Barnacle: Detecting and Characterizing Tandem Duplications and Fusions in Transcriptome Assemblies

Peer reviewed: 
Yes, item is peer reviewed.
Scholarly level: 
Faculty/Staff
Final version published as: 

BMC Genomics 2013, 14:550 doi:10.1186/1471-2164-14-550

Date created: 
2013
Keywords: 
Transcriptome assembly
Chimeric transcripts
Fusion
Partial tandem duplication
PTD
Internal tandem duplication
ITD
RNA-seq
Transcriptome
Abstract: 

Background

Chimeric transcripts, including partial and internal tandem duplications (PTDs, ITDs) and gene fusions, are important in the detection, prognosis, and treatment of human cancers.

Results

We describe Barnacle, a production-grade analysis tool that detects such chimeras in de novo assemblies of RNA-seq data, and supports prioritizing them for review and validation by reporting the relative coverage of co-occurring chimeric and wild-type transcripts. We demonstrate applications in large-scale disease studies, by identifying PTDs in MLL, ITDs in FLT3, and reciprocal fusions between PML and RARA, in two deeply sequenced acute myeloid leukemia (AML) RNA-seq datasets.

Conclusions

Our analyses of real and simulated data sets show that, with appropriate filter settings, Barnacle makes highly specific predictions for three types of chimeric transcripts that are important in a range of cancers: PTDs, ITDs, and fusions. High specificity makes manual review and validation efficient, which is necessary in large-scale disease studies. Characterizing an extended range of chimera types will help generate insights into progression, treatment, and outcomes for complex diseases.

Language: 
English
Document type: 
Article
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