# Tracking transcriptome diversity in real-time

> **NIH NIH R35** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2022 · $76,727

## Abstract

SUMMARY
Recent studies have provided unprecedented insights into how individual molecular mechanisms
are correlated to changes in gene expression levels. It is now recognized that substantial
transcriptome complexity arises from decisions involved in the processing of nascent mRNAs.
However, by and large, the many studies of gene expression have focused on characterizing
steady-state mRNA levels, even though living systems are inherently dynamic. Thus, a key open
question in functional genomics is: how to the dynamics of individual molecular mechanisms
combine to influence the cellular transcriptome? Our overarching hypothesis is that the fate of an
mRNA is governed by kinetic interactions underlying molecular efficiency across disparate steps
in the mRNA lifecycle – at the core, transcription elongation, mRNA splicing, and 3’ end cleavage.
Current knowledge of spatiotemporal coordination across these processes likely represents the
tip of the iceberg. In this proposal, we will combine genetic, molecular, and cellular genomic
techniques with high-dimensional computational analyses to address two specific themes of
mechanistic efficiency. First, we aim to dissect the kinetic basis for efficient mRNA biogenesis
and maturation. Work from my research and others has suggested that there is substantial
variability in kinetic actions and rate-limiting steps for mature mRNA production across genes.
Determining the molecular logic underlying this variability will inform our understanding of the
molecular basis for transcriptome complexity in both homeostatic and diseased cells. We will
address this issue by answering three questions. 1) What are the kinetics of each individual step
in mRNA processing?; 2) What are the factors that govern rate-limiting steps of mature mRNA
production; and 3) How does the RNA processing machinery balance speed and accuracy? The
goal of the second theme of our research is to determine how RNA processing kinetics underlie
the regulation of cellular transitions. The kinetics of gene regulatory processes likely play a crucial
role in cellular responses or transitions, by altering the order of molecular events or speed of
processes to rapidly regulate gene expression dynamics. To dissect the kinetic plasticity
underlying cellular response, we will answer related questions in two disparate systems: 4) How
do immune cells rapidly change their transcriptome upon stimulation?; and 5) How is
transcriptome complexity regulated upon neuronal differentiation? Our research will result in
insights crucial to uncovering the cascade of molecular events that cumulatively establish steady-
state gene expression levels, with implications for improved therapeutic designs or strategies that
target the early progression of cellular shifts rather than only the final outcome.

## Key facts

- **NIH application ID:** 10651131
- **Project number:** 3R35GM133762-04S1
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** Athma A Pai
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $76,727
- **Award type:** 3
- **Project period:** 2019-08-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10651131

## Citation

> US National Institutes of Health, RePORTER application 10651131, Tracking transcriptome diversity in real-time (3R35GM133762-04S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10651131. Licensed CC0.

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