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This Week in Nucleic Acids Research: Oct 16, 2013

A team from the Translational Genomics Research Institute and the Cancer Treatment Centers of America present on a strategy and sample preparation protocol for characterizing copy number profiles and finding translocations in tumor samples with the help of long-insert whole-genome sequencing — a scheme that they demonstrated using matched tumor-normal samples from individuals with several cancer types. By doing shallow sequencing on genomic libraries containing some 900 base to 1,000 base inserts, the study's authors say, it's possible to pick up copy number and translocation patterns with more limited sequencing than that required when using inserts in the 300 base to 400 base pair range.

For another Nucleic Acids Research study, researchers from the Seattle Children's Research Institute and the University of Washington introduce two new reporter systems for tracking genome editing events. The methods focus on assessing transcriptional activity and single-strand annealing, respectively, at specific loci during genome editing. As such, the new "Active/Repressed," or AR-TLR, and "Single-Strand Annealing," or SSA-TLR, and intended to complement the fluorescent Traffic Light Reporter approach that members of the team developed previously to delve into the DNA repair processes at play when endonuclease enzymes chop up DNA at targeted sites.

The University of Nottingham's Conrad Nieduszynski and colleagues describe the approaches they used to track genome replication dynamics in Saccharomyces cerevisiae. Along with methods that involved synchronizing yeast cells, for example, the team also turned to a Sort-seq method for assessing asynchronous cells as well as a "marker frequency analysis," or MFA, method that uses increasing sequencing depths to determine replication dynamics. "[W]ith current sequencing costs, we prefer approaches that enrich for cells undergoing genome replication," study authors write. "However, we foresee that direct sequencing of DNA samples from exponentially growing cells might become the most appropriate approach as sequencing costs decrease and read numbers increase."