Title |
Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms
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Published in |
PLOS ONE, October 2012
|
DOI | 10.1371/journal.pone.0048745 |
Pubmed ID | |
Authors |
Sara Kangaspeska, Susanne Hultsch, Henrik Edgren, Daniel Nicorici, Astrid Murumägi, Olli Kallioniemi |
Abstract |
RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts. |
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Country | Count | As % |
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United States | 3 | 33% |
France | 2 | 22% |
Peru | 1 | 11% |
Germany | 1 | 11% |
Montenegro | 1 | 11% |
Canada | 1 | 11% |
Demographic breakdown
Type | Count | As % |
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Scientists | 5 | 56% |
Members of the public | 3 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 1% |
France | 1 | 1% |
Norway | 1 | 1% |
Italy | 1 | 1% |
United Kingdom | 1 | 1% |
Singapore | 1 | 1% |
Unknown | 69 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 22 | 29% |
Researcher | 17 | 23% |
Student > Master | 11 | 15% |
Student > Bachelor | 8 | 11% |
Professor > Associate Professor | 4 | 5% |
Other | 8 | 11% |
Unknown | 5 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 33 | 44% |
Biochemistry, Genetics and Molecular Biology | 17 | 23% |
Computer Science | 7 | 9% |
Medicine and Dentistry | 7 | 9% |
Engineering | 4 | 5% |
Other | 1 | 1% |
Unknown | 6 | 8% |