Conserved and divergent signals in 5’ splice site sequences across fungi, metazoa and plants
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Published:2023-10-13
Issue:10
Volume:19
Page:e1011540
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ISSN:1553-7358
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Container-title:PLOS Computational Biology
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language:en
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Short-container-title:PLoS Comput Biol
Author:
Beckel Maximiliano S.,
Kaufman Bruno,
Yanovsky Marcelo,
Chernomoretz ArielORCID
Abstract
In eukaryotic organisms the ensemble of 5’ splice site sequences reflects the balance between natural nucleotide variability and minimal molecular constraints necessary to ensure splicing fidelity. This compromise shapes the underlying statistical patterns in the composition of donor splice site sequences. The scope of this study was to mine conserved and divergent signals in the composition of 5’ splice site sequences. Because 5’ donor sequences are a major cue for proper recognition of splice sites, we reasoned that statistical regularities in their composition could reflect the biological functionality and evolutionary history associated with splicing mechanisms.
Results: We considered a regularized maximum entropy modeling framework to mine for non-trivial two-site correlations in donor sequence datasets corresponding to 30 different eukaryotes. For each analyzed species, we identified minimal sets of two-site coupling patterns that were able to replicate, at a given regularization level, the observed one-site and two-site frequencies in donor sequences. By performing a systematic and comparative analysis of 5’splice sites we showed that lineage information could be traced from joint di-nucleotide probabilities. We were able to identify characteristic two-site coupling patterns for plants and animals, and propose that they may echo differences in splicing regulation previously reported between these groups.
Funder
Fondo para la Investigación Científica y Tecnológica
Secretaria de Ciencia y Tecnica, Universidad de Buenos Aires
Publisher
Public Library of Science (PLoS)
Subject
Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics
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