Accurately Predicting Double-Strand Breaks Using Public Genetic Databases
Double-strand breaks (DSBs) cause chromosomal rearrangements, such as deletions, translocations, and fusions of DNA . This results in a host of issues with cellular function, making it important to map where DSBs can occur in the genome. Mourad et al used public data on the epigenome, chromatin structure, DNA motifs, and DNA shape to computationally predict DSBs at a resolution lower than 1 kb.
The authors first tested if DSBs could be accurately predicted from epigenome marks, chromatin structure, and DNA motifs. Using public ChIP-seq  and DNase-seq  databases researchers were able to determine that DSBs were most enriched at DNase I hypersensitivity sites, H3H4 methylation, and CTCF marks. This highlights the importance of active chromatin and DNA damage response in predicting DSBs. Next, the authors tried to determine DSBs using DNA motifs and shape. Transcription factor binding sites were found to be good predictors of DSBs. These sites include activity for CTCF, p53, p63, and p73.
To show the versatility of these methods, Maurad et al used their prediction methods from NHEK cells in U2OS cells to determine if it translated accurately between cell types from the same species. NHEK trained DSB predictions in U2OS cells were only slightly less precise than DSB predictions with methods derived in U2OS cells. The reliability of identical prediction methods across cell types indicates that DSBs follow similar patterns in different cell lines from the same species.
The above method uses epigenomic marks, chromatin structure, DNA motifs, and DNA shape to predict DSBs and is accurate at less than 1 kb even when only one or two marks are available. The use of public data allows this technique to be more cost efficient and easier to work with than other high-throughput methods available for DSB identification, making it a desirable tool for future research involving DSBs.
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