@article{eb9b8b604b544ea196454fef7efdafef,
title = "Delineating COVID-19 immunological features using single-cell RNA sequencing",
abstract = "Understanding the molecular mechanisms of coronavirus disease 2019 (COVID-19) pathogenesis and immune response is vital for developing therapies. Single-cell RNA sequencing has been applied to delineate the cellular heterogeneity of the host response toward COVID-19 in multiple tissues and organs. Here, we review the applications and findings from over 80 original COVID-19 single-cell RNA sequencing studies as well as many secondary analysis studies. We describe that single-cell RNA sequencing reveals multiple features of COVID-19 patients with different severity, including cell populations with proportional alteration, COVID-19-induced genes and pathways, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in single cells, and adaptation of immune repertoire. We also collect published single-cell RNA sequencing datasets from original studies. Finally, we discuss the limitations in current studies and perspectives for future advance.",
author = "Wendao Liu and Johnathan Jia and Yulin Dai and Wenhao Chen and Guangsheng Pei and Qiheng Yan and Zhongming Zhao",
note = "Funding Information: The authors thank all the members in the Bioinformatics and Systems Medicine Laboratory (BSML) for valuable discussion and help, especially Dr. Hyun-Hwan Jeong who helped create Table S4 . We thank the three reviewers whose comments helped improve the manuscript. We also thank those investigators who generated the scRNA-seq data for COVID-19 studies. We are sorry for those related studies that we were not able to include in this review article due to our limited search function and space. The diagrams were created with Biorender.com . Z.Z. was partially supported by National Institutes of Health grants ( R01LM012806 , R01DE030122 , and R01DE029818 ) and Cancer Prevention and Research Institute of Texas (CPRIT RP180734 and RP210045 ). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Funding for open access charge: CPRIT (RP180734). Publisher Copyright: {\textcopyright} 2022 The Author(s)",
year = "2022",
month = sep,
day = "13",
doi = "10.1016/j.xinn.2022.100289",
language = "English (US)",
volume = "3",
pages = "100289",
journal = "The Innovation",
issn = "2666-6758",
publisher = "Cell Press",
number = "5",
}