Integrating imaging and multi-omics data to infer single-cell 3D genome structures
About This Grant
PROJECT SUMMARY/ABSTRACT The three-dimensional organization of eukaryotic genomes plays a crucial role in transcriptional regulation and cellular functions. However, current genome structure models, primarily derived from genomic data, have significant limitations. They lack precise physical dimensions, fail to capture nuclear morphologies accurately, and are constrained by a resolution limit of approximately 200 kb—insufficient for studying interactions between regulatory control regions. These shortcomings hinder the use of 3D genome structures in understanding gene regulation and cellular processes. Recent advances in imaging technologies have provided powerful tools to explore 3D genome organization. In this project, we will develop a probabilistic approach to integrate genomic and imaging data to reconstruct 3D genome structures from thousands of imaged nuclei. We have three aims: (1) Develop integrative methods for inferring high-resolution single cell genome structures from sparse imaging and multi-omics data. This integration minimizes experimental biases and improves resolution and coverage by 100-fold compared to imaging alone. Our approach will offer unprecedented insights into the structural basis of gene regulation, enhancer networks, and the role of chromatin architecture in epigenetic memory formation—insights unattainable through single-cell genome-wide imaging or genomics data alone. (2) Structure-Function Mapping by analyzing the 3D regulatory architecture. We will analyze the 3D regulatory environment of genes in mouse embryonic stem cells and the reorganization of the microenvironment surrounding cell-type-specific long genes in the mouse brain cortex. For the first time, we will systematically classify genes based on their 3D regulatory microenvironment and investigate its role in gene expression. (3) We will expand our Integrative Genome Modeling (IGM) platform to incorporate imaging- based features. The platform generates a population of genome structures to reproduce the input experimental data. We will dedicate significant effort to improve user experience and enhance computational efficiency.
Grant Summary
Integrating imaging and multi-omics data to infer single-cell 3D genome structures is a NIGMS - National Institute of General Medical Sciences grant providing up to $364K for university, nonprofit, healthcare org. Applications are due 2030-02-28 (open). Check eligibility and apply with FindGrants.
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Eligibility
How to Apply
Up to $364K
2030-02-28
- 1Confirm your organization is eligible for Integrating imaging and multi-omics data to infer single-cell 3D genome structures from NIGMS - National Institute of General Medical Sciences, checking organization type, location, and any population or project requirements.
- 2Gather the required documents and information, including your organization details, project plan, and budget figures.
- 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
- 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NIGMS - National Institute of General Medical Sciences before the deadline.
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Integrating imaging and multi-omics data to infer single-cell 3D genome structures: Frequently Asked Questions
Who is eligible for the Integrating imaging and multi-omics data to infer single-cell 3D genome structures?
Integrating imaging and multi-omics data to infer single-cell 3D genome structures is offered by NIGMS - National Institute of General Medical Sciences and is generally open to university, nonprofit, healthcare org. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.
How much funding does the Integrating imaging and multi-omics data to infer single-cell 3D genome structures provide?
Integrating imaging and multi-omics data to infer single-cell 3D genome structures provides up to $364K per award from NIGMS - National Institute of General Medical Sciences. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.
When is the Integrating imaging and multi-omics data to infer single-cell 3D genome structures deadline?
Applications for Integrating imaging and multi-omics data to infer single-cell 3D genome structures are due 2030-02-28 (open). Because deadlines can change, verify the date with the funder, NIGMS - National Institute of General Medical Sciences, and give yourself enough time to prepare a complete, competitive application before the close date.
How do you apply for the Integrating imaging and multi-omics data to infer single-cell 3D genome structures?
To apply for Integrating imaging and multi-omics data to infer single-cell 3D genome structures, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NIGMS - National Institute of General Medical Sciences.