A team from the US, Russia, and China describes a database containing information on somatic mutations found in normal human tissues. The SomaMutDB currently contains information on more than 2.4 million single nucleotide variants and 120,000 million small insertions and deletions found in some two dozen studies focused on a range of sample types from hundreds of individuals, the researchers say, and span 19 normal tissue or cell types. This collection is accompanied by tools for searching, viewing, and analyzing the data, they note, including half a dozen tools for analyzing mutational signatures. The authors argue that "such an integrated resource will prove valuable for understanding somatic mutations and their possible role in human aging and age-related diseases."
Researchers at BGI-Shenzhen, the University of Chinese Academy of Sciences, and elsewhere shares a database called VThunter for digging into viral receptor-related expression signatures using single-cell RNA sequencing data. By applying its analytical pipeline to more than 2.1 million individual cells from almost four dozen animal species analyzed by scRNA-seq for hundreds of prior studies, for example, the team tracked down more than 100 viral receptors for 142 viruses, while getting a look at related expression signatures in infected host cells. "Information on viral receptor expression signatures is fundamental for understanding the molecular mechanisms underlying host infection by viruses," the authors write, explaining that "we also developed a comprehensive and user-friendly database, name VThunter, to ensure that the curated data were publicly available and could be easily utilized."
Finally, a Harbin Medical University, Harbin Institute of Technology, and Peking Union Medical College team presents a collection of single-cell data representing SARS-CoV-2 responses in 10 human tissue types. Along with a related analytical pipeline, the SCovid database currently contains scRNA-seq profiles for more than 1 million individual cells from COVID-19 cases and controls characterized in 21 available datasets, the researchers note, highlighting thousands of differentially expressed or stable genes in the human tissues considered. "[W]e developed SCovid, a single-cell atlas for exposing molecular characteristics of COVID-19 across 10 human tissues," they report, noting that "we will focus … on the latest data and construct unified analysis pipelines, so as to continuously update our database."