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Quantifying splice-site usage: a simple yet powerful approach to analyze splicing.

ABSTRACT: RNA splicing, and variations in this process referred to as alternative splicing, are critical aspects of gene regulation in eukaryotes. From environmental responses in plants to being a primary link between genetic variation and disease in humans, splicing differences confer extensive phenotypic changes across diverse organisms (1-3). Regulation of splicing occurs through differential selection of splice sites in a splicing reaction, which results in variation in the abundance of isoforms and/or splicing events. However, genomic determinants that influence splice-site selection remain largely unknown. While traditional approaches for analyzing splicing rely on quantifying variant transcripts (i.e. isoforms) or splicing events (i.e. intron retention, exon skipping etc.) (4), recent approaches focus on analyzing complex/mutually exclusive splicing patterns (5-8). However, none of these approaches explicitly measure individual splice-site usage, which can provide valuable information about splice-site choice and its regulation. Here, we present a simple approach to quantify the empirical usage of individual splice sites reflecting their strength, which determines their selection in a splicing reaction. Splice-site strength/usage, as a quantitative phenotype, allows us to directly link genetic variation with usage of individual splice-sites. We demonstrate the power of this approach in defining the genomic determinants of splice-site choice through GWAS. Our pilot analysis with more than a thousand splice sites hints that sequence divergence in cis rather than trans is associated with variations in splicing among accessions of Arabidopsis thaliana. This approach allows deciphering principles of splicing and has broad implications from agriculture to medicine.

SUBMITTER: Dent CI

PROVIDER: S-EPMC8121094 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Budding yeast spliceosomal factors ScSlu7 and ScPrp18 interact and mediate intron 3'ss choice during second step pre-mRNA splicing. The fission yeast genome with abundant multi-intronic transcripts, degenerate splice signals and SR proteins is an apt unicellular fungal model to deduce roles for core spliceosomal factors in alternative splice-site choice, intron retention and to study the cellular implications of regulated splicing. From our custom microarray data we deduce a stringent reproducible subset of S. pombe alternative events. We examined the role of factors SpSlu7 or SpPrp18 for these splice events and investigated the relationship to growth phase and stress. Wild-type log and stationary phase cells showed ats1+ exon 3 skipped and intron 3 retained transcripts. Interestingly the non-consensus 5'ss in ats1+ intron 3 caused SpSlu7 and SpPrp18 dependent intron retention. We validated the use of an alternative 5'ss in dtd1+ intron 1 and of an upstream alternative 3'ss in DUF3074 intron 1. The dtd1+ intron 1 non-canonical 5'ss yielded an alternative mRNA whose levels increased in stationary phase. Utilization of dtd1+ intron 1 sub-optimal 5' ss required functional SpPrp18 and SpSlu7 while compromise in SpSlu7 function alone hampered the selection of the DUF3074 intron 1 non canonical 3'ss. We analysed the relative abundance of these splice isoforms during mild thermal, oxidative and heavy metal stress and found stress-specific splice patterns for ats1+ and DUF3074 intron 1 some of which were SpSlu7 and SpPrp18 dependent. By studying ats1+ splice isoforms during compromised transcription elongation rates in wild-type, spslu7-2 and spprp18-5 mutant cells we found dynamic and intron context-specific effects in splice-site choice. Our work thus shows the combinatorial effects of splice site strength, core splicing factor functions and transcription elongation kinetics to dictate alternative splice patterns which in turn serve as an additional recourse of gene regulation in fission yeast.

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Quantifying splice-site usage: a simple yet powerful approach to analyze splicing.

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