bioRxivGenomicsPreprint
Widespread 3' UTR splicing regulates expression of oncogene transcripts in sequence-dependent and independent manners
Jack J. RileyiD, Cristina N. Alexandru-Crivac, Sam Bryce-SmithiD, Stuart A. WilsoniD, Ian M. SudberyiD
Abstract
BackgroundSplicing in 3 untranslated regions (3 UTRs) is generally considered a signal to elicit transcript degradation via nonsense-mediated decay (NMD) due to the presence of an exon junction complex (EJC) downstream of the stop codon. However, 3 UTR intron (3UI)-containing transcripts are widespread and highly expressed in both normal tissues and cancers. ResultsHere we present and characterise a novel transcriptome assembly built from 7897 solid tumour and normal samples from The Cancer Genome Atlas. We identify thousands of 3UI-containing transcript isoforms, many of which are expressed across multiple cancer types. We find that the expression of core NMD component UPF1 negatively correlates with global 3UI splicing between normal samples, however this correlation is lost in colon cancer. We find that 3UIs found exclusively within 3 UTRs (bona-fide 3UIs) are not predominantly NMD-sensitising, unlike introns present in 3 UTRs due to premature termination. We identify HRAS as an example where 3UI splicing rescues the transcript from NMD. Bona-fide, but not premature termination codon (PTC) carrying 3UI-transcripts are spliced more in cancer samples compared to matched normals in the majority of cancer types analysed. In colon cancer, differentially spliced 3UI-containing transcripts are enriched in the canonical Wnt signalling pathway, with CTNNB1 being the most over-spliced in colon cancer compared to normal. We show that manipulating Wnt signalling can further regulate splicing of Wnt component transcript 3 UTRs. ConclusionsOur results indicate that 3 UTR splicing is not a rare occurrence, especially in colon cancer, where 3 UTR splicing regulates transcript expression in EJC-dependent and independent manners.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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