Quantifying splice-site usage: a simple yet powerful approach to analyze splicing. (14th May 2021)

• Record Type: Journal Article
• Authors: Dent, Craig I; Singh, Shilpi; Mukherjee, Sourav; Mishra, Shikhar; Sarwade, Rucha D; Shamaya, Nawar; Loo, Kok Ping; Harrison, Paul; Sureshkumar, Sridevi; Powell, David; Balasubramanian, Sureshkumar
• Is Part Of: NAR genomics and bioinformatics. Volume 3:issue 2(2021)
• Publication Date: 2021-05-14
• Subjects: Genomics -- Periodicals; Bioinformatics -- Periodicals; 572.8
• DOI: 10.1093/nargab/lqab041
• Languages: English
• ISSNs: 2631-9268

Abstract

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.