Publication in PLOS Describes New Method for RNA Transcript Mapping Including New Suffix Array Algorithm
CARLSBAD, Calif. – April 5, 2011 – -- Life Technologies Corporation today announced that company scientists, in collaboration with Indiana University School of Medicine researchers, published study results indicating the utility of RNA-Seq mapping to detect gene fusions in cancer cells.
The study, titled “RNA-Seq Mapping and Detection of Gene Fusions with a Suffix Array Algorithm,” was published on April 5 in PLOS, the Public Library of Science (www.plos.org).
Advances in sequencing technology are enabling detailed characterization of RNA transcripts from biological samples, but the fundamental challenge of accurately mapping reads and gleaning biological meaning from the data remains. One class of transcripts, gene fusions, is particularly important in cancer. For example, 95% of patients with clinical chronic myeloid leukemia (CML) express the BCR-ABL gene fusion in their leukemia cells due to a reciprocal translocation between the long arms of chromosomes 9 and 22. BCR-ABL is also found to be a factor in 30% to 50% of adult acute lymphoblastic leukemia cases. Fusion genes are thought to cause tumorigenesis by over-activating proto-oncogenes, deactivating tumor suppressors, or altering the regulation and/or splicing of other genes which lead to defects in key signaling pathways.
In the current study, the investigators used Life Technologies’ RNA-Seq to describe a new method enabling detection of fusions in cancer cell lines. The method includes a new algorithm to find fusion breakpoints.
“This new algorithm, called SASR (Suffix Array Splice Read mapping), makes it easier to detect reads that span fusion junctions,” said Onur Sakarya, first author on the study and a senior scientist with Life Technologies’ Ion Bioinformatics group.
"The SASR algorithm described in this publication provides a novel unbiased approached to gene fusion and splicing discovery. This method will greatly increase the sensitivity and specificity of junction detection compared to current methods and allow researchers to harness more data from their RNA-sequencing projects," said Milan Radovich, Ph.D., a collaborator on the study and assistant research professor of surgery at the Indiana University School of Medicine in Indianapolis.
Life Tech co-authors include: Heinz B. Breu, Yongzhi Chen, Yulei N. Wang, Catalin Barbacioru, Sowni Utiramerur, Penn P. Whitley, Joel P. Brockman, Paolo Vatta, Zheng Zhang, Liviu Popescu, Matthew W. Muller, Vidya Kudlingar, Nriti Garg, Chieh-Yuan Li, Benjamin S. Kong, John P. Bodeau, Robert C. Nutter, Jian Gu, Kelli S. Bramlett, Jeffrey K. Ichikawa, Fiona C. Hyland and Asim S. Siddiqui.
The published paper is available at:
RNA-Seq is available for Research Use Only; Not for diagnostic use.
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Life Technologies ContactSuzanne Clancy