# Spatial multiomic mapping of gene function with CRISPRoff

> **NIH NIH UM1** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2023 · $1,630,579

## Abstract

PROJECT SUMMARY / ABSTRACT
A hallmark goal in human biology is to define the relationship between genes and phenotypes.
Mapping the function of every gene in human cells will enable us to begin to define how gene
expression programs impart specialized and adaptive human cellular functions required for life.
We are especially interested in how transcription factors and epigenetic regulators enact cell
type specific gene expression programs to dictate cell function during early development.
Elucidating how individual genes function to regulate transcription and thus to program cell
phenotypes will transform our understanding of human biology, development and disease.
A mechanistic understanding of gene function requires scalable approaches for perturbing gene
activity, single cell molecular phenotyping assays and robust models of human multicellular
biology. We recently developed CRISPRoff— a programmable epigenetic memory writer
consisting of a single dead Cas9 fusion protein that durably and robustly silences gene
expression. Unlike CRISPR mutagenesis approaches, CRISPRoff gene silencing effectively
programs null alleles at the level of target gene mRNA and protein in polyclonal cell populations
without induction of DNA damage or the unpredictability of DNA repair processes. We are
proposing to optimize a generalizable multiomic CRISPRoff platform for molecularly
phenotyping null alleles at single-cell resolution in multicellular models of human development.
We will then use this CRISPRoff platform to create single-cell molecular multiomic maps of
nuclear gene function across space and time. Lastly, we will evaluate genetic compensation and
paralog functional redundancy in multicellular models. Our proposed research will serve to
demonstrate the utility of this multiomics CRISPRoff platform for characterizing null alleles and
motivate extending this approach to functionally map null allele phenotypes for all genes
encoded by the human genome. The results of the proposed research will serve as a
fundamental resource and roadmap for a broad community of biomedical scientists and greatly
inform our understanding of gene function in human biology and disease.

## Key facts

- **NIH application ID:** 10693360
- **Project number:** 5UM1HG012660-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Luke Gilbert
- **Activity code:** UM1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $1,630,579
- **Award type:** 5
- **Project period:** 2022-09-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10693360

## Citation

> US National Institutes of Health, RePORTER application 10693360, Spatial multiomic mapping of gene function with CRISPRoff (5UM1HG012660-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10693360. Licensed CC0.

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