A team from the University of California, San Diego, and elsewhere shares chromatin accessibility maps generated by single-cell chromatin profiling across dozens of adult human tissues. The chromatin accessibility atlas includes around 1.2 million apparent cis-regulatory elements identified in 222 cell types using sci-ATAC-seq-based chromatin accessibility profiling on 30 adult human tissues, the researchers report, along with available profiles for 15 fetal tissues and other published sci-ATAC-seq datasets. "We used these chromatin accessibility maps to delineate cell type-specificity of fetal and adult human [candidate cis-regulatory elements] and to systematically interpret the non-coding variants associated with complex human traits and diseases," they write. "This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues, life stages, and organ systems."
In a journal pre-proof article posted to Cell, researchers from the Harvard TH Chan School of Public Health use mathematical modeling to track the transmissibility and immune consequences of SARS-CoV-2 variants of concern — particularly variants linked to immune escape and/or higher-than-usual transmissibility rates — compared to wild type versions of SARS-CoV-2 in human populations. "We show that variants with enhanced transmissibility frequently increase epidemic severity, whereas those with partial immune escape fail to spread widely, or primarily cause reinfections and breakthrough infections," the authors report, adding that "when these phenotypes are combined, a variant can continue spreading even as immunity builds up in the population, limiting the impact of vaccination and exacerbating the epidemic."
Finally, a Johns Hopkins University team outlines a method that combines fluorescent biosensor barcoding with multiplexing and deep learning to tease apart cell signaling networks — an approach used to assess KRAS mutation effects and other tyrosine kinase signaling network interactions. The multiplexed method relies on barcoding proteins that generate fluorescence spanning a range of emission spectra, the investigators note, making it possible to read more than 100 barcodes distinct from conventional biosensor tags. "Mixtures of barcoded cells expressing different biosensors are simultaneously imaged and analyzed by deep learning models to achieve massively multiplexed tracking of signaling events," they write. "Importantly, different biosensors in cell mixtures show highly coordinated activities, thus facilitating the delineation of their temporal relationship."