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NIH
Forecasted

FOR-HG-25-020

Genomic Variant Interactions With Other Variants Or The Environment (UM1 Clinical Trials Not Allowed)

Summary

AI-generated

Genetic and Environmental Interactions on Genomic Variant Impact

The National Human Genome Research Institute (NHGRI) is launching a consortium-based initiative to investigate how genetic and environmental interactions modify the functional impact of genomic variants. The research targets a fundamental gap: most variant effect prediction and polygenic score development assume additive effects, yet epistatic interactions and gene-environment interactions often drive phenotypic outcomes. Funded centers will develop and apply experimental frameworks to test variant combinations systematically, with the goal of identifying structure within the interaction landscape that improves variant prioritization, clarifies genome-wide association study (GWAS) results, and enhances polygenic risk prediction. Research spans computational biology, functional genomics, and statistical genetics, encompassing variant effect prediction, experimental variant testing, and shared analysis strategies across cell types and assays.

Critical structural requirement: This is a UM1 cooperative agreement mechanism requiring funded centers to become IGVF Consortium members with mandatory participation in resource sharing, collaborative assay design, and shared analysis pipelines—not a traditional single-PI grant. Applicants must understand consortium governance obligations and institutional commitment beyond standard NIH grants.

  • Who can apply: Institutions capable of meeting UM1 cooperative agreement requirements and IGVF Consortium membership obligations; applicants unfamiliar with consortium governance structures should clarify expectations before applying.
  • Funding & project length: Not stated.
  • Award mechanism: UM1 (cooperative agreement with consortium governance).
  • Key dates: NOFO expected 2025; application due date expected 2025.
  • Best fit for: Computational and experimental genomics teams with capacity for large-scale variant testing, GWAS interpretation, and collaborative resource development.

Insights (6)

UM1 Mechanism Requires Institutional Governance Infrastructure Beyond Traditional Grants

eligibility

The UM1 activity code mandates cooperative agreement structures with formal governance, management plans, and institutional commitment that exceed standard R01/R21 requirements. Applicants must ensure their institution can support consortium-level administrative overhead, steering committees, and compliance reporting before applying.

Mandatory IGVF Consortium Membership Creates Binding Resource-Sharing and Coordination Obligations

collaboration

This is not optional collaboration—funded centers must become IGVF members and participate in mandatory resource sharing, coordinated assay development, and shared analysis strategies. Your research roadmap must explicitly address how your center will contribute to and benefit from consortium infrastructure, not just pursue independent aims.

Experimental Variant Testing Capability and Interaction Framework Design Are Core Competitive Strengths

strategic fit

The initiative prioritizes centers with established capacity to experimentally validate genetic and environmental interactions at scale, paired with a novel conceptual framework for predicting which interactions merit testing. Preliminary data demonstrating interaction detection methodology and computational prediction models will substantially strengthen competitiveness.

Narrow Scope and Consortium Structure Suggest Highly Selective, Limited Award Pool

competition

The specificity of the interaction-testing focus, combined with UM1's governance demands and mandatory consortium participation, indicates this will fund only a small number of mature, well-resourced centers. Applicants should expect intense competition from established genomics centers with existing experimental infrastructure.

GWAS Interpretation and Polygenic Score Improvement Offer Clear Translational Impact Narrative

strategic fit

The initiative explicitly frames interaction research as a pathway to better GWAS understanding and improved polygenic scores—outcomes with direct clinical and public health relevance. Applications that connect interaction findings to real-world variant prioritization and risk prediction will resonate with NHGRI's precision genomics mission.

UM1 Centers Require Established Research Programs; Early-Stage Investigators at Structural Disadvantage

career stage

The consortium governance, resource-sharing obligations, and experimental scale implicit in this initiative favor established research groups with existing infrastructure and team depth. ESI applicants should consider partnering as co-PIs with senior investigators rather than leading independently.

Key Facts

Deadline

Posted

Fri, June 6, 2025

Expected Awards

5

UM1
93.172
Grants.gov

Keywords

genome-wide association studies
genetic interactions
environmental interactions
genomic variants
polygenic scores
variant effect prediction
gene-environment interactions
IGVF Consortium
experimental variant testing
epistasis
systems genetics

Research Areas

NIH Institute
Human Genome ResearchNHGRI
OpenAlex
Life SciencesD1Physical SciencesD3Health SciencesD4
Fields
Agricultural & Biological SciencesF11Biochemistry, Genetics & Molecular BiologyF13Computer ScienceF17Immunology & MicrobiologyF24MathematicsF26MedicineF27
Subfields
BiotechnologyS1305GeneticsS1311Molecular BiologyS1312Artificial IntelligenceS1702Computer Science ApplicationsS1706Applied MathematicsS2604Statistics & ProbabilityS2613Genetics (Medical)S2716
Topics
Genetic diversity and population structureT10012Genomics and Phylogenetic StudiesT10015Statistical Methods and InferenceT10136Genomics and Chromatin DynamicsT10222Genetic Associations and EpidemiologyT10261Developmental Biology and Gene RegulationT10268Epigenetics and DNA MethylationT10269Advanced Causal Inference TechniquesT10845+7 more
MeSH
AnatomyAOrganismsBDiseasesC
Chemicals & DrugsD
Nucleic Acids & NucleotidesD13
Analytical/Diagnostic/Therapeutic TechniquesE
Investigative TechniquesE05
Phenomena & ProcessesG
Chemical PhenomenaG02MetabolismG03Genetic PhenomenaG05
Disciplines & OccupationsH
Natural Science DisciplinesH01
Information ScienceL
Health CareN
Health Care ServicesN02Health Care EconomicsN03
ANZSRC FoR
Biological Sciences31
Bioinformatics & Computational Biology3102Genetics3105
Biomedical & Clinical Sciences32
Immunology3204Medical Biotechnology3206
Information & Computing46
Artificial Intelligence4602Data Management & Data Science4605Machine Learning4611
Mathematical Sciences49
Statistics4905

Gotchas (3)

Soft Block
planningprogram collaboration

This initiative requires funded centers to become IGVF Consortium members and participate in mandatory consortium activities, including resource sharing, collaboration on assays/variants/cell types, a

AI

95%

Source Text

As IGVF Consortium members, centers will work together to ensure all consortium resources are accessible to a wide variety of potential users. Centers are also expected to collaborate with other consortium components to coordinate assays, variants, and cell types, and to develop shared analysis strategies to meet consortium goals.

Soft Block
planningaward mechanism instrument

The NOFO will use the UM1 activity code, which is a consortium/cooperative agreement mechanism with specific governance and management requirements that differ substantially from traditional R01/R21 m

AI

90%

Source Text

This NOFO will utilize the UM1 activity code.

Warning
submissiontimeline deadlines

The text states the NOFO is 'expected to be published in 2025' and application due date is 'expected to be in 2025,' but provides no specific dates. This vagueness could lead applicants to miss the ac

AI

85%

Source Text

The NOFO is expected to be published in 2025 with an expected application due date in 2025.

AI-generated content — verify with the issuing agency’s official FOA/NOFO. Not endorsed by HHS.

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