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
CeMM 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; Graduate School of Computer Science, Saarland University, 66123 Saarbrücken, Germany.
Cell Stem Cell. 2016 Dec 1;19(6):808-822. doi: 10.1016/j.stem.2016.10.019. Epub 2016 Nov 17.
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.
造血干细胞在一个涉及广泛表观基因组重塑的分化过程中产生所有血细胞。在此,我们展示了相关DNA甲基化动态变化的全基因组参考图谱。我们采用了一种元表观基因组学方法,该方法结合了多个小细胞池的DNA甲基化谱,并进行单细胞甲基化组测序以评估细胞间的异质性。所得数据集确定了源自胎儿肝脏、脐带血、骨髓和外周血的造血干细胞之间的特征差异。我们还观察到髓系和淋巴系祖细胞之间的谱系特异性DNA甲基化,对未成熟的多淋巴系祖细胞进行了表征,并检测到成熟巨核细胞中逐渐出现的DNA甲基化差异。我们将这些模式与基因表达、组蛋白修饰和染色质可及性联系起来,并使用机器学习直接从DNA甲基化数据中推导人类造血分化模型。我们的结果有助于更好地理解人类造血干细胞分化,并为研究血液相关疾病提供了一个框架。