Prediction of Mutant mRNA Splice Isoforms by Information Theory-Based Exon Definition

Abstract

Mutations that affect mRNA splicing often produce multiple mRNA isoforms, resulting in complex molecular phenotypes. Definition of an exon and its inclusion in mature mRNA relies on joint recognition of both acceptor and donor splice sites. This study predicts cryptic and exon-skipping isoforms in mRNA produced by splicing mutations from the combined information contents (R(i), which measures binding-site strength, in bits) and distribution of the splice sites defining these exons. The total information content of an exon (R(i),total) is the sum of the R(i) values of its acceptor and donor splice sites, adjusted for the self-information of the distance separating these sites, that is, the gap surprisal. Differences between total information contents of an exon (ΔR(i,total)) are predictive of the relative abundance of these exons in distinct processed mRNAs. Constraints on splice site and exon selection are used to eliminate nonconforming and poorly expressed isoforms. Molecular phenotypes are computed by the Automated Splice Site and Exon Definition Analysis (http://splice.uwo.ca) server. Predictions of splicing mutations were highly concordant (85.2%; n = 61) with published expression data. In silico exon definition analysis will contribute to streamlining assessment of abnormal and normal splice isoforms resulting from mutations.

A human APOC3 missense variant and monoclonal antibody accelerate apoC-III clearance and lower triglyceride-rich lipoprotein levels

“…The impact of the APOC3 A43T coding variant on APOC3 exon splicing was assessed using the Automated Splice Site and Exon Definition Analyses (ASSEDA) server (MutationForcaster; https://www.mutationforecaster.com/learn.php#asseda; ref. 43).…”

Expanding the mutational spectrum of LZTR1 in schwannomatosis

“…uwo.ca). 17 The predicted effects of missense variants on LZTR1 function were assessed using the following open access software: PolyPhen 2 (http://genetics.bwh. harvard.edu/pph2/), 18 SIFT (http://sift.jcvi.org/www/SIFT_enst_submit.html), 19 Mutation Taster (http://www.mutationtaster.org/) 20 and ClustalW2 (http:// www.ebi.ac.uk/Tools/clustalw2/index.html).…”

Validation of predicted mRNA splicing mutations using high-throughput transcriptome data

“…Nevertheless, novel or strengthened cryptic sites can be activated independently of any direct effect on the corresponding natural splice site. The prevalence of these splicing events has been determined by ourselves and others 5, 11– 13 . The diversity of possible molecular phenotypes makes such aberrant splicing challenging to corroborate at the scale required for complete genome (or exome) analyses.…”

“…Splicing variants, in particular, are known to be a significant cause of human disease 2– 5 and indeed have even been hypothesized to be the most frequent cause of hereditary disease 6 . Computational identification of mRNA splicing mutations within DNA sequencing (DNA-Seq) data has been implemented to varying degrees of sensitivity, with most software only evaluating conservation solely at the intronic dinucleotides adjacent to the junction (i.e.…”

“…7). Other approaches are capable of detecting significant mutations at other positions with constitutive, and in certain instances, cryptic, splice sites 5, 8, 9 which can result in aberrations in mRNA splicing. Presently, only information theory-based mRNA splicing mutation analysis has been implemented on a genome scale 10 .…”