High-throughput screening of Drosophila models to identify autism gene networks that disrupt sleep and circadian rhythms

  • Awarded: 2020
  • Award Type: Pilot
  • Award #: 735135

Sleep and circadian (approximately 24 hour) rhythm disturbances are prevalent in as many as 80 percent of individuals with autism spectrum disorders (ASDs). Indeed, sleep disruption may be an important contributor to the core neurodevelopmental, cognitive, and social challenges emblematic of ASD.

Over 150 genetic loci have been identified as likely contributing to ASD risk. Yet for most of these genes, it is unclear how they function in vivo to contribute to ASD-related symptoms. ASD results, in part, from multiple genetic risk factors and synergistic allele-specific interactions amongst risk genes may play an important role in the manifestation of the condition. Yet how the plethora of ASD risk genes interact with each other within gene networks remains a major challenge.

In the current project, Ravi Allada plans to address this issue using novel high-throughput behavioral screening of transgenic RNA interference libraries in both wild-type fruit flies and flies sensitized with disruptions of ASD risk genes. Specifically, Allada’s team plans to look at altered sleep patterns and circadian rhythms in these models.

The proposed studies provide an economical strategy to reveal in vivo behavioral functions of ASD risk genes for ASD-relevant phenotypes in a valid animal model. These studies exploit the advantages of the Drosophila model system, including the deep conservation with vertebrate models of ASD-related phenotypes, including circadian rhythms and sleep. The use of the Drosophila model will enable the economical testing of large numbers of genes and genetic interactions in a short time. Given the polygenic nature of ASD, understanding the complex interaction architecture among these genes is a major challenge and the proposed approach may reveal gene functions missed by conventional single gene disruption strategies.

Future studies of the underlying mechanisms for these genetic pathways may lead to a better understanding of ASD pathophysiology as well as the discovery of novel therapeutic targets.

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