Epigenetics & Chromatin最新文献

The functioning of the human immune system is highly dependent on the sex of the individual, which comes by virtue of sex chromosomes and hormonal differences. Epigenetic mechanisms such as X chromosome inactivation, mosaicism, skewing, and dimorphism in X chromosome genes and Y chromosome regulatory genes create a sex-based variance in the immune response between males and females. This leads to differential susceptibility in immune-related disorders like infections, autoimmunity, and malignancies. Various naturally available immunomodulators are also available which target immune pathways containing X chromosome genes.

Histone methyltransferase SETDB1 (SET domain bifurcated histone lysine methyltransferase 1, also known as ESET or KMT1E) is known to be involved in the deposition of the di- and tri-methyl marks on H3K9 (H3K9me2 and H3K9me3), which are associated with transcription repression. SETDB1 exerts an essential role in the silencing of endogenous retroviruses (ERVs) in embryonic stem cells (mESCs) by tri-methylating H3K9 (H3K9me3) and interacting with DNA methyltransferases (DNMTs). Additionally, SETDB1 is engaged in regulating multiple biological processes and diseases, such as ageing, tumors, and inflammatory bowel disease (IBD), by methylating both histones and non-histone proteins. In this review, we provide an overview of the complex biology of SETDB1, review the upstream regulatory mechanisms of SETDB1 and its partners, discuss the functions and molecular mechanisms of SETDB1 in cell fate determination and stem cell, as well as in tumors and other diseases. Finally, we discuss the current challenges and prospects of targeting SETDB1 for the treatment of different diseases, and we also suggest some future research directions in the field of SETDB1 research.

Chromatin plays a central role in the conversion of energy in cells: alteration of chromatin structure to make DNA accessible consumes energy, and compaction of chromatin preserves energy. Alteration of chromatin structure uses energy sources derived from carbon metabolism such as ATP and acetyl-CoA; conversely, chromatin compaction and epigenetic modification feedback to metabolism and energy homeostasis by controlling gene expression and storing metabolites. Coordination of these dual chromatin events must be flexibly modulated in response to environmental changes such as during development and exposure to stress. Aging also alters chromatin structure and the coordination of metabolism, chromatin dynamics, and other cell processes. Noncoding RNAs and other RNA species that associate directly with chromatin or with chromatin modifiers contribute to spatiotemporal control of transcription and energy conversion. The time required for generating the large amounts of RNAs and chromatin modifiers observed in super-enhancers may be critical for regulation of transcription and may be impacted by aging. Here, taking into account these factors, we review alterations of chromatin that are fundamental to cell responses to metabolic changes due to stress and aging to maintain redox and energy homeostasis. We discuss the relationship between spatiotemporal control of energy and chromatin function, as this emerging concept must be considered to understand how cell homeostasis is maintained.

Background: Cellular identity is determined partly by cell type-specific epigenomic profiles that regulate gene expression. In neuroscience, there is a pressing need to isolate and characterize the epigenomes of specific CNS cell types in health and disease. In this study, we developed an in vivo tagging mouse model (Camk2a-NuTRAP) for paired isolation of neuronal DNA and RNA without cell sorting and then used this model to assess epigenomic regulation, DNA modifications in particular, of gene expression between neurons and glia.

Results: After validating the cell-specificity of the Camk2a-NuTRAP model, we performed TRAP-RNA-Seq and INTACT-whole genome oxidative bisulfite sequencing (WGoxBS) to assess the neuronal translatome and epigenome in the hippocampus of young mice (4 months old). WGoxBS findings were validated with enzymatic methyl-Seq (EM-Seq) and nanopore sequencing. Comparing neuronal data to microglial and astrocytic data from NuTRAP models, microglia had the highest global mCG levels followed by astrocytes and then neurons, with the opposite pattern observed for hmCG and mCH. Differentially modified regions between cell types were predominantly found within gene bodies and distal intergenic regions, rather than proximal promoters. Across cell types there was a negative correlation between DNA modifications (mCG, mCH, hmCG) and gene expression at proximal promoters. In contrast, a negative correlation of gene body mCG and a positive relationship between distal promoter and gene body hmCG with gene expression was observed. Furthermore, we identified a neuron-specific inverse relationship between mCH and gene expression across promoter and gene body regions.

Conclusions: Neurons, astrocytes, and microglia demonstrate different genome-wide levels of mCG, hmCG, and mCH that are reproducible across analytical methods. However, modification-gene expression relationships are conserved across cell types. Enrichment of differential modifications across cell types in gene bodies and distal regulatory elements, but not proximal promoters, highlights epigenomic patterning in these regions as potentially greater determinants of cell identity. These findings also demonstrate the importance of differentiating between mC and hmC in neuroepigenomic analyses, as up to 30% of what is conventionally interpreted as mCG can be hmCG, which often has a different relationship to gene expression than mCG.

Background: In a heterogeneous population of cells, individual cells can behave differently and respond variably to the environment. This cellular diversity can be assessed by measuring DNA methylation patterns. The loci with variable methylation patterns are informative of cellular heterogeneity and may serve as biomarkers of diseases and developmental progression. Cell-to-cell methylation heterogeneity can be evaluated through single-cell methylomes or computational techniques for pooled cells. However, the feasibility and performance of these approaches to precisely estimate methylation heterogeneity require further assessment.

Results: Here, we proposed model-based methods adopted from a mathematical framework originally from biodiversity, to estimate genome-wide DNA methylation heterogeneity. We evaluated the performance of our models and the existing methods with feature comparison, and tested on both synthetic datasets and real data. Overall, our methods have demonstrated advantages over others because of their better correlation with the actual heterogeneity. We also demonstrated that methylation heterogeneity offers an additional layer of biological information distinct from the conventional methylation level. In the case studies, we showed that distinct profiles of methylation heterogeneity in CG and non-CG methylation can predict the regulatory roles between genomic elements in Arabidopsis. This opens up a new direction for plant epigenomics. Finally, we demonstrated that our score might be able to identify loci in human cancer samples as putative biomarkers for early cancer detection.

Conclusions: We adopted the mathematical framework from biodiversity into three model-based methods for analyzing genome-wide DNA methylation heterogeneity to monitor cellular heterogeneity. Our methods, namely MeH, have been implemented, evaluated with existing methods, and are open to the research community.

Background: During early mammalian development, DNA methylation undergoes two waves of reprogramming, enabling transitions between somatic cells, oocyte and embryo. The first wave of de novo DNA methylation establishment occurs in oocytes. Its molecular mechanisms have been studied in mouse, a classical mammalian model. Current model describes DNA methyltransferase 3A (DNMT3A) and its cofactor DNMT3L as two essential factors for oocyte DNA methylation-the ablation of either leads to nearly complete abrogation of DNA methylation. However, DNMT3L is not expressed in human oocytes, suggesting that the mechanism uncovered in mouse is not universal across mammals.

Results: We analysed available RNA-seq data sets from oocytes of multiple mammals, including our novel data sets of several rodent species, and revealed that Dnmt3l is expressed only in the oocytes of mouse, rat and golden hamster, and at a low level in guinea pigs. We identified a specific promoter sequence recognised by an oocyte transcription factor complex associated with strong Dnmt3l activity and demonstrated that it emerged in the rodent clade Eumuroida, comprising the families Muridae (mice, rats, gerbils) and Cricetidae (hamsters). In addition, an evolutionarily novel promoter emerged in the guinea pig, driving weak Dnmt3l expression, likely without functional relevance. Therefore, Dnmt3l is expressed and consequently plays a role in oocyte de novo DNA methylation only in a small number of rodent species, instead of being an essential pan-mammalian factor. In contrast to somatic cells, where catalytically inactive DNMT3B interacts with DNMT3A, forming a heterotetramer, we did not find evidence for the expression of such inactive Dnmt3b isoforms in the oocytes of the tested species.

Conclusions: The analysis of RNA-seq data and genomic sequences revealed that DNMT3L is likely to play a role in oocytes de novo DNA methylation only in mice, rats, gerbils and hamsters. The mechanism governing de novo DNA methylation in the oocytes of most mammalian species, including humans, occurs through a yet unknown mechanism that differs from the current model discovered in mouse.

Cell-cell communication is mediated by membrane receptors and their ligands, such as the Eph/ephrin system, orchestrating cell migration during development and in diverse cancer types. Epigenetic mechanisms are key for integrating external "signals", e.g., from neighboring cells, into the transcriptome in health and disease. Previously, we reported ephrinA5 to trigger transcriptional changes of lncRNAs and protein-coding genes in cerebellar granule cells, a cell model for medulloblastoma. LncRNAs represent important adaptors for epigenetic writers through which they regulate gene expression. Here, we investigate a lncRNA-mediated targeting of DNMT1 to specific gene loci by the combined power of in silico modeling of RNA/DNA interactions and wet lab approaches, in the context of the clinically relevant use case of ephrinA5-dependent regulation of cellular motility of cerebellar granule cells. We provide evidence that Snhg15, a cancer-related lncRNA, recruits DNMT1 to the Ncam1 promoter through RNA/DNA triplex structure formation and the interaction with DNMT1. This mediates DNA methylation-dependent silencing of Ncam1, being abolished by ephrinA5 stimulation-triggered reduction of Snhg15 expression. Hence, we here propose a triple helix recognition mechanism, underlying cell motility regulation via lncRNA-targeted DNA methylation in a clinically relevant context.