Bioinformatics analyses of the transcriptome reveal Ube3a-dependent effects on mitochondrial-related pathways

Julia Panov, Lilach Simchi, Yonatan Feuermann, Hanoch Kaphzan

Research output: Contribution to journalArticlepeer-review

Abstract

The UBE3A gene encodes the ubiquitin E3-ligase protein, UBE3A, which is implicated in severe neurodevelopmental disorders. Lack of UBE3A expression results in Angelman syndrome, while UBE3A overexpression, due to genomic 15q duplication, results in autism. The cellular roles of UBE3A are not fully understood, yet a growing body of evidence indicates that these disorders involve mitochondrial dysfunction and increased oxidative stress. We utilized bioinformatics approaches to delineate the effects of murine Ube3a deletion on the expression of mitochondrial-related genes and pathways. For this, we generated an mRNA sequencing dataset from mouse embryonic fibroblasts (MEFs) in which both alleles of Ube3a gene were deleted and their wild-type controls. Since oxidative stress and mitochondrial dysregulation might not be exhibited in the resting baseline state, we also activated mitochondrial functioning in the cells of these two genotypes using TNFα application. Transcriptomes of the four groups of MEFs, Ube3a+/+ and Ube3a−/−, with or without the application of TNFα, were analyzed using various bioinformatics tools and machine learning approaches. Our results indicate that Ube3a deletion affects the gene expression profiles of mitochondrial-associated pathways. We further confirmed these results by analyzing other publicly available human transcriptome datasets of Angelman syndrome and 15q duplication syndrome.

Original languageEnglish
Article number4156
Number of pages21
JournalInternational Journal of Molecular Sciences
Volume21
Issue number11
DOIs
StatePublished - 1 Jun 2020

Bibliographical note

Funding Information:
Funding: This research was funded by the Israel Science Foundation, grant number 287/15, and Angelman Syndrome Foundation, personal grant HK.

Funding Information:
This research was funded by the Israel Science Foundation, grant number 287/15, and Angelman Syndrome Foundation, personal grant HK. Acknowledgments: Tauber Bioinformatics Research Center at the University of Haifa.

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Angelman syndrome
  • Bioinformatics
  • Gene expression
  • Machine learning
  • Mitochondria
  • Oxidative stress
  • Reactive oxygen species

ASJC Scopus subject areas

  • Catalysis
  • Molecular Biology
  • Spectroscopy
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Inorganic Chemistry

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