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.

Public Health Relevance

Mendelian conditions, many of which are diseases but also include phenotypic differences that may not be considered a 'disease,' are caused mainly by mutations in the protein coding regions of the genome. Although the genes underlying thousands of Mendelian phenotypes have been identified, there are thousands of Mendelian conditions for which the gene(s) remain to be discovered. We propose to use an extensive network of clinicians and investigators, next-generation sequencing coupled with new analytical paradigms and technological innovations to efficiently discover novel genes for as many Mendelian conditions as possible.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project with Complex Structure Cooperative Agreement (UM1)
Project #
5UM1HG006493-07
Application #
9392572
Study Section
Special Emphasis Panel (ZHG1)
Program Officer
Wang, Lu
Project Start
2011-12-05
Project End
2019-11-30
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
7
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Washington
Department
Genetics
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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