Evidence map›Paper›PMID 30002371›Full record

ArticleNature communications2018

Lineage marker synchrony in hematopoietic genealogies refutes the PU.1/GATA1 toggle switch paradigm.

Michael K Strasser, Philipp S Hoppe, Dirk Loeffler, Konstantinos D Kokkaliaris, Timm Schroeder, Fabian J Theis, Carsten Marr

Abstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Heritable changes in division speed accompany the diversification of single T cell fate.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  7. Article
  8. Article
  9. Review
  10. Analyzing signaling activity and function in hematopoietic cells.The Journal of experimental medicine · 2021
    Review
  11. Article
  12. Review
  13. Probing pluripotency gene regulatory networks with quantitative live cell imaging.Computational and structural biotechnology journal · 2020
    Review
  14. Article
  15. Article
  16. Maps of variability in cell lineage trees.PLoS computational biology · 2019
    Article
  17. Modeling the Hematopoietic Landscape.Frontiers in cell and developmental biology · 2019
    Review
  18. Article
  19. Article
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

7 authors.

Michael K StrasserInstitute of Computational Biology, Helmholtz Zentrum München, 85764, Neuherberg, Germany.
Philipp S HoppeDepartment of Biosystems Science and Engineering (D-BSSE), ETH Zurich, 4058, Basel, Switzerland.
Dirk LoefflerDepartment of Biosystems Science and Engineering (D-BSSE), ETH Zurich, 4058, Basel, Switzerland.
Konstantinos D KokkaliarisDepartment of Biosystems Science and Engineering (D-BSSE), ETH Zurich, 4058, Basel, Switzerland.ORCID http://orcid.org/0000-0002-9952-3463
Timm SchroederDepartment of Biosystems Science and Engineering (D-BSSE), ETH Zurich, 4058, Basel, Switzerland.
Fabian J TheisInstitute of Computational Biology, Helmholtz Zentrum München, 85764, Neuherberg, Germany.ORCID http://orcid.org/0000-0002-2419-1943
Carsten MarrInstitute of Computational Biology, Helmholtz Zentrum München, 85764, Neuherberg, Germany. carsten.marr@helmholtz-muenchen.de.ORCID http://orcid.org/0000-0003-2154-4552

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) MA 5282/3-1
6 · The paper itself

Abstract

Molecular regulation of cell fate decisions underlies health and disease. To identify molecules that are active or regulated during a decision, and not before or after, the decision time point is crucial. However, cell fate markers are usually delayed and the time of decision therefore unknown. Fortunately, dividing cells induce temporal correlations in their progeny, which allow for retrospective inference of the decision time point. We present a computational method to infer decision time points from correlated marker signals in genealogies and apply it to differentiating hematopoietic stem cells. We find that myeloid lineage decisions happen generations before lineage marker onsets. Inferred decision time points are in agreement with data from colony assay experiments. The levels of the myeloid transcription factor PU.1 do not change during, but long after the predicted lineage decision event, indicating  that the PU.1/GATA1 toggle switch paradigm cannot explain the initiation of early myeloid lineage choice.

Indexed as

Cell DifferentiationCell LineageHematopoiesisAlgorithmsAnimalsComputational BiologyGATA1 Transcription FactorHematopoietic Stem CellsModels, BiologicalMyeloid CellsProto-Oncogene ProteinsProto-Oncogene Protein Spi-1Time FactorsTrans-ActivatorsGATA1 Transcription FactorProto-Oncogene ProteinsProto-Oncogene Protein Spi-1Trans-Activators

Identifiers

PMID30002371
PMCPMC6043612

What OpenQuestion holds

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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.