ABSTRACT: DNA methylation is a mechanism of epigenetic regulation that is common to all vertebrates. Functional studies support its relevance for tissue homeostasis, but the global dynamics of DNA methylation during in vivo differentiation have not been worked out in detail. Here we report high-resolution DNA methylation maps of adult stem cell differentiation in mouse, focusing on 19 purified cell populations of the blood and skin lineages. Except for global demethylation in erythrocytes, observed DNA methylation changes were locus-specific and relatively modest in size. They frequently overlapped with lineage-associated transcription factors and their binding sites, suggesting that DNA methylation may protect cells from aberrant transcription factor activation. DNA methylation and gene expression provided highly complementary information, and combining the two enabled us to infer the blood lineage hierarchy directly from genomic data. In summary, our dataset and analysis demonstrate that in vivo differentiation of adult stem cells is associated with small but informative changes in the distribution of DNA methylation across the mouse genome. We used microarray data to compare the gene expression profiles between various purified cell populations of the blood and skin lineages. Microarray data were obtained for 13 blood cell types (HSC, MPP1, MPP2, CLP, CMP, MEP, GMP, CD4, CD8, B-cell, Eryth, Granu, Mono) and 6 skin cell types (TBSC, ABSC, MTAC, CLDC, EPro, EDif). A subset of these microarray profiles have already been uploaded to GEO as part of previous research and were reused for the current study (GSE20244: MPP1, MPP2, CLP, CMP, GMP; GSE6506: CD4, CD8, B-cell, Eryth, Granu, Mono; GSE31028: TBSC, ABSC, MTAC). All microarray profiles that had not been made public previously are included here (HSC, MEP, CLDC, EPro, EDif). Furthermore, all data are available for download from the paper's supplementary website (http://invivomethylation.computational-epigenetics.org/). This submission includes the gene expression component of the study. The complete dataset representing the GSE38557 Samples, and the GSE20244, GSE6506, and GSE31028 Samples listed above, is linked below as a supplementary file.
