A human commons cell atlas reveals cell type specificity for OAS1 isoforms

Creators: Galvez-Merchán, Ángel; Booeshaghi, A. Sina; Pachter, Lior¹

1. California Institute of Technology

Abstract

We describe an open source Human Commons Cell Atlas comprising 2.9 million cells across 27 tissues that can be easily updated and that is structured to facilitate custom analyses. To showcase the flexibility of the atlas, we demonstrate that it can be used to study isoforms of genes at cell resolution. In particular, we study cell type specificity of isoforms of OAS1, which has been shown to offer SARS-CoV-2 protection in certain individuals that display higher expression of the p46 isoform. Using our commons cell atlas we localize the OAS1 p44b isoform to the testis, and find that it is specific to round and elongating spermatids. By virtue of enabling customized analyses via a modular and dynamic atlas structure, the commons cell atlas should be useful for exploratory analyses that are intractable within the rigid framework of current gene-centric cell atlases.

Copyright and License

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

Acknowledgement

We thank Tara Chari for assistance in producing Figure 1A. The authors acknowledge the Howard Hughes Medical Institute for funding A.S.B. through the Hanna H. Gray Fellows program. Thanks to the Caltech Bioinformatics Resource Center for assisting with pre-processing the data.

Contributions

The CCA atlas concept emerged from an initiative by ASB to uniformly preprocess the datasets in (Svensson, da Veiga Beltrame, and Pachter 2020). ÁGM conceived of the idea of examining the OAS1 isoforms at single-cell resolution across human tissues after the publication of (Zhou et al. 2021). ASB conceived the CCA structure and associated mx toolkit. ÁGM pre-processed the CCA datasets, and ASB wrote mx. ÁGM and ASB developed the CCA quality control. ÁGM led the OAS1 analysis, with help from ASB and LP. ASB developed the ‘mx assign’ cell assignment approach, and ÁGM and ASB benchmarked it. ÁGM drafted the initial version of the manuscript, which was edited and reviewed by all authors.

Data Availability

The code and data needed to reprocess the results of this manuscript can be found here https://github.com/pachterlab/GBP_2024/. The CCA GitHub can be found here https://github.com/cellatlas/human/. A summary of the datasets in the CCA can be found here https://cellatlas.github.io/human/.

Code Availability