Combining MeDIP-seq and MRE-seq to investigate genome-wide CpG methylation

De novo non-canonical nanopore basecalling enables private communication using heavily-modified DNA data at single-molecule level

Hidden messages in DNA molecules by employing chemical modifications has been suggested for private data storage and transmission at high information density. However, rapidly decoding these "molecular keys" with corresponding basecallers remains challenging. We present DeepSME, a nanopore sequencing and deep-learning based framework towards single-molecule encryption, demonstrated by using 5-hydroxymethylcytosine (5hmC) substitution for individual nucleotide recognition rather than sequential interactions. This non-natural, motif-insensitive methylation disrupts ion current, resulting in a readout failure of 67.2%-100%, concealing the privacy within the DNAs. We further develop an alignment-free DeepSME basecaller as a key to reconstitute the digital information. Our three-stage training pipeline, expands k-mer size from 46 to 49, achieving over 92% precision and recall from scratch. DeepSME deciphers fully 5hmC concealed text and image within 16× coverage depth with an F1-score of 86.4%, surpassing all the state-of-the-art basecallers. Demonstrated on edge computing devices, DeepSME holds supreme potential for DNA-based private communications and broader bioengineering and medical applications.

Multi-scale DNA language model improves 6 mA binding sites prediction

DNA methylation at the N6 position of adenine (N6-methyladenine, 6 mA), which refers to the attachment of a methyl group to the N6 site of the adenine (A) of DNA, is an important epigenetic modification in prokaryotic and eukaryotic genomes. Accurately predicting the 6 mA binding sites can provide crucial insights into gene regulation, DNA repair, disease development and so on. Wet experiments are commonly used for analyzing 6 mA binding sites. However, they suffer from high cost and expensive time. Therefore, various deep learning methods have been widely used to predict 6 mA binding sites recently. In this study, we develop a framework based on multi-scale DNA language model named "iDNA6mA-MDL". "iDNA6mA-MDL" integrates multiple kmers and the nucleotide property and frequency method for feature embedding, which can capture a full range of DNA sequence context information. At the prediction stage, it also leverages DNABERT to compensate for the incomplete capture of global DNA information. Experiments show that our framework obtains average AUC of 0.981 on a classic 6 mA rice gene dataset, going beyond all existing advanced models under fivefold cross-validations. Moreover, "iDNA6mA-MDL" outperforms most of the popular state-of-the-art methods on another 11 6 mA datasets, demonstrating its effectiveness in 6 mA binding sites prediction.

Role of Epigenetic Factors in Determining the Biological Behavior and Prognosis of Hepatocellular Carcinoma

BACKGROUND

The current study's objective is to evaluate the molecular genetic mechanisms influencing the biological behavior of hepatocellular carcinoma (HCC) by analyzing the transcriptomic and epigenetic signatures of the tumors.

METHODS

Transcriptomic data were downloaded from the NCBI GEO database. We investigated the expression differences between the GSE46444 (48 cirrhotic tissues versus 88 HCC tissues) and GSE63898 (168 cirrhotic tissues versus 228 HCC tissues) data sets using GEO2R. Differentially expressed genes were evaluated using GO and KEGG metabolic pathway analysis websites. Whole genome bisulfite sequencing (WGBS) and Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq) data sets (26 HCC tissues versus 26 adjacent non-tumoral tissues) were also downloaded from the NCBI SRA database. These data sets were analyzed using Bismark and QSEA, respectively. The methylation differences between the groups were assessed using functional enrichment analysis.

RESULTS

In the GSE46444 data set, 80 genes were upregulated, and 315 genes were downregulated in the tumor tissue (HCC tissue) compared to the non-tumor cirrhotic tissue. In the GSE63898 data set, 1261 genes were upregulated, and 458 genes were downregulated in the cirrhotic tissue compared to the tumor tissues. WGBS revealed that 20 protein-coding loci were hypermethylated. while the hypomethylated regions were non-protein-coding. The methylated residues of the tumor tissue, non-tumorous cirrhotic tissue, and healthy tissue were comparable. MeDIP-Seq, conducted on tumoral and non-tumoral tissues, identified hypermethylated or hypomethylated areas as protein-coding regions. The functional enrichment analysis indicated that these genes were related to pathways including peroxisome, focal adhesion, mTOR, RAP1, Phospholipase D, Ras, and PI3K/AKT signal transduction.

CONCLUSIONS

The investigation of transcriptomic and epigenetic mechanisms identified several genes significant in the biological behavior of HCC. These genes present potential targets for the development of targeted therapy.

Emerging methylation-based approaches in microbiome engineering

Bacterial epigenetics, particularly through DNA methylation, exerts significant influence over various biological processes such as DNA replication, uptake, and gene regulation in bacteria. In this review, we explore recent advances in characterizing bacterial epigenomes, accompanied by emerging strategies that harness bacterial epigenetics to elucidate and engineer diverse bacterial species with precision and effectiveness. Furthermore, we delve into the potential of epigenetic modifications to steer microbial functions and influence community dynamics, offering promising opportunities for understanding and modulating microbiomes. Additionally, we investigate the extensive diversity of DNA methyltransferases and emphasize their potential utility in the context of the human microbiome. In summary, this review highlights the potential of DNA methylation as a powerful toolkit for engineering microbiomes.

Cis-regulatory evolution of the recently expanded Ly49 gene family

Comparative genomics has revealed the rapid expansion of multiple gene families involved in immunity. Members within each gene family often evolved distinct roles in immunity. However, less is known about the evolution of their epigenome and cis-regulation. Here we systematically profile the epigenome of the recently expanded murine Ly49 gene family that mainly encode either inhibitory or activating surface receptors on natural killer cells. We identify a set of cis-regulatory elements (CREs) for activating Ly49 genes. In addition, we show that in mice, inhibitory and activating Ly49 genes are regulated by two separate sets of proximal CREs, likely resulting from lineage-specific losses of CRE activity. Furthermore, we find that some Ly49 genes are cross-regulated by the CREs of other Ly49 genes, suggesting that the Ly49 family has begun to evolve a concerted cis-regulatory mechanism. Collectively, we demonstrate the different modes of cis-regulatory evolution for a rapidly expanding gene family.

The role of imprinting genes' loss of imprints in cancers and their clinical implications

Genomic imprinting plays an important role in the growth and development of mammals. When the original imprint status of these genes is lost, known as loss of imprinting (LOI), it may affect growth, neurocognitive development, metabolism, and even tumor susceptibility. The LOI of imprint genes has gradually been found not only as an early event in tumorigenesis, but also to be involved in progression. More than 120 imprinted genes had been identified in humans. In this review, we summarized the most studied LOI of two gene clusters and 13 single genes in cancers. We focused on the roles they played, that is, as growth suppressors and anti-apoptosis agents, sustaining proliferative signaling or inducing angiogenesis; the molecular pathways they regulated; and especially their clinical significance. It is notable that 12 combined forms of multi-genes' LOI, 3 of which have already been used as diagnostic models, achieved good sensitivity, specificity, and accuracy. In addition, the methods used for LOI detection in existing research are classified into detection of biallelic expression (BAE), differentially methylated regions (DMRs), methylation, and single-nucleotide polymorphisms (SNPs). These all indicated that the detection of imprinting genes' LOI has potential clinical significance in cancer diagnosis, treatment, and prognosis.

Untangling the gordian knot: The intertwining interactions between developmental hormone signaling and epigenetic mechanisms in insects

Hormones control developmental and physiological processes, often by regulating the expression of multiple genes simultaneously or sequentially. Crosstalk between hormones and epigenetics is pivotal to dynamically coordinate this process. Hormonal signals can guide the addition and removal of epigenetic marks, steering gene expression. Conversely, DNA methylation, histone modifications and non-coding RNAs can modulate regional chromatin structure and accessibility and regulate the expression of numerous (hormone-related) genes. Here, we provide a review of the interplay between the classical insect hormones, ecdysteroids and juvenile hormones, and epigenetics. We summarize the mode-of-action and roles of these hormones in post-embryonic development, and provide a general overview of epigenetic mechanisms. We then highlight recent advances on the interactions between these hormonal pathways and epigenetics, and their involvement in development. Furthermore, we give an overview of several 'omics techniques employed in the field. Finally, we discuss which questions remain unanswered and possible avenues for future research.

Profound DNA methylomic differences between single- and multi-fraction alpha irradiations of lung fibroblasts

BACKGROUND

Alpha (α)-radiation is a ubiquitous environmental agent with epigenotoxic effects. Human exposure to α-radiation at potentially harmful levels can occur repetitively over the long term via inhalation of naturally occurring radon gas that accumulates in enclosed spaces, or as a result of a single exposure from a nuclear accident. Alterations in epigenetic DNA methylation (DNAm) have been implicated in normal aging and cancer pathogenesis. Nevertheless, the effects of aberrations in the methylome of human lung cells following exposure to single or multiple α-irradiation events on these processes remain unexplored.

RESULTS

We performed genome-wide DNAm profiling of human embryonic lung fibroblasts from control and irradiated cells using americium-241 α-sources. Cells were α-irradiated in quadruplicates to seven doses using two exposure regimens, a single-fraction (SF) where the total dose was given at once, and a multi-fraction (MF) method, where the total dose was equally distributed over 14 consecutive days. Our results revealed that SF irradiations were prone to a decrease in DNAm levels, while MF irradiations mostly increased DNAm. The analysis also showed that the gene body (i.e., exons and introns) was the region most altered by both the SF hypomethylation and the MF hypermethylation. Additionally, the MF irradiations induced the highest number of differentially methylated regions in genes associated with DNAm biomarkers of aging, carcinogenesis, and cardiovascular disease. The DNAm profile of the oncogenes and tumor suppressor genes suggests that the fibroblasts manifested a defensive response to the MF α-irradiation. Key DNAm events of ionizing radiation exposure, including changes in methylation levels in mitochondria dysfunction-related genes, were mainly identified in the MF groups. However, these alterations were under-represented, indicating that the mitochondria undergo adaptive mechanisms, aside from DNAm, in response to radiation-induced oxidative stress.

CONCLUSIONS

We identified a contrasting methylomic profile in the lung fibroblasts α-irradiated to SF compared with MF exposures. These findings demonstrate that the methylome response of the lung cells to α-radiation is highly dependent on both the total dose and the exposure regimen. They also provide novel insights into potential biomarkers of α-radiation, which may contribute to the development of innovative approaches to detect, prevent, and treat α-particle-related diseases.

The role of PI3K/AKT signaling pathway in myocardial ischemia-reperfusion injury

Myocardial ischemia has a high incidence and mortality rate, and reperfusion is currently the standard intervention. However, reperfusion may lead to further myocardial damage, known as myocardial ischemia/reperfusion injury (MIRI). There are currently no effective clinical treatments for MIRI. The PI3K/Akt signaling pathway is involved in cardiovascular health and disease and plays an important role in reducing myocardial infarct size and restoring cardiac function after MIRI. Activation of the PI3K/Akt pathway provides myocardial protection through synergistic upregulation of antioxidant, anti-inflammatory, and autophagy activities and inhibition of mitochondrial dysfunction and cardiomyocyte apoptosis. Many studies have shown that PI3K/Akt has a significant protective effect against MIRI. Here, we reviewed the molecular regulation of PI3K/Akt in MIRI and summarized the molecular mechanism by which PI3K/Akt affects MIRI, the effects of ischemic preconditioning and ischemic postconditioning, and the role of related drugs or activators targeting PI3K/Akt in MIRI, providing novel insights for the formulation of myocardial protection strategies. This review provides evidence of the role of PI3K/Akt activation in MIRI and supports its use as a therapeutic target.

Non-small Cell Lung Cancer Epigenomes Exhibit Altered DNA Methylation in Smokers and Never-smokers

Epigenetic alterations are widespread in cancer and can complement genetic alterations to influence cancer progression and treatment outcome. To determine the potential contribution of DNAmethylation alterations to tumor phenotype in non-small cell lung cancer (NSCLC) in both smoker and never-smoker patients, we performed genome-wide profiling of DNA methylation in 17 primary NSCLC tumors and 10 matched normal lung samples using the complementary assays, methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylation sensitive restriction enzyme sequencing (MRE-seq). We reported recurrent methylation changes in the promoters of several genes, many previously implicated in cancer, including FAM83A and SEPT9 (hypomethylation), as well as PCDH7, NKX2-1, and SOX17 (hypermethylation). Although many methylation changes between tumors and their paired normal samples were shared across patients, several were specific to a particular smoking status. For example, never-smokers displayed a greater proportion of hypomethylated differentially methylated regions (hypoDMRs) and a greater number of recurrently hypomethylated promoters, including those of ASPSCR1, TOP2A, DPP9, and USP39, all previously linked to cancer. Changes outside of promoters were also widespread and often recurrent, particularly methylation loss over repetitive elements, highly enriched for ERV1 subfamilies. Recurrent hypoDMRs were enriched for several transcription factor binding motifs, often for genes involved in signaling and cell proliferation. For example, 71% of recurrent promoter hypoDMRs contained a motif for NKX2-1. Finally, the majority of DMRs were located within an active chromatin state in tissues profiled using the Roadmap Epigenomics data, suggesting that methylation changes may contribute to altered regulatory programs through the adaptation of cell type-specific expression programs.

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).

The Transition from Cancer "omics" to "epi-omics" through Next- and Third-Generation Sequencing

Deciphering cancer etiopathogenesis has proven to be an especially challenging task since the mechanisms that drive tumor development and progression are far from simple. An astonishing amount of research has revealed a wide spectrum of defects, including genomic abnormalities, epigenomic alterations, disturbance of gene transcription, as well as post-translational protein modifications, which cooperatively promote carcinogenesis. These findings suggest that the adoption of a multidimensional approach can provide a much more precise and comprehensive picture of the tumor landscape, hence serving as a powerful tool in cancer research and precision oncology. The introduction of next- and third-generation sequencing technologies paved the way for the decoding of genetic information and the elucidation of cancer-related cellular compounds and mechanisms. In the present review, we discuss the current and emerging applications of both generations of sequencing technologies, also referred to as massive parallel sequencing (MPS), in the fields of cancer genomics, transcriptomics and proteomics, as well as in the progressing realms of epi-omics. Finally, we provide a brief insight into the expanding scope of sequencing applications in personalized cancer medicine and pharmacogenomics.

Locus-Specific Enrichment Analysis of 5-Hydroxymethylcytosine Reveals Novel Genes Associated with Breast Carcinogenesis

Highlights

Abstract

An imbalance in DNA methylation is a hallmark epigenetic alteration in cancer. The conversion of 5-methylcytosine (5-mC) to 5-hydroxymethyl cytosine (5-hmC), which causes the imbalance, results in aberrant gene expression. The precise functional role of 5-hydroxymethylcytosine in breast cancer remains elusive. In this study, we describe the landscape of 5-mC and 5-hmC and their association with breast cancer development. We found a distinguishable global loss of 5-hmC in the localized and invasive types of breast cancer that strongly correlate with TET expression. Genome-wide analysis revealed a unique 5-mC and 5-hmC signature in breast cancer. The differentially methylated regions (DMRs) were primarily concentrated in the proximal regulatory regions such as the promoters and UTRs, while the differentially hydroxymethylated regions (DhMRs) were densely packed in the distal regulatory regions, such as the intergenic regions (>−5 kb from TSSs). Our results indicate 4809 DMRs and 4841 DhMRs associated with breast cancer. Validation of nine 5-hmC enriched loci in a distinct set of breast cancer and normal samples positively correlated with their corresponding gene expression. The novel 5-hmC candidates such as TXNL1, and CNIH3 implicate a pro-oncogenic role in breast cancer. Overall, these results provide new insights into the loci-specific accumulation of 5-mC and 5-hmC, which are aberrantly methylated and demethylated in breast cancer.

msPIPE: a pipeline for the analysis and visualization of whole-genome bisulfite sequencing data

BACKGROUND

DNA methylation is an important epigenetic modification that is known to regulate gene expression. Whole-genome bisulfite sequencing (WGBS) is a powerful method for studying cytosine methylation in a whole genome. However, it is difficult to obtain methylation profiles using the WGBS raw reads and is necessary to be proficient in all types of bioinformatic tools for the study of DNA methylation. In addition, recent end-to-end pipelines for DNA methylation analyses are not sufficient for addressing those difficulties.

RESULTS

Here we present msPIPE, a pipeline for DNA methylation analyses with WGBS data seamlessly connecting all the required tasks ranging from data pre-processing to multiple downstream DNA methylation analyses. The msPIPE can generate various methylation profiles to analyze methylation patterns in the given sample, including statistical summaries and methylation levels. Also, the methylation levels in the functional regions of a genome are computed with proper annotation. The results of methylation profiles, hypomethylation, and differential methylation analysis are plotted in publication-quality figures. The msPIPE can be easily and conveniently used with a Docker image, which includes all dependent packages and software related to DNA methylation analyses.

CONCLUSION

msPIPE is a new end-to-end pipeline designed for methylation calling, profiling, and various types of downstream DNA methylation analyses, leading to the creation of publication-quality figures. msPIPE allows researchers to process and analyze the WGBS data in an easy and convenient way. It is available at https://github.com/jkimlab/msPIPE and https://hub.docker.com/r/jkimlab/mspipe .

Experimental and Computational Approaches for Non-CpG Methylation Analysis

Cytosine methylation adjacent to adenine, thymine, and cytosine residues but not guanine of the DNA is distinctively known as non-CpG methylation. This CA/CT/CC methylation accounts for 15% of the total cytosine methylation and varies among different cell and tissue types. The abundance of CpG methylation has largely concealed the role of non-CpG methylation. Limitations in the early detection methods could not distinguish CpG methylation from non-CpG methylation. Recent advancements in enrichment strategies and high throughput sequencing technologies have enabled the detection of non-CpG methylation. This review discusses the advanced experimental and computational approaches to detect and describe the genomic distribution and function of non-CpG methylation. We present different approaches such as enzyme-based and antibody-based enrichment, which, when coupled, can also improve the sensitivity and specificity of non-CpG detection. We also describe the current bioinformatics pipelines and their specific application in computing and visualizing the imbalance of CpG and non-CpG methylation. Enrichment modes and the computational suites need to be further developed to ease the challenges of understanding the functional role of non-CpG methylation.

Developmental Pathways Are Epigenetically Reprogrammed during Lung Cancer Brain Metastasis

Non-small cell lung cancer (NSCLC) is one of the most commonly diagnosed and deadliest cancers worldwide, with roughly half of all patients initially presenting with both primary and metastatic disease. While the major events in the metastatic cascade have been identified, a mechanistic understanding of how NSCLC routinely and successfully colonizes the brain is largely unknown. Recent studies have begun demonstrating the role of epigenetic misregulation during tumorigenesis and metastasis, including widespread changes in DNA methylation and histone modifications. To better understand the role of altered DNA methylation in NSCLC metastasis to the brain, we measured DNA methylation during disease progression for 12 patients, globally profiling the methylation status of normal lung, primary lung tumor, and brain metastasis samples. The variation in methylation was similar during metastatic spread and primary tumorigenesis but less coordinated across genomic features during metastasis. The greatest recurrent changes during metastatic progression were methylation gains in DNA methylation valleys (DMV) harboring the constitutive heterochromatin mark H3K9me3 as well as bivalent marks H3K27me3 and H3K4me1. In a lymph node-derived cancer cell line, EZH2 binding within DMVs was lost, accompanied by an increase in DNA methylation, exemplifying epigenetic switching. The vast majority of the differentially methylated region-associated DMVs harbored developmental genes, suggesting that altered epigenetic regulation of developmentally important genes may confer a selective advantage during metastatic progression. The characterization of epigenetic changes during NSCLC brain metastasis identified recurrent methylation patterns that may be prognostic biomarkers and contributors to disease progression.

SIGNIFICANCE

Altered DNA methylation in lung cancer brain metastases corresponds with loss of EZH2 occupancy at developmental genes, which could promote stem-like phenotypes permissive of dissemination and survival in different microenvironments.

Plant DNA Methylation Responds to Nutrient Stress

Nutrient stress as abiotic stress has become one of the important factors restricting crop yield and quality. DNA methylation is an essential epigenetic modification that can effectively regulate genome stability. Exploring DNA methylation responses to nutrient stress could lay the foundation for improving plant tolerance to nutrient stress. This article summarizes the plant DNA methylation patterns, the effects of nutrient stress, such as nitrogen, phosphorus, iron, zinc and sulfur stress, on plant DNA methylation and research techniques for plant DNA methylation, etc. Our discussion provides insight for further research on epigenetics response to nutrient stress in the future.

The H3K27M mutation alters stem cell growth, epigenetic regulation, and differentiation potential

BACKGROUND

Neurodevelopmental disorders increase brain tumor risk, suggesting that normal brain development may have protective properties. Mutations in epigenetic regulators are common in pediatric brain tumors, highlighting a potentially central role for disrupted epigenetic regulation of normal brain development in tumorigenesis. For example, lysine 27 to methionine mutation (H3K27M) in the H3F3A gene occurs frequently in Diffuse Intrinsic Pontine Gliomas (DIPGs), the most aggressive pediatric glioma. As H3K27M mutation is necessary but insufficient to cause DIPGs, it is accompanied by additional mutations in tumors. However, how H3K27M alone increases vulnerability to DIPG tumorigenesis remains unclear.

RESULTS

Here, we used human embryonic stem cell models with this mutation, in the absence of other DIPG contributory mutations, to investigate how H3K27M alters cellular proliferation and differentiation. We found that H3K27M increased stem cell proliferation and stem cell properties. It interfered with differentiation, promoting anomalous mesodermal and ectodermal gene expression during both multi-lineage and germ layer-specific cell specification, and blocking normal differentiation into neuroectoderm. H3K27M mutant clones exhibited transcriptomic diversity relative to the more homogeneous wildtype population, suggesting reduced fidelity of gene regulation, with aberrant expression of genes involved in stem cell regulation, differentiation, and tumorigenesis. These phenomena were associated with global loss of H3K27me3 and concordant loss of DNA methylation at specific genes in H3K27M-expressing cells.

CONCLUSIONS

Together, these data suggest that H3K27M mutation disrupts normal differentiation, maintaining a partially differentiated state with elevated clonogenicity during early development. This disrupted response to early developmental cues could promote tissue properties that enable acquisition of additional mutations that cooperate with H3K27M mutation in genesis of DMG/DIPG. Therefore, this work demonstrates for the first time that H3K27M mutation confers vulnerability to gliomagenesis through persistent clonogenicity and aberrant differentiation and defines associated alterations of histone and DNA methylation.

Whole-genome profiling of DNA methylation and hydroxymethylation identifies distinct regulatory programs among innate lymphocytes

Innate lymphocytes encompass a diverse array of phenotypic identities with specialized functions. DNA methylation and hydroxymethylation are essential for epigenetic fidelity and fate commitment. The landscapes of these modifications are unknown in innate lymphocytes. Here, we characterized the whole-genome distribution of methyl-CpG and 5-hydroxymethylcytosine in mouse ILC3, ILC2, and NK cells. We identified differentially methylated and hydroxymethylated DNA regions between ILC-NK subsets and correlated them with transcriptional signatures. We associated lineage-determining transcription factors with demethylation and demonstrated unique patterns of DNA methylation/hydroxymethylation in relationship to open chromatin regions, histone modifications, and transcription factor binding sites. We further discovered a novel association between hydroxymethylation and NK cell super-enhancers. Using mice lacking DNA hydroxymethylase TET2, we showed its requirement for optimal production of hallmark cytokines by ILC3 and IL-17A by inflammatory ILC2. These findings provide a powerful resource for studying innate lymphocyte epigenetic regulation and decode the regulatory logic governing their identity.

Genome-Wide DNA Methylation and Its Effect on Gene Expression During Subclinical Mastitis in Water Buffalo

Subclinical mastitis (SCM) in buffalo is one of the most challenging paradoxes for the dairy sector with very significant milk production losses and poses an imminent danger to milch animal’s milk-producing ability. We present here the genome-wide methylation specific to SCM in water buffalo and its consequential effect on the gene expression landscape for the first time. Whole-genome DNA methylation profiles from peripheral blood lymphocytes and gene expression profiles from milk somatic cells of healthy and SCM cases were catalogued from the MeDIP-Seq and RNA-Seq data. The average methylation in healthy buffaloes was found to be higher than that in the SCM-infected buffaloes. DNA methylation was abundant in the intergenic region followed by the intronic region in both healthy control and SCM groups. A total of 3,950 differentially methylated regions (DMRs) were identified and annotated to 370 differentially methylated genes (DMGs), most of which were enriched in the promoter region. Several important pathways were activated due to hypomethylation and belonged to the Staphylococcus aureus infection, Th17 cell differentiation, and antigen processing and presentation pathways along with others of defense responses. DNA methylome was compared with transcriptome to understand the regulatory role of DNA methylation on gene expression specific to SCM in buffaloes. A total of 4,778 significant differentially expressed genes (DEGs) were extracted in response to SCM, out of which 67 DMGs were also found to be differentially expressed, suggesting that during SCM, DNA methylation could be one of the epigenetic regulatory mechanisms of gene expression. Genes like CSF2RB, LOC102408349, C3 and PZP like, and CPAMD8 were found to be downregulated in our study, which are known to be involved in the immune response to SCM. Association of DNA methylation with transposable elements, miRNAs, and lncRNAs was also studied. The present study reports a buffalo SCM web resource (BSCM2TDb) available at http://webtom.cabgrid.res.in/BSCM2TDb that catalogues all the mastitis-related information of the analyses results of this study in a single place. This will be of immense use to buffalo researchers to understand the host–pathogen interaction involving SCM, which is required in endeavors of mastitis control and management.

Challenges in promoter methylation analysis in the new era of translational oncology: a focus on liquid biopsy

Toward the discovery of novel reliable biomarkers, epigenetic alterations have been repeatedly proposed for the diagnosis and the development of therapeutic strategies against cancer. Indeed, for promoter methylation to actively become a tumor marker for clinical use, it must be combined with a highly informative technology evaluated in an appropriate biospecimen. Methodological standardization related to epigenetic research is, in fact, one of the most challenging tasks. Moreover, tissue-based biopsy is being complemented and, in some cases, replaced by liquid biopsy. This review will highlight the advancements made for both pre-analytical and analytical implementation for the prospective use of methylation biomarkers in clinical settings, with particular emphasis on liquid biopsy.

DiseaseMeth version 3.0: a major expansion and update of the human disease methylation database

DNA methylation has a growing potential for use as a biomarker because of its involvement in disease. DNA methylation data have also substantially grown in volume during the past 5 years. To facilitate access to these fragmented data, we proposed DiseaseMeth version 3.0 based on DiseaseMeth version 2.0, in which the number of diseases including increased from 88 to 162 and High-throughput profiles samples increased from 32 701 to 49 949. Experimentally confirmed associations added 448 pairs obtained by manual literature mining from 1472 papers in PubMed. The search, analyze and tools sections were updated to increase performance. In particular, the FunctionSearch now provides for the functional enrichment of genes from localized GO and KEGG annotation. We have also developed a unified analysis pipeline for identifying differentially DNA methylated genes (DMGs) from the original data stored in the database. 22 718 DMGs were found in 99 diseases. These DMGs offer application in disease evaluation using two self-developed online tools, Methylation Disease Correlation and Cancer Prognosis & Co-Methylation. All query results can be downloaded and can also be displayed through a box plot, heatmap or network module according to whichever search section is used. DiseaseMeth version 3.0 is freely available at http://diseasemeth.edbc.org/.

AIAP: A Quality Control and Integrative Analysis Package to Improve ATAC-seq Data Analysis

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a technique widely used to investigate genome-wide chromatin accessibility. The recently published Omni-ATAC-seq protocol substantially improves the signal/noise ratio and reduces the input cell number. High-quality data are critical to ensure accurate analysis. Several tools have been developed for assessing sequencing quality and insertion size distribution for ATAC-seq data; however, key quality control (QC) metrics have not yet been established to accurately determine the quality of ATAC-seq data. Here, we optimized the analysis strategy for ATAC-seq and defined a series of QC metrics for ATAC-seq data, including reads under peak ratio (RUPr), background (BG), promoter enrichment (ProEn), subsampling enrichment (SubEn), and other measurements. We incorporated these QC tests into our recently developed ATAC-seq Integrative Analysis Package (AIAP) to provide a complete ATAC-seq analysis system, including quality assurance, improved peak calling, and downstream differential analysis. We demonstrated a significant improvement of sensitivity (20%–60%) in both peak calling and differential analysis by processing paired-end ATAC-seq datasets using AIAP. AIAP is compiled into Docker/Singularity, and it can be executed by one command line to generate a comprehensive QC report. We used ENCODE ATAC-seq data to benchmark and generate QC recommendations, and developed qATACViewer for the user-friendly interaction with the QC report. The software, source code, and documentation of AIAP are freely available at https://github.com/Zhang-lab/ATAC-seq_QC_analysis.

Common DNA methylation dynamics in endometriod adenocarcinoma and glioblastoma suggest universal epigenomic alterations in tumorigenesis

Trends in altered DNA methylation have been defined across human cancers, revealing global loss of methylation (hypomethylation) and focal gain of methylation (hypermethylation) as frequent cancer hallmarks. Although many cancers share these trends, little is known about the specific differences in DNA methylation changes across cancer types, particularly outside of promoters. Here, we present a comprehensive comparison of DNA methylation changes between two distinct cancers, endometrioid adenocarcinoma (EAC) and glioblastoma multiforme (GBM), to elucidate common rules of methylation dysregulation and changes unique to cancers derived from specific cells. Both cancers exhibit significant changes in methylation over regulatory elements. Notably, hypermethylated enhancers within EAC samples contain several transcription factor binding site clusters with enriched disease ontology terms highlighting uterine function, while hypermethylated enhancers in GBM are found to overlap active enhancer marks in adult brain. These findings suggest that loss of original cellular identity may be a shared step in tumorigenesis.

Human placental cytotrophoblast epigenome dynamics over gestation and alterations in placental disease

The human placenta and its specialized cytotrophoblasts rapidly develop, have a compressed lifespan, govern pregnancy outcomes, and program the offspring's health. Understanding the molecular underpinnings of these behaviors informs development and disease. Profiling the extraembryonic epigenome and transcriptome during the 2nd and 3rd trimesters revealed H3K9 trimethylation overlapping deeply DNA hypomethylated domains with reduced gene expression and compartment-specific patterns that illuminated their functions. Cytotrophoblast DNA methylation increased, and several key histone modifications decreased across the genome as pregnancy advanced. Cytotrophoblasts from severe preeclampsia had substantially increased H3K27 acetylation globally and at genes that are normally downregulated at term but upregulated in this syndrome. In addition, some cases had an immature pattern of H3K27ac peaks, and others showed evidence of accelerated aging, suggesting subtype-specific alterations in severe preeclampsia. Thus, the cytotrophoblast epigenome dramatically reprograms during pregnancy, placental disease is associated with failures in this process, and H3K27 hyperacetylation is a feature of severe preeclampsia.

Epigenomic differences in the human and chimpanzee genomes are associated with structural variation

Structural variation (SV), including insertions and deletions (indels), is a primary mechanism of genome evolution. However, the mechanism by which SV contributes to epigenome evolution is poorly understood. In this study, we characterized the association between lineage-specific indels and epigenome differences between human and chimpanzee to investigate how SVs might have shaped the epigenetic landscape. By intersecting medium-to-large human-chimpanzee indels (20 bp-50 kb) with putative promoters and enhancers in cranial neural crest cells (CNCCs) and repressed regions in induced pluripotent cells (iPSCs), we found that 12% of indels overlap putative regulatory and repressed regions (RRRs), and 15% of these indels are associated with lineage-biased RRRs. Indel-associated putative enhancer and repressive regions are approximately 1.3 times and approximately three times as likely to be lineage-biased, respectively, as those not associated with indels. We found a twofold enrichment of medium-sized indels (20-50 bp) in CpG island (CGI)-containing promoters than expected by chance. Lastly, from human-specific transposable element insertions, we identified putative regulatory elements, including NR2F1-bound putative CNCC enhancers derived from SVAs and putative iPSC promoters derived from LTR5s. Our results show that different types of indels are associated with specific epigenomic diversity between human and chimpanzee.

Deconstructing Stepwise Fate Conversion of Human Fibroblasts to Neurons by MicroRNAs

Cell-fate conversion generally requires reprogramming effectors to both introduce fate programs of the target cell type and erase the identity of starting cell population. Here, we reveal insights into the activity of microRNAs miR-9/9∗ and miR-124 (miR-9/9∗-124) as reprogramming agents that orchestrate direct conversion of human fibroblasts into motor neurons by first eradicating fibroblast identity and promoting uniform transition to a neuronal state in sequence. We identify KLF-family transcription factors as direct target genes for miR-9/9∗-124 and show their repression is critical for erasing fibroblast fate. Subsequent gain of neuronal identity requires upregulation of a small nuclear RNA, RN7SK, which induces accessibilities of chromatin regions and neuronal gene activation to push cells to a neuronal state. Our study defines deterministic components in the microRNA-mediated reprogramming cascade.

Challenges and Perspectives in the Epigenetics of Climate Change-Induced Forests Decline

Forest tree species are highly vulnerable to the effects of climate change. As sessile organisms with long generation times, their adaptation to a local changing environment may rely on epigenetic modifications when allele frequencies are not able to shift fast enough. However, the current lack of knowledge on this field is remarkable, due to many challenges that researchers face when studying this issue. Huge genome sizes, absence of reference genomes and annotation, and having to analyze huge amounts of data are among these difficulties, which limit the current ability to understand how climate change drives tree species epigenetic modifications. In spite of this challenging framework, some insights on the relationships among climate change-induced stress and epigenomics are coming. Advances in DNA sequencing technologies and an increasing number of studies dealing with this topic must boost our knowledge on tree adaptive capacity to changing environmental conditions. Here, we discuss challenges and perspectives in the epigenetics of climate change-induced forests decline, aiming to provide a general overview of the state of the art.

Epigenetic Variation Analysis Leads to Biomarker Discovery in Gastric Adenocarcinoma

As one of the most common malignant tumors worldwide, gastric adenocarcinoma (GC) and its prognosis are still poorly understood. Various genetic and epigenetic factors have been indicated in GC carcinogenesis. However, a comprehensive and in-depth investigation of epigenetic alteration in gastric cancer is still missing. In this study, we systematically investigated some key epigenetic features in GC, including DNA methylation and five core histone modifications. Data from The Cancer Genome Atlas Program and other studies (Gene Expression Omnibus) were collected, analyzed, and validated with multivariate statistical analysis methods. The landscape of epi-modifications in gastric cancer was described. Chromatin state transition analysis showed a histone marker shift in gastric cancer genome by employing a Hidden-Markov-Model based approach, indicated that histone marks tend to label different sets of genes in GC compared to control. An additive effect of these epigenetic marks was observed by integrated analysis with gene expression data, suggesting epigenetic modifications may cooperatively regulate gene expression. However, the effect of DNA methylation was found more significant without the presence of the five histone modifications in our study. By constructing a PPI network, key genes to distinguish GC from normal samples were identified, and distinct patterns of oncogenic pathways in GC were revealed. Some of these genes can also serve as potential biomarkers to classify various GC molecular subtypes. Our results provide important insights into the epigenetic regulation in gastric cancer and other cancers in general. This study describes the aberrant epigenetic variation pattern in GC and provides potential direction for epigenetic biomarker discovery.

New Strategies for Clinical Trials in Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that poses several challenges in terms of clinical diagnosis and investigation of molecular etiology. The lack of knowledge on the pathogenic mechanisms underlying ASD has hampered the clinical trials that so far have tried to target ASD behavioral symptoms. In order to improve our understanding of the molecular abnormalities associated with ASD, a deeper and more extensive genetic profiling of targeted individuals with ASD was needed.

METHODS

The recent availability of new and more powerful sequencing technologies (third-generation sequencing) has allowed to develop novel strategies for the characterization of comprehensive genetic profiles of individuals with ASD. In particular, this review will describe integrated approaches based on the combination of various omics technologies that will lead to a better stratification of targeted cohorts for the design of clinical trials in ASD.

RESULTS

In order to analyze the big data collected by assays such as the whole genome, epigenome, transcriptome, and proteome, it is critical to develop an efficient computational infrastructure. Machine learning models are instrumental to identify non-linear relationships between the omics technologies and, therefore, establish a functional informative network among the different data sources.

CONCLUSION

The potential advantage provided by these new integrated omics-based strategies is better characterization of the genetic background of ASD cohorts, to identify novel molecular targets for drug development, and ultimately offer a more personalized approach in the design of clinical trials for ASD.

DNA methylation methods: Global DNA methylation and methylomic analyses

DNA methylation provides a pivotal layer of epigenetic regulation in eukaryotes that has significant involvement for numerous biological processes in health and disease. The function of methylation of cytosine bases in DNA was originally proposed as a "silencing" epigenetic marker and focused on promoter regions of genes for decades. Improved technologies and accumulating studies have been extending our understanding of the roles of DNA methylation to various genomic contexts including gene bodies, repeat sequences and transcriptional start sites. The demand for comprehensively describing DNA methylation patterns spawns a diversity of DNA methylation profiling technologies that target its genomic distribution. These approaches have enabled the measurement of cytosine methylation from specific loci at restricted regions to single-base-pair resolution on a genome-scale level. In this review, we discuss the different DNA methylation analysis technologies primarily based on the initial treatments of DNA samples: bisulfite conversion, endonuclease digestion and affinity enrichment, involving methodology evolution, principles, applications, and their relative merits. This review may offer referable information for the selection of various platforms for genome-wide analysis of DNA methylation.

Predicting DNA Methylation States with Hybrid Information Based Deep-Learning Model

DNA methylation plays an important role in the regulation of some biological processes. Up to now, with the development of machine learning models, there are several sequence-based deep learning models designed to predict DNA methylation states, which gain better performance than traditional methods like random forest and SVM. However, convolutional network based deep learning models that use one-hot encoding DNA sequence as input may discover limited information and cause unsatisfactory prediction performance, so more data and model structures of diverse angles should be considered. In this work, we proposed a hybrid sequence-based deep learning model with both MeDIP-seq data and Histone information to predict DNA methylated CpG states (MHCpG). We combined both MeDIP-seq data and histone modification data with sequence information and implemented convolutional network to discover sequence patterns. In addition, we used statistical data gained from previous three input data and adopted a 3-layer feedforward neuron network to extract more high-level features. We compared our method with traditional predicting methods using random forest and other previous methods like CpGenie and DeepCpG, the result showed that MHCpG exceeded the other approaches and gained more satisfactory performance.

DeepH&M: Estimating single-CpG hydroxymethylation and methylation levels from enrichment and restriction enzyme sequencing methods

Increased appreciation of 5-hydroxymethylcytosine (5hmC) as a stable epigenetic mark, which defines cell identity and disease progress, has engendered a need for cost-effective, but high-resolution, 5hmC mapping technology. Current enrichment-based technologies provide cheap but low-resolution and relative enrichment of 5hmC levels, while single-base resolution methods can be prohibitively expensive to scale up to large experiments. To address this problem, we developed a deep learning-based method, "DeepH&M," which integrates enrichment and restriction enzyme sequencing methods to simultaneously estimate absolute hydroxymethylation and methylation levels at single-CpG resolution. Using 7-week-old mouse cerebellum data for training the DeepH&M model, we demonstrated that the 5hmC and 5mC levels predicted by DeepH&M were in high concordance with whole-genome bisulfite-based approaches. The DeepH&M model can be applied to 7-week-old frontal cortex and 79-week-old cerebellum, revealing the robust generalizability of this method to other tissues from various biological time points.

Epigenomic programming in early fetal brain development

Aim: To provide a comprehensive understanding of gene regulatory networks in the developing human brain and a foundation for interpreting pathogenic deregulation. Materials & methods: We generated reference epigenomes and transcriptomes of dissected brain regions and primary neural progenitor cells (NPCs) derived from cortical and ganglionic eminence tissues of four normal human fetuses. Results: Integration of these data across developmental stages revealed a directional increase in active regulatory states, transcription factor activities and gene transcription with developmental stage. Consistent with differences in their biology, NPCs derived from cortical and ganglionic eminence regions contained common, region specific, and gestational week specific regulatory states. Conclusion: We provide a high-resolution regulatory network for NPCs from different brain regions as a comprehensive reference for future studies.

TFIID Enables RNA Polymerase II Promoter-Proximal Pausing

RNA polymerase II (RNAPII) transcription is governed by the pre-initiation complex (PIC), which contains TFIIA, TFIIB, TFIID, TFIIE, TFIIF, TFIIH, RNAPII, and Mediator. After initiation, RNAPII enzymes pause after transcribing less than 100 bases; precisely how RNAPII pausing is enforced and regulated remains unclear. To address specific mechanistic questions, we reconstituted human RNAPII promoter-proximal pausing in vitro, entirely with purified factors (no extracts). As expected, NELF and DSIF increased pausing, and P-TEFb promoted pause release. Unexpectedly, the PIC alone was sufficient to reconstitute pausing, suggesting RNAPII pausing is an inherent PIC function. In agreement, pausing was lost upon replacement of the TFIID complex with TATA-binding protein (TBP), and PRO-seq experiments revealed widespread disruption of RNAPII pausing upon acute depletion (t = 60 min) of TFIID subunits in human or Drosophila cells. These results establish a TFIID requirement for RNAPII pausing and suggest pause regulatory factors may function directly or indirectly through TFIID.

Precision Medicine in Lymphoma by Innovative Instrumental Platforms

In recent years, many efforts have been addressed to the growing field of precision medicine in order to offer individual treatments to every patient on the basis of his/her genetic background. Formerly adopted to achieve new disease classifications as it is still done, innovative platforms, such as microarrays, genome-wide association studies (GWAS), and next generation sequencing (NGS), have made the progress in pharmacogenetics faster and cheaper than previously expected. Several studies in lymphoma patients have demonstrated that these platforms can be used to identify biomarkers predictive of drug efficacy and tolerability, discovering new possible druggable proteins. Indeed, GWAS and NGS allow the investigation of the human genome, finding interesting associations with putative or unexpected targets, which in turns may represent new therapeutic possibilities. Importantly, some objective difficulties have initially hampered the translation of findings in clinical routines, such as the poor quantity/quality of genetic material or the paucity of targets that could be investigated at the same time. At present, some of these technical issues have been partially solved. Furthermore, these analyses are growing in parallel with the development of bioinformatics and its capabilities to manage and analyze big data. Because of pharmacogenetic markers may become important during drug development, regulatory authorities (i.e., EMA, FDA) are preparing ad hoc guidelines and recommendations to include the evaluation of genetic markers in clinical trials. Concerns and difficulties for the adoption of genetic testing in routine are still present, as well as affordability, reliability and the poor confidence of some patients for these tests. However, genetic testing based on predictive markers may offers many advantages to caregivers and patients and their introduction in clinical routine is justified.

Long-Term In Vitro Expansion of Epithelial Stem Cells Enabled by Pharmacological Inhibition of PAK1-ROCK-Myosin II and TGF-β Signaling

Despite substantial self-renewal capability in vivo, epithelial stem and progenitor cells located in various tissues expand for a few passages in vitro in feeder-free condition before they succumb to growth arrest. Here, we describe the EpiX method, which utilizes small molecules that inhibit PAK1-ROCK-Myosin II and TGF-β signaling to achieve over one trillion-fold expansion of human epithelial stem and progenitor cells from skin, airway, mammary, and prostate glands in the absence of feeder cells. Transcriptomic and epigenomic studies show that this condition helps epithelial cells to overcome stresses for continuous proliferation. EpiX-expanded basal epithelial cells differentiate into mature epithelial cells consistent with their tissue origins. Whole-genome sequencing reveals that the cells retain remarkable genome integrity after extensive in vitro expansion without acquiring tumorigenicity. EpiX technology provides a solution to exploit the potential of tissue-resident epithelial stem and progenitor cells for regenerative medicine.

Transcriptional Responses to IFN-γ Require Mediator Kinase-Dependent Pause Release and Mechanistically Distinct CDK8 and CDK19 Functions

Transcriptional responses to external stimuli remain poorly understood. Using global nuclear run-on followed by sequencing (GRO-seq) and precision nuclear run-on sequencing (PRO-seq), we show that CDK8 kinase activity promotes RNA polymerase II pause release in response to interferon-γ (IFN-γ), a universal cytokine involved in immunity and tumor surveillance. The Mediator kinase module contains CDK8 or CDK19, which are presumed to be functionally redundant. We implemented cortistatin A, chemical genetics, transcriptomics, and other methods to decouple their function while assessing enzymatic versus structural roles. Unexpectedly, CDK8 and CDK19 regulated different gene sets via distinct mechanisms. CDK8-dependent regulation required its kinase activity, whereas CDK19 governed IFN-γ responses through its scaffolding function (i.e., it was kinase independent). Accordingly, CDK8, not CDK19, phosphorylates the STAT1 transcription factor (TF) during IFN-γ stimulation, and CDK8 kinase inhibition blocked activation of JAK-STAT pathway TFs. Cytokines such as IFN-γ rapidly mobilize TFs to "reprogram" cellular transcription; our results implicate CDK8 and CDK19 as essential for this transcriptional reprogramming.

Development of a method for identifying and functionally analyzing allele-specific DNA methylation based on BS-seq data

Aim: To comprehensively identify allele-specific DNA methylation (ASM) at the genome-wide level. Methods: Here, we propose a new method, called GeneASM, to identify ASM using high-throughput bisulfite sequencing data in the absence of haplotype information. Results: A total of 2194 allele-specific DNA methylated genes were identified in the GM12878 lymphocyte lineage using GeneASM. These genes are mainly enriched in cell cytoplasm function, subcellular component movement or cellular linkages. GM12878 methylated DNA immunoprecipitation sequencing, and methylation sensitive restriction enzyme sequencing data were used to evaluate ASM. The relationship between ASM and disease was further analyzed using the The Cancer Genome Atlas (TCGA) data of lung adenocarcinoma (LUAD), and whole genome bisulfite sequencing data. Conclusion: GeneASM, which recognizes ASM by high-throughput bisulfite sequencing and heterozygous single-nucleotide polymorphisms, provides new perspective for studying genomic imprinting.

Maternal Low-Fat Diet Programs the Hepatic Epigenome despite Exposure to an Obesogenic Postnatal Diet

Obesity and metabolic disease present a danger to long-term health outcomes. It has been hypothesized that epigenetic marks established during early life might program individuals and have either beneficial or harmful consequences later in life. In the present study, we examined whether maternal diet alters DNA methylation and whether such modifications persist after an obesogenic postnatal dietary challenge. During gestation and lactation, male Sprague-Dawley rats were exposed to either a high-fat diet (HF; n = 10) or low-fat diet (LF; n = 10). After weaning, all animals were fed a HF diet for an additional nine weeks. There were no differences observed in food intake or body weight between groups. Hepatic DNA methylation was quantified using both methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylation-sensitive restriction enzyme sequencing (MRE-seq). Overall, 1419 differentially methylated regions (DMRs) were identified. DMRs tended to be located in CpG shores and were enriched for genes involved in metabolism and cancer. Gene expression was measured for 31 genes in these pathways. Map3k5 and Igf1r were confirmed to be differentially expressed. Finally, we attempted to quantify the functional relevance of intergenic DMRs. Using chromatin contact data, we saw that conserved DMRs were topologically associated with metabolism genes, which were associated with differential expression of Adh5, Enox1, and Pik3c3. We show that although maternal dietary fat is unable to reverse offspring weight gain in response to a postnatal obesogenic diet, early life diet does program the hepatic methylome. Epigenetic alterations occur primarily in metabolic and cancer pathways and are associated with altered gene expression, but it is unclear whether they bear consequence later in life.

Maternal and Post-weaning High-Fat Diets Produce Distinct DNA Methylation Patterns in Hepatic Metabolic Pathways within Specific Genomic Contexts

Calorie-dense high-fat diets (HF) are associated with detrimental health outcomes, including obesity, cardiovascular disease, and diabetes. Both pre- and post-natal HF diets have been hypothesized to negatively impact long-term metabolic health via epigenetic mechanisms. To understand how the timing of HF diet intake impacts DNA methylation and metabolism, male Sprague–Dawley rats were exposed to either maternal HF (MHF) or post-weaning HF diet (PHF). At post-natal week 12, PHF rats had similar body weights but greater hepatic lipid accumulation compared to the MHF rats. Genome-wide DNA methylation was evaluated, and analysis revealed 1744 differentially methylation regions (DMRs) between the groups with the majority of the DMR located outside of gene-coding regions. Within differentially methylated genes (DMGs), intragenic DNA methylation closer to the transcription start site was associated with lower gene expression, whereas DNA methylation further downstream was positively correlated with gene expression. The insulin and phosphatidylinositol (PI) signaling pathways were enriched with 25 DMRs that were associated with 20 DMGs, including PI3 kinase (Pi3k), pyruvate kinase (Pklr), and phosphodiesterase 3 (Pde3). Together, these results suggest that the timing of HF diet intake determines DNA methylation and gene expression patterns in hepatic metabolic pathways that target specific genomic contexts.

A high-fat diet alters genome-wide DNA methylation and gene expression in SM/J mice

BACKGROUND

While the genetics of obesity has been well defined, the epigenetics of obesity is poorly understood. Here, we used a genome-wide approach to identify genes with differences in both DNA methylation and expression associated with a high-fat diet in mice.

RESULTS

We weaned genetically identical Small (SM/J) mice onto a high-fat or low-fat diet and measured their weights weekly, tested their glucose and insulin tolerance, assessed serum biomarkers, and weighed their organs at necropsy. We measured liver gene expression with RNA-seq (using 21 total libraries, each pooled with 2 mice of the same sex and diet) and DNA methylation with MRE-seq and MeDIP-seq (using 8 total libraries, each pooled with 4 mice of the same sex and diet). There were 4356 genes with expression differences associated with diet, with 184 genes exhibiting a sex-by-diet interaction. Dietary fat dysregulated several pathways, including those involved in cytokine-cytokine receptor interaction, chemokine signaling, and oxidative phosphorylation. Over 7000 genes had differentially methylated regions associated with diet, which occurred in regulatory regions more often than expected by chance. Only 5-10% of differentially methylated regions occurred in differentially expressed genes, however this was more often than expected by chance (p = 2.2 × 10- 8).

CONCLUSIONS

Discovering the gene expression and methylation changes associated with a high-fat diet can help to identify new targets for epigenetic therapies and inform about the physiological changes in obesity. Here, we identified numerous genes with altered expression and methylation that are promising candidates for further study.

MethRaFo: MeDIP-seq methylation estimate using a Random Forest Regressor

Motivation

Profiling of genome wide DNA methylation is now routinely performed when studying development, cancer and several other biological processes. Although Whole genome Bisulfite Sequencing provides high-quality methylation measurements at the resolution of nucleotides, it is relatively costly and so several studies have used alternative methods for such profiling. One of the most widely used low cost alternatives is MeDIP-Seq. However, MeDIP-Seq is biased for CpG enriched regions and thus its results need to be corrected in order to determine accurate methylation levels.

Results

Here we present a method for correcting MeDIP-Seq results based on Random Forest regression. Applying the method to real data from several different tissues (brain, cortex, penis) we show that it achieves almost 4 fold decrease in run time while increasing accuracy by as much as 20% over prior methods developed for this task.

Availability and implementation

MethRaFo is freely available as a python package (with a R wrapper) at https://github.com/phoenixding/methrafo.

Contact

zivbj@cs.cmu.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Soluble inflammatory mediators induce transcriptional re-organization that is independent of dna methylation changes in cultured human chorionic villous trophoblasts

The studies proposed here were undertaken to test the hypothesis that, under specific circumstances (e.g., a strong enough inflammatory stimulus), genes that are repressed at the maternal-fetal interface via DNA methylation might be de-methylated, allowing either a maternal immune response to the semi-allogenic fetus or the onset of early labor. Chorionic trophoblasts (CT) were isolated from fetal membranes, followed by incubation with medium from LPS-activated PBMC or resting PBMC medium for 2 h. RNA and DNA were isolated from the cells for RNA-seq and DNA methylation studies. Two hrs after being exposed to conditioned medium from LPS-activated PBMC, CT showed differential expression of 114 genes, all but 2 of which showed higher expression in the stimulated cells than is the unstimulated cells. We also identified 318 differentially methylated regions (DMRs) that associated with 306 genes (155 protein coding genes) in the two groups, but the observed methylation changes had negligible impact on the observed transcriptional changes in CT.

CT display complex patterns of transcription in response to inflammation. DNA methylation does not appear to be an important regulator of the observed transcriptional changes.