December 9, 2021
PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)
PA-20-195 - NIH Exploratory/Developmental Research Grant Program (Parent R21 Clinical Trial Not Allowed)
PA-21-259 - PHS 2021-2 Omnibus Solicitation of the NIH, CDC and FDA for Small Business Innovation Research Grant Applications (Parent SBIR [R43/R44] Clinical Trial Not Allowed)
PA-21-262 - PHS 2021-2 Omnibus Solicitation of the NIH for Small Business Technology Transfer Grant Applications (Parent STTR [R41/R42] Clinical Trial Not Allowed)
NOT-HG-20-010 - Notice of Special Interest: Development of Statistical, Population Genetics and Computational Methods Related to Polygenic Prediction of Health and Disease in Diverse Populations
NOT-HG-21-018 - Notice of Special Interest (NOSI): Advancing Genomic Technology Development for Research and Clinical Application
National Human Genome Research Institute (NHGRI)
Purpose
The National Human Genome Research Institute (NHGRI) is issuing this Notice of Special Interest (NOSI) to encourage applications that develop novel computational or experimental approaches for genomic studies of how genetic variants relate to genomic function, phenotype, and disease.
The Human Genome Project produced the reference human genome, and then projects such ENCODE characterized many functional elements in the genome. Projects such as the International HapMap Project, the 1000 Genomes Project, and many disease sequencing studies found over 900 million variant sites in the genome. Many genome-wide association (GWAS) studies discovered statistical associations among these variants and numerous diseases and traits. The Impact of Genomic Variation on Function (IGVF) Consortium is an NHGRI project to develop a framework for systematically understanding the effects of genomic variation on genome function and how these effects shape phenotypes.
Relating variants to function and disease risk is a large scientific area. The key open question is: How do variants in genomic elements result in differences in how those genomic elements function, resulting in differences in regulation and molecular phenotypes that lead to differences in disease risk or traits? An understanding of these risk variants can contribute to personalized risk prediction and the development of therapies focused on risk variants.
Even with the efforts mentioned above, new methods are still needed; many new ideas in this field will be best developed through investigator-initiated work such as called for in this NOSI.
As highlighted in the NHGRI Strategic Vision (https://www.nature.com/articles/s41586-020-2817-4)
determining the connection of specific variants to phenotypes remains challenging. Systematic approaches, including tactics that connect high-throughput molecular readouts of functional genomic assays to organismal phenotypes, are required to establish the phenotypic consequences of all genomic variants individually and in combination in a cell-type context across the life span.
New methods to analyse data that account for human diversity, coupled with a growing clarity about genotype phenotype relationships, must be developed to deduce associations and interactions among genomic variants and environmental factors, improve estimates of penetrance and expressivity, and enhance the clinical utility of genomic information for predicting risk, prognosis, treatment response, and, ultimately, clinical outcomes.
Scope
NHGRI seeks applications that will develop methods to provide a better understanding of how genetic variation relates to function, phenotype, and disease risk or traits. For this NOSI, the term disease risk or traits is used broadly, to encompass diseases, risk of diseases, protective effects against diseases, molecular phenotypes, organismal phenotypes, clinical phenotypes or outcomes, traits, responses to therapeutic drugs or vaccines, and other outcomes relevant to human health and disease.
The focus should be on developing approaches that can be applied generally to many or all genes, variants, diseases, or phenotypes. Approaches may be developed and tested using specific genomic elements, variants, cell types, diseases, traits, regulatory interactions, or networks; however, the generalizability of the approach must be explained well. Approaches that are comprehensive across the genome and assay many or all variants at once are encouraged. This NOSI is not intended for approaches that are only applicable to or focus on specific diseases, genes, or variants. This NOSI aims to support the development of novel approaches, so applications whose major aim is the production of data sets using existing approaches are also not appropriate for this NOSI.
Use of model organisms or model systems is encouraged, particularly when approaches are especially suited for these systems. However, information from these models should be relevant to humans, such as through understanding of general principles or methodological advances.
The proposed work may occur in several areas; in all cases these methods will need to be at the genomic scale and generalizable across diseases, in keeping with the NHGRI mission:
- Statistical genetics: Developing novel methods to find statistical associations among variants and phenotypes. Improved methods are needed to deal with structural variants, multi-allelic variants, complex genomic regions, and molecular phenotypes. Methods are also needed to address complexities such as ancestrally diverse populations, admixture, and longitudinal data, as well as to incorporate other variables such as gene interactions and environmental factors.
- Causality: Developing computational or experimental methods to identify or narrow down the set of disease-associated variants to those most likely to be causal. The causal variants would result in mechanistic differences in how genomic elements function, contributing to the difference in phenotypes. The linkage disequilibrium patterns in the genome mean that disease- or trait-associated regions may contain many genes, other functional genomic elements, and variants. Thus, determining which specific variants affect the function of genes or other genomic elements is a major challenge.
- Function: Developing computational or experimental methods to study how variants result in differences in function, or how the functional differences lead to differences in disease risk or traits. This NOSI supports methods development that could be applied generally to any diseases, traits, or genes; studies where the focus is on particular genes, variants, or diseases, such as tumor genomics, should be submitted to the appropriate disease-focused Institute or Center.
- Comparative genomics: Developing computational or experimental methods that use comparative genomics to provide insight into how variants result in differences in function and relate to phenotypes and disease. This may include the development of analyses of the functional consequences of variants in conserved or divergent sequences. The approaches developed should be relevant to understanding how human variants relate to health and disease.
- Clinical interpretation: Developing computational or experimental methods that use functional genomics data to better interpret genomes in a clinical context. This may include developing approaches to deduce whether variants are pathogenic, benign, or protective; better assess penetrance or predict individuals at risk of disease; connect in a comprehensive way phenotype data with functional data for sets of variants in the context of precision medicine and health; or interpret VUS.
The methods and data should be released broadly, to allow others to evaluate the methods and compare them with other methods. NHGRI encourages investigators who plan to collect phenotype or environmental exposure data to use the standard protocols in the PhenX Toolkit (www.phenxtoolkit.org).
Please see: NHGRI’s Expectation for Sharing Quality Metadata and Phenotypic Data (https://grants.nih.gov/grants/guide/notice-files/NOT-HG-21-022.html).
Genomic studies have generally lacked inclusion of substantial numbers of non-European-ancestry participants, so the production or analysis of data from individuals of diverse ethnicities and ancestries is encouraged.
To enable the widest use of any functional data, any human subjects consents should allow broad, general research use of the data, with no restrictions on the types of researchers who may use the data. Where possible, use of samples consented for submission of data into unrestricted databases is strongly encouraged. Please see: NHGRI Implementation of the NIH Genomic Data Sharing Policy https://grants.nih.gov/grants/guide/notice-files/NOT-HG-20-011.html
Application and Submission Information
Application and Submission Information
This notice applies to receipt dates on February 5, 2022, and subsequent ones through October 5, 2024, for new applications, and November 5, 2024, for renewal and resubmission applications.
Since this NOSI aims to support methods development that is general across diseases or traits, the aims should focus on the development of methods rather than on specific biomedical results or hypotheses. The introduction should explain the general problem that the methods to be developed aim to address. Applicants should be clear how studies of specific diseases or phenotypes will contribute to the development of the methods that apply broadly to many diseases and phenotypes; i.e., the application should be about methods development, not about a specific disease.
Applications for this initiative should be submitted using any of these funding opportunity announcements (FOAs) or any reissues of these announcements, through the expiration date of this notice:
PA-20-185- NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)
PA-20-195- NIH Exploratory/Developmental Research Grant Program (Parent R21 Clinical Trial Not Allowed)
PA-21-259 - PHS 2021-2 Omnibus Solicitation of the NIH, CDC and FDA for Small Business Innovation Research Grant Applications (Parent SBIR [R43/R44] Clinical Trial Not Allowed
PA-21-262 - PHS 2021-2 Omnibus Solicitation of the NIH for Small Business Technology Transfer Grant Applications (Parent STTR [R41/R42] Clinical Trial Not Allowed)
Applicants are encouraged to contact NHGRI staff early in the application process, and also to review the NHGRI guidance to potential applicants for NHGRI support:https://www.genome.gov/research-funding/Funding-Opportunities/guidance.
All instructions in theSF424 (R&R) Application Guideand the funding opportunity announcement used for submission must be followed, with the following addition:
- Applicants must include NOT-HG-22-007 in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.
Research with a focus on technology development, such as the development of assays of the effects of genetic variation on functional data types, genome editing, functional interactions between variants and regulatory elements, DNA or RNA sequencing, or recorders of genomic activity or lineages, should be submitted to NOT-HG-21-018.
Research with a focus on diversity as related to polygenic risk scores or polygenic prediction of health should be submitted to NOT-HG-20-010
Applications nonresponsive to terms of this NOSI will not be considered for the NOSI initiative.
Scientific/Research Contacts
Statistical genetics and general questions:
Alexander Arguello, Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 240-731-3753
Email: alexander.arguello@nih.gov
Statistical genetics and clinical interpretation:
Rongling Li, M.D., Ph.D., M.P.H.
National Human Genome Research Institute (NHGRI)
Telephone: 301-480-2487
Email: lir2@mail.nih.gov
Functional genomics and causality:
Stephanie A. Morris, Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 301-435-5738
Email: morriss2@mail.nih.gov
Comparative genomics:
Alexander Arguello, Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 240-731-3753
Email: alexander.arguello@nih.gov
Peer Review Contacts
Examine your eRA Commons account for review assignment and contact information (information appears two weeks after the submission due date).
Financial/Grants Management Contact
Deanna Ingersoll
National Human Genome Research Institute (NHGRI)
Telephone: 301-435-7858
Email: Deanna.Ingersoll@nih.gov
and Human Services (HHS)
