Abstract
MotivationAlternative splicing removes intronic sequences from pre-mRNAs in alternative ways to produce different forms (isoforms) of mature mRNA. The composition of expressed transcripts gives specific functionalities to cells in a particular condition or developmental stage. In addition, a large fraction of human disease mutations affect splicing and lead to aberrant mRNA and protein products. Current methods that interrogate the transcriptome based on RNA-seq either suffer from short-read length when trying to infer full-length transcripts, or are restricted to predefined units of alternative splicing that they quantify from local read evidence.ResultsInstead of attempting to quantify individual outcomes of the splicing process such as local splicing events or full-length transcripts, we propose to quantify alternative splicing using a simplified probabilistic model of the underlying splicing process. Our model is based on the usage of individual splice sites and can generate arbitrarily complex types of splicing patterns. In our implementation, McSplicer, we estimate the parameters of our model using all read data at once and we demonstrate in our experiments that this yields more accurate estimates compared to competing methods. Our model is able to describe multiple effects of splicing mutations using few, easy to interpret parameters, as we illustrate in an experiment on RNA-seq data from autism spectrum disorder patients.Availability and implementationMcSplicer source code is available at https://github.com/canzarlab/McSplicer and has been deposited in archived format at https://doi.org/10.5281/zenodo.4449881.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
Through alternative splicing (AS), a single gene can produce multiple mRNA transcripts, or isoforms, that combine exons in alternative ways
Our method simultaneously estimates the model parameters, i.e. splice site usages, using all reads mapped to a gene locus, often resulting in more accurate estimates compared to other methods, e.g. event-based methods, that use only reads directly supporting their parameters
We have introduced McSplicer, a novel method that estimates splice site usage across expressed transcripts
Summary
Through alternative splicing (AS), a single gene can produce multiple mRNA transcripts, or isoforms, that combine exons in alternative ways. 95% of human multi-exon proteincoding genes undergo alternative splicing [34], creating a remarkably complex set of transcripts that give specific functionalities to cells and tissues in a particular condition or developmental stage. Even more than in healthy tissue, aberrant splicing is prevalent in various diseases, including cancer and neurologic diseases [13, 51]. RNA sequencing (RNA-seq) is routinely used in genome-wide transcript analysis.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
