# Collaborative Research: DMS/NIGMS 2: Methods for Systematic Analysis of Post-transcriptional Regulation in Single Cells

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA SANTA BARBARA · 2021 · $192,447

## Abstract

Proteins are the drivers of molecular activity in the cell, but we still lack a comprehensive understanding of
the mechanisms by which cells regulate protein abundances. A long-standing question has focused
specifically on the mechanisms and degree of post-transcriptional regulation, which also determines the
degree to which mRNA levels can be used to predict protein abundances. For example, mRNA levels
generally correlate with protein abundance across genes, but that mRNA-protein correlations can vary
significantly within genes across conditions, due in part to post-transcriptional regulation, such as
regulation of protein synthesis and degradation. Post-transcriptional regulation has been analyzed in bulk
samples composed of heterogeneous cell types, but it remains largely unexplored in single cells. To
enable systematic analysis of post-transcriptional regulation at single-cell resolution, we need a novel
analytic framework which 1) accounts for single-cell measurement error and technical bias, which are
convolved with the relevant biological signal for both mRNA and protein abundance 2) leverages
probabilistic models which pool information across genes in functional groups or account for the
determinants contributing to protein abundance, like ribosomal binding proteins 3) models
abundance-dependent missing data in single-cell mRNA and protein data and 4) associates observed
post-transcriptions regulation with likely regulatory mechanisms. To achieve these goals, we build upon
our long-standing collaboration and propose the following aims:
Aim 1. To develop methods for inferring post-transcriptional regulation in single cells. These methods will
employ hierarchical models which account for similarities between genes with common regulatory
mechanisms. We will explicitly model non-ignorable missing data and account for measurement error in
the data.
Aim 2. To apply and validate the methodology from Aim 1. We will analyze single-cell mRNA and protein
measurements from human immune cells and testis with a focus on identifying and validating functionally
related genes regulated by common RNA binding proteins.
The research will be integrated into the education programs at the PI's institutions, with a particular focus
on capstone experiences. Reproducible software implementations for new tools will be developed.
RELEVANCE (See instructions):
Dysregulation of post-transcriptional regulation is very frequent in human cancers and other diseases, and
usually it affects specific subsets of cells. Despite evidence for the importance of post-transcriptional
regulation, it is almost completely unexplored at single-cell level. The goal of the proposed research is to
develop new methodologies for characterising post-transcriptional regulation in single cells.

## Key facts

- **NIH application ID:** 10378378
- **Project number:** 1R01GM144967-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA SANTA BARBARA
- **Principal Investigator:** Alexander Franks
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $192,447
- **Award type:** 1
- **Project period:** 2021-09-23 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10378378

## Citation

> US National Institutes of Health, RePORTER application 10378378, Collaborative Research: DMS/NIGMS 2: Methods for Systematic Analysis of Post-transcriptional Regulation in Single Cells (1R01GM144967-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10378378. Licensed CC0.

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