scholarly journals DNMTs and Impact of CpG Content, Transcription Factors, Consensus Motifs, lncRNAs, and Histone Marks on DNA Methylation

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1336 ◽  
Author(s):  
Jaqueline Loaeza-Loaeza ◽  
Adriana S. Beltran ◽  
Daniel Hernández-Sotelo
Keyword(s):  
Dna Methylation ◽  
Transcriptional Regulation ◽  
Transcription Factors ◽  
Current Knowledge ◽  
Dna Methyltransferases ◽  
Histone Marks ◽  
Spatiotemporal Regulation ◽  
Genome Wide ◽  
Health And Disease ◽  
Methylation Patterns

DNA methyltransferases (DNMTs) play an essential role in DNA methylation and transcriptional regulation in the genome. DNMTs, along with other poorly studied elements, modulate the dynamic DNA methylation patterns of embryonic and adult cells. We summarize the current knowledge on the molecular mechanism of DNMTs’ functional targeting to maintain genome-wide DNA methylation patterns. We focus on DNMTs’ intrinsic characteristics, transcriptional regulation, and post-transcriptional modifications. Furthermore, we focus special attention on the DNMTs’ specificity for target sites, including key cis-regulatory factors such as CpG content, common motifs, transcription factors (TF) binding sites, lncRNAs, and histone marks to regulate DNA methylation. We also review how complexes of DNMTs/TFs or DNMTs/lncRNAs are involved in DNA methylation in specific genome regions. Understanding these processes is essential because the spatiotemporal regulation of DNA methylation modulates gene expression in health and disease.

scholarly journals Diversity of Fungal DNA Methyltransferases and Their Association With DNA Methylation Patterns

2021 ◽  
Vol 11 ◽  
Author(s):  
Yu-Shin Nai ◽  
Yu-Chun Huang ◽  
Ming-Ren Yen ◽  
Pao-Yang Chen
Keyword(s):  
Dna Methylation ◽  
Life Stage ◽  
Dna Methyltransferases ◽  
Fungal Species ◽  
Protein Domain ◽  
Domain Structures ◽  
Genome Wide ◽  
Fungal Dna ◽  
Fungal Genomes ◽  
Methylation Patterns

DNA methyltransferases (DNMTs) are a group of proteins that catalyze DNA methylation by transferring a methyl group to DNA. The genetic variation in DNMTs results in differential DNA methylation patterns associated with various biological processes. In fungal species, DNMTs and their DNA methylation profiles were found to be very diverse and have gained many research interests. We reviewed fungal DNMTs in terms of their biological functions, protein domain structures, and their associated epigenetic regulations compared to those known in plant and animal systems. In addition, we summarized recent reports on potential RNA-directed DNA methylation (RdDM) related to DNMT5 in fungi. We surveyed up to 40 fungal species with published genome-wide DNA methylation profiles (methylomes) and presented the associations between the specific patterns of fungal DNA methylation and their DNMTs based on a phylogenetic tree of protein domain structures. For example, the main DNMTs in Basidiomycota, DNMT1 with RFD domain + DNMT5, contributing to CG methylation preference, were distinct from RID + Dim-2 in Ascomycota, resulting in a non-CG methylation preference. Lastly, we revealed that the dynamic methylation involved in fungal life stage changes was particularly low in mycelium and DNA methylation was preferentially located in transposable elements (TEs). This review comprehensively discussed fungal DNMTs and methylomes and their connection with fungal development and taxonomy to present the diverse usages of DNA methylation in fungal genomes.

scholarly journals Epigenetic engineering of yeast reveals dynamic molecular adaptation to methylation stress and genetic modulators of specific DNMT3 family members

2020 ◽  
Vol 48 (8) ◽  
pp. 4081-4099 ◽  
Author(s):  
Alex I Finnegan ◽  
Somang Kim ◽  
Hu Jin ◽  
Michael Gapinske ◽  
Wendy S Woods ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Time Course ◽  
Cytosine Methylation ◽  
Family Members ◽  
Dynamic Network ◽  
Dna Methyltransferases ◽  
Genome Wide ◽  
Distinct Sequence ◽  
Adenosyl Methionine ◽  
Methylation Patterns

Abstract Cytosine methylation is a ubiquitous modification in mammalian DNA generated and maintained by several DNA methyltransferases (DNMTs) with partially overlapping functions and genomic targets. To systematically dissect the factors specifying each DNMT’s activity, we engineered combinatorial knock-in of human DNMT genes in Komagataella phaffii, a yeast species lacking endogenous DNA methylation. Time-course expression measurements captured dynamic network-level adaptation of cells to DNMT3B1-induced DNA methylation stress and showed that coordinately modulating the availability of S-adenosyl methionine (SAM), the essential metabolite for DNMT-catalyzed methylation, is an evolutionarily conserved epigenetic stress response, also implicated in several human diseases. Convolutional neural networks trained on genome-wide CpG-methylation data learned distinct sequence preferences of DNMT3 family members. A simulated annealing interpretation method resolved these preferences into individual flanking nucleotides and periodic poly(A) tracts that rotationally position highly methylated cytosines relative to phased nucleosomes. Furthermore, the nucleosome repeat length defined the spatial unit of methylation spreading. Gene methylation patterns were similar to those in mammals, and hypo- and hypermethylation were predictive of increased and decreased transcription relative to control, respectively, in the absence of mammalian readers of DNA methylation. Introducing controlled epigenetic perturbations in yeast thus enabled characterization of fundamental genomic features directing specific DNMT3 proteins.

scholarly journals Epigenetic engineering of yeast reveals dynamic molecular adaptation to methylation stress and genetic modulators of specific DNMT3 family members

2020 ◽  
Author(s):  
Alex I. Finnegan ◽  
Somang Kim ◽  
Hu Jin ◽  
Michael Gapinske ◽  
Wendy S. Woods ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Time Course ◽  
Cytosine Methylation ◽  
Family Members ◽  
Dynamic Network ◽  
Dna Methyltransferases ◽  
Genome Wide ◽  
Distinct Sequence ◽  
Adenosyl Methionine ◽  
Methylation Patterns

ABSTRACTCytosine methylation is a ubiquitous modification in mammalian DNA generated and maintained by several DNA methyltransferases (DNMTs) with partially overlapping functions and genomic targets. To systematically dissect the factors specifying each DNMT’s activity, we engineered combinatorial knock-in of human DNMT genes in Komagataella phaffii, a yeast species lacking endogenous DNA methylation. Time-course expression measurements captured dynamic network-level adaptation of cells to DNMT3B1-induced DNA methylation stress and showed that coordinately modulating the availability of S-adenosyl methionine (SAM), the essential metabolite for DNMT-catalyzed methylation, is an evolutionarily conserved epigenetic stress response, also implicated in several human diseases. Convolutional neural networks trained on genome-wide CpG-methylation data learned distinct sequence preferences of DNMT3 family members. A simulated annealing interpretation method resolved these preferences into individual flanking nucleotides and periodic poly(A) tracts that rotationally position highly methylated cytosines relative to phased nucleosomes. Furthermore, the nucleosome repeat length defined the spatial unit of methylation spreading. Gene methylation patterns were similar to those in mammals, and hypo- and hypermethylation were predictive of increased and decreased transcription relative to control, respectively, in the absence of mammalian readers of DNA methylation. Introducing controlled epigenetic perturbations in yeast thus enabled characterization of fundamental genomic features directing specific DNMT3 proteins.

Epigenetic control of hematopoiesis: the PU.1 chromatin connection

2014 ◽  
Vol 395 (11) ◽  
pp. 1265-1274 ◽  
Author(s):  
Boet van Riel ◽  
Frank Rosenbauer
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Current Knowledge ◽  
Dna Methyltransferases ◽  
Chromatin Remodelers ◽  
Cell Lineages ◽  
Protein Partners ◽  
Genome Wide

Abstract Purine-rich box1 (PU.1) is a transcription factor that not only has a key role in the development of most hematopoietic cell lineages but also in the suppression of leukemia. To exert these functions, PU.1 can cross-talk with multiple different proteins by forming complexes in order to activate or repress transcription. Among its protein partners are chromatin remodelers, DNA methyltransferases, and a number of other transcription factors with important roles in hematopoiesis. While a great deal of knowledge has been acquired about PU.1 function over the years, it was the development of novel genome-wide technologies, which boosted our understanding of how PU.1 acts on the chromatin to drive its repertoire of target genes. This review summarizes current knowledge and ideas of molecular mechanisms by which PU.1 controls hematopoiesis and suppresses leukemia.

scholarly journals Flanking sequence preference modulates de novo DNA methylation in the mouse genome

2020 ◽  
Author(s):  
Izaskun Mallona ◽  
Ioana Mariuca Ilie ◽  
Massimiliano Manzo ◽  
Amedeo Caflisch ◽  
Tuncay Baubec
Keyword(s):  
Dna Methylation ◽  
De Novo ◽  
Cell Types ◽  
Dna Methyltransferases ◽  
Flanking Sequence ◽  
Base Pairs ◽  
Genome Wide ◽  
Dynamics Simulations ◽  
Methylation Patterns ◽  
Different Cell Types

AbstractMammalian de novo DNA methyltransferases (DNMT) are responsible for the establishment of cell-type-specific DNA methylation in healthy and diseased tissues. Through genome-wide analysis of de novo methylation activity in murine stem cells we uncover that DNMT3A prefers to methylate CpGs followed by cytosines or thymines, while DNMT3B predominantly methylates CpGs followed by guanines or adenines. These signatures are further observed at non-CpG sites, resembling methylation context observed in specialised cell types, including neurons and oocytes. We further show that these preferences are not mediated by the differential recruitment of the two de novo DNMTs to the genome but are resulting from structural differences in their catalytic domains. Molecular dynamics simulations suggest that, in case of DNMT3A, the preference is due to favourable polar interactions between the flexible Arg836 side chain and the guanine that base-pairs with the cytosine following the CpG. This context-dependent de novo DNA methylation provides additional insights into the complex regulation of methylation patterns in different cell types.

scholarly journals Multi-species and multi-tissue methylation clocks for age estimation in toothed whales and dolphins

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Todd R. Robeck ◽  
Zhe Fei ◽  
Ake T. Lu ◽  
Amin Haghani ◽  
Eve Jourdain ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Age Estimation ◽  
Species Conservation ◽  
Genome Wide ◽  
Epigenetic Aging ◽  
Highly Correlated ◽  
Methylation Patterns ◽  
Cg Dinucleotides ◽  
Free Ranging ◽  
Unique Species

AbstractThe development of a precise blood or skin tissue DNA Epigenetic Aging Clock for Odontocete (OEAC) would solve current age estimation inaccuracies for wild odontocetes. Therefore, we determined genome-wide DNA methylation profiles using a custom array (HorvathMammalMethyl40) across skin and blood samples (n = 446) from known age animals representing nine odontocete species within 4 phylogenetic families to identify age associated CG dinucleotides (CpGs). The top CpGs were used to create a cross-validated OEAC clock which was highly correlated for individuals (r = 0.94) and for unique species (median r = 0.93). Finally, we applied the OEAC for estimating the age and sex of 22 wild Norwegian killer whales. DNA methylation patterns of age associated CpGs are highly conserved across odontocetes. These similarities allowed us to develop an odontocete epigenetic aging clock (OEAC) which can be used for species conservation efforts by provide a mechanism for estimating the age of free ranging odontocetes from either blood or skin samples.

scholarly journals Aging-associated distinctive DNA methylation changes of LINE-1 retrotransposons in pure cell-free DNA from human blood

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wardah Mahmood ◽  
Lars Erichsen ◽  
Pauline Ott ◽  
Wolfgang A. Schulz ◽  
Johannes C. Fischer ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cell Free Dna ◽  
The Past ◽  
Free Dna ◽  
Genome Wide ◽  
Cancerous Cell ◽  
Pure Cell ◽  
Epigenetic Biomarker ◽  
Methylation Patterns ◽  
Cancerous Cells

AbstractLINE-1 hypomethylation of cell-free DNA has been described as an epigenetic biomarker of human aging. However, in the past, insufficient differentiation between cellular and cell-free DNA may have confounded analyses of genome-wide methylation levels in aging cells. Here we present a new methodological strategy to properly and unambiguously extract DNA methylation patterns of repetitive, as well as single genetic loci from pure cell-free DNA from peripheral blood. Since this nucleic acid fraction originates mainly in apoptotic, senescent and cancerous cells, this approach allows efficient analysis of aged and cancerous cell-specific DNA methylation patterns for diagnostic and prognostic purposes. Using this methodology, we observe a significant age-associated erosion of LINE-1 methylation in cfDNA suggesting that the threshold of hypomethylation sufficient for relevant LINE-1 activation and consequential harmful retrotransposition might be reached at higher age. We speculate that this process might contribute to making aging the main risk factor for many cancers.

Genome-Wide DNA Methylation Patterns Analysis of Noncoding RNAs in Temporal Lobe Epilepsy Patients

2017 ◽  
Vol 55 (1) ◽  
pp. 793-803 ◽  
Author(s):  
Wenbiao Xiao ◽  
Yuze Cao ◽  
Hongyu Long ◽  
Zhaohui Luo ◽  
Shuyu Li ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Noncoding Rnas ◽  
Genome Wide ◽  
Methylation Patterns

Abstract 40: Disturbed Flow Alters Genomewide DNA Methylation Patterns, Regulating Endothelial Gene Expression and Atherosclerosis

2014 ◽  
Vol 34 (suppl_1) ◽  
Author(s):  
Jessilyn Dunn ◽  
Haiwei Qiu ◽  
Soyeon Kim ◽  
Daudi Jjingo ◽  
Ryan Hoffman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Dna Methyltransferase ◽  
Methylation Status ◽  
Western Diet ◽  
Dependent Manner ◽  
Gene Promoters ◽  
Genome Wide ◽  
Methylation Patterns ◽  
Endothelial Gene Expression

Atherosclerosis preferentially occurs in arterial regions of disturbed blood flow (d-flow), which alters gene expression, endothelial function, and atherosclerosis. Here, we show that d-flow regulates genome-wide DNA methylation patterns in a DNA methyltransferase (DNMT)-dependent manner. We found that d-flow induced expression of DNMT1, but not DNMT3a or DNMT3b, in mouse arterial endothelium in vivo and in cultured endothelial cells by oscillatory shear (OS) compared to unidirectional laminar shear in vitro. The DNMT inhibitor 5-Aza-2’deoxycytidine (5Aza) or DNMT1 siRNA significantly reduced OS-induced endothelial inflammation. Moreover, 5Aza reduced lesion formation in two atherosclerosis models using ApoE-/- mice (western diet for 3 months and the partial carotid ligation model with western diet for 3 weeks). To identify the 5Aza mechanisms, we conducted two genome-wide studies: reduced representation bisulfite sequencing (RRBS) and transcript microarray using endothelial-enriched gDNA and RNA, respectively, obtained from the partially-ligated left common carotid artery (LCA exposed to d-flow) and the right contralateral control (RCA exposed to s-flow) of mice treated with 5Aza or vehicle. D-flow induced DNA hypermethylation in 421 gene promoters, which was significantly prevented by 5Aza in 335 genes. Systems biological analyses using the RRBS and the transcriptome data revealed 11 mechanosensitive genes whose promoters were hypermethylated by d-flow but rescued by 5Aza treatment. Of those, five genes contain hypermethylated cAMP-response-elements in their promoters, including the transcription factors HoxA5 and Klf3. Their methylation status could serve as a mechanosensitive master switch in endothelial gene expression. Our results demonstrate that d-flow controls epigenomic DNA methylation patterns in a DNMT-dependent manner, which in turn alters endothelial gene expression and induces atherosclerosis.

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