# Functional analysis of autism risk genes during neural development using single cell seq

> **NIH NIH R01** · YALE UNIVERSITY · 2020 · $622,499

## Abstract

The brain represents a complex organ with a myriad of functionally diverse
cell types. Autism spectrum disorder (ASD) is thought to alter the combinatorial
transcriptional and post-transcriptional code responsible for specifying and
maintaining different cell functions in the vertebrate brain. The proposed studies
will test the central hypothesis that chromatin/transcriptional regulators identified
as ASD risk genes act as developmental switches during early
neurodevelopment, altering the gene expression network and subsequent cell
function.
In this proposal we combine single cell sequencing, with genetic, genomic
and computational approaches in zebrafish and embryoid bodies to i)
characterize the role of ASD-risk genes in healthy neural gene regulatory
networks (Aim 1); 2) Interrogate the effects of ASD loss-of-function (LOF)
mutations in different neural lineages (Aim 2). Cell types and developmental
lineages within the brain that are more significantly affected by each candidate
ASD risk gene will be identified using zebrafish and human cell–derived
organoids.
The experiments outlined in this proposal have the ultimate goal of
identifying how ADS risk genes affect neural gene expression and cell function
during vertebrate development.

## Key facts

- **NIH application ID:** 9893904
- **Project number:** 5R01MH118554-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Antonio J Giraldez
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $622,499
- **Award type:** 5
- **Project period:** 2019-03-15 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9893904

## Citation

> US National Institutes of Health, RePORTER application 9893904, Functional analysis of autism risk genes during neural development using single cell seq (5R01MH118554-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9893904. Licensed CC0.

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