Proteogenomic Database Construction Driven from Large Scale RNA-seq Data.

TitleProteogenomic Database Construction Driven from Large Scale RNA-seq Data.
Publication TypeJournal Article
Year of Publication2013
AuthorsWoo S, Cha S W, Merrihew G, He Y, Castellana N, Guest C, Maccoss M, Bafna V
JournalJ Proteome Res
Date Published2013 Jul 17
ISSN1535-3907
Abstract

The advent of inexpensive RNA-seq technologies and other deep sequencing technologies for RNA has the promise to radically improve genomic annotation, providing information on transcribed regions and splicing events in a variety of cellular conditions. Using MS-based proteogenomics, many of these events can be confirmed directly at the protein level. However, the integration of large amounts of redundant RNA-seq data and mass spectrometry data poses a challenging problem. Our paper addresses this by construction of a compact database that contains all useful information expressed in RNA-seq reads. Applying our method to cumulative C. elegans data reduced 496.2 GB of aligned RNA-seq SAM files to 410 MB of splice graph database written in FASTA format. This corresponds to 1000× compression of data size, without loss of sensitivity. We performed a proteogenomics study using the custom data set, using a completely automated pipeline, and identified a total of 4044 novel events, including 215 novel genes, 808 novel exons, 12 alternative splicings, 618 gene-boundary corrections, 245 exon-boundary changes, 938 frame shifts, 1166 reverse strands, and 42 translated UTRs. Our results highlight the usefulness of transcript + proteomic integration for improved genome annotations.

DOI10.1021/pr400294c
PubMed URLhttp://www.ncbi.nlm.nih.gov/pubmed/23802565?dopt=Abstract
PMCPMC4034692
Alternate JournalJ. Proteome Res.
PubMed ID23802565