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

Authors

Coby Viner, University of Western OntarioFollow
Stephanie Dorman, University of Western OntarioFollow
Ben Shirley, Cytognomix IncFollow
Peter Rogan, The University of Western OntarioFollow

Document Type

Article

Publication Date

Winter 1-13-2014

Journal

F1000Research

Volume

3

First Page

8

URL with Digital Object Identifier

http://f1000research.com/articles/3-8/v1

Abstract

Interpretation of variants present in complete genomes or exomes reveals numerous sequence changes, only a fraction of which are likely to be pathogenic. Mutations have been traditionally inferred from allele frequencies and inheritance patterns in such data. Variants predicted to alter mRNA splicing can be validated by manual inspection of transcriptome sequencing data, however this approach is intractable for large datasets. These abnormal mRNA splicing patterns are characterized by reads demonstrating either exon skipping, cryptic splice site use, and high levels of intron inclusion, or combinations of these properties. We present, Veridical, an in silico method for the automatic validation of DNA sequencing variants that alter mRNA splicing. Veridical performs statistically valid comparisons of the normalized read counts of abnormal RNA species in mutant versus non-mutant tissues. This leverages large numbers of control samples to corroborate the consequences of predicted splicing variants in complete genomes and exomes.

Notes

doi: 10.12688/f1000research.3-8.v1

Citation of this paper:

Viner C, Dorman SN, Shirley BC and Rogan PK (2014) Validation of predicted mRNA splicing mutations using high-throughput transcriptome data [v1; ref status: indexed, http://f1000r.es/2no] F1000Research 2014, 3:8 (doi: 10.12688/f1000research.3-8.v1)