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 manuscript 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 496:2GB of aligned RNA-seq SAM files to 410MB 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 dataset, 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 UTR. Our results highlight the usefulness of transcript+proteomic integration for improved genome annotations.
Woo S, Cha SW, Merrihew G, He Y, Castellana N, Guest CC, McCoss M, Bafna V. (2013) Proteogenomic database construction driven from large scale RNA-seq data. J Proteome Res [Epub ahead of print]. [abstract]
Proteogenomic database construction driven from large scale RNA-seq data is a post from: RNA-Seq Blog