# Structure function relationships from deep mutational scanning in human cardiomyopathy

> **NIH NIH R01** · STANFORD UNIVERSITY · 2022 · $677,725

## Abstract

PROJECT SUMMARY
The natural experiment of human genetic variation can be used to infer structure-function relationships for key
disease genes. We have previously demonstrated that population-scale genetic variation data can be
harnessed to illuminate structure-function relationships for genes causative of the Mendelian disease
hypertrophic cardiomyopathy. However, due to the rarity of individual causative variants, population genetics is
ultimately limiting to the goal of understanding the functional importance of the entire coding region of any
specific gene. There is an urgent need for experimental alternatives. Here, we propose to introduce targeted
genetic variation into human induced pluripotent stem cell derived cardiomyocytes (iPSC-CM) at scale (Aim 1).
We propose two complementary strategies for deep mutational scanning of the most common genes causing
hypertrophic cardiomyopathy, MYH7, MYBPC3 and TNNT2. The first, CRISPR-X, is a fusion of a cytidine
deaminase (AID) with nuclease-inactive Cas9 (dCas9), and provides targeted mutational coverage in situ. The
second, POPcode, uses a uracilated gene template and a set of mutant oligos to create an allelic library, which
is then integrated into the genome using a Dual-Integrase Cassette Exchange (DICE). To characterize these
cells, we further develop a custom microfluidics-based, fast optical method to phenotype single cells in real
time (Aim 2). Predictions of pathogenicity according to both cell size and a fluorescence marker of the
hypertrophy expression program will be mapped to 3D protein structures using our spatial scanning approach
and tested against gold standard adjudicated patient variant data. Finally, we will investigate variant-specific
mechanisms of disease using single cell RNA sequencing to assess the effect of each variant on allelic
stoichiometry and transcriptional programming, as well as protein biochemistry to assess sarcomere protein
interaction and power generation (Aim 3). In summary, we plan comprehensive evaluation of all potential
coding variation in the most frequently causative genes for the most common Mendelian cardiovascular
disease. Using innovative phenotyping tools and novel statistical approaches to the integration of population
and cellular data, we aim to understand the structure and function of these genes in health and disease,
providing an experimental basis for the classification of genetic variants in the clinical setting.

## Key facts

- **NIH application ID:** 10364603
- **Project number:** 5R01HL144843-03
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Euan A Ashley
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $677,725
- **Award type:** 5
- **Project period:** 2020-01-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10364603

## Citation

> US National Institutes of Health, RePORTER application 10364603, Structure function relationships from deep mutational scanning in human cardiomyopathy (5R01HL144843-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10364603. Licensed CC0.

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