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Nucleic Acids Research Papers Present Tool to Estimate Hi-C Library Resolution, Chimeric Mutator Protein, More

A team from US National Eye Institute has developed a new tool to estimate the genomic resolution of Hi-C libraries. The team, led by Anand Swaroop of NEI, write in Nucleic Acids Research that they aimed to answer one of the first questions of conducting a Hi-C analysis: "How deep do I need to sequence my Hi-C library?" Their tool, dubbed HiCRes, accounts for the complexity of the Hi-C library, the portion of uniquely mapped read pairs, and the distribution of those read pairs within its pipeline to estimate the resolution that a Hi-C library can reach at different sequencing depths. They further validated their tool on various combinations of restriction enzymes, species, and cell types. "We demonstrate that HiCRes accurately predicts the resolution of Hi-C libraries obtained from distinct human and mouse cell types generated using different restriction digestion enzymes," the team writes.

A trio of researchers from Seoul National University has developed a new mutator for in vivo mutagenesis. As they report in Nucleic Acids Research, their MutaEco mutator protein increases the mutation rate to enable adaptive laboratory evolution in Escherichia coli without decreasing cell viability. Adaptive laboratory evolution, the researchers note, is a key tool for the study of the molecular mechanisms behind how cells change. In particular, they formed their chimeric mutator protein by fusing a cytidine deaminase to the α-subunit of the E. coli RNA polymerase. "This fusion strategy is expected to accommodate diverse DNA-modifying enzymes and may be easily adapted to various bacterial species," the researchers add.

With their Personal Access to Genome & Analysis of Natural Traits (PAGENT) tool, an international team of researchers aims to provide a third party, publicly available tool for genomic interpretation. The tool encompasses five core modules: quality control of the genetic report, qualitative assessment of genetic characteristics, quantitative assessment of health risks based on polygenic risk scores, querying databases, and a QR code generator for variants of interest. "Overall, PAGEANT represents a new, publicly available tool for third party genetic interpretation, that is totally transparent in its functionalities," the researchers write, adding that "the source code provided can be used for direct customization by the user and to expand the general knowledge about the 'secrets' behind DTC genetic testing results interpretation."