Mutations primarily alter the inclusion of alternatively spliced exons

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Data availability
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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.

The following data sets were generated

(2020) Mutations primarily alter the inclusion of alternatively spliced exons
NCBI Gene Expression Omnibus, GSE151942.

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151942

The following previously published data sets were used

(2016) The Complete Local Genotype-Phenotype Landscape for the Alternative Splicing of a Human Exon
European Nucleotide Archive (accession code PRJEB13140).

https://www.ebi.ac.uk/ena/data/view/PRJEB13140
(2018) Saturation mutagenesis reveals manifold determinants of exon definition
NCBI Gene Expression Omnibus (accession code GSE105785).

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE105785
(2018) Decoding a cancer-relevant splicing decision in the RON proto-oncogene using high-throughput mutagenesis (Supplementary Data 3)
N/A.

https://www.nature.com/articles/s41467-018-05748-7
(2019) High-throughput analysis revealed mutations' diverging effects on SMN1 exon 7 splicing (Supplementary Table 1)
N/A.

https://www.tandfonline.com/doi/full/10.1080/15476286.2019.1630796
1. Cheung R
2. Insigne KD
3. Yao D
4. Burghard CP
5. Wang J
6. Hsiao Y-H E
7. Jones EM
8. Goodman DB
9. Xiao X
10. Kosuri S
(2019) A Multiplexed Assay for Exon Recognition Reveals that an Unappreciated Fraction of Rare Genetic Variants Cause Large-Effect Splicing Disruptions (SRE Library)
Github (KosuriLab/MFASS).

https://github.com/KosuriLab/MFASS/blob/master/processed_data/sre/sre_data_clean.txt
1. Cheung R
2. Insigne KD
3. Yao D
4. Burghard CP
5. Wang J
6. Hsiao Y-H E
7. Jones EM
8. Goodman DB
9. Xiao X
10. Kosuri S
(2019) A Multiplexed Assay for Exon Recognition Reveals that an Unappreciated Fraction of Rare Genetic Variants Cause Large-Effect Splicing Disruptions (SNV Library)
Github (KosuriLab/MFASS).

https://github.com/KosuriLab/MFASS/blob/master/processed_data/snv/snv_data_clean.txt
(2018) Vex-seq: high-throughput identification of the impact of genetic variation on pre-mRNA splicing efficiency
Github (scottiadamson/Vex-seq).

https://github.com/scottiadamson/Vex-seq/blob/master/processed_files/delta_PSI_values.tsv
1. GTEx Consortium
(2017) Genetic effects on gene expression across human tissues (junction read counts file GTEx_Analysis_2016-01-15_v7_STARv2.4.2a_junctions.gct.gz)
GTEx Portal.

https://www.gtexportal.org/home/datasets
1. GTEx Consortium
(2017) 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).

https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v7.p2
(2011) Quantitative evaluation of all hexamers as exonic splicing elements (Supplementary Table 1)
N/A.

https://genome.cshlp.org/content/21/8/1360

Article and author information

Author details

Pablo Baeza-Centurion

Systems Biology, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain

Competing interests
No competing interests declared.
Belen Minana

Gene Regulation, Stem cells and Cancer, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain

Competing interests
No competing interests declared.
Juan Valcarcel

Systems Biology, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain

For correspondence
juan.valcarcel@crg.eu

Competing interests
Juan Valcarcel, Reviewing editor, eLife.
Ben Lehner

Systems Biology, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain

For correspondence
ben.lehner@crg.eu

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0002-8817-1124

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.

Copyright

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.