Cross-tissue immune cell analysis reveals tissue-specific features in humans.
Journal
Science (New York, N.Y.)
ISSN: 1095-9203
Titre abrégé: Science
Pays: United States
ID NLM: 0404511
Informations de publication
Date de publication:
13 05 2022
13 05 2022
Historique:
entrez:
13
5
2022
pubmed:
14
5
2022
medline:
18
5
2022
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 35549406
doi: 10.1126/science.abl5197
pmc: PMC7612735
mid: EMS144957
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
eabl5197Subventions
Organisme : NIAID NIH HHS
ID : K22 AI066976
Pays : United States
Organisme : Wellcome Trust
ID : 105924
Pays : United Kingdom
Organisme : NIDDK NIH HHS
ID : P30 DK132710
Pays : United States
Organisme : Wellcome Trust
ID : 206194
Pays : United Kingdom
Organisme : Cancer Research UK
ID : 10208
Pays : United Kingdom
Organisme : NIAID NIH HHS
ID : U19 AI128949
Pays : United States
Organisme : European Research Council
ID : 646794
Pays : International
Organisme : NHLBI NIH HHS
ID : U01 HL145547
Pays : United States
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Type : CommentIn
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