Chimeric transcript discovery by paired-end transcriptome sequencing
Author(s) -
Christopher A. Maher,
Nallasivam Palanisamy,
J. Chad Brenner,
Xuhong Cao,
Shanker KalyanaSundaram,
Shujun Luo,
Irina Khrebtukova,
Terrence R. Barrette,
Catherine S. Grasso,
Jindan Yu,
Robert J. Lonigro,
Gary P. Schroth,
Chandan KumarSinha,
Arul M. Chinnaiyan
Publication year - 2009
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0904720106
Subject(s) - biology , transcriptome , computational biology , gene , genetics , fusion gene , deep sequencing , dna sequencing , gene expression , genome
Recurrent gene fusions are a prevalent class of mutations arising from the juxtaposition of 2 distinct regions, which can generate novel functional transcripts that could serve as valuable therapeutic targets in cancer. Therefore, we aim to establish a sensitive, high-throughput methodology to comprehensively catalog functional gene fusions in cancer by evaluating a paired-end transcriptome sequencing strategy. Not only did a paired-end approach provide a greater dynamic range in comparison with single read based approaches, but it clearly distinguished the high-level "driving" gene fusions, such as BCR-ABL1 and TMPRSS2-ERG, from potential lower level "passenger" gene fusions. Also, the comprehensiveness of a paired-end approach enabled the discovery of 12 previously undescribed gene fusions in 4 commonly used cell lines that eluded previous approaches. Using the paired-end transcriptome sequencing approach, we observed read-through mRNA chimeras, tissue-type restricted chimeras, converging transcripts, diverging transcripts, and overlapping mRNA transcripts. Last, we successfully used paired-end transcriptome sequencing to detect previously undescribed ETS gene fusions in prostate tumors. Together, this study establishes a highly specific and sensitive approach for accurately and comprehensively cataloguing chimeras within a sample using paired-end transcriptome sequencing.
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