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DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation

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 ma...

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Autores principales: Farlik, Matthias, Halbritter, Florian, Müller, Fabian, Choudry, Fizzah A., Ebert, Peter, Klughammer, Johanna, Farrow, Samantha, Santoro, Antonella, Ciaurro, Valerio, Mathur, Anthony, Uppal, Rakesh, Stunnenberg, Hendrik G., Ouwehand, Willem H., Laurenti, Elisa, Lengauer, Thomas, Frontini, Mattia, Bock, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cell Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5145815/
https://www.ncbi.nlm.nih.gov/pubmed/27867036
http://dx.doi.org/10.1016/j.stem.2016.10.019
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author Farlik, Matthias
Halbritter, Florian
Müller, Fabian
Choudry, Fizzah A.
Ebert, Peter
Klughammer, Johanna
Farrow, Samantha
Santoro, Antonella
Ciaurro, Valerio
Mathur, Anthony
Uppal, Rakesh
Stunnenberg, Hendrik G.
Ouwehand, Willem H.
Laurenti, Elisa
Lengauer, Thomas
Frontini, Mattia
Bock, Christoph
author_facet Farlik, Matthias
Halbritter, Florian
Müller, Fabian
Choudry, Fizzah A.
Ebert, Peter
Klughammer, Johanna
Farrow, Samantha
Santoro, Antonella
Ciaurro, Valerio
Mathur, Anthony
Uppal, Rakesh
Stunnenberg, Hendrik G.
Ouwehand, Willem H.
Laurenti, Elisa
Lengauer, Thomas
Frontini, Mattia
Bock, Christoph
author_sort Farlik, Matthias
collection PubMed
description 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.
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spelling pubmed-51458152016-12-15 DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation Farlik, Matthias Halbritter, Florian Müller, Fabian Choudry, Fizzah A. Ebert, Peter Klughammer, Johanna Farrow, Samantha Santoro, Antonella Ciaurro, Valerio Mathur, Anthony Uppal, Rakesh Stunnenberg, Hendrik G. Ouwehand, Willem H. Laurenti, Elisa Lengauer, Thomas Frontini, Mattia Bock, Christoph Cell Stem Cell Resource 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. Cell Press 2016-12-01 /pmc/articles/PMC5145815/ /pubmed/27867036 http://dx.doi.org/10.1016/j.stem.2016.10.019 Text en © 2016 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Resource
Farlik, Matthias
Halbritter, Florian
Müller, Fabian
Choudry, Fizzah A.
Ebert, Peter
Klughammer, Johanna
Farrow, Samantha
Santoro, Antonella
Ciaurro, Valerio
Mathur, Anthony
Uppal, Rakesh
Stunnenberg, Hendrik G.
Ouwehand, Willem H.
Laurenti, Elisa
Lengauer, Thomas
Frontini, Mattia
Bock, Christoph
DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
title DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
title_full DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
title_fullStr DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
title_full_unstemmed DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
title_short DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
title_sort dna methylation dynamics of human hematopoietic stem cell differentiation
topic Resource
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5145815/
https://www.ncbi.nlm.nih.gov/pubmed/27867036
http://dx.doi.org/10.1016/j.stem.2016.10.019
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