Evidence map›Paper›PMID 32402290›Full record

ArticleCell reports2020

Iterative Single-Cell Analyses Define the Transcriptome of the First Functional Hematopoietic Stem Cells.

Chris Sebastiaan Vink, Fernando Jose Calero-Nieto, Xiaonan Wang, Antonio Maglitto, Samanta Antonella Mariani, Wajid Jawaid, Berthold Göttgens, Elaine Dzierzak

Open access · goldAbstract read
In one paragraph

Article in Cell reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
5.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 68 citations in OpenAlex.

  1. Article
  2. Mechanometabolism instructs hematopoietic stem cell specification.The Journal of experimental medicine · 2026
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  9. Transition of signal requirement in hematopoietic stem cell development from hemogenic endothelial cells.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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  13. Review
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  15. Article
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  17. Article
  18. Hematopoietic Stem Cell Development in Mammalian Embryos.Advances in experimental medicine and biology · 2023
    Review
  19. Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Chris Sebastiaan VinkCentre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, Midlothian, Scotland EH16 4TJ, UK.
Fernando Jose Calero-NietoDepartment of Haematology, Wellcome & MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, Cambridgeshire, England CB2 0AW, UK.
Xiaonan WangDepartment of Haematology, Wellcome & MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, Cambridgeshire, England CB2 0AW, UK.
Antonio MaglittoCentre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, Midlothian, Scotland EH16 4TJ, UK.
Samanta Antonella MarianiCentre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, Midlothian, Scotland EH16 4TJ, UK.
Wajid JawaidDepartment of Haematology, Wellcome & MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, Cambridgeshire, England CB2 0AW, UK.
Berthold GöttgensDepartment of Haematology, Wellcome & MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, Cambridgeshire, England CB2 0AW, UK.
Elaine DzierzakCentre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, Midlothian, Scotland EH16 4TJ, UK. Electronic address: elaine.dzierzak@ed.ac.uk.
University of Edinburgh · GBUniversity of Cambridge · GBWellcome/MRC Cambridge Stem Cell Institute · GBCentre for Inflammation Research · GB

Funding

VISION: ValIdated Systematic IntegratiON of epigenomic dataR24DK106766 · NIDDK · PENNSYLVANIA STATE UNIVERSITY, THE · PI BLOBEL, GERD A, BODINE, DAVID M. · 2016 to 2020
$6.2M
Biotechnology and Biological Sciences Research Council BB/S01845X/1Cancer Research UK 21762Cancer Research UK C1163/A21762Medical Research Council MC_PC_12009Medical Research Council MR/M008975/1Medical Research Council MR/S036113/1NIDDK NIH HHS R24 DK106766Wellcome Trust 097922/Z/11/ZWellcome Trust 206328/Z/17/Z
6 · The paper itself

Abstract

Whereas hundreds of cells in the mouse embryonic aorta transdifferentiate to hematopoietic cells, only very few establish hematopoietic stem cell (HSC) identity at a single time point. The Gata2 transcription factor is essential for HSC generation and function. In contrast to surface-marker-based cell isolation, Gata2-based enrichment provides a direct link to the internal HSC regulatory network. Here, we use iterations of index-sorting of Gata2-expressing intra-aortic hematopoietic cluster (IAHC) cells, single-cell transcriptomics, and functional analyses to connect HSC identity to specific gene expression. Gata2-expressing IAHC cells separate into 5 major transcriptomic clusters. Iterative analyses reveal refined CD31, cKit, and CD27 phenotypic parameters that associate specific molecular profiles in one cluster with distinct HSC and multipotent progenitor function. Thus, by iterations of single-cell approaches, we identify the transcriptome of the first functional HSCs as they emerge in the mouse embryo and localize them to aortic clusters containing 1-2 cells.

Indexed as

AnimalsDisease Models, AnimalHematopoietic Stem CellsMiceSingle-Cell AnalysisTranscriptomeAGMCD27developmentembryofunctional identityGata2hematopoietic stem cellheterogeneityintra-aortic hematopoietic clusterssingle-cell transcriptometransplantation

Identifiers

PMID32402290
PMCPMC7225750
OpenAlexW3025909321

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.