Genome-guided transcript assembly by integrative analysis of RNA sequence data
Research output: Contribution to journal › Article
Colleges, School and Institutes
- Department of Biostatistics, University of California at Berkeley, Berkeley, California, USA.
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
- 1] Department of Statistics, University of California at Berkeley, Berkeley, California, USA. .
- 1] Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California, USA. .
The identification of full length transcripts entirely from short-read RNA sequencing data (RNA-seq) remains a challenge in the annotation of genomes. Here we describe an automated pipeline for genome annotation that integrates RNA-seq and gene-boundary data sets, which we call Generalized RNA Integration Tool, or GRIT. Applying GRIT to Drosophila melanogaster short-read RNA-seq, cap analysis of gene expression (CAGE) and poly(A)-site-seq data collected for the modENCODE project, we recovered the vast majority of previously annotated transcripts and doubled the total number of transcripts cataloged. We found that 20% of protein coding genes encode multiple protein-localization signals and that, in 20-d-old adult fly heads, genes with multiple polyadenylation sites are more common than genes with alternative splicing or alternative promoters. GRIT demonstrates 30% higher precision and recall than the most widely used transcript assembly tools. GRIT will facilitate the automated generation of high-quality genome annotations without the need for extensive manual annotation.
|Number of pages||6|
|Early online date||16 Mar 2014|
|Publication status||Published - Apr 2014|
- Animals, Chromosome Mapping, Drosophila melanogaster, Genome, Insect, Genomics, Molecular Sequence Annotation, RNA, Sequence Analysis, RNA, Journal Article, Research Support, N.I.H., Extramural, Research Support, U.S. Gov't, Non-P.H.S.