Single-cell proteo-genomic reference maps of the hematopoietic system enable the purification and massive profiling of precisely defined cell states View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-11-22

AUTHORS

Sergio Triana, Dominik Vonficht, Lea Jopp-Saile, Simon Raffel, Raphael Lutz, Daniel Leonce, Magdalena Antes, Pablo Hernández-Malmierca, Diana Ordoñez-Rueda, Beáta Ramasz, Tobias Boch, Johann-Christoph Jann, Daniel Nowak, Wolf-Karsten Hofmann, Carsten Müller-Tidow, Daniel Hübschmann, Theodore Alexandrov, Vladimir Benes, Andreas Trumpp, Malte Paulsen, Lars Velten, Simon Haas

ABSTRACT

Single-cell genomics technology has transformed our understanding of complex cellular systems. However, excessive cost and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high-content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all main hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables the functional capacities of precisely mapped cell states to be measured at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry. More... »

PAGES

1577-1589

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  • Journal

    TITLE

    Nature Immunology

    ISSUE

    12

    VOLUME

    22

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41590-021-01059-0

    DOI

    http://dx.doi.org/10.1038/s41590-021-01059-0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1142718374

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/34811546


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