# Highly parallel analysis of 5' and 3' UTR variants in Autism Spectrum Disorders

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2021 · $579,782

## Abstract

Substantial investments are being made to sequence the genomes of families with Autism Spectrum Disorder
(ASD). However, identifying disease mutations outside the ~1% of protein coding sequences is challenging
because 1) the ‘search space’ is so much larger, and thus many more mutations occur by chance, and 2) there
is no simple code to identify deleterious mutations in non-coding sequence, and thus loss of function mutations
must be defined experimentally. In addition, the consequences of mutations in non-coding (i.e. regulatory)
sequences are often highly dependent on the specific cell type. Thus functional assays must be conducted in
vivo, in the appropriate CNS cell types.
To address the search space challenge, we propose to focus specifically on the untranslated regions (UTRs) of
mRNAs. UTRs are important, conserved regulatory sequences that profoundly impact protein levels by altering
translation rates or transcript stability for specific genes. Importantly, in ASD cases there is a 2-fold greater
rate of UTR mutations in known ASD genes than expected by chance, indicating that roughly half of these
UTR mutations may contribute to disease. To address the lack of a code for interpreting UTR mutations, we
have assembled a team with a unique combination of expertise to conduct massively parallel functional
analysis of UTR variants from ASD patients, in ASD-relevant cell types in vitro and in vivo. Combining
two innovative but established components: post-transcriptional massively parallel reporter assays, and cell type
specific translational profiling, we aim to establish a pipeline to 1) Identify UTR mutations that result in altered
protein levels, 2) conduct genetic burden and association testing on these variants, and 3) define the molecular
mechanisms altering protein levels for specific mutations. This pipeline will leverage the existing large investment
in ASD genome sequencing by defining individual non-coding disease causing mutations in a class of sequences
that has, so far, not been the focus of disease studies.

## Key facts

- **NIH application ID:** 10133733
- **Project number:** 5R01MH116999-04
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** JOSEPH D DOUGHERTY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $579,782
- **Award type:** 5
- **Project period:** 2018-07-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10133733

## Citation

> US National Institutes of Health, RePORTER application 10133733, Highly parallel analysis of 5' and 3' UTR variants in Autism Spectrum Disorders (5R01MH116999-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10133733. Licensed CC0.

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