Identification of disease-linked hyperactivating mutations in UBE3A through large-scale functional variant analysis

Kellan P. Weston, Xiaoyi Gao, Jinghan Zhao, Kwang-Soo Kim, Susan E. Maloney, Jill Gotoff, Sumit Parikh, Yen-Chen Leu, Kuen-Phon Wu, Marwan Shinawi, Joshua P. Steimel, Joseph S. Harrison and Jason J. Yi ()
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Kellan P. Weston: Washington University School of Medicine
Xiaoyi Gao: Washington University School of Medicine
Jinghan Zhao: Washington University School of Medicine
Kwang-Soo Kim: Washington University School of Medicine
Susan E. Maloney: Washington University School of Medicine
Jill Gotoff: Geisinger Medical Center
Sumit Parikh: Neurosciences Institute, Cleveland Clinic
Yen-Chen Leu: Academia Sinica
Kuen-Phon Wu: Academia Sinica
Marwan Shinawi: Washington University School of Medicine
Joshua P. Steimel: University of the Pacific
Joseph S. Harrison: University of the Pacific
Jason J. Yi: Washington University School of Medicine

Nature Communications, 2021, vol. 12, issue 1, 1-15

Abstract: Abstract The mechanisms that underlie the extensive phenotypic diversity in genetic disorders are poorly understood. Here, we develop a large-scale assay to characterize the functional valence (gain or loss-of-function) of missense variants identified in UBE3A, the gene whose loss-of-function causes the neurodevelopmental disorder Angelman syndrome. We identify numerous gain-of-function variants including a hyperactivating Q588E mutation that strikingly increases UBE3A activity above wild-type UBE3A levels. Mice carrying the Q588E mutation exhibit aberrant early-life motor and communication deficits, and individuals possessing hyperactivating UBE3A variants exhibit affected phenotypes that are distinguishable from Angelman syndrome. Additional structure-function analysis reveals that Q588 forms a regulatory site in UBE3A that is conserved among HECT domain ubiquitin ligases and perturbed in various neurodevelopmental disorders. Together, our study indicates that excessive UBE3A activity increases the risk for neurodevelopmental pathology and suggests that functional variant analysis can help delineate mechanistic subtypes in monogenic disorders.

Date: 2021
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DOI: 10.1038/s41467-021-27156-0

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