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This Week in Nucleic Acids Research: Jan 17, 2018

A team of Polish researchers describes a new tool they have developed called PlasFlow that can identify bacterial plasmid sequences from environmental samples. With assembled metagenomes as its input, the tool uses a neural network approach to uncover and identify plasmid sequences without having to know anything about the samples' taxonomical or functional composition. According to the researchers, their tool could reach an accuracy of 96 percent and performed better on the test datasets than other available tools.

Researchers from the US and Sweden used long-read sequencing to assemble the genome of the Saccharomyces cerevisiae strain CEN.PK113-7D. They sequenced its genome using both Oxford Nanopore and Pacific Biosciences platforms and then assembled those sequences using MinIon reads only, PacBio reads only, and both MinIon and PacBio reads. Illumina short reads were used in each instance for error correction. Such a long-read approach enabled them to assemble all 16 main yeast chromosomes in one step and, when they compared this strain to the reference, identify chromosomal rearrangements. The researchers further report uncovering full-length transcripts using Oxford Nanopore's direct RNA sequencing approach.

Researchers from Harbin Medical University in China used a computational approach to tie together lncRNAs and the genes whose transcription they affect in multiple cancer types. By applying this approach to 20 cancer types, the researchers developed what they've dubbed a LncRNA Modulator Atlas in Pan-cancer (LncMAP). From this, they uncovered wide heterogeneity among the types of cancer, but also found lncRNA modulators that affect multiple cancer types. "Our study provides a systems-level dissection of lncRNA-mediated regulatory perturbations in cancer, and also presents a valuable tool and resource for investigating the function of lncRNAs in cancer," the researchers wrote.