Single-cell screening of SARS-CoV-2 target cells in pets, livestock, poultry and wildlife

  1. Dongsheng Chen
  2. Jian Sun
  3. Jiacheng Zhu
  4. Xiangning Ding
  5. Tianming Lan
  6. Linnan Zhu
  7. Rong Xiang
  8. Peiwen Ding
  9. Haoyu Wang
  10. Xiaoling Wang
  11. Weiying Wu
  12. Jiaying Qiu
  13. Shiyou Wang
  14. Haimeng Li
  15. Fuyu An
  16. Heng Bao
  17. Le Zhang
  18. Lei Han
  19. Yixin Zhu
  20. Xiran Wang
  21. Feiyue Wang
  22. Yuting Yuan
  23. Wendi Wu
  24. Chengcheng Sun
  25. Haorong Lu
  26. Jihong Wu
  27. Xinghuai Sun
  28. Shenghai Zhang
  29. Sunil Kumar Sahu
  30. Haixia Chen
  31. Dongming Fang
  32. Lihua Luo
  33. Yuying Zeng
  34. Yiquan Wu
  35. ZeHua Cui
  36. Qian He
  37. Sanjie Jiang
  38. Xiaoyan Ma
  39. Weimin Feng
  40. Yan Xu
  41. Fang Li
  42. Zhongmin Liu
  43. Lei Chen
  44. Fang Chen
  45. Xin Jin
  46. Wei Qiu
  47. Huanming Yang
  48. Jian Wang
  49. Yan Hua
  50. Yahong Liu
  51. Huan Liu
  52. Xun Xu

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Abstract

A few animals have been suspected to be intermediate hosts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, a large-scale single-cell screening of SARS-CoV-2 target cells on a wide variety of animals is missing. Here, we constructed the single-cell atlas for 11 representative species in pets, livestock, poultry, and wildlife. Notably, the proportion of SARS-CoV-2 target cells in cat was found considerably higher than other species we investigated and SARS-CoV-2 target cells were detected in multiple cell types of domestic pig, implying the necessity to carefully evaluate the risk of cats during the current COVID-19 pandemic and keep pigs under surveillance for the possibility of becoming intermediate hosts in future coronavirus outbreak. Furthermore, we screened the expression patterns of receptors for 144 viruses, resulting in a comprehensive atlas of virus target cells. Taken together, our work provides a novel and fundamental strategy to screen virus target cells and susceptible species, based on single-cell transcriptomes we generated for domesticated animals and wildlife, which could function as a valuable resource for controlling current pandemics and serve as an early warning system for coping with future infectious disease threats.

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    SciScore for 10.1101/2020.06.13.149690: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics statement: Sample collection and research were performed with the approval of Institutional Review Board on Ethics Committee of BGI (Approval letter reference number BGI-NO.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We downloaded homolog gene lists using BioMart27.
    BioMart27
    suggested: None
    As for pangolin, goose and pigeon, which lack homologs records on Ensemble, single-copy orthologs were identified from two species genomes by cluster analysis of gene families using OrthoFinder28 (OrthoFinder version 2.3.3) with the default parameters.
    OrthoFinder
    suggested: (OrthoFinder, RRID:SCR_017118)
    The genomes using for reads alignment were downloaded from NCBI Assembly (Supplementary Table 6).
    NCBI Assembly
    suggested: (NCBI Assembly Archive Viewer, RRID:SCR_012917)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.06.13.149690v1 on bioRxiv