On the Cooperation between Epigenetics and Transcription Factor Networks in the Specification of Tissue Stem Cells

Abstract

It is generally accepted that epigenetic modifications, such as DNA and histone methylations, affect transcription and that a gene’s transcription feeds back on its epigenetic profile. Depending on the epigenetic modification, positive and negative feedback loops have been described. Here, we study whether such interrelation are mandatory and how transcription factor networks affect it. We apply self-organizing map machine learning to a published data set on the specification and differentiation of murine intestinal stem cells in order to provide an integrative view of gene transcription and DNA, as well as histone methylation during this process. We show that, although gain/loss of H3K4me3 at a gene promoter is generally considered to be associated with its increased/decreased transcriptional activity, such an interrelation is not mandatory, i.e., changes of the modification level do not necessarily affect transcription. Similar considerations hold for H3K27me3. In addition, even strong changes in the transcription of a gene do not necessarily affect its H3K4me3 and H3K27me3 modification profile. We provide a mechanistic explanation of these phenomena that is based on a model of epigenetic regulation of transcription. Thereby, the analyzed data suggest a broad variance in gene specific regulation of histone methylation and support the assumption of an independent regulation of transcription by histone methylation and transcription factor networks. The results provide insights into basic principles of the specification of tissue stem cells and highlight open questions about a mechanistic modeling of this process.

DNA methylation, transcriptome and genetic copy number signatures of diffuse cerebral WHO grade II/III gliomas resolve cancer heterogeneity and development

“…Changes of methylation with only minor effect on transcription was found for GPCRs also upon cell differentiation. Overall we find striking agreement between gene functions in these three regimes between cell developmental data [57], WHO grade IV GBM [26] and the LGG studied here. Interestingly, methylation seems to-activate enhancers in TF-networks while it de-activates enhancers for developmental processes [72] or, in other words, enhancer and promoter methylation seem to act in an antagonistic fashion for both types of processes.…”

“…They revealed the largest diversity and were divided into four expression (E2-E5) and three methylation (M2-M4) subtypes, which only partly match each other, thus reflecting partly decoupled expression and methylation patterns due to different possible interaction mechanisms [26, 57]. Particularly, decoupling between transcription and methylation can be rationalized in terms of independent regulation mechanisms of transcription by epigenetic and transcription factor (TF)-networks which are governed by bistable epigenetic switches [57]. Applying this model to cell differentiation data we recently identified situations where variant transcription of genes is accompanied by invariant epigenetic promoter states or vice versa.…”

“…Here we perform molecular subtyping which has emerged as an important concept to describe glioma heterogeneity and to better understand the biology of this devastating disease. We show that genomic, transcriptomic and methylation data provide partly overlapping but also distinct molecular subgroups, suggesting that different omics-views provide complementary and partly independent information about modes of gene-regulation [26, 57] with potentially different prognostic and therapeutic relevance. We aimed at characterizing the functional context of these different modes with special emphasis on the cellular composition of the tumors and their microenvironment and on possible impact for tumor development from lower grade to higher grade gliomas.…”

Teratogenic Rubella Virus Alters the Endodermal Differentiation Capacity of Human Induced Pluripotent Stem Cells

“…Alterations of gene expression patterns during development are governed by epigenetic mechanisms in cooperation with regulation via transcription factor networks [32,33]. Particularly, we found that gene signatures of epigenetic impact, such as targets of the polycomb repressive complex 2 (PRC2), of H3K27me3, and of bivalently (H3K4me3 and H3K27me3) marked gene promoters, have an almost antagonistic expression profile as compared to the stemness signatures (Figure 4A, in comparison to Figure 1F).…”

Portrayal of the human blood transcriptome of 3,388 adults and its relation to ageing and health

“…Differences of biological mechanisms behind transcriptomic [11] and the epigenetic predictors [71] of ageing or disease progression are not completely clear [11]. We recently reported that transcriptomic and epigenetic mechanisms partly decouple in cancer development [72,73] and cell differentiation [50]. Thus, the expression changes observed might reflect changed chromatin organization leading to altered cell function in type 1 compared with type 2 as discussed, e.g., as epigenetic mechanisms accompanying ageing [74] and inflammation [75][76][77][78] and associating with changes of DNA-methylation and histonemarks governing gene activity.…”