DocumentCode
28837
Title
MMBIRFinder: A Tool to Detect Microhomology-Mediated Break-Induced Replication
Author
Segar, Matthew W. ; Sakofsky, Cynthia J. ; Malkova, Anna ; Yunlong Liu
Author_Institution
Sch. of Med., Center for Comput. Biol. & Bioinf., Indiana Univ., Indianapolis, IN, USA
Volume
12
Issue
4
fYear
2015
fDate
July-Aug. 1 2015
Firstpage
799
Lastpage
806
Abstract
The introduction of next-generation sequencing technologies has radically changed the way we view structural genetic events. Microhomology-mediated break-induced replication (MMBIR) is just one of the many mechanisms that can cause genomic destabilization that may lead to cancer. Although the mechanism for MMBIR remains unclear, it has been shown that MMBIR is typically associated with template-switching events. Currently, to our knowledge, there is no existing bioinformatics tool to detect these template-switching events. We have developed MMBIRFinder, a method that detects template-switching events associated with MMBIR from whole-genome sequenced data. MMBIRFinder uses a half-read alignment approach to identify potential regions of interest. Clustering of these potential regions helps narrow the search space to regions with strong evidence. Subsequent local alignments identify the template-switching events with single-nucleotide accuracy. Using simulated data, MMBIRFinder identified 83 percent of the MMBIR regions within a five nucleotide tolerance. Using real data, MMBIRFinder identified 16 MMBIR regions on a normal breast tissue data sample and 51 MMBIR regions on a triple-negative breast cancer tumor sample resulting in detection of 37 novel template-switching events. Finally, we identified template-switching events residing in the promoter region of seven genes that have been implicated in breast cancer.
Keywords
bioinformatics; cancer; genetics; genomics; macromolecules; pattern clustering; sequences; tumours; MMBIRFinder; genomic destabilization; half-read alignment approach; microhomology-mediated break-induced replication; next-generation sequencing technologies; normal breast tissue data sample; nucleotide tolerance; potential clustering regions; single-nucleotide accuracy; structural genetic events; subsequent local alignments; template-switching events; triple-negative breast cancer tumor sample; whole-genome sequenced data; Bioinformatics; Computational biology; DNA; Genomics; IEEE transactions; Sequential analysis; Biology and genetics; Life and Medical Sciences; life and medical sciences;
fLanguage
English
Journal_Title
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher
ieee
ISSN
1545-5963
Type
jour
DOI
10.1109/TCBB.2014.2359450
Filename
6948337
Link To Document