# Revealing the molecular underpinnings of transcriptional heterogeneity

> **NIH NIH F30** · UNIVERSITY OF PENNSYLVANIA · 2020 · $32,737

## Abstract

Project summary
Transcriptional regulation, where transcription factors bind to DNA to control the level of mRNA produced, has
primarily been studied using bulk biochemical assays which average signal across large numbers of cells.
However, single cell studies have shown that individual cells within isogenic populations can transcribe quite
differently than the average, with important consequences for biological processes such as cancer,
development, and cellular differentiation. Still, the molecular basis for this single cell transcriptional variability
remains mysterious. Namely, we do not know what molecules bind to the DNA in cells and determine whether
or not it transcribes a locus at a particular time. This is true both upon initial induction of gene expression,
where the same gene responds to the same signal at different times in different cells, as well as at steady
state, where due to the pulsatile nature of transcription, the same gene fires at different times in different cells.
These questions remain unanswered because current biochemical assays cannot directly associate the
molecules bound to a gene promoter at a given time with its instantaneous transcriptional activity in single cells
due to limits of detection efficiency. What if instead, we could sort out subpopulations of cells by transcriptional
activity in large numbers, allowing us to harness utilize bulk biochemical assays to determine associated
differences in molecular factor binding to promoter DNA? Here we propose to utilize novel single-molecule
fluorescent signal amplification methods (clampFISH and third generation hybridization chain reaction) to
separate isogenic cellular populations by whether or not they were actively transcribing at fixed time points. In
our preliminary work, we showed that clampFISH is capable of sorting fixed cells by specific endogenous and
even nascent transcripts. Once cells are sorted into locus-specific transcriptional subpopulations, we will be
able to profile them to assess what is molecularly bound at the target promoter in the context of its activity. We
have started by targeting human FKBP5 and mouse Hbb-b1 genomic loci because they are well-studied, so we
have candidate factors to interrogate, and display heterogeneous transcription between cells and over time. In
Aim 1, we plan to investigate the factors that are tightly associated with transcriptional bursts by sorting out
cells that do and do not contain nascent transcripts. In Aim 2, we plan to evaluate which factors are tightly
associated with the temporal heterogeneity of transcriptional response after induction by sorting out cells that
have responded (i.e. contain high levels of target RNA) from those that have not at different time points after
initial induction. In each of these cases, by performing ChIP as well as ATAC-seq and Capture-C on sorted
populations, I will determine whether candidate factors or interactions are present either in tight association
with or irrespec...

## Key facts

- **NIH application ID:** 9992052
- **Project number:** 1F30HG010822-01A1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Connie Lan Jiang
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $32,737
- **Award type:** 1
- **Project period:** 2020-06-01 → 2021-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9992052

## Citation

> US National Institutes of Health, RePORTER application 9992052, Revealing the molecular underpinnings of transcriptional heterogeneity (1F30HG010822-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9992052. Licensed CC0.

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