A University of California, San Francisco- and Berkeley-led team presents a computational approach for inferring phylogenetic relationships from single-cell sequence data. The method, known as Cassiopeia, encompasses "a novel suite of three algorithms specifically aimed at reconstructing large phylogenies from lineage tracing experiments with special consideration for the Cas9-mutagenesis process and missing data," the researchers say. They presented Cassiopeia in combination with related algorithm assessment and lineage tracing simulation framework to compare the tool to other algorithms, as well as experimental lineage tracing data spanning almost 34,600 cells from 11 clonal populations that were followed over time. "We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes," the authors report, "and provide insight into the principles for the design of improved Cas9-enabled [target site] recorders."
Researchers from the University of Sydney, the Westmead Institute for Medical Research, and other centers in Australia and Denmark describe a metagenomic classification pipeline, designed to identify and classify both prokaryotic and eukaryotic representatives in a given microbial community based on metagenomic sequence data. The tool — known as "ConClave-based Metagenomics," or CCMetagen — hinges on the existing ConClave read sorting and mapping method, the team notes, and appears to compare favorably to other metagenomic software when it comes to uncovering microbial community members from both bacterial and fungal groups, the authors suggest. "We expect that a range of novel ecological and evolutionary insights will be obtained as information about microbial eukaryotes in metagenomic studies becomes more accessible," they write.
Finally, a team from the Chinese Academy of Sciences share a database that brings together circular RNA, or circRNA, data gleaned from nearly 1,100 RNA sequence datasets spanning 19 tissue types and half a dozen vertebrate species. The resulting collection, contained online in the so-called CircAtlas, currently contains more than a million circRNAs, the researchers report, along with some additional accompanying expression, functional, and conservation information. Together, they say, "the circAtlas can serve as a comprehensive functional circRNA resource to efficiently browse, annotate, and prioritize the circRNAs and provide insights into their conservation and functions."