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This Week in Nucleic Acids Research: Feb 13, 2019

Researchers from France and Italy describe microRNAs that appear to influence cell type transitions in triple-negative breast cancers (TNBC) lacking estrogen, progesterone, or HER2 receptors. Using a computational approach called "clustered miRNA master regulator analysis," or ClustMMRA, and breast cancer RNA and miRNA sequence data from the Cancer Genome Atlas project, the team searched for miRNAs associated with cancer features or molecular subtypes, leading to a set of experimentally validated miRNAs such as miR-199 that seemed to influence the epithelial-to-mesenchymal transition and cell proliferation in TNBC. "[O]ur computational pipeline and experimental validations characterize a new genomic cluster of miRNAs implicated in the TNBC phenotype that might be further explored in diagnosis and therapeutic strategies," they write.

A Duke University- and Zhejiang University-led team takes a look at oxidative DNA damage patterns in the yeast model organism Saccharomyces cerevisiae. The researchers relied on a combination of DNA sequencing and microarrays to map breakpoints in yeast cells exposed to hydrogen peroxide, grown under low-oxygen conditions, or treated with the antioxidant glutathione. Their results revealed an over-representation of gene conversions and crossover events under oxidative stress, along with point mutations, small insertions and deletions, and amplification of a gene coding for an enzyme related to hydrogen peroxide tolerance. On the other hand, low oxygen conditions or glutathione treatment showed potential ties to muted spontaneous recombination rates.

Finally, researchers from the University of British Columbia, the Vancouver Prostate Center, and elsewhere present a structural variant detection tool called SViCT, designed to pick up gene fusions, insertions, deletions, inversions, and other structural variant events in circulating, cell-free DNA with discordant read pair data, contig assembly, reference genome re-mapping, and additional algorithmic steps. The team applied the SViCT approach to simulated and real cfDNA datasets, uncovering new and known structural variants in circulating tumor DNA from eight individuals with metastatic, castration-resistant prostate cancer.