COVID-19 Integrated Analyses using Single Cell Data

Recently, we’ve been writing here about the work of the Viral Genomics group at Broad and how they’re using Terra to support their workflows for genome assembly and phylogenomic analysis of novel coronavirus (SARS-CoV-2) genomes recovered from patients.

Today, I’d like to share with you a project that focuses on the cells and organs in the human body that may be infected by the virus. With more information about the specific cell types that can be infected by the virus, researchers will be better able to generate hypotheses for transmission, pathogenesis, clinical associations, and therapeutics.

The Human Cell Atlas Lung Biological Network, including our colleagues at Broad’s Klarman Cell Observatory (KCO), recently shared a manuscript pre-print describing how they used millions of single-cell RNA-seq profiles from 25 tissues and organs to identify the cells likely to be infected with SARS-CoV-2 throughout the body, and the gene expression programs within those cells that could provide clues to disease mechanisms and therapies. The KCO conducted this work as part of a large international collaboration, including the Human Cell Atlas Lung Biological Network, the National Heart, Lung, and Blood Institute’s LungMap Consortium, and many more institutions.

Building upon previous research that identified specific genes that mediate SARS-CoV-2 infection, this work is important because it not only pinpoints specific types of cells that express potential mediators of infection, but also relates the level of expression of the viral entry genes in specific cell types to key factors that were associated with more severe COVID-19: age, sex, and smoking status.

The authors of the study wanted to ensure it was possible for others to build on their work by making all of the necessary data and code publicly available. They’ve published a Terra workspace containing a set of Jupyter notebooks that will allow researchers to reproduce many of the core analyses in their manuscript. The workspace’s Data section also contains metadata from a variety of organ and tissue samples that are necessary for the analysis (age, sex, or smoking status).

This will help researchers build upon the authors’ work by providing the clinical and biomedical research community with an efficient way to apply the consortium’s analysis to new data. Interested researchers can create their own copies of the workspace, upload their own data into their copy, and share their analysis with colleagues.

Additionally, our Single Cell Portal team has created a dedicated page to collect these new studies, with interactive visualizations of this data enabling gene query within cell types across many organs in the human body.

We hope these resources will be useful to those working on a solution to the current crisis. To get in touch with the authors of the study, please reach out to lung@humancellatlas.org

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