This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. DESCRIPTION (provided by applicant): Genetic research is entering an exciting new phase, one in which comprehensive information about genetic variation can systematically be examined for association to medically important traits. Such studies will take many forms: hypothesis-driven examination of one or a few polymorphisms in vast clinical collections, studies of thousands of variants in candidate genes or regions of linkage, and genome-wide scans of hundreds of thousands of markers in each patient. Some will involve genotyping standard sets of variants, while others will require discovery of new variants and development of custom assays. In all cases a critical challenge is information systems to design experiments, manage millions of genotypes, and perform sophisticated analysis of correlations among variants, and between variants and disease phenotypes. We propose to create an NCRR Genotyping Center (GC) at the Broad Institute (BI), formerly the Whitehead/MIT Center for Genome Research. Our goal is to create a resource that will make it possible for any investigator to accomplish the four goals: (1) Design genotyping experiments using secure and confidential informatics tools for sample management, single nucleotide polymorphism (SNP) selection and discovery; (2) genotype selected Snips at high quality and throughput; (3) perform automated quality control and data management; and (4) to analyze data with rapidly evolving methods to study associations. Our application builds on over a decade''s expertise at the Broad in the creation of high-throughput methods for genomic research, international projects to create public maps of genome sequence and variation, creation of analytic methods and software for genetic research, and discovery of genes for a human disease. Enabling broad access to genetic variation research requires more than genotyping: it requires combining a breadth of high-throughput technologies with innovative methods for data management and analysis.
We aim to bridge this gap by combining the necessary range of technologies and advanced analytic tools in a single NCRR GC, and making them broadly available to investigators around the country.

National Institute of Health (NIH)
National Center for Research Resources (NCRR)
Specialized Center--Cooperative Agreements (U54)
Project #
Application #
Study Section
Special Emphasis Panel (ZRR1-CR-9 (01))
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Massachusetts Institute of Technology
United States
Zip Code
Sanders, A R; Drigalenko, E I; Duan, J et al. (2017) Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis. Transl Psychiatry 7:e1093
Power, Robert A; Tansey, Katherine E; Buttenschøn, Henriette Nørmølle et al. (2017) Genome-wide Association for Major Depression Through Age at Onset Stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. Biol Psychiatry 81:325-335
Dhankani, Varsha; Gibbs, David L; Knijnenburg, Theo et al. (2016) Using Incomplete Trios to Boost Confidence in Family Based Association Studies. Front Genet 7:34
Keenan, Tanya; Zhao, Wei; Rasheed, Asif et al. (2016) Causal Assessment of Serum Urate Levels in Cardiometabolic Diseases Through a Mendelian Randomization Study. J Am Coll Cardiol 67:407-416
Ehret, Georg B (see original citation for additional authors) (2016) The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals. Nat Genet 48:1171-1184
Franke, Barbara; Stein, Jason L; Ripke, Stephan et al. (2016) Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat Neurosci 19:420-431
Malik, Rainer; Freilinger, Tobias; Winsvold, Bendik S et al. (2015) Shared genetic basis for migraine and ischemic stroke: A genome-wide analysis of common variants. Neurology 84:2132-45
Peyrot, W J; Lee, S H; Milaneschi, Y et al. (2015) The association between lower educational attainment and depression owing to shared genetic effects? Results in ~25,000 subjects. Mol Psychiatry 20:735-43
Traylor, Matthew; Mäkelä, Kari-Matti; Kilarski, Laura L et al. (2014) A novel MMP12 locus is associated with large artery atherosclerotic stroke using a genome-wide age-at-onset informed approach. PLoS Genet 10:e1004469
Power, Robert A; Keller, Matthew C; Ripke, Stephan et al. (2014) A recessive genetic model and runs of homozygosity in major depressive disorder. Am J Med Genet B Neuropsychiatr Genet 165B:157-66

Showing the most recent 10 out of 147 publications