# Machine learning-based multi-omics modeling and CRISPR/Cas9-mediated gene editing in elucidating molecular transducer of physical activity

> **NIH NIH U01** · UNIVERSITY OF VIRGINIA · 2021 · $521,758

## Abstract

ABSTRACT
Regular exercise (physical activity) is the most effective intervention that promotes health and combats non-
communicable disease (NCD). However, our understanding of the molecule(s) responsible for the superb
benefits of exercise is obscure. The NIH Common Fund project “Molecular Transducers of Physical Activity
Consortium (MoTrPAC)” is a large-scale discovery study designed to understand the molecular responses to
exercise training, which has released the first batch of multi-omics data, including RNA-seq, Reduced
Representation Bisulfite Sequencing, proteomics, phosphoproteomics, acetylproteomics, and targeted and
untargeted metabolomics, from 5 tissues collected at different time points in rats following an acute bout of
endurance exercise. These endeavors have laid a solid foundation for elucidation of the molecular transducer of
physical activity. We have recently made significant progress in four areas, which poised us to explore these
data and elucidate the mechanism(s) in an unprecedented manner. Specifically, 1) We have obtained similar
time-course, transcriptomics data in 4 tissues in mice following acute and long-term endurance exercise and
developed machine learning capability for mining the multi-omics data for identification of regulatory factors that
mediate the exercise benefits; 2) We have perfected CRISPR/Cas9-mediated gene editing for generation of loss-
of-function knock-in mice as well as techniques to generate tissue-specific, inducible gain-of-function transgenic
mice; 3) We have established comprehensive phenotypic analysis in mice; and 4) We have had a successful
experience in elucidating the regulation and function of extracellular superoxide dismutase (EcSOD), a humoral
factor expressed in skeletal muscle and promoted by endurance exercise, in mediating the health benefits and
protection against diseases. We hypothesize that endurance exercise promotes expression and release of one
or more humoral factors from one or multiple tissues/organs, which is sufficient and necessary mediating the
health benefits of exercise. To this end, we propose
1) Identify candidate molecular transducers of physical activity by machine learning-based multi-omics modeling.
2) Generate loss-of-function knock-in and tissue-specific, gain-of-function transgenic mice using CRISPR/Cas9-
mediated gene editing and transgenesis.
3) Elucidate the role of the candidate molecular transducers of physical activity in health benefits of exercise.
The experimental design and model systems are both conceptually and technically innovative. The findings will
significantly improve the mechanistic understanding of exercise-induced adaptations with great potential impact
on the future development of therapeutics for NCD.

## Key facts

- **NIH application ID:** 10264175
- **Project number:** 5U01AG070960-02
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Zhen Yan
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $521,758
- **Award type:** 5
- **Project period:** 2020-09-30 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10264175

## Citation

> US National Institutes of Health, RePORTER application 10264175, Machine learning-based multi-omics modeling and CRISPR/Cas9-mediated gene editing in elucidating molecular transducer of physical activity (5U01AG070960-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10264175. Licensed CC0.

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