# Methods to Elucidate the Dynamics of Transcriptional Regulation and Chromatin

> **NIH NIH R35** · DUKE UNIVERSITY · 2022 · $429,165

## Abstract

Project Summary
Within a cell, though the sequence of the genome is essentially fixed, its state is constantly changing. Two aspects
of this changing state at a given point in time are the specific arrangement of myriad protein complexes along the
genome in the form of chromatin, and the rate of transcript production for each gene. Each of these influences
the other, and each also changes in response to the cell's internal or external environment, setting up a complex
dynamical system that undergirds cellular function and adaptation. A fundamental research objective is to
understand the dynamic relationship between these two, genome-wide: how transcription is influenced by the
chromatin landscape, and how the chromatin landscape is influenced by transcription.
A central goal of our research group is to develop models capable of predicting a cell's genome-wide transcription
state from knowledge of its genome-wide chromatin state. To build such models requires simultaneously profiling
a cell's genome-wide chromatin and transcription states at different times and under different conditions:
Observing how the two change together as they respond to a changing environment, particularly in the context
of directed perturbation, provides the statistical leverage needed to build predictive models capable of providing
causal and mechanistic interpretations. Our models will initially be developed and validated by monitoring
dynamic chromatin occupancy and transcription in budding yeast under various conditions: as they progress
through the cell cycle (a temporal series of highly regulated events controlling cell proliferation, aberrations of
which can lead to cancer), in response to environmental stresses, and across genetic strains, including mutants
that disrupt chromatin remodeling or TF expression. We also have access to massive amounts of data assaying the
dynamics of transcription and chromatin in the context of human hormone response and chromatin remodeling.
The distinct yeast and human contexts offer an opportunity to develop methods that are broadly applicable
across this spectrum and provide mechanistic insight into foundational questions in genomic regulation.
The proposed research will produce computational and statistical methods based on Bayesian probabilistic
graphical modeling approaches that can (1) more accurately, comprehensively, and scalably profile both chromatin
occupancy and transcriptional regulation as they change over time, and (2) infer mechanistic links between the
two that elucidate how the cell dynamically regulates its genome-wide transcription program and chromatin
organization in response to changing conditions.
More generally, as advanced experimental technologies and assays continue to be pioneered at a rapid pace, we
need to concomitantly develop sophisticated new computational and statistical methods, not merely to store
or process the ever-growing amounts of data, but to formulate models that provide mechanistically grounded
...

## Key facts

- **NIH application ID:** 10405481
- **Project number:** 5R35GM141795-02
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Alexander J Hartemink
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $429,165
- **Award type:** 5
- **Project period:** 2021-06-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10405481

## Citation

> US National Institutes of Health, RePORTER application 10405481, Methods to Elucidate the Dynamics of Transcriptional Regulation and Chromatin (5R35GM141795-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10405481. Licensed CC0.

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