This Electronic Medical Records and Genomics (eMERGE) Network ?eMERGE Phase III: Central Genome Sequencing and Genotyping Facility? (RFA-HG-027), will provide state-of-the-art capabilities for the generation of the DNA sequence of key genes and genomic regions in eMERGE patients. The work will be performed within the Baylor DNA Diagnostic Laboratories, a collaborative effort of the Human Genome Sequencing Center (HGSC) and the Department of Molecular and Human Genetics (DMHG), merging the complementary expertise of both groups to enable CAP and CLIA certified clinical sequencing tests. A complementary, collaborative group at Partners-Broad will work in parallel to achieve similar goals. An appended document ?BCM-Partners-Broad eMERGE Sequencing Core Collaboration Plan? details the collaboration. At BCM, the complete sequences of ~100 selected genes, followed by validation of putative variants, will be carried out initially via a custom DNA capture panel, with alternate methods potentially introduced as the program matures. In this revised proposal, a total of 12,500 samples will be analyzed over the course of the project (2,700 in year one; 3,267 per year, thereafter) at BCM. As described in the original application, the methods will be based upon the NimbleGen DNA capture technology and Illumina DNA sequencing procedures that were pioneered at the HGSC. The content of the capture panel at BCM will be coordinated with the panel designed and utilized by Dr. Heidi Rehm?s group at Harvard, ensuring simple but robust cross reference between platforms. Further, we will utilize the Codified variant interpretation and reporting to provide automated reports to eMERGE participants. Sanger methods for validation of key variants will be available. A key modification of the Aims will be to expand the use of distributed computing to enable facile access to all project data from multiple (and potentially all) sites. Data will be collected from sequenced samples and securely stored in a single harmonized format. These data, interpretation results and clinical reports will be accessible to qualified users via secure access and transfer protocols. The eMERGE data commons will allow for rapid, secure and equitable transfer of data and information across the eMERGE investigator network and will create an environment for real-time reinterpretation of results as new tools and knowledge become available. To facilitate progress, four working groups from the two Centers will be formed: 1. Assay Design; 2. Sequencing Production; 3. Physician Interface; 4. Data Commons.

Public Health Relevance

The mission of the Electronic Medical Records and Genomics (eMERGE) Network is to integrate the use of genomic methods into clinical practice, by melding of clinical phenotype data, including recognition of environmental exposure, with the full knowledge of DNA variation. The proposed central genome sequencing and genotyping facility will provide DNA sequence data for eMERGE patients from selected genomic regions, as the foundation for further eMERGE activities. The data will be highly accurate, generated in a regulated clinical diagnostic laboratory (i.e. CLIA/CAP approved) and able to be incorporated into patient records. The proposed facility's investigators will work with the eMERGE clinical sites, the coordinating center and NHGRI to accomplish the shared goals of the eMERGE Network.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01HG008664-02
Application #
9134845
Study Section
Special Emphasis Panel (ZHG1-HGR-L (M1))
Program Officer
Wiley, Kenneth L
Project Start
2015-09-01
Project End
2019-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
2
Fiscal Year
2016
Total Cost
$2,641,744
Indirect Cost
$305,169
Name
Baylor College of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030
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Wan, Zhiyu; Vorobeychik, Yevgeniy; Xia, Weiyi et al. (2017) Expanding Access to Large-Scale Genomic Data While Promoting Privacy: A Game Theoretic Approach. Am J Hum Genet 100:316-322