Proteogenomic database construction driven from large scale RNA-seq data.
J Proteome Res
; 13(1): 21-8, 2014 Jan 03.
Article
en En
| MEDLINE
| ID: mdl-23802565
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.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Genoma
/
Análisis de Secuencia de ARN
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Caenorhabditis elegans
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Proteoma
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Bases de Datos Genéticas
/
Bases de Datos de Proteínas
Límite:
Animals
Idioma:
En
Revista:
J Proteome Res
Asunto de la revista:
BIOQUIMICA
Año:
2014
Tipo del documento:
Article
País de afiliación:
Estados Unidos