Science AdvancesNeurosciencePeer-reviewed journal article
Sex-biasing influence of autism-associated Ube3a gene overdosage at connectomic, behavioral and transcriptomic levels
Caterina MontaniiD, Luigi BalascoiD, Marco PaganiiD, Filomena Grazia AlvinoiD, Noemi BarsottiiD, A. Elizabeth de GuzmaniD, Alberto GalbuseraiD, Alessia De Felice, Thomas Nickl‐JockschatiD, Sara MigliariniiD, Simona CasarosaiD, Pierre LauiD, Lorenzo MattioniiD, Massimo PasqualettiiD, Giovanni ProvenzanoiD, Yuri BozziiD, Michael Vincent LombardoiD, Alessandro GozziiD
Abstract
Many neurodevelopmental conditions, including autism, affect males more than females. Genomic mechanisms enhancing risk in males may contribute to this sex-bias. The ubiquitin protein ligase E3A gene (Ube3a) exerts pleiotropic effects on cellular homeostasis via control of protein turnover and by acting as transcriptional coactivator with steroid hormone receptors. Overdosage of Ube3a via duplication or triplication of chromosomal region 15q11-13 causes 1-2% of autistic cases. Here, we test the hypothesis that increased dosage of Ube3a may influence autism-relevant phenotypes in a sex-biased manner. We report robust sex-biasing effects on brain connectomics and repetitive behaviors in mice with extra copies of Ube3a. These effects were associated with a profound transcriptional dysregulation of several known autism-associated genes (e.g., FMR1, SCN2A, PTEN, MEF2C, SHANK3, TSC2) as well as differentially-expressed genes identified in human 15q duplication and in autistic patients. Notably, increased Ube3a dosage also affects multiple sex-relevant mechanisms, including genes on the X chromosome, genes influenced by sex steroid hormones, downstream targets of the androgen and estrogen receptors, or genes that are sex-differentially regulated by transcription factors. These results suggest that Ube3a overdosage can critically contribute to sex-bias in neurodevelopmental conditions via influence on sex-differential mechanisms.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell type annotation
- research focus: clustering
- approach: statistical model
- approach: experimental assay
- Citations
- 15
- FWCI
- 3.70
- Field percentile
- top 6%
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