Functionalizing the autism variome

  • Awarded: 2021
  • Award Type: Targeted: Genomics of ASD: Pathways to Genetic Therapies
  • Award #: 896503

The last four decades have produced an enormous catalog of human genomic variants which has the potential to revolutionize human genetics. The widespread use of genome and exome sequencing has enabled the scientific community to identify variants present in individuals affected with disease with greater frequency. However, despite these advances, for the most part, the scientific community remains unable to: (i) accurately predict which of the variants detected in an individual might be responsible for the disease burden, (ii) understand how variants cause disease, and (iii) determine how to use this knowledge to inform treatment choices. As a result, there is an urgent and growing need for a better understanding of the functional impact of variants detected in affected individuals.

Marc Vidal and Lilia Iakoucheva propose to functionally characterize most variants identified in the entire SFARI target gene set by comparing them to their respective wild-type, or ‘reference,’ gene products. For the majority of alleles of most SFARI target genes, they plan to generate comparative profiles of protein stability and the ability to mediate macromolecular interactions with protein partners.

Their group is particularly well suited for this endeavor since they have generated most of the reference protein interaction profiles that will serve here as wild-type profiles, including their recent “reference map of the human binary interactome network”1. In addition, they have been at the forefront of designing and improving a battery of protein interaction profiling assays over the last two decades2,3. The functional profiles generated here will enhance both the community’s ability to identify true disease-causing variants and provide insight into the underlying disease mechanisms.

References

  1. Luck K. et al. Nature 580, 402-408 (2020) PubMed
  2. Chau K.K. et al. Cell Rep. 36, 109631 (2021) PubMed
  3. Gandal M.J. et al. Science 362, eaat8127 (2018) PubMed
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