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Impact of Genomic Variation on Function (IGVF) Consortium

The IGVF will develop a framework for systematically understanding the effects of genomic variation on genome function and how these effects shape phenotypes.

One of the central problems in biology is understanding how genomic variation affects genome function to influence phenotypes. In 2019, the National Human Genome Research Institute hosted the workshop "From Genome to Phenotype: Genomic Variation Identification, Association, and Function in Human Health and Disease".  Based on the recommendations from the workshop report, NHGRI is initiating a new program-the Impact of Genomic Variation on Function (IGVF) Consortium to develop a framework for systematically understanding the effects of genomic variation on genome function and how these effects shape phenotypes. IGVF is a research consortium that will bring investigators together in a highly collaborative effort to examine how genomes function, how genome function shapes phenotypes, and how these processes are influenced by genomic variation. The program will utilize emerging experimental and computational genomic approaches to build a catalog of the impact of genomic variants on genome function and phenotypes.

Program Goals

  1. Systematic perturbation of the genome to assess the impact of genomic variation on genome function and phenotype
     
  2. High-resolution identification of where and when genes and regulatory elements function
     
  3. Advancement of network-level understanding of the influence of genetic variation and genome function on phenotype
     
  4. Development and testing of innovative predictive models of the impact of genomic variation on genome function
     
  5. Generation of a resource centered on a catalog of variant impacts and including data, tools, and models that will be shared with the broader research community
     
  6. Enabling others to perform related studies using these approaches.

Awardees

Awardee Institution Title Award Number
Characterization Awards
Jay Shendure
Nadav Ahituv
Martin Kircher		 University of Washington
UC San Francisco
Charite Universitatsmedizin Berlin		 Massively parallel characterization of variants and elements impacting transcriptional regulation in dynamic cellular systems HG011966
Lea Starita
Douglas Fowler		 University of Washington The Center for Actionable Variant Analysis; measuring variant function at scale HG011969
Jesse Engreitz
Thomas Quertermous		 Stanford University Stanford Center for Connecting DNA Variants to Function and Phenotype HG011972
Marc Vidal Dana-Farber Cancer Institute Molecular phenotyping of ~100,000 coding variants across Mendelian disease genes HG011989
Gary Hon
William Kraus
Nikhil Munshi		 University of Texas Southwestern Medical Center Multiscale functional characterization of genomic variation in human developmental disorders HG011996
Hyejung Won
Michael Love
Karen Mohlke		 University of North Carolina at Chapel Hill Systematic in vivo characterization of disease-associated regulatory variants HG012003
Luca Pinello
Daniel Bauer
Guillaume Lettre
Richard Sherwood		 Massachusetts General Hospital
Children's Hospital Boston
Montreal Heart Institute
Brigham and Women's Hospital		 Comprehensive characterization of variants underlying heart and blood diseases with CRISPR base editing HG012010
Charles Gersbach
Gregory Crawford
Tim Reddy		 Duke University High-throughput functional annotation of gene regulatory elements and variants critical to complex cellular phenotypes HG012053
Mapping Awards
Jason Buenrostro
Bradley Bernstein		 Broad Institute, Harvard University
Broad Institute, Massachusetts General Hospital		 A foundational resource of functional elements, TF footprints and gene regulatory interactions HG011986
Ansuman Satpathy Stanford University Single-cell Mapping Center for Human Regulatory Elements and Gene Activity HG012076
Seyed Mortazavi
Barbara Wold		 UC Irvine
California Institute of Technology		 Center for Mouse Genomic Variation at Single Cell Resolution HG012077
Predictive Modeling Awards
Alan Boyle University of Michigan Predicting the impact of genomic variation on cellular states HG011952
Andrew S. Allen
Shayan Mukherjee
Charles D. Page Jr.		 Duke University Design, prediction, and prioritization of systematic perturbations of the human genome HG011967
Soumya Raychaudhuri
Alkes Price
Shamil Sunyaev		 Brigham and Women's Hospital
Harvard School of Public Health
Brigham and Women's Hospital		 Predicting the impact of genetic variants, genes and pathways on human disease HG012009
Predrag Radivojac Northeastern University Supporting IGVF by modeling genetics, function, and phenotype with machine learning HG012022
Mark Craven University of Wisconsin Linking variants to multi-scale phenotypes via a synthesis of subnetwork inference and deep learning HG012039
Zhiping Weng
Manuel Garber
Xihong Lin		 University of Massachusetts Medical School
University of Massachusetts Medical School
Harvard School of Public Health		 Predictive modeling of the functional and phenotypic impacts of genetic variants HG012064
Anshul Kundaje Stanford University Predicting context-specific molecular and phenotypic effects of genetic variation through the lens of the cis-regulatory code HG012069
Network Awards
Harinder Singh
Nidhi Sahni
Jishnu Das		 University of Pittsburgh
The University of Texas MD Anderson Cancer Center
University of Pittsburgh		 Linking genome variation to transcriptional network dynamics in human B cells HG012041
Hao Wu
Sreeram Kannan
Hongjun Song		 University of Pennsylvania Defining causal roles of genomic variants on gene regulatory networks with spatiotemporally-resolved single-cell multiomics HG012047
Danwei Huangfu
Michael Beer
Anna-Katerina Hadjantonakis		 Sloan Kettering Institute for Cancer Research
Johns Hopkins University School of Medicine
Sloan Kettering Institute for Cancer Research		 Genomic control of gene regulatory networks governing early human lineage decisions HG012051
Maike Sander
Hannah Carter
Kyle Gaulton
Bing Ren		 UC San Diego The impact of genomic variation on environment-induced changes in pancreatic beta-cell states HG012059
Chongyuan Luo
Kathrin Plath
Noah Zaitlen		 UC Los Angeles Leveraging genetic variation to dissect gene regulatory networks of reprogramming to pluripotency HG012079
Christina Leslie
Alexander Rudensky		 Sloan Kettering Institute for Cancer Research Deciphering the genomics of gene network regulation of T cell and fibroblast states in autoimmune inflammation HG012103
Data and Administrative Coordinating Center Awards
J. Michael Cherry
Mark Gerstein		 Stanford University
Yale University		 A Data and Administrative Coordinating Center for the Impact of Genomic Variation on Function Consortium HG012012
Ting Wang
Feng Yue		 Washington University, Saint Louis
Northwestern University		 WashU-Northwestern Genomic Variation and Function Data and Administrative Coordinating Center HG012070

Affiliate Membership

The IGVF Program offers researchers not currently funded by the IGVF Consortium the opportunity to apply to join the program as non-voting affiliate members. IGVF expects to benefit from the unique expertise affiliated members can bring to the Consortium. IGVF anticipates an affiliated member’s benefits will include the highly interactive research environment, participating in Consortium discussions across a broad range of activities, participating in Consortium analyses and access to data prior to QC.

Affiliate members are expected to contribute to the goals of the IGVF Consortium by generating data and/or analyses, sharing data and/or analyses freely through the IGVF Data and Administrative Coordinating Center (DACC), and/or by contributing to cross- consortium integrative analyses. (An alternative is direct collaboration between an IGVF member and an external researcher, without sharing IGVF resources beyond what that IGVF member has created.) Affiliate members are also expected to be actively engaged in IGVF activities (i.e. participate in working groups as appropriate, attend the IGVF annual meeting) and to abide by all policies approved by the consortium and any other pertinent NIH policies. Failure to abide by these rules and policies may result in suspension of membership.

Affiliate membership does not directly or indirectly imply a commitment to funding by the NIH.

This policy was last updated March 15, 2022.

Expired Funding Opportunities

Notices

Request for Applications

  • RFA-HG-20-043: Systematic Characterization of Genomic Variation on Genomic Function and Phenotype (UM1 Clinical Trial Not Allowed)
    Application Receipt Date(s): November 4, 2020
    Expiration Date: November 5, 2020
     
  • RFA-HG-20-044: Defining Genomic Influence on Gene Network Regulation (U01 Clinical Trial Not Allowed)
    Application Receipt Date(s): November 4, 2020
    Expiration Date: November 5, 2020
     
  • RFA-HG-20-045: Single-cell Profiling of Regulatory Element and Gene Activity in Relationship to Genome Function (UM1 Clinical Trial Not Allowed)
    Application Receipt Date(s): November 4, 2020
    Expiration Date: November 5, 2020
     
  • RFA-HG-20-046: Genomic Variation and Function Data and Administrative Coordinating Center (U24 Clinical Trial Not Allowed)
    Application Receipt Date(s): November 4, 2020
    Expiration Date: November 5, 2020
     
  • RFA-HG-20-047: Developing Predictive Models of the Impact of Genomic Variation on Function (U01 Clinical Trial Not Allowed)
    Application Receipt Date(s): November 4, 2020
    Expiration Date: November 5, 2020
     

Program Staff

Mike Pazin, Ph.D.
Mike Pazin, Ph.D.
  • Program Director, Functional Genomics
  • Division of Genome Sciences
Daniel A. Gilchrist, Ph.D.
Daniel A. Gilchrist, Ph.D.
  • Program Director Computational Genomics and Data Science
  • Division of Genome Sciences
Stephanie Morris
Stephanie A. Morris, Ph.D.
  • Program Director
  • Division of Genome Sciences

Last updated: April 5, 2022