Browsing by Author "Sakofsky, Cynthia J."

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    Break-Induced Replication and Genome Stability
    (MDPI, 2012-10-16) Sakofsky, Cynthia J.; Ayyar, Sandeep; Malkova, Anna; Biology, School of Science
    Genetic instabilities, including mutations and chromosomal rearrangements, lead to cancer and other diseases in humans and play an important role in evolution. A frequent cause of genetic instabilities is double-strand DNA breaks (DSBs), which may arise from a wide range of exogeneous and endogeneous cellular factors. Although the repair of DSBs is required, some repair pathways are dangerous because they may destabilize the genome. One such pathway, break-induced replication (BIR), is the mechanism for repairing DSBs that possesses only one repairable end. This situation commonly arises as a result of eroded telomeres or collapsed replication forks. Although BIR plays a positive role in repairing DSBs, it can alternatively be a dangerous source of several types of genetic instabilities, including loss of heterozygosity, telomere maintenance in the absence of telomerase, and non-reciprocal translocations. Also, mutation rates in BIR are about 1000 times higher as compared to normal DNA replication. In addition, micro-homology-mediated BIR (MMBIR), which is a mechanism related to BIR, can generate copy-number variations (CNVs) as well as various complex chromosomal rearrangements. Overall, activation of BIR may contribute to genomic destabilization resulting in substantial biological consequences including those affecting human health.
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    Break-Induced Replication is a Source of Mutation Clusters Underlying Kataegis
    (Elsevier B.V., 2014-06) Sakofsky, Cynthia J.; Roberts, Steven A.; Malc, Ewa; Mieczkowski, Piotr A.; Resnick, Michael A.; Gordenin, Dmitry A.; Malkova, Anna; Department of Biology, School of Science
    Clusters of simultaneous multiple mutations can be a source of rapid change during carcinogenesis and evolution. Such mutation clusters have been recently shown to originate from DNA damage within long single-strand (ss) DNA formed at resected double-strand breaks and dysfunctional replication forks. We identify here double-strand break (DSB)-induced replication (BIR) as another powerful source of mutation clusters that formed in nearly half of wild-type yeast cells undergoing BIR in the presence of alkylating damage. Clustered mutations were primarily formed along the track of DNA synthesis and were frequently associated with additional breakage and rearrangements. Moreover, the base specificity, strand coordination and strand bias of the mutation spectrum was consistent with mutations arising from damage in persistent ssDNA stretches within unconventional replication intermediates. Together, these features closely resemble kataegic events in cancers, suggesting that replication intermediates during BIR may be the most prominent source of mutation clusters across species.
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    MMBIRFinder: A Tool to Detect Microhomology-Mediated Break-Induced Replication
    (IEEE, 2015) Segar, Matthew W.; Sakofsky, Cynthia J.; Malkova, Anna; Liu, Yunlong; Department of Biohealth Informatics, School of Informatics and Computing
    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.