Mutations primarily alter the inclusion of alternatively spliced exons
Abstract
Genetic analyses and systematic mutagenesis have revealed that synonymous, non-synonymous and intronic mutations frequently alter the inclusion levels of alternatively spliced exons, consistent with the concept that altered splicing might be a common mechanism by which mutations cause disease. However, most exons expressed in any cell are highly-included in mature mRNAs. Here, by performing deep mutagenesis of highly-included exons and by analysing the association between genome sequence variation and exon inclusion across the transcriptome, we report that mutations only very rarely alter the inclusion of highly-included exons. This is true for both exonic and intronic mutations as well as for perturbations in trans. Therefore, mutations that affect splicing are not evenly distributed across primary transcripts but are focussed in and around alternatively spliced exons with intermediate inclusion levels. These results provide a resource for prioritising synonymous and other variants as disease-causing mutations.
Data availability
Raw sequencing data have been submitted to GEO with accession number GSE151942. All scripts used in this study are available at https://github.com/lehner-lab/Constitutive_Exons.
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Mutations primarily alter the inclusion of alternatively spliced exonsNCBI Gene Expression Omnibus, GSE151942.
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The Complete Local Genotype-Phenotype Landscape for the Alternative Splicing of a Human ExonEuropean Nucleotide Archive (accession code PRJEB13140).
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Saturation mutagenesis reveals manifold determinants of exon definitionNCBI Gene Expression Omnibus (accession code GSE105785).
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Genetic effects on gene expression across human tissues (genotype matrix file GTEx_Analysis_2016-01-15_v7_WholeGenomeSeq_635Ind_PASS_AB02_GQ20_HETX_MISS15_PLINKQC.vcf.gz)NCBI database of Genotypes and Phenotypes (dbGaP accession code phs000424.v7.p2).
Article and author information
Author details
Funding
ERC (ERC 616434)
- Ben Lehner
ERC (ERC 670146)
- Belen Minana
Ministerio de Economía y Competitividad (BFU2017-89488-P)
- Ben Lehner
Ministerio de Economía y Competitividad (BFU 2017 89308-P)
- Juan Valcarcel
Banco Santander (Fundación Botín)
- Juan Valcarcel
Fondation Bettencourt Schueller (Liliane Bettencourt Prize for Life Sciences)
- Ben Lehner
Ministerio de Economía y Competitividad (Severo Ochoa PhD fellowship)
- Pablo Baeza-Centurion
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Chris P Ponting, University of Edinburgh, United Kingdom
Publication history
- Received: June 12, 2020
- Accepted: October 27, 2020
- Accepted Manuscript published: October 28, 2020 (version 1)
- Version of Record published: November 18, 2020 (version 2)
Copyright
© 2020, Baeza-Centurion et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Computational and Systems Biology
- Genetics and Genomics
Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and mature MAPT mRNA structures in cells. We used these data to estimate Boltzmann suboptimal structural ensembles, which were then analyzed to predict consequences of mutations on pre-mRNA structure. Further analysis of recent cryo-EM structures of the spliceosome at different stages of the splicing cycle revealed that the footprint of the Bact complex with pre-mRNA best predicted alternative splicing outcomes for exon 10 inclusion of the alternatively spliced MAPT gene, achieving 74% accuracy. We further developed a β-regression weighting framework that incorporates splice site strength, RNA structure, and exonic/intronic splicing regulatory elements capable of predicting, with 90% accuracy, the effects of 47 known and 6 newly discovered mutations on inclusion of exon 10 of MAPT. This combined experimental and computational framework represents a path forward for accurate prediction of splicing-related disease-causing variants.
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- Cell Biology
- Genetics and Genomics
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