Investigators at New York University, the New York Genome Center, and elsewhere present a "weighted-nearest neighbor" (WNN) framework for analyzing multimodal single-cell genomic data. The method is meant to weigh the "relative utility" of multiple sequence, chromatin accessibility, epigenetic, and other regulatory data types from individual cells before bringing such multimodal data types together in an integrated analysis. The team applied this WNN approach to CITE-seq single-cell cell surface protein marker, expression, and other data for some 211,000 individual human peripheral blood mononuclear cells, getting a look at lymphoid cell subpopulations responding to more than 200 antibodies. With this reference atlas, the authors suggest, it is possible to "rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19)."
In a Cell preprint article, investigators from the Shandong First Medical University and Shandong Academy of Medical Sciences describe dozens of coronavirus genomes detected in samples from bats in China's Yunnan province from the spring of 2019 to November of 2020, including several previously undescribed viruses related to SARS-CoV or SARS-CoV-2. For their study, the team did meta-transcriptomic sequencing on more than 400 bat feces, oral swab, or urine samples, generating 24 full-length genome sequences from new and known coronaviruses. That set included three viruses resembling SARS-CoV and four SARS-CoV-2-related viruses, with a virus dubbed RpYN06 from the Rhinolophus pusillus bat showing the closest phylogenetic ties to SARS-CoV-2, albeit with a distinct spike protein-coding gene sequence. In addition, the authors say, the results "reveal more of the diversity and complex evolutionary history of these [bat-borne coronaviruses], including both cross-species transmission and genomic recombination."
Finally, members of the International MetaSUB Consortium outline microbial community and antibiotic resistance features found on mass transit systems, sampling sites in dozens of cities around the world over three years. With trillions of bases of sequence data spanning more than 4,700 metagenomic samples collected for a pilot study from 2015 to 2016 or on specific global sampling days in 2016 and 2017, the team tracked down sequences representing new and known viruses, archaea, CRISPR arrays, and bacteria, while defining core components of urban microbiomes and more flexible features across the urban "pan-microbiome." "Profiles of [antimicrobial resistance] genes varied widely in type and density across cities," the authors report. "Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences."