# Genomic encoding of heterogeneity

> **NIH NIH DP2** · YALE UNIVERSITY · 2024 · $1,507,500

## Abstract

Project Summary/Abstract
In development, the embryo generates many cell types with distinct gene expression programs, leading to
heterogeneity across cells. In cancer, mutation generates heterogeneity, with a growing recognition that non-
genetic (epigenetic) mechanisms contribute to tumor heterogeneity and treatment failure. The ability to take the
same genetic template and form different cell states, exhibiting cell-to-cell variation in gene expression and
behavior, is fundamental to many cell systems across problems in human health including stem cells, cancer,
and immune cell function. Yet, the mechanisms by which cell systems encode heterogeneity in gene expression
are unclear. Pluripotent embryonic stem cells give rise to all the cells of the adult mammal, and primary
embryonic stem cells are genetically stable in culture, making them an ideal system for studying the emergence
of non-genetic heterogeneity in cell systems. Cell-to-cell variation in gene expression that arises in the absence
of environmental signals has previously been termed `noise', or attributed to stochastic processes of gene
expression. However, gene expression heterogeneity is reproducible, suggesting regulation. The goal of this
proposal is to identify regulatory mechanisms by which the genome encodes non-genetic heterogeneity in cell
systems. We will use embryonic stem cells as a model system for gene expression heterogeneity. First, we will
identify transcription factor pairs whose combined activity at enhancers leads to transcriptional heterogeneity of
the regulated gene. In order for heterogeneity to result in forming distinct states with the potential to prime stem
cells into different lineages, heterogeneity must be heritable. Second, using a modified Luria-Delbruck fluctuation
analysis, we will identify memory loci capable of heritable transmission of non-genetic heterogeneity across cell
generations. Motifs such as autoregulation, whereby a gene's product can regulate its own production, may
contribute to the formation of different cell states and therefore to heterogeneity across a cell population. Third,
we will manipulate a single factor within or outside of an autoregulatory loop to determine how it impacts
heterogeneity. To accomplish these goals, we will leverage an assay we have developed which allows the
identification of actively transcribed regulatory regions and genes in small subsets of cells. Completion of these
goals will address longstanding questions about the origins of heterogeneity in cell systems and will advance a
systems level approach for understanding cell state. If successful, the proposal may unlock future studies
applying similar approaches to identify non-genetic drivers of tumor heterogeneity and treatment failure.
Therapeutic targeting of these mechanisms may unlock new treatment strategies for cancer.

## Key facts

- **NIH application ID:** 10909556
- **Project number:** 1DP2HG014283-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Salil Garg
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,507,500
- **Award type:** 1
- **Project period:** 2024-09-25 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10909556

## Citation

> US National Institutes of Health, RePORTER application 10909556, Genomic encoding of heterogeneity (1DP2HG014283-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10909556. Licensed CC0.

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