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.

Consortium Website Data Portal Catalog

One of the central problems in biology is understanding how genomic variation affects genome function to influence phenotypes. NHGRI initiated 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. The program is based on recommendations from the 2019 workshop "From Genome to Phenotype: Genomic Variation Identification, Association, and Function in Human Health and Disease" (workshop report). IGVF is a research consortium that brings 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 utilizes emerging experimental and computational genomic approaches to build a catalog of the impact of genomic variants on genome function and phenotypes.

Visit the IGVF Consortium website.

News
Events
Expired Funding Opportunities
Program Staff

Program Goals

Systematic perturbation of the genome to assess the impact of genomic variation on genome function and phenotype
High-resolution identification of where and when genes and regulatory elements function
Advancement of network-level understanding of the influence of genetic variation and genome function on phenotype
Development and testing of innovative predictive models of the impact of genomic variation on genome function
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
Enabling others to perform related studies using these approaches.

Participants and Projects

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 William Majoros 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 Jishnu Das	University of Pittsburgh 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 Benjamin Hitz	Stanford University Yale University Stanford 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 Members

Research Funding

IGVF Affiliate Members

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.

Application

MS Word

IGVF Affiliate Membership Application

Concept Clearances

Impact of Genomic Variation on Function (Renewal)
September 9, 2024 Council

Consortium for Understanding the Impact of Genomic Variation on Genome Function
February 10, 2020 Council

News

Deciphering the impact of genomic variation on function
Nature Perspective, September 4, 2024
Differences in our DNA have major influences on how our genomes function, but how?
News Feature, September 4, 2024
NIH providing $185 million for research to advance understanding of how human genome functions
NHGRI Press Release, September 9, 2021
NHGRI Launches Impact of Genomic Variation on Function (IGVF) Consortium
ASHG News, September 3, 2020

Events

IGVF Consortium Pre-Application Webinar - September 3, 2020
Sep. 03, 2020
Virtual
IGVF Consortium Pre-Application Webinar - September 9, 2020
Sep. 09, 2020
Virtual

Slides from the Webinars

Frequently Asked Questions for IGVF RFAs

Expired Funding Opportunities

Active

At this time, there are no current funding opportunities.

Expired

NOT-HG-20-055: Notice of Pre-Application Webinars for the Impact of Genomic Variation on Function (IGVF) Consortium FOAs (RFA-HG-20-043, RFA-HG-20-044, RFA-HG-20-045, RFA-HG-20-046, RFA-HG-20-047)
RFA-HG-20-043: Systematic Characterization of Genomic Variation on Genomic Function and Phenotype (UM1 Clinical Trial Not Allowed)
Expiration Date: November 5, 2020
RFA-HG-20-044: Defining Genomic Influence on Gene Network Regulation (U01 Clinical Trial Not Allowed)
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)
Expiration Date: November 5, 2020
RFA-HG-20-046: Genomic Variation and Function Data and Administrative Coordinating Center (U24 Clinical Trial Not Allowed)
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)
Expiration Date: November 5, 2020