Evidence map›Paper›PMID 27867036›Full record

ArticleCell stem cell2016

DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation.

Matthias Farlik, Florian Halbritter, Fabian Müller, Fizzah A Choudry, Peter Ebert, Johanna Klughammer, Samantha Farrow, Antonella Santoro, Valerio Ciaurro, Anthony Mathur and 7 more

Abstract read
In one paragraph

Article in Cell stem cell, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
168citing papers in PubMed, 1 pooled it
–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

168 citing papers in PubMed, 1 synthesis or guideline pooled it.

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108 more citing papers are in PubMed but not listed here.

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

17 authors.

Matthias FarlikCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.
Florian HalbritterCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.
Fabian MüllerMax Planck Institute for Informatics, Saarland Informatics Campus, 66123 Saarbrücken, Germany; Graduate School of Computer Science, Saarland University, 66123 Saarbrücken, Germany.
Fizzah A ChoudryDepartment of Haematology, University of Cambridge, Cambridge CB2 0PT, UK; National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK.
Peter EbertMax Planck Institute for Informatics, Saarland Informatics Campus, 66123 Saarbrücken, Germany; Graduate School of Computer Science, Saarland University, 66123 Saarbrücken, Germany.
Johanna KlughammerCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.
Samantha FarrowDepartment of Haematology, University of Cambridge, Cambridge CB2 0PT, UK; National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK.
Antonella SantoroWellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Clifford Allbutt Building, Hills Road, Cambridge CB2 0AH, UK.
Valerio CiaurroWellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Clifford Allbutt Building, Hills Road, Cambridge CB2 0AH, UK.
Anthony MathurDepartment of Cardiology, Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London EC1A 7BE, UK.
Rakesh UppalDepartment of Cardiology, Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London EC1A 7BE, UK.
Hendrik G StunnenbergFaculty of Science, Department of Molecular Biology, Radboud University, 6525GA Nijmegen, the Netherlands.
Willem H OuwehandDepartment of Haematology, University of Cambridge, Cambridge CB2 0PT, UK; National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0QQ, UK; Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.
Elisa LaurentiDepartment of Haematology, University of Cambridge, Cambridge CB2 0PT, UK; Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Clifford Allbutt Building, Hills Road, Cambridge CB2 0AH, UK.
Thomas LengauerMax Planck Institute for Informatics, Saarland Informatics Campus, 66123 Saarbrücken, Germany.
Mattia FrontiniDepartment of Haematology, University of Cambridge, Cambridge CB2 0PT, UK; National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0QQ, UK. Electronic address: mf471@cam.ac.uk.
Christoph BockCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria; Max Planck Institute for Informatics, Saarland Informatics Campus, 66123 Saarbrücken, Germany; Department of Laboratory Medicine, Medical University of Vienna, 1090 Vienna, Austria; Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, 1090 Vienna, Austria. Electronic address: cbock@cemm.oeaw.ac.at.

Funding

British Heart Foundation RG/09/012/28096Department of Health RP-PG-0310-1002Medical Research Council MC_PC_12009Medical Research Council MR/K024043/1Wellcome Trust 107630/Z/15/Z
6 · The paper itself

Abstract

Hematopoietic stem cells give rise to all blood cells in a differentiation process that involves widespread epigenome remodeling. Here we present genome-wide reference maps of the associated DNA methylation dynamics. We used a meta-epigenomic approach that combines DNA methylation profiles across many small pools of cells and performed single-cell methylome sequencing to assess cell-to-cell heterogeneity. The resulting dataset identified characteristic differences between HSCs derived from fetal liver, cord blood, bone marrow, and peripheral blood. We also observed lineage-specific DNA methylation between myeloid and lymphoid progenitors, characterized immature multi-lymphoid progenitors, and detected progressive DNA methylation differences in maturing megakaryocytes. We linked these patterns to gene expression, histone modifications, and chromatin accessibility, and we used machine learning to derive a model of human hematopoietic differentiation directly from DNA methylation data. Our results contribute to a better understanding of human hematopoietic stem cell differentiation and provide a framework for studying blood-linked diseases.

Indexed as

Binding SitesBone Marrow CellsCell DifferentiationCell LineageCell SeparationChromatinDNA MethylationDNA ReplicationEpigenesis, GeneticFetal BloodHematopoietic Stem CellsHistonesHumansLiverLymphocytesMachine LearningChromatinHistonesTranscription Factorsbioinformatic lineage reconstructioncell type predictionDNA methylation profilinghematopoietic stem cell differentiationimmature lymphoid progenitorslymphoid-myeloid lineage commitmentmegakaryocyte maturationreference epigenome mappingsingle-cell sequencingwhole genome bisulfite sequencing

Identifiers

PMID27867036
PMCPMC5145815

What OpenQuestion holds

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Registered trials

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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.