# Genetic, molecular and computational analysis of MEF2 function in Drosophila myogenesis

> **NIH NIH R01** · SAN DIEGO STATE UNIVERSITY · 2020 · $239,675

## Abstract

Genetic, molecular and computational analysis of MEF2 function in Drosophila myogenesis.
The goal of this proposal is to define the molecular mechanisms by which the transcription factor Myocyte
enhancer factor-2 (MEF2) activates target gene expression. Several studies have identified critical roles for
MEF2 in formation of the musculature and in differentiation of other tissues including immune cells and
neurons. Moreover, variants in MEF2 orthologs in humans are associated with cardiac disease and autism.
However despite the importance of MEF2 to muscle formation and human disease, a relatively small number
of co-factors have been identified that function alongside MEF2 to participate in myogenesis, and no
systematic or genome-wide approaches have been identified to understand how MEF2 controls gene
expression. Moreover, it is not clear how MEF2 interacts with the basal transcription machinery. In this
proposal, we will use the power of the Drosophila system, that has a single Mef2 gene, to execute a three-
pronged approach to identify and characterize factors that interact with MEF2. In Aim 1, we will continue and
expand a genetic modifier screen to identify genes for which haploinsufficiency enhances a Mef2 mutant
phenotype. In preliminary data we demonstrate the feasibility of this approach, and identify a number of
potential co-factors to be characterized. In Aim 2, we will carry out a molecular screen to identify factors that
co-immune purify with MEF2 from embryonic lysates. In preliminary data we demonstrate that MEF2 interacts
with CF2, that was identified in our earlier studies of MEF2 co-factors. In Aim 3, we will continue a bioinformatic
analysis of MEF2 target genes, to identify sequences that are enriched in MEF2 target enhancers and
promoters, and to identify and characterize the factors that interact with these sequences. In preliminary data
we demonstrate the feasibility of this approach by showing that our independent bioinformatic analyses identify
sites for two known MEF2 co-factors, and we identify additional binding activities that might also represent
MEF2 co-factors. In Aim 4, we will collate the factors identified in Aims 1-3 and select for mechanistic analysis
those that have high probability to be MEF2 co-factors. Overall our proposed experiments, which are all based
upon strong preliminary data, will provide new insight into mechanisms by which MEF2 functions in animals.
Given the strong conservation in the sequence and function of MEF2 within the animal kingdom, our findings
will have direct impact upon our understanding of MEF2 function in mammalian development and disease.

## Key facts

- **NIH application ID:** 9980932
- **Project number:** 5R01GM124498-05
- **Recipient organization:** SAN DIEGO STATE UNIVERSITY
- **Principal Investigator:** Richard Matthew Cripps
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $239,675
- **Award type:** 5
- **Project period:** 2017-09-01 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9980932

## Citation

> US National Institutes of Health, RePORTER application 9980932, Genetic, molecular and computational analysis of MEF2 function in Drosophila myogenesis (5R01GM124498-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9980932. Licensed CC0.

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