Grant Macgregor
University of California-Irvine, CA·Genetics
Most DNA does not code for proteins. Yet many genetic changes linked to disease fall in these non-coding regions, which help control when and where genes turn on.
- Fields
Genetics
Biology
- Topics
non-coding variants
regulatory DNA
disease modeling
- Grants
- 1 known grant, through Jul 2030
What they work on
- Build, together with the Center's Bioinformatics Core, a web interface where researchers enter non-coding variants and view conservation, tissue- and development-specific expression, and functional screening results to prioritize variants.
- Import mouse models of non-coding disease variants from the Disease Modeling Core, validate them independently, assess their health, and cryopreserve and catalog them for fee-for-service distribution.
- Generate human pluripotent stem cell models of non-coding disease variants, differentiate them into relevant cell types, and coordinate with the Mutant Mouse Resource and Research Centers to share models widely.
More about the research
Such variants have been hard to study. Their effects depend on tissue type and developmental stage, and researchers have lacked accessible tools to analyze them. This grant supports the Resource and Service Core of the Center for Modeling Non-Coding Disease Variants. The Core's job is to connect the Center's work with the wider research community.
Why it matters
Many genetic variants tied to human disease lie outside genes, and their roles remain largely unknown because they are hard to study. Ready-made, validated mouse and stem cell models, plus a web tool for ranking variants, could help researchers studying many diseases test how non-coding variants cause illness. This could eventually inform diagnosis and the search for treatment targets.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Hyejung Won
University of North Carolina at Chapel Hill, NC·Genetics
Develop single-cell massively parallel reporter assays (scMPRA), which combine DNA barcoding with single-cell RNA sequencing, to measure thousands of Alzheimer's-linked regulatory elements in different brain cell types at once.
Anat Kreimer
Rutgers University-New Brunswick, NJ·Genetics
Develop methods that integrate massively parallel reporter assay (MPRA) data, which test thousands of DNA sequences at once, with other genomic assays and deep learning to reconstruct cell-type-specific gene regulatory networks and their condition-specific regulators.
Yan Li
Case Western Reserve University, OH·Genetics
Map how gene activity changes, cell by cell, as 24 human pluripotent stem cell lines become beta cells, using pooled single-cell RNA sequencing that sorts cells back to their line of origin.
The school
University of California-Irvine: 46 labs on PI Pages, $645M a year on research, 524 research doctorates a year.
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