TY - JOUR
T1 - DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
AU - Farlik, Matthias
AU - Halbritter, Florian
AU - Müller, Fabian
AU - Choudry, Fizzah A.
AU - Ebert, Peter
AU - Klughammer, Johanna
AU - Farrow, Samantha
AU - Santoro, Antonella
AU - Ciaurro, Valerio
AU - Mathur, Anthony
AU - Uppal, Rakesh
AU - Stunnenberg, Hendrik G.
AU - Ouwehand, Willem H.
AU - Laurenti, Elisa
AU - Lengauer, Thomas
AU - Frontini, Mattia
AU - Bock, Christoph
N1 - Publisher Copyright:
© 2016 The Author(s)
PY - 2016/12/1
Y1 - 2016/12/1
N2 - 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.
AB - 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.
KW - bioinformatic lineage reconstruction
KW - cell type prediction
KW - DNA methylation profiling
KW - hematopoietic stem cell differentiation
KW - immature lymphoid progenitors
KW - lymphoid-myeloid lineage commitment
KW - megakaryocyte maturation
KW - reference epigenome mapping
KW - single-cell sequencing
KW - whole genome bisulfite sequencing
UR - http://www.scopus.com/inward/record.url?scp=85000730490&partnerID=8YFLogxK
U2 - 10.1016/j.stem.2016.10.019
DO - 10.1016/j.stem.2016.10.019
M3 - Article
C2 - 27867036
AN - SCOPUS:85000730490
SN - 1934-5909
VL - 19
SP - 808
EP - 822
JO - Cell Stem Cell
JF - Cell Stem Cell
IS - 6
ER -