Advances in the profiling of DNA modifications: cytosine methylation and beyond

Joint single-cell profiling resolves 5mC and 5hmC and reveals their distinct gene regulatory effects

Oxidative modification of 5-methylcytosine (5mC) by ten-eleven translocation (TET) DNA dioxygenases generates 5-hydroxymethylcytosine (5hmC), the most abundant form of oxidized 5mC. Existing single-cell bisulfite sequencing methods cannot resolve 5mC and 5hmC, leaving the cell-type-specific regulatory mechanisms of TET and 5hmC largely unknown. Here, we present joint single-nucleus (hydroxy)methylcytosine sequencing (Joint-snhmC-seq), a scalable and quantitative approach that simultaneously profiles 5hmC and true 5mC in single cells by harnessing differential deaminase activity of APOBEC3A toward 5mC and chemically protected 5hmC. Joint-snhmC-seq profiling of single nuclei from mouse brains reveals an unprecedented level of epigenetic heterogeneity of both 5hmC and true 5mC at single-cell resolution. We show that cell-type-specific profiles of 5hmC or true 5mC improve multimodal single-cell data integration, enable accurate identification of neuronal subtypes and uncover context-specific regulatory effects on cell-type-specific genes by TET enzymes.

Unravelling epigenetic mechanisms in Cerastoderma edule genome: a comparison of healthy and neoplastic cockles

Cancer is a multifaceted genetic disease characterized by the acquisition of several essential hallmarks. Notably, certain cancers exhibit horizontal transmissibility, observed across mammalian species and diverse bivalves, the latter referred to as hemic neoplasia. Within this complex landscape, epigenetic mechanisms such as histone modifications and cytosine methylation emerge as fundamental contributors to the pathogenesis of these transmissible cancers. Our study delves into the epigenetic landscape of Cerastoderma edule, focusing on whole-genome methylation and hydroxymethylation profiles in heathy specimens and transmissible neoplasias by means of Nanopore long-read sequencing. Our results unveiled a global hypomethylation in the neoplastic specimens compared to their healthy counterparts, emphasizing the role of DNA methylation in these tumorigenic processes. Furthermore, we verified that intragenic CpG methylation positively correlated with gene expression, emphasizing its role in modulating transcription in healthy and neoplastic cockles, as also highlighted by some up-methylated oncogenic genes. Hydroxymethylation levels were significantly more elevated in the neoplastic samples, particularly within satellites and complex repeats, likely related to structural functions. Additionally, our analysis also revealed distinct methylation and activity patterns in retrotransposons, providing additional insights into bivalve neoplastic processes. Altogether, these findings contribute to understanding the epigenetic dynamics of bivalve neoplasias and shed light on the roles of DNA methylation and hydroxymethylation in tumorigenesis. Understanding these epigenetic alterations holds promise for advancing our broader understanding of cancer epigenetics.

Understanding the role of DNA methylation in colorectal cancer: Mechanisms, detection, and clinical significance

Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.

Construction of a glycosylation-mediated fluorescent biosensor for label-free measurement of site-specific 5-hydroxymethylcytosine in cancer cells with zero background signal

BACKGROUND

5-hydroxymethylcytosine (5hmC) as an epigenetic modification can regulate gene expression, and its abnormal level is related with various tumor invasiveness and poor prognosis. Nevertheless, the current methods for 5hmC assay usually involve expensive instruments/antibodies, radioactive risk, high background, laborious bisulfite treatment procedures, and non-specific/long amplification time.

RESULTS

We develop a glycosylation-mediated fluorescent biosensor based on helicase-dependent amplification (HDA) for label-free detection of site-specific 5hmC in cancer cells with zero background signal. The glycosylated 5hmC-DNA (5ghmC) catalyzed by β-glucosyltransferase (β-GT) can be cleaved by AbaSI restriction endonuclease to generate two dsDNA fragments with sticky ends. The resultant dsDNA fragments are complementary to the biotinylated probes and ligated by DNA ligases, followed by being captured by magnetic beads. After magnetic separation, the eluted ligation products act as the templates to initiate HDA reaction, generating abundant double-stranded DNA (dsDNA) products within 20 min. The dsDNA products are measured in a label-free manner with SYBR Green I as an indicator. This biosensor can measure 5hmC with a detection limit of 2.75 fM and a wide linear range from 1 × 10-14 to 1 × 10-8 M, and it can discriminate as low as 0.001% 5hmC level in complex mixture. Moreover, this biosensor can measure site-specific 5hmC in cancer cells, and distinguish tumor cells from normal cells.

SIGNIFICANCE

This biosensor can achieve a zero-background signal without the need of either 5hmC specific antibody or bisulfite treatment, and it holds potential applications in biological research and disease diagnosis.

Discovery of a Potent and Cell-Active Inhibitor of DNA 6mA Demethylase ALKBH1

N6-Methyladenine (6mA) of DNA has emerged as a novel epigenetic mark in eukaryotes, and several 6mA effector proteins have been identified. However, efforts to selectively inhibit the biological functions of these effector proteins with small molecules are unsuccessful to date. Here we report the first potent and selective small molecule inhibitor (13h) of AlkB homologue 1 (ALKBH1), the only validated 6mA demethylase. 13h showed an IC50 of 0.026 ± 0.013 μM and 1.39 ± 0.13 μM in the fluorescence polarization (FP) and enzyme activity assay, respectively, and a KD of 0.112 ± 0.017 μM in the isothermal titration calorimetry (ITC) assay. The potency of 13h was well explained by the cocrystal structure of the 13h-ALKBH1 complex. Furthermore, 13h displayed excellent selectivity for ALKBH1. In cells, compound 13h and its derivative 16 were able to engage ALKBH1 and modulate the 6mA levels. Collectively, our study identified the first potent, isoform selective, and cell-active ALKBH1 inhibitor, providing a tool compound for exploring the biological functions of ALKBH1 and DNA 6mA.

5-Hydroxymethylcytosine: the many faces of the sixth base of mammalian DNA

Epigenetic phenomena play a central role in cell regulatory processes and are important factors for understanding complex human disease. One of the best understood epigenetic mechanisms is DNA methylation. In the mammalian genome, cytosines (C) in CpG dinucleotides were long known to undergo methylation at the 5-position of the pyrimidine ring (mC). Later it was found that mC can be oxidized to 5-hydroxymethylcytosine (hmC) or even further to 5-formylcytosine (fC) and to 5-carboxylcytosine (caC) by the action of 2-oxoglutarate-dependent dioxygenases of the TET family. These findings unveiled a long elusive mechanism of active DNA demethylation and bolstered a wave of studies in the area of epigenetic regulation in mammals. This review is dedicated to critical assessment of recent data on biochemical and chemical aspects of the formation and conversion of hmC in DNA, analytical techniques used for detection and mapping of this nucleobase in mammalian genomes as well as epigenetic roles of hmC in DNA replication, transcription, cell differentiation and human disease.

Advances in cancer DNA methylation analysis with methPLIER: use of non-negative matrix factorization and knowledge-based constraints to enhance biological interpretability

DNA methylation is an epigenetic modification that results in dynamic changes during ontogenesis and cell differentiation. DNA methylation patterns regulate gene expression and have been widely researched. While tools for DNA methylation analysis have been developed, most of them have focused on intergroup comparative analysis within a dataset; therefore, it is difficult to conduct cross-dataset studies, such as rare disease studies or cross-institutional studies. This study describes a novel method for DNA methylation analysis, namely, methPLIER, which enables interdataset comparative analyses. methPLIER combines Pathway Level Information Extractor (PLIER), which is a non-negative matrix factorization (NMF) method, with regularization by a knowledge matrix and transfer learning. methPLIER can be used to perform intersample and interdataset comparative analysis based on latent feature matrices, which are obtained via matrix factorization of large-scale data, and factor-loading matrices, which are obtained through matrix factorization of the data to be analyzed. We used methPLIER to analyze a lung cancer dataset and confirmed that the data decomposition reflected sample characteristics for recurrence-free survival. Moreover, methPLIER can analyze data obtained via different preprocessing methods, thereby reducing distributional bias among datasets due to preprocessing. Furthermore, methPLIER can be employed for comparative analyses of methylation data obtained from different platforms, thereby reducing bias in data distribution due to platform differences. methPLIER is expected to facilitate cross-sectional DNA methylation data analysis and enhance DNA methylation data resources.

scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding

Dynamic compartmentalization of eukaryotic DNA into active and repressed states enables diverse transcriptional programs to arise from a single genetic blueprint, whereas its dysregulation can be strongly linked to a broad spectrum of diseases. While single-cell Hi-C experiments allow for chromosome conformation profiling across many cells, they are still expensive and not widely available for most labs. Here, we propose an alternate approach, scENCORE, to computationally reconstruct chromatin compartments from the more affordable and widely accessible single-cell epigenetic data. First, scENCORE constructs a long-range epigenetic correlation graph to mimic chromatin interaction frequencies, where nodes and edges represent genome bins and their correlations. Then, it learns the node embeddings to cluster genome regions into A/B compartments and aligns different graphs to quantify chromatin conformation changes across conditions. Benchmarking using cell-type-matched Hi-C experiments demonstrates that scENCORE can robustly reconstruct A/B compartments in a cell-type-specific manner. Furthermore, our chromatin confirmation switching studies highlight substantial compartment-switching events that may introduce substantial regulatory and transcriptional changes in psychiatric disease. In summary, scENCORE allows accurate and cost-effective A/B compartment reconstruction to delineate higher-order chromatin structure heterogeneity in complex tissues.

Generation of Whole-Genome Bisulfite Sequencing Libraries for Comprehensive DNA Methylome Analysis

Whole-genome bisulfite sequencing (WGBS) enables the detection of DNA methylation at a single base-pair resolution. The treatment of DNA with sodium bisulfite allows the discrimination of methylated and unmethylated cytosines, but the power of this technology can be limited by the input amounts of DNA and the length of DNA fragments due to DNA damage caused by the desulfonation process. Here, we describe a WGBS library preparation protocol that minimizes the loss and damage of DNA, generating high-quality libraries amplified with fewer polymerase chain reaction (PCR) cycles, and hence data with fewer PCR duplicates, from lower amounts of input material. Briefly, genomic DNA is sheared, end-repaired, 3'-adenylated, and ligated to adaptors with fewer clean-up steps in between, minimizing DNA loss. The adapter-ligated DNA is then treated with sodium bisulfite and amplified with a few PCR cycles to reach the yield needed for sequencing.

Inhibition of DNA and RNA methylation disturbs root development of moso bamboo

DNA methylation (5mC) and N6-methyladenosine (m6A) are two important epigenetics regulators, which have a profound impact on plant growth development. Phyllostachys edulis (P. edulis) is one of the fastest spreading plants due to its well-developed root system. However, the association between 5mC and m6A has seldom been reported in P. edulis. In particular, the connection between m6A and several post-transcriptional regulators remains uncharacterized in P. edulis. Here, our morphological and electron microscope observations showed the phenotype of increased lateral root under RNA methylation inhibitor (DZnepA) and DNA methylation inhibitor (5-azaC) treatment. RNA epitranscriptome based on Nanopore direct RNA sequencing revealed that DZnepA treatment exhibits significantly decreased m6A level in the 3'-untranslated region (3'-UTR), which was accompanied by increased gene expression, full-length ratio, higher proximal poly(A) site usage and shorter poly(A) tail length. DNA methylation levels of CG and CHG were reduced in both coding sequencing and transposable element upon 5-azaC treatment. Cell wall synthesis was impaired under methylation inhibition. In particular, differentially expressed genes showed a high percentage of overlap between DZnepA and 5-azaC treatment, which suggested a potential correlation between two methylations. This study provides preliminary information for a better understanding of the link between m6A and 5mC in root development of moso bamboo.

Comparative evaluation and analysis of DNA N4-methylcytosine methylation sites using deep learning

DNA N4-methylcytosine (4mC) is significantly involved in biological processes, such as DNA expression, repair, and replication. Therefore, accurate prediction methods are urgently needed. Deep learning methods have transformed applications that previously require sequencing expertise into engineering challenges that do not require expertise to solve. Here, we compare a variety of state-of-the-art deep learning models on six benchmark datasets to evaluate their performance in 4mC methylation site detection. We visualize the statistical analysis of the datasets and the performance of different deep-learning models. We conclude that deep learning can greatly expand the potential of methylation site prediction.

E-value: a superior alternative to P-value and its adjustments in DNA methylation studies

DNA methylation plays a crucial role in transcriptional regulation. Reduced representation bisulfite sequencing (RRBS) is a technique of increasing use for analyzing genome-wide methylation profiles. Many computational tools such as Metilene, MethylKit, BiSeq and DMRfinder have been developed to use RRBS data for the detection of the differentially methylated regions (DMRs) potentially involved in epigenetic regulations of gene expression. For DMR detection tools, as for countless other medical applications, P-values and their adjustments are among the most standard reporting statistics used to assess the statistical significance of biological findings. However, P-values are coming under increasing criticism relating to their questionable accuracy and relatively high levels of false positive or negative indications. Here, we propose a method to calculate E-values, as likelihood ratios falling into the null hypothesis over the entire parameter space, for DMR detection in RRBS data. We also provide the R package 'metevalue' as a user-friendly interface to implement E-value calculations into various DMR detection tools. To evaluate the performance of E-values, we generated various RRBS benchmarking datasets using our simulator 'RRBSsim' with eight samples in each experimental group. Our comprehensive benchmarking analyses showed that using E-values not only significantly improved accuracy, area under ROC curve and power, over that of P-values or adjusted P-values, but also reduced false discovery rates and type I errors. In applications using real RRBS data of CRL rats and a clinical trial on low-salt diet, the use of E-values detected biologically more relevant DMRs and also improved the negative association between DNA methylation and gene expression.

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.

Integrative mapping of the dog epigenome: Reference annotation for comparative intertissue and cross-species studies

Dogs have become a valuable model in exploring multifaceted diseases and biology relevant to human health. Despite large-scale dog genome projects producing high-quality draft references, a comprehensive annotation of functional elements is still lacking. We addressed this through integrative next-generation sequencing of transcriptomes paired with five histone marks and DNA methylome profiling across 11 tissue types, deciphering the dog's epigenetic code by defining distinct chromatin states, super-enhancer, and methylome landscapes, and thus showed that these regions are associated with a wide range of biological functions and cell/tissue identity. In addition, we confirmed that the phenotype-associated variants are enriched in tissue-specific regulatory regions and, therefore, the tissue of origin of the variants can be traced. Ultimately, we delineated conserved and dynamic epigenomic changes at the tissue- and species-specific resolutions. Our study provides an epigenomic blueprint of the dog that can be used for comparative biology and medical research.

Navigating the pitfalls of mapping DNA and RNA modifications

Chemical modifications to nucleic acids occur across the kingdoms of life and carry important regulatory information. Reliable high-resolution mapping of these modifications is the foundation of functional and mechanistic studies, and recent methodological advances based on next-generation sequencing and long-read sequencing platforms are critical to achieving this aim. However, mapping technologies may have limitations that sometimes lead to inconsistent results. Some of these limitations are technical in nature and specific to certain types of technology. Here, however, we focus on common (yet not always widely recognized) pitfalls that are shared among frequently used mapping technologies and discuss strategies to help technology developers and users mitigate their effects. Although the emphasis is primarily on DNA modifications, RNA modifications are also discussed.

The DNA cytosine methylome revealed two methylation motifs in the upstream regions of genes related to morphological and physiological differentiation in Streptomyces coelicolor A(3)2 M145

DNA methylation is an epigenetic modification detected in both prokaryotic and eukaryotic genomic DNAs. In bacteria, the importance of 5-methylcytosine (m5C) in gene expression has been less investigated than in eukaryotic systems. Through dot-blot analysis employing m5C antibodies against chromosomal DNA, we have previously demonstrated that m5C influences the differentiation of Streptomyces coelicolor A(3)2 M145 in solid sporulating and liquid non-sporulating complex media. Here, we mapped the methylated cytosines of the M145 strain growing in the defined Maltose Glutamate (MG) liquid medium. Sequencing of the M145 genome after bisulfite treatment (BS-sequencing) evidenced 3360 methylated cytosines and the two methylation motifs, GGCmCGG and GCCmCG, in the upstream regions of 321 genes. Besides, the role of cytosine methylation was investigated using the hypo-methylating agent 5'-aza-2'-deoxycytidine (5-aza-dC) in S. coelicolor cultures, demonstrating that m5C affects both growth and antibiotic biosynthesis. Finally, quantitative reverse-transcription polymerase-chain-reaction (RT-qPCR) analysis of genes containing the methylation motifs in the upstream regions showed that 5-aza-dC treatment influenced their transcriptional levels and those of the regulatory genes for two antibiotics. To the best of our knowledge, this is the first study that reports the cytosine methylome of S. coelicolor M145, supporting the crucial role ascribed to cytosine methylation in controlling bacterial gene expression.

Epigenetic analytical approaches in ecotoxicological aquatic research

Environmental epigenetics has become a key research focus in global climate change studies and environmental pollutant investigations impacting aquatic ecosystems. Specifically, triggered by environmental stress conditions, intergenerational DNA methylation changes contribute to biological adaptive responses and survival of organisms to increase their tolerance towards these conditions. To critically review epigenetic analytical approaches in ecotoxicological aquatic research, we evaluated 78 publications reported over the past five years (2016-2021) that applied these methods to investigate the responses of aquatic organisms to environmental changes and pollution. The results show that DNA methylation appears to be the most robust epigenetic regulatory mark studied in aquatic animals. As such, multiple DNA methylation analysis methods have been developed in aquatic organisms, including enzyme restriction digestion-based and methyl-specific immunoprecipitation methods, and bisulfite (in)dependent sequencing strategies. In contrast, only a handful of aquatic studies, i.e. about 15%, have been focusing on histone variants and post-translational modifications due to the lack of species-specific affinity based immunological reagents, such as specific antibodies for chromatin immunoprecipitation applications. Similarly, ncRNA regulation remains as the least popular method used in the field of environmental epigenetics. Insights into the opportunities and challenges of the DNA methylation and histone variant analysis methods as well as decreasing costs of next generation sequencing approaches suggest that large-scale epigenetic environmental studies in model and non-model organisms will soon become available in the near future. Moreover, antibody-dependent and independent methods, such as mass spectrometry-based methods, can be used as an alternative epigenetic approach to characterize global changes of chromatin histone modifications in future aquatic research. Finally, a systematic guide for DNA methylation and histone variant methods is offered for ecotoxicological aquatic researchers to select the most relevant epigenetic analytical approach in their research.

Induction of cytotoxic effects and changes in DNA methylation-related gene expression in a human fibroblast cell line by the metal-organic framework [H2NMe2]3 [Tb(III)(2,6 pyridinedicarboxylate)3] (Tb-MOF)

Lanthanide metal-organic frameworks (lanthanide MOFs) may be utilized for a variety of environmental and human health applications due to their luminescent properties and high thermal and water stability. However, the cytotoxic and epigenetic effects produced in human cells are not known. Therefore, we evaluated the cytotoxic effects, internalization, and changes in the mRNA abundance of DNA methylation and demethylation enzymes by exposing human fibroblast cells to a metal-organic framework [H₂NMe₂]₃ [Tb(III)(2,6 pyridinedicarboxylate)₃] (Tb-MOF). For this purpose, the cells were exposed to six concentrations (0.05 to 1.6 mg/mL) of Tb-MOF for 48 h. Field emission electron microscopy coupled to linear energy dispersive spectroscopy (FESEM‒EDS) and confocal microscopy analysis were performed. The cytotoxicity was determined with crystal violet and MTT assays. The results demonstrated the internalization of Tb-MOF at concentrations as low as 0.05 mg/mL, as well as concentration-dependent toxicity. Additionally, we detected significant changes in the gene expression levels of DNA methyltransferases and demethylases due to the presence of Tb-MOF, suggesting that Tb-MOF could generate epigenetic changes even at low concentrations. The results of our study may establish a foundation for future research attempting to develop and apply secure nanomaterials (e.g., MOFs) to minimize damage to the environment and human health.

Integrated analysis reveals common DNA methylation patterns of alcohol-associated cancers: A pan-cancer analysis

Background: The role of alcohol in carcinogenesis has received increasing attention in recent years. Evidence shows its impacts on various aspects, including epigenetics alteration. The DNA methylation patterns underlying alcohol-associated cancers are not fully understood. Methods: We investigated the aberrant DNA methylation patterns in four alcohol-associated cancers based on the Illumina HumanMethylation450 BeadChip. Pearson coefficient correlations were identified between differential methylated CpG probes and annotated genes. Transcriptional factor motifs were enriched and clustered using MEME Suite, and a regulatory network was constructed. Results: In each cancer, differential methylated probes (DMPs) were identified, and 172 hypermethylated and 21 hypomethylated pan-cancer DMPs (PDMPs) were examined further. Annotated genes significantly regulated by PDMPs were investigated and enriched in transcriptional misregulation in cancers. The CpG island chr19:58220189-58220517 was hypermethylated in all four cancers and silenced in the transcription factor ZNF154. Various biological effects were exerted by 33 hypermethylated and seven hypomethylated transcriptional factor motifs grouped into five clusters. Eleven pan-cancer DMPs were identified to be associated with clinical outcomes in the four alcohol-associated cancers, which might provide a potential point of view for clinical outcome prediction. Conclusion: This study provides an integrated insight into DNA methylation patterns in alcohol-associated cancers and reveals the corresponding features, influences, and potential mechanisms.

Single-cell DNA methylation sequencing by combinatorial indexing and enzymatic DNA methylation conversion

BACKGROUND

DNA methylation is a critical molecular mark involved in cellular differentiation and cell-specific processes. Single-cell whole genome DNA methylation profiling methods hold great potential to resolve the DNA methylation profiles of individual cell-types. Here we present a method that couples single-cell combinatorial indexing (sci) with enzymatic conversion (sciEM) of unmethylated cytosines.

RESULTS

The sciEM method facilitates DNA methylation profiling of single-cells that is highly correlated with single-cell bisulfite-based workflows (r² > 0.99) whilst improving sequencing alignment rates, reducing adapter contamination and over-estimation of DNA methylation levels (CpG and non-CpG). As proof-of-concept we perform sciEM analysis of the temporal lobe, motor cortex, hippocampus and cerebellum of the human brain to resolve single-cell DNA methylation of all major cell-types.

CONCLUSION

To our knowledge sciEM represents the first non-bisulfite single-cell DNA methylation sequencing approach with single-base resolution.

Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls

Cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) identifies genomic regions with DNA methylation, using a protocol adapted to work with low-input DNA samples and with cell-free DNA (cfDNA). We developed a set of synthetic spike-in DNA controls for cfMeDIP-seq to provide a simple and inexpensive reference for quantitative normalization. We designed 54 DNA fragments with combinations of methylation status (methylated and unmethylated), fragment length (80 bp, 160 bp, 320 bp), G + C content (35%, 50%, 65%), and fraction of CpG dinucleotides within the fragment (1/80 bp, 1/40 bp, 1/20 bp). Using 0.01 ng of spike-in controls enables training a generalized linear model that absolutely quantifies methylated cfDNA in MeDIP-seq experiments. It mitigates batch effects and corrects for biases in enrichment due to known biophysical properties of DNA fragments and other technical biases.

Simultaneous Dual-Site Identification of 5mC/8oG in DNA Triplex Using a Nanopore Sensor

DNA triplex participates in delivering site-specific epigenetic modifications critical for the regulation of gene expression. Among these marks, 5mC with 8oG functions comprehensively on gene expression. Recently, few research studies have emphasized the necessity of incorporation detection of 5mC with 8oG using one DNA triplex at the same time. Herein, DNA triplex structure was designed and tailored for the site-specific identification of 5mC with 8oG by means of nanopore electroanalysis. The identification was associated with the distinguishable current modulation types caused by DNA unzipping through the nanopore in an electrical field. Results demonstrated that the epigenetic modification proximity to the latch zone or constriction area of the nanopore enables differentiation of modification series at single nucleotide resolution in one DNA triplex, at both physiological and mildly acidic environment. In addition, our nanopore method enables the kinetic and thermodynamic studies to calculate the free energy of modified DNA triplex with applied potentials. Gibbs' energy provided the direct evidence that the DNA triplex with these epigenetic modifications is more stable in acidic environment. Considering modified DNA functions significantly in gene expression, the presented method may provide future opportunities to understand incorporating epigenetic mechanisms of many dysregulated biological processes on the basis of accurate detection.

Novel deoxyribonucleic acid methylation perturbations in workers exposed to vinyl chloride

To explore the epigenetic mechanism of deoxyribonucleic acid (DNA) damage induced by vinyl chloride (VC), we studied the micronuclei of peripheral blood lymphocytes in 193 subjects (92 in a VC exposure group employed in a chlorine-alkali plant; 101 in a control group employed in a power plant) and selected three pairs from the subjects (exposed and control) for whole-genome bisulfite sequencing (WGBS). The results showed that the rate of micronucleus formation in the VC exposure group was higher than that of control group (6.05 ± 3.28‰ vs. 2.01 ± 1.79‰). A total of 9534 differentially methylated regions (DMRs) were identified by WGBS, of which 4816 were hypomethylated and 4718 were hypermethylated. The Kyoto encyclopedia of genes and genomes (KEGG) pathway and gene ontology (GO) analyses showed the top three KEGG pathways were cancer , neuroactive ligand-receptor interaction, and axon guidance, and the top three GO-BP pathways enriched were multicellular organismal process, developmental process, and anatomical structure development. In the most enriched DMR pathway (pathways in cancer), we found that BCL2, TJP2, TAOK1, PFKFB3, LIPI, and LIPH were hypermethylated, and the methylation levels of BNIP1 and GRPEL2 were decreased. The methylation of differentially methylated genes (DMGs) mentioned above were verified by methylation-specific PCR (MSP) and agarose gel electrophoresis (AGE) in 50 pairs of subjects, where the coincidence rate was 60-100%. In conclusion, the epigenetic perturbations of specific DMGs (BCL2, TJP2, TAOK1, PFKFB3, LIPI, LIPH, BNIP1, and GRPEL2) may be associated with DNA damage from vinyl chloride exposure.

Wild epigenetics: insights from epigenetic studies on natural populations

Epigenetic mechanisms such as DNA methylation, histone modifications and non-coding RNAs are increasingly targeted in studies of natural populations. Here, I review some of the insights gained from this research, examine some of the methods currently in use and discuss some of the challenges that researchers working on natural populations are likely to face when probing epigenetic mechanisms. While studies supporting the involvement of epigenetic mechanisms in generating phenotypic variation in natural populations are amassing, many of these studies are currently correlative in nature. Thus, while empirical data point to widespread contributions of epigenetic mechanisms in generating phenotypic variation, there are still concerns as to whether epigenetic variation is instead ultimately controlled by genetic variation. Disentangling these two sources of variation will be a key to resolving the debate about the importance of epigenetic mechanisms, and studies on natural populations that partition the relative contribution of genetic and epigenetic factors to phenotypic variation can play an important role in this debate.

Comprehensive analysis reveals common DNA methylation patterns of tobacco-associated cancers: A pan-cancer analysis

The role of tobacco in carcinogenesis has received increasing attention across a number of disciplines in recent years. Accumulating evidences reveal that tobacco consumption affects various epigenetic modifications, especially DNA methylation. However, the genetic modifications of methylation patterns involved in tobacco-attributable cancers remain poorly understood. In this manuscript, aberrant DNA methylation patterns were investigated in 9 tobacco-attributable cancers. Differential methylated probes (DMPs) were identified in each cancer type and a total of 2,392 hyper- and 736 hypomethylated pan-cancer DMPs (PDMPs) were screened out for further analysis. PDMP-associated genes were mostly enriched in metabolism-associated pathways, suggesting the potential roles of methylation alternation in reprogramming cancer cell metabolism. Hypomethylated PDMPs cg12422154, cg02772121 and cg06051311 constituted an enhancer region, significantly downregulating TRIM15, TRIM26 and RPP21, which serve as epigenetically therapeutic biomarkers. Forty-three hypermethylated and 13 hypomethylated transcription factor motifs were clustered into 6 groups, and exhibited various biological functions. Forty-nine PDMPs were reported to be associated with prognosis, providing effective tools to predict clinical outcomes. In summary, our studies revealed the characteristics, influences and potential mechanisms of DNA methylation patterns of tobacco-attributable cancer.

Targeting Epigenetic Mechanisms to Treat Alcohol Use Disorders (AUD)

BACKGROUND

The impact of abusive alcohol consumption on human health is remarkable. According to the World Health Organization (WHO), approximately 3.3 million people die annually because of harmful alcohol consumption (the figure represents around 5.9% of global deaths). Alcohol Use Disorder (AUD) is a chronic disease where individuals exhibit compulsive alcohol drinking and present negative emotional states when they do not drink. In the most severe manifestations of AUD, the individuals lose control over intake despite a decided will to stop drinking. Given the multiple faces and the specific forms of this disease, the term AUD often appears in the plural (AUDs). Since only a few approved pharmacological treatments are available to treat AUD and they do not apply to all individuals or AUD forms, the search for compounds that may help to eliminate the burden of the disease and complement other therapeutical approaches is necessary.

METHODS

This work reviews recent research focused on the involvement of epigenetic mechanisms in the pathophysiology of AUD. Excessive drinking leads to chronic and compulsive consumption that eventually damages the organism. The central nervous system is a key target and is the focus of this study. The search for the genetic and epigenetic mechanisms behind the intricated dysregulation induced by ethanol will aid researchers in establishing new therapy approaches.

CONCLUSION

Recent findings in the field of epigenetics are essential and offer new windows for observation and research. The study of small molecules that inhibit key epienzymes involved in nucleosome architecture dynamics is necessary in order to prove their action and specificity in the laboratory and to test their effectivity and safety in clinical trials with selected patients bearing defined alterations caused by ethanol.

DNA methylation patterns at and beyond the histological margin of early-stage invasive lung adenocarcinoma radiologically manifested as pure ground-glass opacity

Background

Early-stage lung cancers radiologically manifested as ground-glass opacities (GGOs) have been increasingly identified, among which pure GGO (pGGO) has a good prognosis after local resection. However, the optimal surgical margin is still under debate. Precancerous lesions exist in tumor-adjacent tissues beyond the histological margin. However, potential precancerous epigenetic variation patterns beyond the histological margin of pGGO are yet to be discovered and described.

Results

A genome-wide high-resolution DNA methylation analysis was performed on samples collected from 15 pGGO at tumor core (TC), tumor edge (TE), para-tumor tissues at the 5 mm, 10 mm, 15 mm, 20 mm beyond the tumor, and peripheral normal (PN) tissue. TC and TE were tested with the same genetic alterations, which were also observed in histologically normal tissue at 5 mm in two patients with lower mutation allele frequency. According to the difference of methylation profiles between PN samples, 2284 methylation haplotype blocks (MHBs), 1657 differentially methylated CpG sites (DMCs), and 713 differentially methylated regions (DMRs) were identified using reduced representation bisulfite sequencing (RRBS). Two different patterns of methylation markers were observed: Steep (S) markers sharply changed at 5 mm beyond the histological margin, and Gradual (G) markers changed gradually from TC to PN. S markers composed 86.2% of the tumor-related methylation markers, and G markers composed the other 13.8%. S-marker-associated genes enriched in GO terms that were related to the hallmarks of cancer, and G-markers-associated genes enriched in pathways of stem cell pluripotency and transcriptional misregulation in cancer. Significant difference in DNA methylation score was observed between peripheral normal tissue and tumor-adjacent tissues 5 mm further from the histological margin (p < 0.001 in MHB markers). DNA methylation score at and beyond 10 mm from histological margin is not significantly different from peripheral normal tissues (p > 0.05 in all markers).

Conclusions

According to the methylation pattern observed in our study, it was implied that methylation alterations were not significantly different between tissues at or beyond P10 and distal normal tissues. This finding explained for the excellent prognosis from radical resections with surgical margins of more than 15 mm. The inclusion of epigenetic characteristics into surgical margin analysis may yield a more sensitive and accurate assessment of remnant cancerous and precancerous cells in the surgical margins.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01140-3.

DNA methylation and histone variants in aging and cancer

Aging-related diseases such as cancer can be traced to the accumulation of molecular disorder including increased DNA mutations and epigenetic drift. We provide a comprehensive review of recent results in mice and humans on modifications of DNA methylation and histone variants during aging and in cancer. Accumulated errors in DNA methylation maintenance lead to global decreases in DNA methylation with relaxed repression of repeated DNA and focal hypermethylation blocking the expression of tumor suppressor genes. Epigenetic clocks based on quantifying levels of DNA methylation at specific genomic sites is proving to be a valuable metric for estimating the biological age of individuals. Histone variants have specialized functions in transcriptional regulation and genome stability. Their concentration tends to increase in aged post-mitotic chromatin, but their effects in cancer are mainly determined by their specialized functions. Our increased understanding of epigenetic regulation and their modifications during aging has motivated interventions to delay or reverse epigenetic modifications using the epigenetic clocks as a rapid readout for efficacity. Similarly, the knowledge of epigenetic modifications in cancer is suggesting new approaches to target these modifications for cancer therapy.

Characterizing the properties of bisulfite sequencing data: maximizing power and sensitivity to identify between-group differences in DNA methylation

BACKGROUND

The combination of sodium bisulfite treatment with highly-parallel sequencing is a common method for quantifying DNA methylation across the genome. The power to detect between-group differences in DNA methylation using bisulfite-sequencing approaches is influenced by both experimental (e.g. read depth, missing data and sample size) and biological (e.g. mean level of DNA methylation and difference between groups) parameters. There is, however, no consensus about the optimal thresholds for filtering bisulfite sequencing data with implications for the reproducibility of findings in epigenetic epidemiology.

RESULTS

We used a large reduced representation bisulfite sequencing (RRBS) dataset to assess the distribution of read depth across DNA methylation sites and the extent of missing data. To investigate how various study variables influence power to identify DNA methylation differences between groups, we developed a framework for simulating bisulfite sequencing data. As expected, sequencing read depth, group size, and the magnitude of DNA methylation difference between groups all impacted upon statistical power. The influence on power was not dependent on one specific parameter, but reflected the combination of study-specific variables. As a resource to the community, we have developed a tool, POWEREDBiSeq, which utilizes our simulation framework to predict study-specific power for the identification of DNAm differences between groups, taking into account user-defined read depth filtering parameters and the minimum sample size per group.

CONCLUSIONS

Our data-driven approach highlights the importance of filtering bisulfite-sequencing data by minimum read depth and illustrates how the choice of threshold is influenced by the specific study design and the expected differences between groups being compared. The POWEREDBiSeq tool, which can be applied to different types of bisulfite sequencing data (e.g. RRBS, whole genome bisulfite sequencing (WGBS), targeted bisulfite sequencing and amplicon-based bisulfite sequencing), can help users identify the level of data filtering needed to optimize power and aims to improve the reproducibility of bisulfite sequencing studies.

Stories that can't be told by SNPs; DNA methylation variation in plant populations

Epigenetic variation has been observed in many plant populations. This variation can influence qualitative and quantitative traits. A key question is whether there is novel information in the epigenome that is not captured by SNP-based genetic markers. The answer likely varies depending on the sources and stability of epigenetic variation as well as the type of population being studied. We consider the epigenetic variation in several plant systems and how this relates to potential for hidden information that could increase our understanding of phenotypic variation.

Detection of 5-formylcytosine in Mitochondrial Transcriptome

Posttranscriptional RNA modifications have recently emerged as essential posttranscriptional regulators of gene expression. Here we present two methods for single nucleotide resolution detection of 5-formylcytosine (f⁵C) in RNA. The first relies on chemical protection of f⁵C against bisulfite treatment, the second method is based on chemical reduction of f⁵C to hm⁵C. In combination with regular bisulfite treatment of RNA, the methods allow for precise mapping of f⁵C. The protocol is used for f⁵C detection in mtDNA-encoded RNA, however, it can be straightforwardly applied for transcriptome-wide analyses.

Perspectives on studying molecular adaptations of amphibians in the genomic era

Understanding the genetic mechanisms underlying particular adaptations/phenotypes of organisms is one of the core issues of evolutionary biology. The use of genomic data has greatly advanced our understandings on this issue, as well as other aspects of evolutionary biology, including molecular adaptation, speciation, and even conservation of endangered species. Despite the well-recognized advantages, usages of genomic data are still limited to non-mammal vertebrate groups, partly due to the difficulties in assembling large or highly heterozygous genomes. Although this is particularly the case for amphibians, nonetheless, several comparative and population genomic analyses have shed lights into the speciation and adaptation processes of amphibians in a complex landscape, giving a promising hope for a wider application of genomics in the previously believed challenging groups of organisms. At the same time, these pioneer studies also allow us to realize numerous challenges in studying the molecular adaptations and/or phenotypic evolutionary mechanisms of amphibians. In this review, we first summarize the recent progresses in the study of adaptive evolution of amphibians based on genomic data, and then we give perspectives regarding how to effectively identify key pathways underlying the evolution of complex traits in the genomic era, as well as directions for future research.

Cell-Free DNA-Methylation-Based Methods and Applications in Oncology

Liquid biopsy based on cell-free DNA (cfDNA) enables non-invasive dynamic assessment of disease status in patients with cancer, both in the early and advanced settings. The analysis of DNA-methylation (DNAm) from cfDNA samples holds great promise due to the intrinsic characteristics of DNAm being more prevalent, pervasive, and cell- and tumor-type specific than genomics, for which established cfDNA assays already exist. Herein, we report on recent advances on experimental strategies for the analysis of DNAm in cfDNA samples. We describe the main steps of DNAm-based analysis workflows, including pre-analytics of cfDNA samples, DNA treatment, assays for DNAm evaluation, and methods for data analysis. We report on protocols, biomolecular techniques, and computational strategies enabling DNAm evaluation in the context of cfDNA analysis, along with practical considerations on input sample requirements and costs. We provide an overview on existing studies exploiting cell-free DNAm biomarkers for the detection and monitoring of cancer in early and advanced settings, for the evaluation of drug resistance, and for the identification of the cell-of-origin of tumors. Finally, we report on DNAm-based tests approved for clinical use and summarize their performance in the context of liquid biopsy.

Detection of preQ0 deazaguanine modifications in bacteriophage CAjan DNA using Nanopore sequencing reveals same hypermodification at two distinct DNA motifs

In the constant evolutionary battle against mobile genetic elements (MGEs), bacteria have developed several defense mechanisms, some of which target the incoming, foreign nucleic acids e.g. restriction-modification (R-M) or CRISPR-Cas systems. Some of these MGEs, including bacteriophages, have in turn evolved different strategies to evade these hurdles. It was recently shown that the siphophage CAjan and 180 other viruses use 7-deazaguanine modifications in their DNA to evade bacterial R-M systems. Among others, phage CAjan genome contains a gene coding for a DNA-modifying homolog of a tRNA-deazapurine modification enzyme, together with four 7-cyano-7-deazaguanine synthesis genes. Using the CRISPR-Cas9 genome editing tool combined with the Nanopore Sequencing (ONT) we showed that the 7-deazaguanine modification in the CAjan genome is dependent on phage-encoded genes. The modification is also site-specific and is found mainly in two separate DNA sequence contexts: GA and GGC. Homology modeling of the modifying enzyme DpdA provides insight into its probable DNA binding surface and general mode of DNA recognition.

A comprehensive evaluation of computational tools to identify differential methylation regions using RRBS data

DNA methylation plays a vital role in transcription regulation. Reduced representation bisulfite sequencing (RRBS) is becoming common for analyzing genome-wide methylation profiles at the single nucleotide level. A major goal of RRBS studies is to detect differentially methylated regions (DMRs) between different biological conditions. The previous tools to predict DMRs lack consistency. Here, we simulated RRBS datasets with significant attributes of real sequencing data under a wide range of scenarios, and systematically evaluated seven DMR detection tools in terms of type I error rate, precision/recall (PR), and area under ROC curve (AUC) using different methylation levels, sequencing coverage depth, length of DMRs, read length, and sample sizes. DMRfinder, methylSig, and methylKit were our preferred tools for RRBS data analysis, in terms of their AUC and PR curves. Our comparison highlights the different applicability of DMR detection tools and provides information to guide researchers towards the advancement of sequence-based DMR analysis.

Identification and validation of novel DNA methylation markers for early diagnosis of lung adenocarcinoma

Lung cancer has the highest mortality of all cancers worldwide. Epigenetic alterations have emerged as potential biomarkers for early diagnosis of various cancer tissue types. To identify methylation markers for early diagnosis of lung adenocarcinoma, we aimed to integrate genome‐wide DNA methylation and gene expression data from The Cancer Genome Atlas. To this end, we first examined the global DNA methylation pattern of lung adenocarcinoma and investigated the relationship between DNA methylation subtypes and clinical features. We then extracted differentially methylated and expressed genes, and adopted feature selection techniques to determine the final methylation markers. The performance of the markers in predicting lung adenocarcinoma was evaluated on three independent datasets from Gene Expression Omnibus. Protein levels of marker genes were validated by immunohistochemistry, and their biological function was further verified in vivo. We identified three novel methylation markers in lung adenocarcinoma including cg08032924, cg14823851, and cg19161124, mapping to CMTM2, TBX4, and DPP6, respectively. Validating these results on three independent datasets indicated that the three markers can achieve extremely high sensitivity and specificity in distinguishing lung adenocarcinoma from normal samples. Immunohistochemistry quantification results confirmed that markers are weakly expressed in human lung adenocarcinoma, and CMTM2 decreased tumor growth of mouse Lewis lung carcinoma in vivo. Overall, our study identified three novel methylation markers in lung adenocarcinoma which may contribute toward an improved diagnosis potentially leading to a better outcome for patients with lung adenocarcinoma.

BioMethyl: an R package for biological interpretation of DNA methylation data

Motivation

The accumulation of publicly available DNA methylation datasets has resulted in the need for tools to interpret the specific cellular phenotypes in bulk tissue data. Current approaches use either single differentially methylated CpG sites or differentially methylated regions that map to genes. However, these approaches may introduce biases in downstream analyses of biological interpretation, because of the variability in gene length. There is a lack of approaches to interpret DNA methylation effectively. Therefore, we have developed computational models to provide biological interpretation of relevant gene sets using DNA methylation data in the context of The Cancer Genome Atlas.

Results

We illustrate that Biological interpretation of DNA Methylation (BioMethyl) utilizes the complete DNA methylation data for a given cancer type to reflect corresponding gene expression profiles and performs pathway enrichment analyses, providing unique biological insight. Using breast cancer as an example, BioMethyl shows high consistency in the identification of enriched biological pathways from DNA methylation data compared to the results calculated from RNA sequencing data. We find that 12 out of 14 pathways identified by BioMethyl are shared with those by using RNA-seq data, with a Jaccard score 0.8 for estrogen receptor (ER) positive samples. For ER negative samples, three pathways are shared in the two enrichments with a slight lower similarity (Jaccard score = 0.6). Using BioMethyl, we can successfully identify those hidden biological pathways in DNA methylation data when gene expression profile is lacking.

Availability and implementation

BioMethyl R package is freely available in the GitHub repository (https://github.com/yuewangpanda/BioMethyl).

Supplementary information

Supplementary data are available at Bioinformatics online.

Translational Opportunities for Microfluidic Technologies to Enable Precision Epigenomics

Personalizing health care by taking genetic, environmental, and lifestyle factors into account is central to modern medicine. The crucial and pervasive roles epigenetic factors play in shaping gene-environment interactions are now well recognized. However, identifying robust epigenetic biomarkers and translating them to clinical tests has been difficult due in part to limitations of available platforms to detect epigenetic features genome-wide (epigenomic assays). This Feature introduces several important prospects for precision epigenomics, highlights capabilities and limitations of current laboratory technologies, and emphasizes opportunities for microfluidic tools to facilitate translation of epigenetic analyses to the clinic, with a particular focus on methods to profile gene-associated histone modifications and their impacts on chromatin structure and gene expression.

BpForms and BcForms: a toolkit for concretely describing non-canonical polymers and complexes to facilitate global biochemical networks

Non-canonical residues, caps, crosslinks, and nicks are important to many functions of DNAs, RNAs, proteins, and complexes. However, we do not fully understand how networks of such non-canonical macromolecules generate behavior. One barrier is our limited formats for describing macromolecules. To overcome this barrier, we develop BpForms and BcForms, a toolkit for representing the primary structure of macromolecules as combinations of residues, caps, crosslinks, and nicks. The toolkit can help omics researchers perform quality control and exchange information about macromolecules, help systems biologists assemble global models of cells that encompass processes such as post-translational modification, and help bioengineers design cells.

Epigenetic regulation in the pathophysiology of Lewy body dementia

Lewy body dementia encompasses both dementia with Lewy bodies and Parkinson's disease dementia. Although both are common causes of dementia, they remain relatively understudied. The review summarises the clinico-pathologic characteristics of Lewy Body dementia and discusses the genetic and environmental evidence contributing to the risk of developing the condition. Considering that the pathophysiology of Lewy body dementia is not yet fully understood, here we focus on the role of epigenetic mechanisms as potential key mediators of gene-environment interactions in the development of the disease. We examine available important data on genomics, epigenomics, gene expression and proteomic studies in Lewy body dementia on human post-mortem brain and peripheral tissues. Genetic variation and epigenetic modifications in key genes involved in the disorder, such as apolipoprotein E (APOE), α-synuclein (SNCA) and glucocerobrosidase (GBA), suggest a central involvement of epigenetics in DLB but conclusive evidence is scarce. This is due to limitations of existing literature, such as small sample sizes, lack of replication and lack of studies interrogating cell-type specific epigenetic modifications in the brain. Future research in the field can improve the understanding of this common but complex and rapidly progressing type of dementia and potentially open early diagnostic and effective therapeutic targets.

Quantitative comparison of within-sample heterogeneity scores for DNA methylation data

DNA methylation is an epigenetic mark with important regulatory roles in cellular identity and can be quantified at base resolution using bisulfite sequencing. Most studies are limited to the average DNA methylation levels of individual CpGs and thus neglect heterogeneity within the profiled cell populations. To assess this within-sample heterogeneity (WSH) several window-based scores that quantify variability in DNA methylation in sequencing reads have been proposed. We performed the first systematic comparison of four published WSH scores based on simulated and publicly available datasets. Moreover, we propose two new scores and provide guidelines for selecting appropriate scores to address cell-type heterogeneity, cellular contamination and allele-specific methylation. Most of the measures were sensitive in detecting DNA methylation heterogeneity in these scenarios, while we detected differences in susceptibility to technical bias. Using recently published DNA methylation profiles of Ewing sarcoma samples, we show that DNA methylation heterogeneity provides information complementary to the DNA methylation level. WSH scores are powerful tools for estimating variance in DNA methylation patterns and have the potential for detecting novel disease-associated genomic loci not captured by established statistics. We provide an R-package implementing the WSH scores for integration into analysis workflows.

The epigenetic modulation of alcohol/ethanol and cannabis exposure/co-exposure during different stages

Studies have reported the significant economic impact of smoking cannabis and drinking alcohol In the USA. It was estimated that the costs of cannabis-related treatment, hospitalization and loss of work-related pay have amounted to $200 billion. (Andersen AM, Dogan MV, Beach SRH, Philibert RA. 2015 Genes 6, 991-1022. ( doi:10.3390/genes6040991 )). Data from the National Epidemiologic Survey on Alcohol and Related Conditions showed that individuals with general anxiety disorder and substance use disorder (GAD-SUD) have higher psychiatric comorbidity rates than those without substance use disorder (Alegría AA, Hasin DS, Nunes EV, Liu SM, Davies C, Grant BF, Blanco C. 2010 J. Clin. Psychiatry 71, 1187-1195. ( doi:10.4088/JCP.09m05328gry )). Moreover, the criminal justice system is significantly impacted by this cost (Andersen AM, Dogan MV, Beach SRH, Philibert RA. 2015 Genes 6, 991-1022. ( doi:10.3390/genes6040991 )). Despite the increasing use of cannabis, there are still too many obscure facts. One of the new areas that scientific evidence shows is impacted negatively by cannabis use is the epigenome, which is an understudied area that we are still learning about. In addition, over the past few decades, we have seen various social and healthcare changes that have raised critical questions about their ongoing roles in regulating marijuana and alcohol use. This is important because of the increasing popularity and usage across various ages especially young adults and teenagers. More than 97.5 million Americans over 12 years old have used cannabis for non-medical use despite the significant side effects, with 1 in 10 users developing cannabis dependence (Crean RD, Crane NA, Mason BJ. 2011 J. Addict. Med. 5, 1-8. ( doi:10.1097/ADM.0b013e31820c23fa ), Office of Applied Studies. 2006 Substance Abuse and Mental Health Services Administration, USA.). It was reported that 16% of substance abuse admissions in the USA were for cannabis-related symptoms, which is second only to alcohol-related disorders (Agalioti T, Lomvardas S, Parekh B, Yie J, Maniatis T, Thanos D. 2000 Cell 103, 667-678. ( doi:10.1016/S0092-8674(00)00169-0 ), Soutoglou E, Talianidis I. 2002 Science 295, 1901-1904. ( doi:10.1126/science.1068356 )). Today there are thirty-one states and the District of Columbia that currently have legalized marijuana for either medical or recreational use. Data about marijuana use from NIAAA's National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) indicates that 'in total, 79 000 people were interviewed on alcohol and drug use. When examined by age young adults (ages 18-21) were found to be at highest risk for marijuana use and marijuana use disorder, with use increasing from 10.5 to 21.2% and disorder increasing from 4.4 to 7.5%'. 'Given these facts, George Koob, PhD, director of NIAAA stated the importance for the scientific community to convey this information to the public about the potential hazards of marijuana and it's use'. On the other hand, according to the National Institute on Alcohol Abuse and Alcoholism, 16 million adults suffer from alcohol use disorders. To the best of our knowledge, epigenetic mechanisms have been previously studied in alcohol and cannabis abuse separately. Recent studies highlighted the molecular mechanisms that are linked with drug-induced transcriptional regulation, behavioural abnormalities and neurodegeneration, which has emphasized the role of chromatin modification/remodelling in the generation of drug activation of certain genes and the disabling of others, and the effect of that on addiction (Maze I, Nestler EJ. 2011 Ann. N. Y. Acad. Sci. 1216, 99-113. ( doi:10.1111/j.1749-6632.2010.05893.x ); Renthal W, Nestler EJ. 2008 Trends Mol. Med. 14, 341-350. ( doi:10.1016/j.molmed.2008.06.004 )). In this review, we will give an overview of epigenome science relevant to cannabis/the endocannabinoid system and the potential of epigenetic overlap between alcohol and cannabinergic activity at different stages, to aid further investigations that could bring more treatment options to our horizon.

Epigenetics: Linking Early Postnatal Nutrition to Obesity Programming?

Despite constant research and public policy efforts, the obesity epidemic continues to be a major public health threat, and new approaches are urgently needed. It has been shown that nutrient imbalance in early life, from conception to infancy, influences later obesity risk, suggesting that obesity could result from "developmental programming". In this review, we evaluate the possibility that early postnatal nutrition programs obesity risk via epigenetic mechanisms, especially DNA methylation, focusing on four main topics: (1) the dynamics of epigenetic processes in key metabolic organs during the early postnatal period; (2) the epigenetic effects of alterations in early postnatal nutrition in animal models or breastfeeding in humans; (3) current limitations and remaining outstanding questions in the field of epigenetic programming; (4) candidate pathways by which early postnatal nutrition could epigenetically program adult body weight set point. A particular focus will be given to the potential roles of breast milk fatty acids, neonatal metabolic and hormonal milieu, and gut microbiota. Understanding the mechanisms by which early postnatal nutrition can promote lifelong metabolic modifications is essential to design adequate recommendations and interventions to "de-program" the obesity epidemic.

DNA methylation and gene expression profiles characterize epigenetic regulation of lncRNAs in colon adenocarcinoma

The long noncoding RNAs (lncRNAs) are associated with tumorigenesis and progression of cancer. While DNA methylation is a common epigenetic regulator of gene expression, the methylation of lncRNAs was rarely studied. To address this gap, we integrated DNA methylation and RNA-seq data to characterize the landscape of lncRNA methylation in colon adenocarcinoma (COAD). We collected and analyzed the lncRNA expression and methylation data from The Cancer Genome Atlas and Cancer Cell Line Encyclopedia to identify the epigenetically regulated lncRNAs. We further investigated the biological and clinical relevance of the identified lncRNAs via bioinformatics analysis. We identified 20 epigenetically upregulated lncRNAs in COAD, including several well-studied lncRNAs whose methylation regulation were poorly investigated, such as PVT1 and UCA1. We also revealed several novel tumor-associated lncRNAs in COAD, including GATA2-As1 and CYTOR. Next, we explored their biology function using gene set enrichment analysis and competitive endogenous RNA analysis. We characterized the methylation landscape of lncRNA in COAD and identified 20 epigenetically upregulated lncRNAs. Our findings will shed new light on the epigenetic regulation of lncRNA expression by DNA methylation.

D-GPM: A Deep Learning Method for Gene Promoter Methylation Inference

Whole-genome bisulfite sequencing generates a comprehensive profiling of the gene methylation levels, but is limited by a high cost. Recent studies have partitioned the genes into landmark genes and target genes and suggested that the landmark gene expression levels capture adequate information to reconstruct the target gene expression levels. This inspired us to propose that the methylation level of the promoters in landmark genes might be adequate to reconstruct the promoter methylation level of target genes, which would eventually reduce the cost of promoter methylation profiling. Here, we propose a deep learning model called Deep-Gene Promoter Methylation (D-GPM) to predict the whole-genome promoter methylation level based on the promoter methylation profile of the landmark genes from The Cancer Genome Atlas (TCGA). D-GPM-15%-7000 × 5, the optimal architecture of D-GPM, acquires the least overall mean absolute error (MAE) and the highest overall Pearson correlation coefficient (PCC), with values of 0.0329 and 0.8186, respectively, when testing data. Additionally, the D-GPM outperforms the regression tree (RT), linear regression (LR), and the support vector machine (SVM) in 95.66%, 92.65%, and 85.49% of the target genes by virtue of its relatively lower MAE and in 98.25%, 91.00%, and 81.56% of the target genes based on its relatively higher PCC, respectively. More importantly, the D-GPM predominates in predicting 79.86% and 78.34% of the target genes according to the model distribution of the least MAE and the highest PCC, respectively.

Genome-wide allele-specific methylation is enriched at gene regulatory regions in a multi-generation pedigree from the Norfolk Island isolate

Background

Allele-specific methylation (ASM) occurs when DNA methylation patterns exhibit asymmetry among alleles. ASM occurs at imprinted loci, but its presence elsewhere across the human genome is indicative of wider importance in terms of gene regulation and disease risk. Here, we studied ASM by focusing on blood-based DNA collected from 24 subjects comprising a 3-generation pedigree from the Norfolk Island genetic isolate. We applied a genome-wide bisulphite sequencing approach with a genotype-independent ASM calling method to map ASM across the genome. Regions of ASM were then tested for enrichment at gene regulatory regions using Genomic Association Test (GAT) tool.

Results

In total, we identified 1.12 M CpGs of which 147,170 (13%) exhibited ASM (P ≤ 0.05). When including contiguous ASM signal spanning ≥ 2 CpGs, this condensed to 12,761 ASM regions (AMRs). These AMRs tagged 79% of known imprinting regions and most (98.1%) co-localised with known single nucleotide variants. Notably, miRNA and lncRNA showed a 3.3- and 1.8-fold enrichment of AMRs, respectively (P < 0.005). Also, the 5′ UTR and start codons each showed a 3.5-fold enrichment of AMRs (P < 0.005). There was also enrichment of AMRs observed at subtelomeric regions of many chromosomes. Five out of 11 large AMRs localised to the protocadherin cluster on chromosome 5.

Conclusions

This study shows ASM extends far beyond genomic imprinting in humans and that gene regulatory regions are hotspots for ASM. Future studies of ASM in pedigrees should help to clarify transgenerational inheritance patterns in relation to genotype and disease phenotypes.

Air pollution and DNA methylation: effects of exposure in humans

Air pollution exposure is estimated to contribute to approximately seven million early deaths every year worldwide and more than 3% of disability-adjusted life years lost. Air pollution has numerous harmful effects on health and contributes to the development and morbidity of cardiovascular disease, metabolic disorders, and a number of lung pathologies, including asthma and chronic obstructive pulmonary disease (COPD). Emerging data indicate that air pollution exposure modulates the epigenetic mark, DNA methylation (DNAm), and that these changes might in turn influence inflammation, disease development, and exacerbation risk. Several traffic-related air pollution (TRAP) components, including particulate matter (PM), black carbon (BC), ozone (O₃), nitrogen oxides (NO_x), and polyaromatic hydrocarbons (PAHs), have been associated with changes in DNAm; typically lowering DNAm after exposure. Effects of air pollution on DNAm have been observed across the human lifespan, but it is not yet clear whether early life developmental sensitivity or the accumulation of exposures have the most significant effects on health. Air pollution exposure-associated DNAm patterns are often correlated with long-term negative respiratory health outcomes, including the development of lung diseases, a focus in this review. Recently, interventions such as exercise and B vitamins have been proposed to reduce the impact of air pollution on DNAm and health. Ultimately, improved knowledge of how exposure-induced change in DNAm impacts health, both acutely and chronically, may enable preventative and remedial strategies to reduce morbidity in polluted environments.