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Single-cell characterization of haematopoietic progenitors and their trajectories in homeostasis and perturbed haematopoiesis
Open accessAbstract
The dynamics of haematopoietic stem cell differentiation and the hierarchy of oligopotent stem cells in the bone marrow remain controversial. Here we dissect haematopoietic progenitor populations at single cell resolution, deriving an unbiased reference model of transcriptional states in normal and perturbed murine bone marrow. We define the signature of the naive haematopoietic stem cell and find a continuum of core progenitor states. Core cell populations mix transcription of pre-myeloid and pre-lymphoid programs, but do not mix erythroid or megakaryocyte programs with other fates. CRISP-seq perturbation analysis confirms our models and reveals that Cebpa regulates entry into all myeloid fates, while Irf8 and PU.1 deficiency block later differentiation towards monocyte or granulocyte fates. Our transcriptional map defines a reference network model for blood progenitors and their differentiation trajectories during normal and perturbed haematopoiesis.
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“Furthermore, with improved abilities to simultaneously interrogate gene expression, while perturbing key master regulators of this process, such as hematopoietic transcription factors (TFs), it has become clear that there are distinct transition points that occur over this continuous transcriptomic landscape, suggesting the presence of punctuated transitions (Giladi et al., 2018).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Giladi et al., 2018
In the citing paper
“It is still unclear how continuous lineage decisions could be made, but there is support for cells expressing distinct modules of transcriptional programs that cooperate to subtly and continuously prime cells to differentiate along target lineages (Giladi et al., 2018; Velten et al., 2017).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Giladi et al., 2018
In the citing paper
“Such approaches have contributed to our understanding of the relationship between enhancer elements and the genes they regulate (Giladi et al., 2018).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Giladi et al., 2018
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Self-citation
Metadata
- Authors
- Giladi, A., Paul, F., Herzog, Y., Lubling, Y., Weiner, A., Yofe, I., Jaitin, D., Cabezas-Wallscheid, N., Dress, R., Ginhoux, F., Trumpp, A., Tanay, A., & Amit, I.
- Affiliations
- Weizmann Institute of Science (IL)
- Agency for Science, Technology and Research (SG)
- German Cancer Research Center (DE)
- Corresponding author
- Tanay, Amos
- Amit, Ido
- ORCID
- Venue
- Nature Cell Biology
- Published
- 2018-06-18
- Volume
- 20
- Issue
- 7
- Pages
- 836-846
- ISSN
- 1465-7392 (ISSN-L)
- 1476-4679
- OpenAlex
- W2808039892
- Cited by
- 366
- References
- 71
- Citations by year
- 2026: 16 · 2025: 39 · 2024: 44 · 2023: 58 · 2022: 49 · 2021: 56 · 2020: 55 · 2019: 44 · 2018: 5
- FWCI
- 30.33
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Nature Cell Biology (publishedVersion)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Topics
- Health Sciences › Medicine › Hematology › Hematopoietic Stem Cell Transplantation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
- Keywords
- hematopoietic stem cells, hematopoietic progenitor cells, hematopoiesis, transcriptional states, bone marrow, differentiation trajectories, CEBPA, IRF8, PU.1, myeloid differentiation, monocyte differentiation, granulocytic differentiation, cytokines and growth factors, single-cell transcriptomics
- MeSH terms
- Filgrastim, Gene Editing, Interferon Regulatory Factor-8, Proto-Oncogene Protein Spi-1, Animals, Cells, Cultured, Erythropoietin, Female, Gene Expression Regulation, Genotype, Hematinics, Hematopoiesis, Hematopoietic Stem Cells, Homeostasis, Mice, Inbred C57BL, Phenotype, Proto-Oncogene Proteins, Recombinant Proteins, Time Factors, Trans-Activators, Cellular Senescence, Cell Lineage, Gene Expression Profiling, CCAAT-Enhancer-Binding Proteins, Cell Proliferation, Interferon Regulatory Factors, Single-Cell Analysis, Transcriptome, CRISPR-Cas Systems
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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