bioRxivGenomicsPreprint
The impact of biological sex on alternative splicing
Guy KarlebachiD, Diogo F. T. VeigaiD, Anne Deslattes MaysiD, Christina ChatzipantsiouiD, Pablo Prieto Barja, Maria ChatzouiD, Anil K Kesarwani, Daniel DanišiD, Georgios KararigasiD, Xingmin ZhangiD, Joshy GeorgeiD, Robin SteinhausiD, Peter HanseniD, Dominik SeelowiD, Julie A. McMurryiD, Melissa Anne HaendeliD, Jeremy J. YangiD, Tudor Ionel OpreaiD, Olga AnczukówiD, Jacques BanchereauiD, Peter N. RobinsoniD
Abstract
Over 95% of human genes undergo alternative splicing (AS) in a developmental, tissue-specific, or signal transduction-dependent manner. Here, we present a large-scale survey of sex-biased differential alternative splicing (DAS) across 7027 samples of 39 tissues from 532 individuals (351 males and 181 females) from the Genotype-Tissue Expression project. We detected a total of 1278 statistically significant DAS events affecting 888 different genes and 4417 significant differential gene expression (DGE) events in 3221 genes. Only 267 (29.3%) of the differentially spliced genes were also differentially expressed. Genes that displayed sex-biased DGE or DAS across multiple tissues were enriched in functions related to signaling including histone demethylation. The probability of a gene showing significant differential AS varies by chromosome and is highest for the X chromosome, with differentially spliced X chromosomal genes additionally being more likely to escape X chromosomal inactivation. A small but significant association was found between sex-biased AS and transcripts that undergo physiological nonsense-mediated decay (NMD). We show a significant overlap of differential splicing and genes that display estrogen-induced alternative splicing, that are involved in estrogen response pathway. Further, we show overlap of the involved exons with estrogen-receptor bindings sites. Our results provide a comprehensive survey of sex-biased AS and its characteristics across a large collection of human tissues.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 27
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