A basic framework to explain splice-site choice in eukaryotes

Craig I. Dent, Stefan Prodic, Aiswarya Balakrishnan, Aaryan Chhabra, James D. G. Georges, Sourav Mukherjee, Jordyn Coutts, Michael Gitonobel, Rucha D. Sarwade, Joseph Rosenbluh, Mauro D’Amato, Partha P. Das, Ya-Long Guo, Alexandre Fournier-Level, Richard Burke, Sridevi Sureshkumar, David Powell and Sureshkumar Balasubramanian ()
Additional contact information
Craig I. Dent: Clayton Campus
Stefan Prodic: Clayton Campus
Aiswarya Balakrishnan: Clayton Campus
Aaryan Chhabra: Clayton Campus
James D. G. Georges: Clayton Campus
Sourav Mukherjee: Clayton Campus
Jordyn Coutts: Clayton Campus
Michael Gitonobel: Clayton Campus
Rucha D. Sarwade: Clayton Campus
Joseph Rosenbluh: Clayton Campus
Mauro D’Amato: LUM University
Partha P. Das: Clayton
Ya-Long Guo: Chinese Academy of Sciences
Alexandre Fournier-Level: University of Melbourne
Richard Burke: Clayton Campus
Sridevi Sureshkumar: Clayton Campus
David Powell: Clayton Campus
Sureshkumar Balasubramanian: Clayton Campus

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract Changes in splicing can mediate phenotypic variation, ranging from flowering time differences in plants to genetic diseases in humans. Splicing changes occur due to differences in splice-site strength, often influenced by genetic variation and the environment. How genetic variation influences splice-site strength remains poorly understood, largely because splice-site usage across transcriptomes has not been empirically quantified. Here, we quantify the use of individual splice-sites in Arabidopsis, Drosophila and humans and treat these measurements as molecular phenotypes to map variation in splice-site usage through GWAS. We carry out more than 130,000 GWAS with splice-site usage phenotypes, cataloguing genetic variation associated with changes in the usage of individual splice-sites across transcriptomes. We find that most of the common, genetically controlled variation in splicing is cis and there are no major trans hotspots in the three species analyzed. We group splice-sites based on GT[N]4 or [N]4AG sequence, quantify their average use, develop a ranking and show that these hexamer rankings provide a simple and comparable feature across species to explain most of the splice-site choice. Transcriptome analyses in several species suggest that hexamer rankings offer a rule that helps explain splice-site choices, forming a basis for a shared splicing logic in eukaryotes.

Date: 2025
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DOI: 10.1038/s41467-025-63622-9

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