链接 个人水平的基因类型，从3000多个外显子到由人类定义的个人临床表型 表型本体论术语。在这次更新应用中，我们在这些成功的基础上构建最大限度地利用新基因 MC的发现，利用从&gt；16,500立即访问&gt；22,000个已准备好序列的样本 家庭和163个MC，获得几个大的出生缺陷队列，总计超过24,000个三联体(&gt；94,000 样本总数)和积极的样本征集计划，包括案例汇总和案例匹配 接受过临床外显子组测序的未确诊患者。我们提出了四个具体目标：(1) 征集、组织和管理来自不明原因(即没有)的家系的表型信息和DNA样本 已知的潜在基因)来自世界各地的样本保管人，通过提交给我们的中心或 用于测序的样品或用于进一步分析的序列数据；(2)应用我们建立的生产流水线 对与未解释的MC相对应的样本进行外显子组和基因组测序并改进这一过程 通过持续的技术创新；(3)尽可能多地确定无法解释的MC的遗传基础 可能，通过使用高效的研究设计和有效的创新分析，最大限度地扩大新发现；(4) 发挥领导作用，传播和公开分享方法和数据，以促进全球努力 发现MCs背后的全部基因。

PROJECT SUMMARY/ABSTRACT (FROM FUNDED PARENT AWARD) To date, 2,937 genes underlying 4,163 Mendelian conditions (MCs) have been discovered. However, the genetic basis of over 3,000 MCs remains unknown, and hundreds of novel MCs are described each year. In 2011, the NHGRI and NHLBI established the Centers for Mendelian Genomics (CMG) to facilitate large-scale discovery of genes responsible for MCs. In Phase-1 of the CMG program, and in partnership with 182 investigators from 117 institutions in 27 countries, the University of Washington CMG (UW-CMG) assessed 6,598 samples from 2,404 families and has, to date, produced 4,116 exome and 97 whole genome sequences. This extensive collaborative effort resulted in an unparalleled pace of discovery with the identification of genes for 237 MCs, including 123 novel discoveries. The translation and impact of these discoveries on diagnostics and clinical care has been immediate and substantial—when combined with discoveries made by the genetics community at-large, variants in genes identified as underlying MCs since 2012 represent ~25% of positive results in clinical diagnostic efforts. Additionally, the UW-CMG has developed multiple new analytical tools including CADD, PRIMUS, SimRare, STAR, RV-TDT, CHP, VAT and Spliceosaurus as well as methodological innovations including MIPs, smMIPs and approaches for low input exome and genome sequencing. The UW- CMG remains deeply committed to open data sharing with rolling submission of eligible exome and genome data to dbGaP (614 deposited and 1,748 pending deposition) and development of a new data browser (http://geno2mp.gs.washington.edu) that, for the first time, publicly provides anonymized links between individual-level genotypes, from over 3,000 exomes, to individual clinical phenotypes, defined by Human Phenotype Ontology terms. In this renewal application, we build from these successes to maximize novel gene discovery for MCs, capitalizing on immediate access to >22,000 sequence-ready samples from >16,500 families and 163 MCs, access to several large cohorts of birth defects totaling more than 24,000 trios (>94,000 samples total) and an aggressive sample solicitation plan including case aggregation and case matching of undiagnosed patients who have undergone clinical exome sequencing. We propose four specific aims: (1) Solicit, organize, and curate phenotypic information and DNA samples from families with unexplained (i.e., no known underlying gene) MCs from sample custodians around the world, by submission to our center of either samples for sequencing or sequence data for further analysis; (2) Apply our established production pipeline for exome and genome sequencing to samples corresponding to unexplained MCs and to improve this process through ongoing technology innovation; (3) Determine the genetic basis of as many unexplained MCs as is possible, maximizing novel discovery, by use of efficient study design and effective, innovative analysis; (4) Take a leadership role to disseminate and openly share methods and data to promote worldwide efforts to discover the full complement of genes underlying MCs.