# Revealing the dynamics of RNA metabolism with nucleotide recoding chemistry

> **NIH NIH R01** · YALE UNIVERSITY · 2024 · $375,463

## Abstract

PROJECT SUMMARY
Cellular RNA levels in both healthy and diseased cells are highly dynamic, yet most analyses of
RNA concentrations (RNA-sequencing, RNA-seq) capture only a static snapshot of cellular
RNA. RNA levels are controlled at diverse steps in RNA metabolism including transcriptional
initiation, transcriptional pausing, RNA processing, and RNA degradation. Further, each of these
steps can lead to different transcript isoforms by influencing the transcript initiation site, splicing
patterns, and termination positions, thereby leading to distinct transcript isoforms that can have
different coding potential, localization, and stability. Comparisons of the kinetics of these steps
under different conditions is therefore central to understanding regulation of gene expression.
There is a pressing need for robust and accessible technologies that can be easily adapted to
study the kinetic regulation of the broad range of steps in RNA metabolism. The overall
objective of this ongoing work is to add a temporal dimension to RNA-seq, transforming it from a
static endpoint assay into a robust technique to measure the kinetics of RNA metabolism and
reveal the diverse ways these kinetics are regulated and impacted by disease and therapeutics.
This platform is based on RNA metabolic labeling and improvements in nucleotide chemistry to
study RNA dynamics at a range of timescales. Work supported by this grant has led to improved
chemistry, a well-documented open-source software package to perform the first replicate-
aware and robust comparisons across experimental conditions, new insights into promoter-
proximal pausing of RNA polymerase II, and improved analyses of nascent transcription. To
fulfill the potential of these approaches, this integrated platform still needs to be extended to
transcript-isoform resolution, new sequencing formats, and provide improved integration across
experiments and timescale. The work described in Aim 1 will extend this platform to provide
robust detection of changes with transcript-isoform resolution. The work in Aim 2 will extend this
platform to long-read sequencing formats and will include optimization of chemistry and
processing for extended sequencing modalities. Aim 3 will establish experimental workflows to
optimally integrate analyses across timescales and experimental steps, to provide broad insight
into changes in RNA expression across the entire lifecycle of the transcript. Each of these aims
will include specific applications to reveal new biology and establish the general applicability of
the platform. Successful completion of these aims will establish nucleotide recoding chemistry
as a general platform to reveal RNA dynamics with isoform resolution across distinct levels of
gene expression.

## Key facts

- **NIH application ID:** 10978974
- **Project number:** 2R01GM137117-05
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Matthew David Simon
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $375,463
- **Award type:** 2
- **Project period:** 2020-07-01 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10978974

## Citation

> US National Institutes of Health, RePORTER application 10978974, Revealing the dynamics of RNA metabolism with nucleotide recoding chemistry (2R01GM137117-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10978974. Licensed CC0.

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