Introducing COCOS: codon consequence scanner for annotating reading frame changes induced by stop-lost and frame shift variants.

TitleIntroducing COCOS: codon consequence scanner for annotating reading frame changes induced by stop-lost and frame shift variants.
Publication TypeJournal Article
Year of Publication2017
AuthorsButkiewicz M, Haines JL, Bush WS
JournalBioinformatics
Volume33
Issue10
Pagination1561-1562
Date Published2017 May 15
ISSN1367-4811
KeywordsCodon, Frameshift Mutation, Genomics, Humans, INDEL Mutation, Reading Frames, Sequence Analysis, DNA, Sequence Analysis, Protein, Software
Abstract

Summary: Reading frame altering genomic variants can impact gene expression levels and the structure of protein products, thus potentially inducing disease phenotypes. Current annotation approaches report the impact of such variants in the context of altered DNA sequence only; attributes of the resulting transcript, reading frame and translated protein product are not reported. To remedy this shortcoming, we present a new genetic annotation approach termed Codon Consequence Scanner (COCOS). Implemented as an Ensembl variant effect predictor (VEP) plugin, COCOS captures amino acid sequence alterations stemming from variants that produce an altered reading frame, such as stop-lost variants and small insertions and deletions (InDels). To highlight its significance, COCOS was applied to data from the 1000 Genomes Project. Transcripts affected by stop-lost variants introduce a median of 15 amino acids, while InDels have a more extensive impact with a median of 66 amino acids being incorporated. Captured sequence alterations are written out in FASTA format and can be further analyzed for impact on the underlying protein structure.Availability and Implementation: COCOS is available to all users on github: https://github.com/butkiem/COCOS.Contact: mariusz.butkiewicz@case.edu.

DOI10.1093/bioinformatics/btw820
Alternate JournalBioinformatics
PubMed ID28122779
PubMed Central IDPMC5423451
Grant ListU01 AG032984 / AG / NIA NIH HHS / United States
UF1 AG047133 / AG / NIA NIH HHS / United States