# Dynamic genetic regulation of gene expression in diverse differentiation trajectories with human embryoid bodies

> **NIH NIH F31** · JOHNS HOPKINS UNIVERSITY · 2024 · $18,483

## Abstract

Understanding the functional impact of genetic variation, particularly its impact on
disease, remains a key challenge in human genetics. Most disease-associated genetic loci lie in
regulatory regions of the human genome and are suspected to act by regulating the expression
levels of nearby genes. Yet despite extensive efforts to characterize genetic regulatory effects
on gene expression, most disease loci have not been explained by association with expression
levels. Pervasive context-specificity of these regulatory effects introduces one key bottleneck
contributing to this discrepancy. Detecting regulatory effects requires observation of gene
expression in the specific cell states where the effect is active, and large-scale efforts have
primarily focused on measuring expression levels in healthy adult tissues. Characterizing
genetic regulation in increasingly diverse and dynamic cellular contexts will therefore reveal
novel genetic regulatory effects which may help elucidate molecular mechanisms of disease
loci.
 To analyze genetic regulation of gene expression in diverse cellular contexts we will
leverage single-cell RNA-sequencing of embryoid bodies from multiple human donors.
Embryoid bodies are three-dimensional aggregates of induced pluripotent stem cells that
spontaneously differentiate into dozens of non-discrete cell types. Analysis of expression at the
single-cell level will enable us to cut through the heterogeneity of these complex aggregates and
map each cell to a unique position within a clearly defined differentiation landscape. Embryoid
bodies thus offer a unified experimental framework for the study of diverse differentiation
trajectories, accelerating the exploration of genetic regulation across the many cell states that
may contribute to human disease.
 In this proposed research, I will develop novel computational and statistical tools that
leverage the expansive and multifurcating landscape of cellular differentiation to improve our
ability to resolve context-specific and dynamic genetic regulatory effects. I will develop a
probabilistic model to compare gene expression dynamics between individuals, and a
hypothesis testing framework to attribute inter-individual differences to genetic variation. I will
validate the dynamic genetic regulatory effects we discover using in vitro and in vivo chromatin
accessibility data. Finally, I will search for overlap between newly discovered regulatory variants
and known disease loci to reveal novel insights into the target genes mediating genetic effects
on common diseases.

## Key facts

- **NIH application ID:** 10843742
- **Project number:** 5F31HG012896-02
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Joshua Popp
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $18,483
- **Award type:** 5
- **Project period:** 2023-01-17 → 2024-05-06

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10843742

## Citation

> US National Institutes of Health, RePORTER application 10843742, Dynamic genetic regulation of gene expression in diverse differentiation trajectories with human embryoid bodies (5F31HG012896-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10843742. Licensed CC0.

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