Genome accessibility as a high-resolution biomarker for autism gene therapy

  • Awarded: 2021
  • Award Type: Targeted: Genomics of ASD: Pathways to Genetic Therapies
  • Award #: 896724

Early intervention for autism spectrum disorder (ASD) provides the best chance for minimizing challenges that interfere with quality of life. However, the development of diagnostic tools and targeted therapeutics for ASD has been challenging due to the highly heterogeneous etiology of the condition. Recently, de novo mutations (DNMs) in chromatin modifiers and transcriptional regulators (CMTRs) have been recognized as major genetic drivers of ASD. Given that CMTRs orchestrate complex gene expression programs, ASD phenotypes resulting from DNMs in CMTRs may be due to broad disruptions in gene expression.

Numerous groups have performed phenotypic studies in various model systems for specific ASD risk genes; however, there exists no integrative, high-throughput functional study of high-confidence CMTR risk genes. Another complicating factor is that there is no consensus within the field regarding which biological phenotypes are most relevant to ASD.

Here, Neville Sanjana and his group at the New York Genome Center and New York University propose to develop chromatin accessibility as a novel biomarker of CMTR function. Sanjana’s team will use an innovative forward genetic screen (CRISPR-sciATAC)1 to knockdown all CMTRs cataloged in the SPARK prioritized ASD gene list, and measure changes in chromatin accessibility genome-wide in human cortical neurons derived from induced pluripotent stem cells. This integrated map can advise novel approaches for diagnosis, and even pinpoint which ASD risk genes will yield the biggest benefit when targeted with gene augmentation therapeutics.

Sanjana’s team will then examine activity of DNMs in noncoding regions using a massively parallel reporter assay and connect these noncoding variants to their target genes using CRISPR perturbations coupled with single-cell RNA-sequencing (STING-seq)2. In addition to providing a variant-to-gene map for CMTR-associated noncoding DNMs, these approaches will capture the key regulatory networks disrupted by these mutations and serve as a predictive tool to identify DNMs that contribute to ASD susceptibility.

References

1.Liscovitch-Brauer N. et al. Nat. Biotechnol. 39, 1270-1277 (2021) PubMed
2.Morris J.A. et al. bioRxiv (2021) Preprint
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