Molecular Mechanisms

Targeting autism haploinsufficiency with novel molecular feedback circuits

For many proteins encoded by autism risk genes, having too much or too little of them in each neuron are both problematic. To treat such disorders, it is important to increase the amount of gene expression in the “too little” scenario without overshooting into the “too much” scenario. Wei-Hsiang Huang, in collaboration with Xiaojing Gao, plan to work on a feedback control loop, consisting of engineered biomolecules, to achieve such quantitatively consistent regulation of gene levels.

Cell-type-specific interactome disruption prioritize risk missense mutations for autism

Although thousands of de novo missense mutations have been detected in people with ASD, it is challenging to identify which mutations induce risk. To address this gap, Haiyuan Yu and Kathryn Roeder aim to continue their efforts to develop an experimentally and computationally integrated interactome perturbation screening pipeline to study these mutations. Additionally, they plan to continue to develop analytical methods to identify ASD risk genes and understand the interrelationships among these genes.

High-throughput autism variant functional testing using genetic interaction technologies in model systems

There is a critical unmet need to define ASD-causing genes and determine how variants in those genes perturb molecular networks leading to disease. This project aims to address these issues using robust functional assays in model organisms designed to uncover disease networks and provide clinical predictive values of large numbers of variants. Christopher Loewen and colleagues expect to provide much needed progress in identifying clinically relevant ASD susceptibility variants to improve our understanding of ASD and potential treatments.

Platforms to accelerate development of antisense oligonucleotide therapeutics for haploinsufficiencies associated with autism

A critical step towards antisense oligonucleotide (ASO) development for haploinsufficiency is the identification of targets that have demonstrable inhibitory effects on the expression of ASD genes. Jonathan Sebat’s team proposes to accelerate ASO development for ASD risk genes using novel high-throughput platforms for target identification, focusing on regulatory RNA targets that can be readily characterized in transcriptome-wide screens.

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