# Landscapes for Cell State Transition Leveraging by Single-Cell Multi-Omics

> **NIH NIH R35** · METHODIST HOSPITAL RESEARCH INSTITUTE · 2024 · $403,739

## Abstract

The overall goal of this project is to develop novel mathematic methods and toolkits to connect cell fate
transition and epigenetic regulation across tissues and diseases. Cell fate transition often occurs in organ
development, tissue regeneration, and pathogenesis. Dysregulation of the cell fate transition can lead to
abnormal development or diseases, such as type 2 diabetes, obesity, heart failure, and Alzheimer’s disease.
Quantitively decoding how cell fate changes can provide novel mechanistic insight into organogenesis and
tissue regeneration, and help identify new strategies for the treatment of human diseases. However, our
knowledge of cell fate transition and its regulation is only the tip of the iceberg due to the impracticality of long-
term tracing of cell transcriptomes. In the past decade, numerous single-cell atlases containing millions of cells
in different tissues, organs, developmental stages, and biological conditions are routinely developed by
consortia such as the Human Cell Atlas (HCA). These atlases provide an opportunity for the unbiased study of
cellular dynamics and the regulation mechanism. The lack of computational methods presents a major
knowledge gap in the understanding of cell dynamics and the regulation leveraging by those large reference
atlases. To address this knowledge gap, we proposed a new concept of “reference-based cellular dynamic
inference”, which is a novel strategy to automatically annotate the cell state transition in new datasets by
learning from the appropriate reference, allowing us to easily perform comparative analysis among different
tissues and disease conditions. In this project, we will pursue three parallel but complementary research
directions: 1) to develop the first computational methods and toolkits for generating cell dynamics atlases and
analyzing cell state transition based on the appropriate reference atlases; 2) to develop novel statistical models
for studying epigenetic regulation of cell fate from single-cell multiomics data; 3) to generate the first dynamic
reference landscapes of cell differentiation, such as cardiogenesis, hematopoiesis, and neurogenesis, and in-
house landscapes of transdifferentiation. This project will be built on the foundation of our recent studies for the
development of computational approaches to uncover cell state transition from single-cell transcriptomes in
both homogeneous and heterogeneous cell populations and the studies for investigating the role of epigenetic
regulation on cell fate transition. The proposed studies will generate advanced computational toolkits and
broadly applicable dynamic reference atlases, which are expected to reveal profound mechanisms controlling
cell state transition in health and disease. In the long term, the ability to build cell dynamics reference
landscapes will open a new horizon to understand the diversity of cell fate through comparative analyses
across tissues and diseases and enhance regenerative medicine.

## Key facts

- **NIH application ID:** 10914218
- **Project number:** 5R35GM150460-02
- **Recipient organization:** METHODIST HOSPITAL RESEARCH INSTITUTE
- **Principal Investigator:** Guangyu Wang
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $403,739
- **Award type:** 5
- **Project period:** 2023-09-01 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10914218

## Citation

> US National Institutes of Health, RePORTER application 10914218, Landscapes for Cell State Transition Leveraging by Single-Cell Multi-Omics (5R35GM150460-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10914218. Licensed CC0.

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