5-Methylcytosine in eukaryotic DNA

NSUN6 inhibitor discovery guided by its mRNA substrate bound crystal structure

NSUN6 preferentially catalyzes the methylation of cytosine nucleotides in mRNA substrates, which enhances transcription. Dysregulation of NSUN6 catalysis drives the oncogenesis of certain cancers. In this study, we determined the crystal structure of human NSUN6 in complex with its S-adenosyl-L-methionine analog and a bound NECT-2 3'-UTR RNA substrate at 2.9 Å resolution. The complex structure reveals how NSUN6 recognizes the specific CUC[CU]A consensus motif of the substrate and facilitates the methyl transfer from S-adenosyl-L-methionine (SAM) to mRNA. By combining the structural data with nuclear magnetic resonance (NMR)-based fragment screening, a virtual screening, and a further comprehensive biochemical verification, we identified thiamine disulfide as a non-SAM analog lead compound that competes with the CUC[CU]A substrate for binding to NSUN6. Our findings pave the way for the discovery of potent inhibitors for the treatment of NSUN6-driven cancers in the future.

Differential methylation region detection via an array-adaptive normalized kernel-weighted model

A differentially methylated region (DMR) is a genomic region that has significantly different methylation patterns between biological conditions. Identifying DMRs between different biological conditions is critical for developing disease biomarkers. Although methods for detecting DMRs in microarray data have been introduced, developing methods with high precision, recall, and accuracy in determining the true length of DMRs remains a challenge. In this study, we propose a normalized kernel-weighted model to account for similar methylation profiles using the relative probe distance from "nearby" CpG sites. We also extend this model by proposing an array-adaptive version in attempt to account for the differences in probe spacing between Illumina's Infinium 450K and EPIC bead array respectively. We also study the asymptotic results of our proposed statistic. We compare our approach with a popular DMR detection method via simulation studies under large and small treatment effect settings. We also discuss the susceptibility of our method in detecting the true length of the DMRs under these two settings. Lastly, we demonstrate the biological usefulness of our method when combined with pathway analysis methods on oral cancer data. We have created an R package called idDMR, downloadable from GitHub repository with link: https://github.com/DanielAlhassan/idDMR, that allows for the convenient implementation of our array-adaptive DMR method.

DNA Methylation in the Adaptive Response to Exercise

Emerging evidence published over the past decade has highlighted the role of DNA methylation in skeletal muscle function and health, including as an epigenetic transducer of the adaptive response to exercise. In this review, we aim to synthesize the latest findings in this field to highlight: (1) the shifting understanding of the genomic localization of altered DNA methylation in response to acute and chronic aerobic and resistance exercise in skeletal muscle (e.g., promoter, gene bodies, enhancers, intergenic regions, un-annotated regions, and genome-wide methylation); (2) how these global/regional methylation changes relate to transcriptional activity following exercise; and (3) the factors (e.g., individual demographic or genetic features, dietary, training history, exercise parameters, local epigenetic characteristics, circulating hormones) demonstrated to alter both the pattern of DNA methylation after exercise, and the relationship between DNA methylation and gene expression. Finally, we discuss the changes in non-CpG methylation and 5-hydroxymethylation after exercise, as well as the importance of emerging single-cell analyses to future studies-areas of increasing focus in the field of epigenetics. We anticipate that this review will help generate a framework for clinicians and researchers to begin developing and testing exercise interventions designed to generate targeted changes in DNA methylation as part of a personalized exercise regimen.

Emerging Roles of Vitamin B12 in Aging and Inflammation

Vitamin B12 (cobalamin) is an essential nutrient for humans and animals. Metabolically active forms of B12-methylcobalamin and 5-deoxyadenosylcobalamin are cofactors for the enzymes methionine synthase and mitochondrial methylmalonyl-CoA mutase. Malfunction of these enzymes due to a scarcity of vitamin B12 leads to disturbance of one-carbon metabolism and impaired mitochondrial function. A significant fraction of the population (up to 20%) is deficient in vitamin B12, with a higher rate of deficiency among elderly people. B12 deficiency is associated with numerous hallmarks of aging at the cellular and organismal levels. Cellular senescence is characterized by high levels of DNA damage by metabolic abnormalities, increased mitochondrial dysfunction, and disturbance of epigenetic regulation. B12 deficiency could be responsible for or play a crucial part in these disorders. In this review, we focus on a comprehensive analysis of molecular mechanisms through which vitamin B12 influences aging. We review new data about how deficiency in vitamin B12 may accelerate cellular aging. Despite indications that vitamin B12 has an important role in health and healthy aging, knowledge of the influence of vitamin B12 on aging is still limited and requires further research.

SNN6mA: Improved DNA N6-methyladenine site prediction using Siamese network-based feature embedding

DNA N6-methyladenine (6mA) is one of the most common and abundant modifications, which plays essential roles in various biological processes and cellular functions. Therefore, the accurate identification of DNA 6mA sites is of great importance for a better understanding of its regulatory mechanisms and biological functions. Although significant progress has been made, there still has room for further improvement in 6mA site prediction in DNA sequences. In this study, we report a smart but accurate 6mA predictor, termed as SNN6mA, using Siamese network. To be specific, DNA segments are firstly encoded into feature vectors using the one-hot encoding scheme; then, these original feature vectors are mapped to a low-dimensional embedding space derived from Siamese network to capture more discriminative features; finally, the obtained low-dimensional features are fed to a fully connected neural network to perform final prediction. Stringent benchmarking tests on the datasets of two species demonstrated that the proposed SNN6mA is superior to the state-of-the-art 6mA predictors. Detailed data analyses show that the major advantage of SNN6mA lies in the utilization of Siamese network, which can map the original features into a low-dimensional embedding space with more discriminative capability. In summary, the proposed SNN6mA is the first attempt to use Siamese network for 6mA site prediction and could be easily extended to predict other types of modifications. The codes and datasets used in the study are freely available at https://github.com/YuXuan-Glasgow/SNN6mA for academic use.

Insights into the Inhibitory Mechanisms of the Covalent Drugs for DNMT3A

The perturbations of DNA methyltransferase 3 alpha (DNMT3A) may cause uncontrolled gene expression, resulting in cancers and tumors. The DNMT inhibitors Azacytidine (AZA) and Zebularine (ZEB) inhibit the DNMT family with no specificities, and consequently would bring side effects during the treatment. Therefore, it is vital to understand the inhibitory mechanisms in DNMT3A to inform the new inhibitor design for DNMTs. Herein, we carried out molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) simulations to investigate the inhibitory mechanisms of the AZA and ZEB. The results were compared to the methyl transfer of cytosine. We showed how the AZA might stop the methyl transfer process, whereas the ZEB might be stuck in a methyl-transferred intermediate (IM3). The IM3 state then fails the elimination due to the unique protein dynamics that result in missing the catalytic water chain. Our results brought atomic-level insights into the mechanisms of the two drugs in DNMT3A, which could benefit the new generation of drug design for the DNMTs.

Prediction of DNA Methylation based on Multi-dimensional feature encoding and double convolutional fully connected convolutional neural network

DNA methylation takes on critical significance to the regulation of gene expression by affecting the stability of DNA and changing the structure of chromosomes. DNA methylation modification sites should be identified, which lays a solid basis for gaining more insights into their biological functions. Existing machine learning-based methods of predicting DNA methylation have not fully exploited the hidden multidimensional information in DNA gene sequences, such that the prediction accuracy of models is significantly limited. Besides, most models have been built in terms of a single methylation type. To address the above-mentioned issues, a deep learning-based method was proposed in this study for DNA methylation site prediction, termed the MEDCNN model. The MEDCNN model is capable of extracting feature information from gene sequences in three dimensions (i.e., positional information, biological information, and chemical information). Moreover, the proposed method employs a convolutional neural network model with double convolutional layers and double fully connected layers while iteratively updating the gradient descent algorithm using the cross-entropy loss function to increase the prediction accuracy of the model. Besides, the MEDCNN model can predict different types of DNA methylation sites. As indicated by the experimental results,the deep learning method based on coding from multiple dimensions outperformed single coding methods, and the MEDCNN model was highly applicable and outperformed existing models in predicting DNA methylation between different species. As revealed by the above-described findings, the MEDCNN model can be effective in predicting DNA methylation sites.

Context and Mutation in Gymnosperm Chloroplast DNA

Mutations and subsequent repair processes are known to be strongly context-dependent in the flowering-plant chloroplast genome. At least six flanking bases, three on each side, can have an influence on the relative rates of different types of mutation at any given site. In this analysis, examine context and substitution at noncoding and fourfold degenerate coding sites in gymnosperm DNA. The sequences are analyzed in sets of three, allowing the inference of the substitution direction and the generation of context-dependent rate matrices. The size of the dataset limits the analysis to the tetranucleotide context of the sites, but the evidence shows that there are significant contextual effects, with patterns that are similar to those observed in angiosperms. These effects most likely represent an influence on the underlying mutation/repair dynamics. The data extend the plastome lineages that feature very complex patterns of mutation, which can have significant effects on the evolutionary dynamics of the chloroplast genome.

Advances in epigenetic modifications of autophagic process in pulmonary hypertension

Pulmonary hypertension is characterized by pulmonary arterial remodeling that results in increased pulmonary vascular resistance, right ventricular failure, and premature death. It is a threat to public health globally. Autophagy, as a highly conserved self-digestion process, plays crucial roles with autophagy-related (ATG) proteins in various diseases. The components of autophagy in the cytoplasm have been studied for decades and multiple studies have provided evidence of the importance of autophagic dysfunction in pulmonary hypertension. The status of autophagy plays a dynamic suppressive or promotive role in different contexts and stages of pulmonary hypertension development. Although the components of autophagy have been well studied, the molecular basis for the epigenetic regulation of autophagy is less understood and has drawn increasing attention in recent years. Epigenetic mechanisms include histone modifications, chromatin modifications, DNA methylation, RNA alternative splicing, and non-coding RNAs, which control gene activity and the development of an organism. In this review, we summarize the current research progress on epigenetic modifications in the autophagic process, which have the potential to be crucial and powerful therapeutic targets against the autophagic process in pulmonary hypertension development.

The Interplay between Dysregulated Metabolism and Epigenetics in Cancer

Cellular metabolism (or energetics) and epigenetics are tightly coupled cellular processes. It is arguable that of all the described cancer hallmarks, dysregulated cellular energetics and epigenetics are the most tightly coregulated. Cellular metabolic states regulate and drive epigenetic changes while also being capable of influencing, if not driving, epigenetic reprogramming. Conversely, epigenetic changes can drive altered and compensatory metabolic states. Cancer cells meticulously modify and control each of these two linked cellular processes in order to maintain their tumorigenic potential and capacity. This review aims to explore the interplay between these two processes and discuss how each affects the other, driving and enhancing tumorigenic states in certain contexts.

Unveiling the Methyl Transfer Mechanisms in the Epigenetic Machinery DNMT3A-3L: A Comprehensive Study Integrating Assembly Dynamics with Catalytic Reactions

In epigenetic mechanisms, DNA methyltransferase 3 alpha (DNMT3A) acts as an initiator for DNA methylation and prevents the downstream genes from expressing. Perturbations of DNMT3A functions may cause uncontrolled gene expression, resulting in pathogenic consequences such as cancers. It is, therefore, vitally important to understand the catalytic process of DNMT3A in its biological macromolecule assembly, viz., heterotetramer: (DNMT3A-3 L)^dimer. In this study, we utilized molecular dynamics (MD) simulations, Markov State Models (MSM), and quantum mechanics/molecular mechanics simulations (QM/MM) to investigate the de novo methyl transfer process. We identified the dynamics of the key residues relevant to the insertion of the target cytosine (dC) into the catalytic domain of DNMT3A, and the detailed potential energy surface of the seven-step reaction referring to methyl transfer. Our calculated potential energy barrier (22.51 kcal/mol) approximates the former experimental data (23.12 kcal/mol). The conformational change of the 5-methyl-cytosine (5mC) intermediate was found necessary in forming a four-water chain for the elimination step, which is unique to the other DNMTs. The biological assembly facilitates the creation of such a water chain, and the elimination occurs in an asynchronized mechanism in the two catalytic pockets. We anticipate the findings can enable a better understanding of the general mechanisms of the de novo methyl transfer for fulfilling the key enzymatic functions in epigenetics. And the unique elimination of DNMT3A might ignite novel methods for designing anti-cancer and tumor inhibitors of DNMTs.

MultiScale-CNN-4mCPred: a multi-scale CNN and adaptive embedding-based method for mouse genome DNA N4-methylcytosine prediction

N4-methylcytosine (4mC) is an important epigenetic mechanism, which regulates many cellular processes such as cell differentiation and gene expression. The knowledge about the 4mC sites is a key foundation to exploring its roles. Due to the limitation of techniques, precise detection of 4mC is still a challenging task. In this paper, we presented a multi-scale convolution neural network (CNN) and adaptive embedding-based computational method for predicting 4mC sites in mouse genome, which was referred to as MultiScale-CNN-4mCPred. The MultiScale-CNN-4mCPred used adaptive embedding to encode nucleotides, and then utilized multi-scale CNNs as well as long short-term memory to extract more in-depth local properties and contextual semantics in the sequences. The MultiScale-CNN-4mCPred is an end-to-end learning method, which requires no sophisticated feature design. The MultiScale-CNN-4mCPred reached an accuracy of 81.66% in the 10-fold cross-validation, and an accuracy of 84.69% in the independent test, outperforming state-of-the-art methods. We implemented the proposed method into a user-friendly web application which is freely available at: http://www.biolscience.cn/MultiScale-CNN-4mCPred/ .

Capture Methylation-Sensitive Restriction Enzyme Sequencing (Capture MRE-Seq) for Methylation Analysis of Highly Degraded DNA Samples

Understanding the impact of DNA methylation within different disease contexts often requires accurate assessment of these modifications in a genome-wide fashion. Frequently, patient-derived tissues stored in long-term hospital tissue banks have been preserved using formalin-fixation paraffin-embedding (FFPE). While these samples can comprise valuable resources for studying disease, the fixation process ultimately compromises the DNA's integrity and leads to degradation. Degraded DNA can complicate CpG methylome profiling using traditional techniques, particularly when performing methylation-sensitive restriction enzyme sequencing (MRE-seq), yielding high backgrounds and resulting in lowered library complexity. Here, we describe Capture MRE-seq, a new MRE-seq protocol tailored to preserving unmethylated CpG information when using samples with highly degraded DNA. The results using Capture MRE-seq correlate well (0.92) with traditional MRE-seq calls when profiling non-degraded samples, and can recover unmethylated regions in highly degraded samples when traditional MRE-seq fails, which we validate using bisulfite sequencing-based data (WGBS) as well as methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq).

A method to build extended sequence context models of point mutations and indels

The mutation rate of a specific position in the human genome depends on the sequence context surrounding it. Modeling the mutation rate by estimating a rate for each possible k-mer, however, only works for small values of k since the data becomes too sparse for larger values of k. Here we propose a new method that solves this problem by grouping similar k-mers. We refer to the method as k-mer pattern partition and have implemented it in a software package called kmerPaPa. We use a large set of human de novo mutations to show that this new method leads to improved prediction of mutation rates and makes it possible to create models using wider sequence contexts than previous studies. As the first method of its kind, it does not only predict rates for point mutations but also insertions and deletions. We have additionally created a software package called Genovo that, given a k-mer pattern partition model, predicts the expected number of synonymous, missense, and other functional mutation types for each gene. Using this software, we show that the created mutation rate models increase the statistical power to detect genes containing disease-causing variants and to identify genes under strong selective constraint.

ALKBH4 Stabilization Is Required for Arsenic-Induced 6mA DNA Methylation Inhibition, Keratinocyte Malignant Transformation, and Tumorigenicity

Inorganic arsenic is one of the well-known human skin carcinogens. However, the molecular mechanism by which arsenic promotes carcinogenesis remains unclear. Previous studies have established that epigenetic changes, including changes in DNA methylation, are among the critical mechanisms that drive carcinogenesis. N6-methyladenine (6mA) methylation on DNA is a widespread epigenetic modification that was initially found on bacterial and phage DNA. Only recently has 6mA been identified in mammalian genomes. However, the function of 6mA in gene expression and cancer development is not well understood. Here, we show that chronic low doses of arsenic induce malignant transformation and tumorigenesis in keratinocytes and lead to the upregulation of ALKBH4 and downregulation of 6mA on DNA. We found that reduced 6mA levels in response to low levels of arsenic were mediated by the upregulation of the 6mA DNA demethylase ALKBH4. Moreover, we found that arsenic increased ALKBH4 protein levels and that ALKBH4 deletion impaired arsenic-induced tumorigenicity in vitro and in mice. Mechanistically, we found that arsenic promoted ALKBH4 protein stability through reduced autophagy. Together, our findings reveal that the DNA 6mA demethylaseALKBH4 promotes arsenic tumorigenicity and establishes ALKBH4 as a promising target for arsenic-induced tumorigenesis.

Enhancer RNAs step forward: new insights into enhancer function

Enhancers confer precise spatiotemporal patterns of gene expression in response to developmental and environmental stimuli. Over the last decade, the transcription of enhancer RNAs (eRNAs) – nascent RNAs transcribed from active enhancers – has emerged as a key factor regulating enhancer activity. eRNAs are relatively short-lived RNA species that are transcribed at very high rates but also quickly degraded. Nevertheless, eRNAs are deeply intertwined within enhancer regulatory networks and are implicated in a number of transcriptional control mechanisms. Enhancers show changes in function and sequence over evolutionary time, raising questions about the relationship between enhancer sequences and eRNA function. Moreover, the vast majority of single nucleotide polymorphisms associated with human complex diseases map to the non-coding genome, with causal disease variants enriched within enhancers. In this Primer, we survey the diverse roles played by eRNAs in enhancer-dependent gene expression, evaluating different models for eRNA function. We also explore questions surrounding the genetic conservation of enhancers and how this relates to eRNA function and dysfunction.

Summary: This Primer evaluates the ideas that underpin developing models for eRNA function, exploring cases in which perturbed eRNA function contributes to disease.

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

As one of the most prevalent post-transcriptional epigenetic modifications, N5-methylcytosine (m5C) plays an essential role in various cellular processes and disease pathogenesis. Therefore, it is important accurately identify m5C modifications in order to gain a deeper understanding of cellular processes and other possible functional mechanisms. Although a few computational methods have been proposed, their respective models have been developed using small training datasets. Hence, their practical application is quite limited in genome-wide detection. To overcome the existing limitations, we propose Deepm5C, a bioinformatics method for identifying RNA m5C sites throughout the human genome. To develop Deepm5C, we constructed a novel benchmarking dataset and investigated a mixture of three conventional feature-encoding algorithms and a feature derived from word-embedding approaches. Afterward, four variants of deep-learning classifiers and four commonly used conventional classifiers were employed and trained with the four encodings, ultimately obtaining 32 baseline models. A stacking strategy is effectively utilized by integrating the predicted output of the optimal baseline models and trained with a one-dimensional (1D) convolutional neural network. As a result, the Deepm5C predictor achieved excellent performance during cross-validation with a Matthews correlation coefficient and an accuracy of 0.697 and 0.855, respectively. The corresponding metrics during the independent test were 0.691 and 0.852, respectively. Overall, Deepm5C achieved a more accurate and stable performance than the baseline models and significantly outperformed the existing predictors, demonstrating the effectiveness of our proposed hybrid framework. Furthermore, Deepm5C is expected to assist community-wide efforts in identifying putative m5Cs and to formulate the novel testable biological hypothesis.

Substitution rate heterogeneity across hexanucleotide contexts in noncoding chloroplast DNA

Substitutions between closely related noncoding chloroplast DNA sequences are studied with respect to the composition of the 3 bases on each side of the substitution, that is the hexanucleotide context. There is about 100-fold variation in rate, among the contexts, particularly on substitutions of A and T. Rate heterogeneity of transitions differs from that of transversions, resulting in a more than 200-fold variation in the transitions: transversion bias. The data are consistent with a CpG effect, and it is shown that both the A + T content and the arrangement of purines/pyrimidines along the same DNA strand are correlated with rate variation. Expected equilibrium A + T content ranges from 36.4% to 82.8% across contexts, while G–C skew ranges from −77.4 to 72.2 and A–T skew ranges from −63.9 to 68.2. The predicted equilibria are associated with specific features of the content of the hexanucleotide context, and also show close agreement with the observed context-dependent compositions. Finally, by controlling for the content of nucleotides closer to the substitution site, it is shown that both the third and fourth nucleotide removed on each side of the substitution directly influence substitution dynamics at that site. Overall, the results demonstrate that noncoding sites in different contexts are evolving along very different evolutionary trajectories and that substitution dynamics are far more complex than typically assumed. This has important implications for a number of types of sequence analysis, particularly analyses of natural selection, and the context-dependent substitution matrices developed here can be applied in future analyses.

An Interplay between Epigenetics and Translation in Oocyte Maturation and Embryo Development: Assisted Reproduction Perspective

Germ cell quality is a key prerequisite for successful fertilization and early embryo development. The quality is determined by the fine regulation of transcriptomic and proteomic profiles, which are prone to alteration by assisted reproduction technology (ART)-introduced in vitro methods. Gaining evidence shows the ART can influence preset epigenetic modifications within cultured oocytes or early embryos and affect their developmental competency. The aim of this review is to describe ART-determined epigenetic changes related to the oogenesis, early embryogenesis, and further in utero development. We confront the latest epigenetic, related epitranscriptomic, and translational regulation findings with the processes of meiotic maturation, fertilization, and early embryogenesis that impact the developmental competency and embryo quality. Post-ART embryo transfer, in utero implantation, and development (placentation, fetal development) are influenced by environmental and lifestyle factors. The review is emphasizing their epigenetic and ART contribution to fetal development. An epigenetic parallel among mouse, porcine, and bovine animal models and human ART is drawn to illustrate possible future mechanisms of infertility management as well as increase the awareness of the underlying mechanisms governing oocyte and embryo developmental complexity under ART conditions.

Hyb4mC: a hybrid DNA2vec-based model for DNA N4-methylcytosine sites prediction

BACKGROUND

DNA N4-methylcytosine is part of the restrictive modification system, which works by regulating some biological processes, for example, the initiation of DNA replication, mismatch repair and inactivation of transposon. However, using experimental methods to detect 4mC sites is time-consuming and expensive. Besides, considering the huge differences in the number of 4mC samples among different species, it is challenging to achieve a robust multi-species 4mC site prediction performance. Hence, it is of great significance to develop effective computational tools to identify 4mC sites.

RESULTS

This work proposes a flexible deep learning-based framework to predict 4mC sites, called Hyb4mC. Hyb4mC adopts the DNA2vec method for sequence embedding, which captures more efficient and comprehensive information compared with the sequence-based feature method. Then, two different subnets are used for further analysis: Hyb_Caps and Hyb_Conv. Hyb_Caps is composed of a capsule neural network and can generalize from fewer samples. Hyb_Conv combines the attention mechanism with a text convolutional neural network for further feature learning.

CONCLUSIONS

Extensive benchmark tests have shown that Hyb4mC can significantly enhance the performance of predicting 4mC sites compared with the recently proposed methods.

Gigantic genomes of salamanders indicate that body temperature, not genome size, is the driver of global methylation and 5-methylcytosine deamination in vertebrates

Transposable elements (TEs) are sequences that replicate and move throughout genomes, and they can be silenced through methylation of cytosines at CpG dinucleotides. TE abundance contributes to genome size, but TE silencing variation across genomes of different sizes remains underexplored. Salamanders include most of the largest C-values - 9 to 120 Gb. We measured CpG methylation levels in salamanders with genomes ranging from 2N = ∼58 Gb to 4N = ∼116 Gb. We compared these levels to results from endo- and ectothermic vertebrates with more typical genomes. Salamander methylation levels are approximately 90%, higher than all endotherms. However, salamander methylation does not differ from other ectotherms, despite an approximately 100-fold difference in nuclear DNA content. Because methylation affects the nucleotide compositional landscape through 5-methylcytosine deamination to thymine, we quantified salamander CpG dinucleotide levels and compared them to other vertebrates. Salamanders and other ectotherms have comparable CpG levels, and ectotherm levels are higher than endotherms. These data show no shift in global methylation at the base of salamanders, despite a dramatic increase in TE load and genome size. This result is reconcilable with previous studies that considered endothermy and ectothermy, which may be more important drivers of methylation in vertebrates than genome size.

Analysis and Performance Assessment of the Whole Genome Bisulfite Sequencing Data Workflow: Currently Available Tools and a Practical Guide to Advance DNA Methylation Studies

DNA methylation is associated with transcriptional repression, genomic imprinting, stem cell differentiation, embryonic development, and inflammation. Aberrant DNA methylation can indicate disease states, including cancer and neurological disorders. Therefore, the prevalence and location of 5-methylcytosine in the human genome is a topic of interest. Whole-genome bisulfite sequencing (WGBS) is a high-throughput method for analyzing DNA methylation. This technique involves library preparation, alignment, and quality control. Advancements in epigenetic technology have led to an increase in DNA methylation studies. This review compares the detailed experimental methodology of WGBS using accessible and up-to-date analysis tools. Practical codes for WGBS data processing are included as a general guide to assist progress in DNA methylation studies through a comprehensive case study.

The Role of MeCP2 in Regulating Synaptic Plasticity in the Context of Stress and Depression

Methyl-CpG-binding protein 2 (MeCP2) is a transcriptional regulator that is highly abundant in the brain. It binds to methylated genomic DNA to regulate a range of physiological functions implicated in neuronal development and adult synaptic plasticity. MeCP2 has mainly been studied for its role in neurodevelopmental disorders, but alterations in MeCP2 are also present in stress-related disorders such as major depression. Impairments in both stress regulation and synaptic plasticity are associated with depression, but the specific mechanisms underlying these changes have not been identified. Here, we review the interplay between stress, synaptic plasticity, and MeCP2. We focus our attention on the transcriptional regulation of important neuronal plasticity genes such as BDNF and reelin (RELN). Moreover, we provide evidence from recent studies showing a link between chronic stress-induced depressive symptoms and dysregulation of MeCP2 expression, underscoring the role of this protein in stress-related pathology. We conclude that MeCP2 is a promising target for the development of novel, more efficacious therapeutics for the treatment of stress-related disorders such as depression.

Modified cytosines versus cytosine in a DNA polymerase: retrieving thermodynamic and kinetic constants at the single molecule level

DNA methylation plays key roles in various areas, such as gene expression, regulation, epigenetics, and cancers. Since 5-methylcytosine (5mC) is commonly present in methylated DNA, characterizing the binding kinetics and thermodynamics of the nucleotide to the enzymatic pocket can help to understand the DNA replication process. Furthermore, 5-carboxycytosine (5caC) is a form that appears through the iterative oxidation of 5mC, and its effect on the DNA replication process is still not well known. Here, we immobilized a DNA polymerase (DNAP) with an orientation control on a tip of an atomic force microscope (AFM), and observed the interaction between the immobilized deoxyguanosine triphosphate (dGTP) on the surface and the DNAP in the presence of a DNA duplex. The interaction probability increased as the concentration of the DNA strand, and the affinity constant between the DNAP and DNA was obtained by fitting the change. Increasing the concentration of dGTP in solution diminished the interaction probability, and a fitting allowed us to retrieve the affinity constant between dGTP and the DNAP holding the DNA in the reaction pocket. Because the dissociation constant could be obtained through the loading rate dependence of the unbinding force value, both affinity and kinetic constants for cytosine (C), 5mC, and 5caC in the DNAP were compared in the light of the steric and electronic effect of the substituents at 5-position of cytosine.

Proteome-Wide Profiling of Readers for DNA Modification

DNA modifications, represented by 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC), play important roles in epigenetic regulation of biological processes. The specific recognition of DNA modifications by the transcriptional protein machinery is thought to be a potential mechanism for epigenetic-driven gene regulation, and many modified DNA-specific binding proteins have been uncovered. However, the panoramic view of the roles of DNA modification readers at the proteome level remains largely unclear. Here, a recently developed concatenated tandem array of consensus transcription factor (TF) response elements (catTFREs) approach is employed to profile the binding activity of TFs at DNA modifications. Modified DNA-binding activity is quantified for 1039 TFs, representing 70% of the TFs in the human genome. Additionally, the modified DNA-binding activity of 600 TFs is monitored during the mouse brain development from the embryo to the adult stages. Readers of these DNA modifications are predicted, and the hierarchical networks between the transcriptional protein machinery and modified DNA are described. It is further demonstrated that ZNF24 and ZSCAN21 are potential readers of 5fC-modified DNA. This study provides a landscape of TF-DNA modification interactions that can be used to elucidate the epigenetic-related transcriptional regulation mechanisms under physiological conditions.

Advances in mapping the epigenetic modifications of 5-methylcytosine (5mC), N6-methyladenine (6mA), and N4-methylcytosine (4mC)

DNA modification plays a pivotal role in regulating gene expression in cell development. As prevalent markers on DNA, 5-methylcytosine (5mC), N6-methyladenine (6mA), and N4-methylcytosine (4mC) can be recognized by specific methyltransferases, facilitating cellular defense and the versatile regulation of gene expression in eukaryotes and prokaryotes. Recent advances in DNA sequencing technology have permitted the positions of different modifications to be resolved at the genome-wide scale, which has led to the discovery of several novel insights into the complexity and functions of multiple methylations. In this review, we summarize differences in the various mapping approaches and discuss their pros and cons with respect to their relative read depths, speeds, and costs. We also discuss the development of future sequencing technologies and strategies for improving the detection resolution of current sequencing technologies. Lastly, we speculate on the potentially instrumental role that these sequencing technologies might play in future research.

An ancestral recombination graph of human, Neanderthal, and Denisovan genomes

Many humans carry genes from Neanderthals, a legacy of past admixture. Existing methods detect this archaic hominin ancestry within human genomes using patterns of linkage disequilibrium or direct comparison to Neanderthal genomes. Each of these methods is limited in sensitivity and scalability. We describe a new ancestral recombination graph inference algorithm that scales to large genome-wide datasets and demonstrate its accuracy on real and simulated data. We then generate a genome-wide ancestral recombination graph including human and archaic hominin genomes. From this, we generate a map within human genomes of archaic ancestry and of genomic regions not shared with archaic hominins either by admixture or incomplete lineage sorting. We find that only 1.5 to 7% of the modern human genome is uniquely human. We also find evidence of multiple bursts of adaptive changes specific to modern humans within the past 600,000 years involving genes related to brain development and function.

Silencing of Transposable Elements Mediated by 5-mC and Compensation of the Heterochromatin Content by Presence of B Chromosomes in Astyanax scabripinnis

The way in which transcriptional activity overcomes the physical DNA structure and gene regulation mechanisms involves complex processes that are not yet fully understood. Modifications in the cytosine-guanine sequence of DNA by 5-mC are preferentially located in heterochromatic regions and are related to gene silencing. Herein, we investigate evidence of epigenetic regulation related to the B chromosome model and transposable elements in A. scabripinnis. Indirect immunofluorescence using anti-5-mC to mark methylated regions was employed along with quantitative ELISA to determine the total genomic DNA methylation level. 5-mC signals were dispersed in the chromosomes of both females and males, with preferential accumulation in the B chromosome. In addition to the heterochromatic methylated regions, our results suggest that methylation is associated with transposable elements (LINE and Tc1-Mariner). Heterochromatin content was measured based on the C-band length in relation to the size of chromosome 1. The B chromosome in A. scabripinnis comprises heterochromatin located in the pericentromeric region of both arms of this isochromosome. In this context, individuals with B chromosomes should have an increased heterochromatin content when compared to individuals that do not. Although, both heterochromatin content and genome methylation showed no significant differences between sexes or in relation to the occurrence of B chromosomes. Our evidence suggests that the B chromosome can have a compensation effect on the heterochromatin content and that methylation possibly operates to silence TEs in A. scabripinnis. This represents a sui generis compensation and gene activity buffering mechanism.

The DNA methyltransferase DNMT3A contributes to autophagy long-term memory

Macroautophagy/autophagy is a conserved catabolic pathway that targets cytoplasmic components for their degradation and recycling in an autophagosome-dependent lysosomal manner. Under physiological conditions, this process maintains cellular homeostasis. However, autophagy can be stimulated upon different forms of cellular stress, ranging from nutrient starvation to exposure to drugs. Thus, this pathway can be seen as a central component of the integrated and adaptive stress response. Here, we report that even brief induction of autophagy is coupled in vitro to a persistent downregulation of the expression of MAP1LC3 isoforms, which are key components of the autophagy core machinery. In fact, DNA-methylation mediated by de novo DNA methyltransferase DNMT3A of MAP1LC3 loci upon autophagy stimulation leads to the observed long-term decrease of MAP1LC3 isoforms at transcriptional level. Finally, we report that the downregulation of MAP1LC3 expression can be observed in vivo in zebrafish larvae and mice exposed to a transient autophagy stimulus. This epigenetic memory of autophagy provides some understanding of the long-term effect of autophagy induction and offers a possible mechanism for its decline upon aging, pathological conditions, or in response to treatment interventions.Abbreviations: ACTB: actin beta; ATG: autophagy-related; 5-Aza: 5-aza-2'-deoxycytidine; BafA1: bafilomycin A1; CBZ: carbamazepine; CDKN2A: cyclin dependent kinase inhibitor 2A; ChIP: chromatin immunoprecipitation; Clon.: clonidine; CpG: cytosine-guanine dinucleotide: DMSO: dimethyl sulfoxide; DNA: deoxyribonucleic acid; DNMT: DNA methyltransferase; DNMT1: DNA methyltransferase 1; DNMT3A: DNA methyltransferase alpha; DNMT3B: DNA methyltransferase beta; dpf: days post-fertilization; EBSS: Earle's balanced salt solution; EM: Zebrafish embryo medium; GABARAP: GABA type A receptor associated protein; GABARAPL1: GABA type A receptor associated protein like 1; GABARAPL2: GABA type A receptor associated protein like 2; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GRO-Seq: Global Run-On sequencing; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; MAP1LC3A: microtubule-associated protein 1 light chain 3 alpha; MAP1LC3B: microtubule-associated protein 1 light chain 3 beta; MAP1LC3B2: microtubule-associated protein 1 light chain 3 beta 2; MEM: minimum essential medium; MEF: mouse embryonic fibroblasts; mRNA: messenger RNA; MTOR: mechanistic target of rapamycin kinase; PBS: phosphate-buffered saline; PIK3C3: phosphatidylinositol 3-kinase catalytic subunit type 3; RB1CC1/FIP200: RB1 inducible coiled-coil 1; RT-qPCR: quantitative reverse transcription polymerase chain reaction; SQSTM1/p62: sequestosome 1; Starv.: starvation; Treh.: trehalose; ULK1: unc-51 like autophagy activating kinase 1.

Extreme C-to-A Hypermutation at a Site of Cytosine-N4 Methylation

Mutation produces the raw material for adaptive evolution but also imposes a burden because most mutations are deleterious. The rate of mutation at a particular site is affected by a variety of factors.

Methylation of cytosine in DNA at position C5 increases the rate of C→T mutations in bacteria and eukaryotes. Methylation at the N4 position, employed by some restriction-modification systems, is not known to increase the mutation rate. Here, I report that a Salmonella enterica Type III restriction-modification system that includes a cytosine-N4 methyltransferase causes an enormous increase in the rate of mutation of the methylated cytosines, which occur at the overlined C in the motif CACC̅GT. Mutations consist mainly of C→A transversions, the rate of which is increased ∼500-fold by the restriction-modification system. The rate of C→T transitions is also increased and somewhat exceeds that at C5-methylated cytosines in Dcm sites. Two other Salmonella N4 methyltransferases investigated do not have such dramatic effects, although in one case there is a modest increase in C→A mutations along with an increase in C→T mutations. The sensitivity of the C→A rate to orientation with respect to both DNA replication and transcription is higher at hypermutable sites than at other cytosines, suggesting a fundamental mechanistic difference between hypermutation and ordinary mutation.

EvoLSTM: context-dependent models of sequence evolution using a sequence-to-sequence LSTM

Motivation

Accurate probabilistic models of sequence evolution are essential for a wide variety of bioinformatics tasks, including sequence alignment and phylogenetic inference. The ability to realistically simulate sequence evolution is also at the core of many benchmarking strategies. Yet, mutational processes have complex context dependencies that remain poorly modeled and understood.

Results

We introduce EvoLSTM, a recurrent neural network-based evolution simulator that captures mutational context dependencies. EvoLSTM uses a sequence-to-sequence long short-term memory model trained to predict mutation probabilities at each position of a given sequence, taking into consideration the 14 flanking nucleotides. EvoLSTM can realistically simulate mammalian and plant DNA sequence evolution and reveals unexpectedly strong long-range context dependencies in mutation probabilities. EvoLSTM brings modern machine-learning approaches to bear on sequence evolution. It will serve as a useful tool to study and simulate complex mutational processes.

Availability and implementation

Code and dataset are available at https://github.com/DongjoonLim/EvoLSTM.

Supplementary information

Supplementary data are available at Bioinformatics online.

Analysis and annotation of DNA methylation in two nonhuman primate species using the Infinium Human Methylation 450K and EPIC BeadChips

Aim: Nonhuman primates are essential for research on many human diseases. The Infinium Human Methylation450/EPIC BeadChips are popular tools for the study of the methylation state across the human genome at affordable cost. Methods: We performed a precise evaluation and re-annotation of the BeadChip probes for the analysis of genome-wide DNA methylation patterns in rhesus macaques and African green monkeys through in silico analyses combined with functional validation by pyrosequencing. Results: Up to 165,847 of the 450K and 261,545 probes of the EPIC BeadChip can be reliably used. The annotation files are provided in a format compatible with a variety of standard bioinformatic pipelines. Conclusion: Our study will facilitate high-throughput DNA methylation analyses in Macaca mulatta and Chlorocebus sabaeus.

Molecular Aspects of Senescence and Organismal Ageing-DNA Damage Response, Telomeres, Inflammation and Chromatin

Cells can become senescent in response to stress. Senescence is a process characterised by a stable proliferative arrest. Sometimes it can be beneficial—for example, it can suppress tumour development or take part in tissue repair. On the other hand, studies show that it is also involved in the ageing process. DNA damage response (DDR) is triggered by DNA damage or telomere shortening during cell division. When left unresolved, it may lead to the activation of senescence. Senescent cells secrete certain proteins in larger quantities. This phenomenon is referred to as senescence-associated secretory phenotype (SASP). SASP can induce senescence in other cells; evidence suggests that overabundance of senescent cells contributes to ageing. SASP proteins include proinflammatory cytokines and metalloproteinases, which degrade the extracellular matrix. Shortening of telomeres is another feature associated with organismal ageing. Older organisms have shorter telomeres. Restoring telomerase activity in mice not only slowed but also partially reversed the symptoms of ageing. Changes in chromatin structure during senescence include heterochromatin formation or decondensation and loss of H1 histones. During organismal ageing, cells can experience heterochromatin loss, DNA demethylation and global histone loss. Cellular and organismal ageing are both complex processes with many aspects that are often related. The purpose of this review is to bring some of these aspects forward and provide details regarding them.

Effect of fluoride in drinking water on the level of 5-methylcytosine in human and rat blood

DNA methylation is an epigenetic modification of genome that is involved in many human diseases. Recent studies revealed DNA methylation may be associated with fluorosis. This study was aimed to evaluate the dose-response effect of fluoride on DNA methylation in human and rat blood. A commercial ELISA kit was employed to evaluate 5-methylcytosine (5-mC) level of genome in human and rat blood. A total of 281 subjects were enrolled in this study and divided into four equal-size groups by the quartile of fluoride in drinking water. The difference of 5-mC among the four groups was significant. The U-shaped relationship was found between fluoride and 5-mC in the population. The U-shaped curve was also observed in the rats with three months of fluoride treatments. Taken together, these results clue the disruption of DNA methylation in mammals may has a certain association with fluoride in natural exposures.

Distinct nucleotide patterns among three subgenomes of bread wheat and their potential origins during domestication after allopolyploidization

BACKGROUND

The speciation and fast global domestication of bread wheat have made a great impact on three subgenomes of bread wheat. DNA base composition is an essential genome feature, which follows the individual-strand base equality rule and [AT]-increase pattern at the genome, chromosome, and polymorphic site levels among thousands of species. Systematic analyses on base compositions of bread wheat and its wild progenitors could facilitate further understanding of the evolutionary pattern of genome/subgenome-wide base composition of allopolyploid species and its potential causes.

RESULTS

Genome/subgenome-wide base-composition patterns were investigated by using the data of polymorphic site in 93 accessions from worldwide populations of bread wheat, its diploid and tetraploid progenitors, and their corresponding reference genome sequences. Individual-strand base equality rule and [AT]-increase pattern remain in recently formed hexaploid species bread wheat at the genome, subgenome, chromosome, and polymorphic site levels. However, D subgenome showed the fastest [AT]-increase across polymorphic site from Aegilops tauschii to bread wheat than that on A and B subgenomes from wild emmer to bread wheat. The fastest [AT]-increase could be detected almost all chromosome windows on D subgenome, suggesting different mechanisms between D and other two subgenomes. Interestingly, the [AT]-increase is mainly contributed by intergenic regions at non-selective sweeps, especially the fastest [AT]-increase of D subgenome. Further transition frequency and sequence context analysis indicated that three subgenomes shared same mutation type, but D subgenome owns the highest mutation rate on high-frequency mutation type. The highest mutation rate on D subgenome was further confirmed by using a bread-wheat-private SNP set. The exploration of loci/genes related to the [AT] value of D subgenome suggests the fastest [AT]-increase of D subgenome could be involved in DNA repair systems distributed on three subgenomes of bread wheat.

CONCLUSIONS

The highest mutation rate is detected on D subgenome of bread wheat during domestication after allopolyploidization, leading to the fastest [AT]-increase pattern of D subgenome. The phenomenon may come from the joint action of multiple repair systems inherited from its wild progenitors.

Divergent genes in gerbils: prevalence, relation to GC-biased substitution, and phenotypic relevance

Background

Two gerbil species, sand rat (Psammomys obesus) and Mongolian jird (Meriones unguiculatus), can become obese and show signs of metabolic dysregulation when maintained on standard laboratory diets. The genetic basis of this phenotype is unknown. Recently, genome sequencing has uncovered very unusual regions of high guanine and cytosine (GC) content scattered across the sand rat genome, most likely generated by extreme and localized biased gene conversion. A key pancreatic transcription factor PDX1 is encoded by a gene in the most extreme GC-rich region, is remarkably divergent and exhibits altered biochemical properties. Here, we ask if gerbils have proteins in addition to PDX1 that are aberrantly divergent in amino acid sequence, whether they have also become divergent due to GC-biased nucleotide changes, and whether these proteins could plausibly be connected to metabolic dysfunction exhibited by gerbils.

Results

We analyzed ~ 10,000 proteins with 1-to-1 orthologues in human and rodents and identified 50 proteins that accumulated unusually high levels of amino acid change in the sand rat and 41 in Mongolian jird. We show that more than half of the aberrantly divergent proteins are associated with GC biased nucleotide change and many are in previously defined high GC regions. We highlight four aberrantly divergent gerbil proteins, PDX1, INSR, MEDAG and SPP1, that may plausibly be associated with dietary metabolism.

Conclusions

We show that through the course of gerbil evolution, many aberrantly divergent proteins have accumulated in the gerbil lineage, and GC-biased nucleotide substitution rather than positive selection is the likely cause of extreme divergence in more than half of these. Some proteins carry putatively deleterious changes that could be associated with metabolic and physiological phenotypes observed in some gerbil species. We propose that these animals provide a useful model to study the ‘tug-of-war’ between natural selection and the excessive accumulation of deleterious substitutions mutations through biased gene conversion.

Aggressive PDACs Show Hypomethylation of Repetitive Elements and the Execution of an Intrinsic IFN Program Linked to a Ductal Cell of Origin

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive desmoplasia, which challenges the molecular analyses of bulk tumor samples. Here we FACS-purified epithelial cells from human PDAC and normal pancreas and derived their genome-wide transcriptome and DNA methylome landscapes. Clustering based on DNA methylation revealed two distinct PDAC groups displaying different methylation patterns at regions encoding repeat elements. Methylation^low tumors are characterized by higher expression of endogenous retroviral transcripts and double-stranded RNA sensors, which lead to a cell-intrinsic activation of an interferon signature (IFNsign). This results in a protumorigenic microenvironment and poor patient outcome. Methylation^low/IFNsign^high and Methylation^high/IFNsign^low PDAC cells preserve lineage traits, respective of normal ductal or acinar pancreatic cells. Moreover, ductal-derived Kras ^G12D/Trp53 ^-/- mouse PDACs show higher expression of IFNsign compared with acinar-derived counterparts. Collectively, our data point to two different origins and etiologies of human PDACs, with the aggressive Methylation^low/IFNsign^high subtype potentially targetable by agents blocking intrinsic IFN signaling. SIGNIFICANCE: The mutational landscapes of PDAC alone cannot explain the observed interpatient heterogeneity. We identified two PDAC subtypes characterized by differential DNA methylation, preserving traits from normal ductal/acinar cells associated with IFN signaling. Our work suggests that epigenetic traits and the cell of origin contribute to PDAC heterogeneity.This article is highlighted in the In This Issue feature, p. 521.

Quantifying Influences on Intragenomic Mutation Rate

We report work to quantify the impact on the probability of human genome polymorphism both of recombination and of sequence context at different scales. We use population-based analyses of data on human genetic variants obtained from the public Ensembl database. For recombination, we calculate the variance due to recombination and the probability that a recombination event causes a mutation. We employ novel statistical procedures to take account of the spatial auto-correlation of recombination and mutation rates along the genome. Our results support the view that genomic diversity in recombination hotspots arises largely from a direct effect of recombination on mutation rather than predominantly from the effect of selective sweeps. We also use the statistic of variance due to context to compare the effect on the probability of polymorphism of contexts of various sizes. We find that when the 12 point mutations are considered separately, variance due to context increases significantly as we move from 3-mer to 5-mer and from 5-mer to 7-mer contexts. However, when all mutations are considered in aggregate, these differences are outweighed by the effect of interaction between the central base and its immediate neighbors. This interaction is itself dominated by the transition mutations, including, but not limited to, the CpG effect. We also demonstrate strand-asymmetry of contextual influence in intronic regions, which is hypothesized to be a result of transcription coupled DNA repair. We consider the extent to which the measures we have used can be used to meaningfully compare the relative magnitudes of the impact of recombination and context on mutation.

The role and mechanisms of DNA methylation in the oocyte

Epigenetic information in the mammalian oocyte has the potential to be transmitted to the next generation and influence gene expression; this occurs naturally in the case of imprinted genes. Therefore, it is important to understand how epigenetic information is patterned during oocyte development and growth. Here, we review the current state of knowledge of de novo DNA methylation mechanisms in the oocyte: how a distinctive gene-body methylation pattern is created, and the extent to which the DNA methylation machinery reads chromatin states. Recent epigenomic studies building on advances in ultra-low input chromatin profiling methods, coupled with genetic studies, have started to allow a detailed interrogation of the interplay between DNA methylation establishment and chromatin states; however, a full mechanistic description awaits.

Rapid Genomic and Epigenetic Alterations in Gynogenetic Carassius auratus Red Var. Derived from Distant Hybridization

Gynogenesis is an important reproductive mode in fish and is used fairly widely in genetic breeding. Gynogenetic offspring (2n = 100, abbreviated as GRCC) were generated through the distant hybridization of Carassius auratus red var. (2n = 100, RCC) (♀) × Megalobrama amblycephala (2n = 48, BSB) (♂), in which male and female individual both had normal gonadal development. To better understand genomic and epigenetic consequences of GRCC, fluorescence in situ hybridization, amplified fragment length polymorphism, and methylation-sensitive amplification polymorphism analysis were performed on GRCC and RCC. GRCC possess two sets of RCC-derived chromosomes and one to three microchromosomes, in which 30.44% of bands inherit these patterns from red crucian carp and blunt snout bream, and 24.12% of novel bands were found by amplified fragment length polymorphism analysis. In terms of methylation, the DNA methylation level of GRCC was lower than that of their parents, and 45.29% of methylation patterns in GRCC were altered compared with their parents. GRCC show a special genetic composition in the genome, in which genome-wide changes and the adjustment of DNA methylation levels and patterns occurred. The result revealed that genetic and epigenetic changes were rapidly triggered in gynogenetic fish that were derived from distant hybridization, showing a special genetic composition in the genome. This study provides new insights into fish genetic breeding and the evolutionary patterns of the vertebrate genome.

Hypomethylation Causes MIR21 Overexpression in Tumors

miR-21 is an oncogenic microRNA (miRNA) that is upregulated in many solid tumors. However, the effect of MIR21 hypomethylation on miR-21 expression in tumors and the mechanism of miR-21 DNA demethylation remain unclear. In this study, we confirmed that the expression of miR-21 was significantly increased in multiple tumors. We analyzed eight types of cancer, including breast cancer (BRCA), lung adenocarcinoma (LUAD), renal and renal clear cell carcinoma (KIRC), bladder urothelial carcinoma (BLCA), hepatocellular carcinoma (LIHC), lung squamous cell cancer (LUSC), renal papillary cell carcinoma (KIRP), and pancreatic adenocarcinoma (PAAD). MIR21 DNA methylation levels were elevated in these cancers. CpG loci located approximately 200 bp upstream of the transcription initiation site strongly affect MIR21 expression. We also confirmed MIR21 hypomethylation by pyrosequencing of fresh clear cell renal cell carcinoma (ccRCC) samples. Demethylating agent was proved to increase hsa-miR-21-5p level in HEK293T cells, while knockdown of DNA demethylases TET3 and TDG decreased MIR21 expression. In addition, we showed that the cg02515217 CpG locus in MIR21 promoter was a conserved binding site of transcription factors CEBPB, MEIS3, and TEAD4, which were co-expressed with miR-21 in tumors. These observations identified that gene hypomethylation regulated the expression of MIR21 in tumors.

A Method for Identification of the Methylation Level of CpG Islands From NGS Data

In the course of sample preparation for Next Generation Sequencing (NGS), DNA is fragmented by various methods. Fragmentation shows a persistent bias with regard to the cleavage rates of various dinucleotides. With the exception of CpG dinucleotides the previously described biases were consistent with results of the DNA cleavage in solution. Here we computed cleavage rates of all dinucleotides including the methylated CpG and unmethylated CpG dinucleotides using data of the Whole Genome Sequencing datasets of the 1000 Genomes project. We found that the cleavage rate of CpG is significantly higher for the methylated CpG dinucleotides. Using this information, we developed a classifier for distinguishing cancer and healthy tissues based on their CpG islands statuses of the fragmentation. A simple Support Vector Machine classifier based on this algorithm shows an accuracy of 84%. The proposed method allows the detection of epigenetic markers purely based on mechanochemical DNA fragmentation, which can be detected by a simple analysis of the NGS sequencing data.

Understanding epigenomics based on the rice model

The purpose of this paper provides a comprehensive overview of the recent researches on rice epigenomics, including DNA methylation, histone modifications, noncoding RNAs, and three-dimensional genomics. The challenges and perspectives for future research in rice are discussed. Rice as a model plant for epigenomic studies has much progressed current understanding of epigenetics in plants. Recent results on rice epigenome profiling and three-dimensional chromatin structure studies reveal specific features and implication in gene regulation during rice plant development and adaptation to environmental changes. Results on rice chromatin regulator functions shed light on mechanisms of establishment, recognition, and resetting of epigenomic information in plants. Cloning of several rice epialleles associated with important agronomic traits highlights importance of epigenomic variation in rice plant growth, fitness, and yield. In this review, we summarize and analyze recent advances in rice epigenomics and discuss challenges and directions for future research in the field.

Cytosine epigenetic modification modulates the formation of an unprecedented G4 structure in the WNT1 promoter

Time-resolved imino proton nuclear magnetic resonance spectra of the WT22m sequence d(GGGCCACCGGGCAGTGGGCGGG), derived from the WNT1 promoter region, revealed an intermediate G-quadruplex G4(I) structure during K⁺-induced conformational transition from an initial hairpin structure to the final G4(II) structure. Moreover, a single-base C-to-T mutation at either position C₄ or C₇ of WT22m could lock the intermediate G4(I) structure without further conformational change to the final G4(II) structure. Surprisingly, we found that the intermediate G4(I) structure is an atypical G4 structure, which differs from a typical hybrid G4 structure of the final G4(II) structure. Further studies of modified cytosine analogues associated with epigenetic regulation indicated that slight modification on a cytosine could modulate G4 structure. A simplified four-state transition model was introduced to describe such conformational transition and disclose the possible mechanism for G4 structural selection caused by cytosine modification.

N6-Deoxyadenosine Methylation in Mammalian Mitochondrial DNA

N⁶-Methyldeoxyadenosine (6mA) has recently been shown to exist and play regulatory roles in eukaryotic genomic DNA (gDNA). However, the biological functions of 6mA in mammals have yet to be adequately explored, largely due to its low abundance in most mammalian genomes. Here, we report that mammalian mitochondrial DNA (mtDNA) is enriched for 6mA. The level of 6mA in HepG2 mtDNA is at least 1,300-fold higher than that in gDNA under normal growth conditions, corresponding to approximately four 6mA modifications on each mtDNA molecule. METTL4, a putative mammalian methyltransferase, can mediate mtDNA 6mA methylation, which contributes to attenuated mtDNA transcription and a reduced mtDNA copy number. Mechanistically, the presence of 6mA could repress DNA binding and bending by mitochondrial transcription factor (TFAM). Under hypoxia, the 6mA level in mtDNA could be further elevated, suggesting regulatory roles for 6mA in mitochondrial stress response. Our study reveals DNA 6mA as a regulatory mark in mammalian mtDNA.