Cross-tissue immune cell analysis reveals tissue-specific features in humans

Author:

Domínguez Conde C.1ORCID,Xu C.1ORCID,Jarvis L. B.2ORCID,Rainbow D. B.2ORCID,Wells S. B.3ORCID,Gomes T.1ORCID,Howlett S. K.2ORCID,Suchanek O.4,Polanski K.1ORCID,King H. W.5ORCID,Mamanova L.1ORCID,Huang N.1ORCID,Szabo P. A.6ORCID,Richardson L.1ORCID,Bolt L.1ORCID,Fasouli E. S.1ORCID,Mahbubani K. T.7ORCID,Prete M.1ORCID,Tuck L.1ORCID,Richoz N.4,Tuong Z. K.14ORCID,Campos L.18ORCID,Mousa H. S.2ORCID,Needham E. J.2ORCID,Pritchard S.1,Li T.1ORCID,Elmentaite R.1ORCID,Park J.1ORCID,Rahmani E.910,Chen D.3ORCID,Menon D. K.11ORCID,Bayraktar O. A.1,James L. K.5ORCID,Meyer K. B.1ORCID,Yosef N.9101213ORCID,Clatworthy M. R.14ORCID,Sims P. A.3ORCID,Farber D. L.6ORCID,Saeb-Parsy K.7ORCID,Jones J. L.2ORCID,Teichmann S. A.114ORCID

Affiliation:

1. Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.

2. Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

3. Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.

4. Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK.

5. Centre for Immunobiology, Blizard Institute, Queen Mary University of London, London, UK.

6. Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, USA.

7. Department of Surgery, University of Cambridge and NIHR Cambridge Biomedical Research Centre, Cambridge, UK.

8. West Suffolk Hospital NHS Trust, Bury Saint Edmunds, UK.

9. Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.

10. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.

11. Department of Anaesthesia, University of Cambridge, Cambridge, UK.

12. Chan Zuckerberg Biohub, San Francisco, CA, USA.

13. Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA.

14. Theory of Condensed Matter, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK.

Abstract

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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