UW Center for Mendelian Genomics

 描述(申请人提供)：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，3000多种MC的遗传基础仍不清楚，每年都有数百种新型MC被描述。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，华盛顿大学CMG(UW-CMG)与来自27个国家和地区117个机构的182名研究人员合作，评估了来自2404个家庭的6598个样本，迄今已产生4116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无与伦比的发现速度，鉴定了237个MC的基因，其中包括123个新发现。这些发现对诊断和临床护理的转化和影响是立竿见影的--与整个基因学界的发现相结合，自2012年以来被确认为潜在MC的基因变异约占临床诊断工作积极结果的25%。此外，UW-CMG开发了多种新的分析工具，包括CADD、Primus、SimRare、STAR、RV-TDT、CHP、VAT和Spliceosaurus，以及包括MIP、smMIP和低输入外显子组和基因组测序方法在内的方法创新。UW-CMG仍然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数据给数据库GaP(614个已交存，1,748个待交存)，并开发一个新的数据浏览器(http://geno2mp.gs.washington.edu))，首次公开提供从3,000多个外显子到由人类表型本体论术语定义的个人临床表型之间的匿名链接。在这一续订应用中，我们以这些成功为基础，最大限度地为MC发现新的基因，包括立即获得来自&gt；16,500个家庭和163个MC的22,000个已准备好序列的样本，获得几个大型出生缺陷队列，总计超过24,000个Trio(&gt；94,000个样本)，以及积极的样本征集计划，包括病例聚合和已进行临床外显子组测序的未确诊患者的病例匹配。我们提出了四个具体目标：(1)从世界各地的样本保管人那里收集、组织和管理来自不明原因(即未知的潜在基因)MC家族的表型信息和DNA样本，将样本提交给我们的中心进行测序或序列数据用于进一步分析；(2)将我们建立的外显子组和基因组测序流水线应用于与不明原因MC对应的样本，并通过持续的技术创新来改进这一过程；(3)通过高效的研究设计和有效的创新分析，确定尽可能多的未解释MC的遗传基础，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，以促进全世界努力发现乳腺癌潜在基因的全部补充。

 DESCRIPTION (provided by applicant): To date, 2,937 genes underlying 4,163 Mendelian conditions (MCs) has 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.