methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data

Conserved DNA methylation signatures in the prefrontal cortex of female newborn and juvenile guinea pigs following antenatal betamethasone exposure

Antenatal corticosteroids (ACS) improve perinatal survival when there is a risk of preterm birth. Although evidence suggests an increased risk of developing neurobehavioural disorders in exposed offspring, the mechanisms involved remain largely unknown. Here, we investigated the DNA methylation patterns in the prefrontal cortex (PFC) of ACS-exposed guinea pig offspring. We hypothesized that differential methylation will be evident at both newborn and juvenile ages. In two separate cohorts, pregnant guinea pigs were administered a subcutaneous injection of saline or betamethasone (1 mg/kg) on gestational days 50/51 to mimic a single course of ACS. The gDNA was isolated from the PFC of term-born female offspring on postnatal day 1 (PND1, n = 7/group) and PND14 (n = 6-7/group) to identify differentially methylated CpG sites (DMCs) using reduced representative bisulphite sequencing. In the PND1 PFC, 1521 DMCs, annotating 144 genes were identified following ACS. Identified genes are involved in pathways regulating 'developmental cellular process'. In the PND14 PFC, 776 DMCs representing 46 genes were identified and enriched in 'synaptic signalling' pathways. Though no individual DMCs were identified at both PND1 and PND14, differential methylation was consistently observed at the binding sites of transcription factors PLAGL1, TFAP2C, ZNF263 and SP1 at both ages. We have established that ACS exposure leads to altered DNA methylation in the PFC of guinea pig offspring at both newborn and juvenile ages. Notably, a unique methylation signature was consistently observed at four key transcription factor binding sites at both post-natal time points. These changes may predispose the development of altered neurobehavioural phenotypes that have been described in ACS-exposed offspring.

Shedding light on DNA methylation and its clinical implications: the impact of long-read-based nanopore technology

DNA methylation is an essential epigenetic mechanism for regulation of gene expression, through which many physiological (X-chromosome inactivation, genetic imprinting, chromatin structure and miRNA regulation, genome defense, silencing of transposable elements) and pathological processes (cancer and repetitive sequences-associated diseases) are regulated. Nanopore sequencing has emerged as a novel technique that can analyze long strands of DNA (long-read sequencing) without chemically treating the DNA. Interestingly, nanopore sequencing can also extract epigenetic status of the nucleotides (including both 5-Methylcytosine and 5-hydroxyMethylcytosine), and a large variety of bioinformatic tools have been developed for improving its detection properties. Out of all genomic regions, long read sequencing provides advantages in studying repetitive elements, which are difficult to characterize through other sequencing methods. Transposable elements are repetitive regions of the genome that are silenced and usually display high levels of DNA methylation. Their demethylation and activation have been observed in many cancers. Due to their repetitive nature, it is challenging to accurately estimate DNA methylation levels within transposable elements using short sequencing technologies. The advantage to sequence native DNA (without PCR amplification biases or harsh bisulfite treatment) and long and ultra long reads coupled with epigenetic states of the DNA allows to accurately estimate DNA methylation levels in transposable elements. This is a big step forward for epigenomic studies, and unsolved questions regarding gene expression and transposable elements silencing through DNA methylation can now be answered.

Identification of a DNA methylation signature in whole blood of newborn guinea pigs and human neonates following antenatal betamethasone exposure

Antenatal corticosteroids (ACS) are administered where there is risk of preterm birth to promote fetal lung development and improve perinatal survival. However, treatment may be associated with increased risk of developing neurobehavioural disorders. We have recently identified that ACS results in significant changes to DNA methylation patterns in the newborn and juvenile prefrontal cortex (PFC) of exposed guinea pig offspring. Methylation changes at transcription factor binding sites (TFBS) for PLAGL1, TFAP2C, ZNF263, and SP1 were consistently noted at both post-natal stages, suggesting a long-lasting signature of ACS exposure. In this study, we determined if comparable methylation changes are also present in the newborn blood of ACS-exposed guinea pig offspring, as this would determine whether blood methylation patterns may be used as a peripheral biomarker of changes in the brain. Pregnant guinea pigs were treated with saline or betamethasone (1 mg/kg) on gestational days 50/51. gDNA from whole blood of term-born offspring on post-natal day (PND) 1 was used for reduced representation bisulfite sequencing. Overall, 1677 differentially methylated CpG sites (DMCs) were identified in response to ACS. While no specific DMCs identified in the blood overlapped with those previously reported in the PFC of PND1 offspring, significant differential methylation at TFBSs for PLAGL1, TFAP2C, EGR1, ZNF263, and SP1 was persistently observed. Furthermore, re-examination of our previously reported data of DMCs in human neonatal blood following ACS identified the presence of this same TFBS signature in human infants, suggesting the potential for clinical translation of our epigenomic data.

Identifying Differential Methylation in Cancer Epigenetics via a Bayesian Functional Regression Model

DNA methylation plays an essential role in regulating gene activity, modulating disease risk, and determining treatment response. We can obtain insight into methylation patterns at a single-nucleotide level via next-generation sequencing technologies. However, complex features inherent in the data obtained via these technologies pose challenges beyond the typical big data problems. Identifying differentially methylated cytosines (dmc) or regions is one such challenge. We have developed DMCFB, an efficient dmc identification method based on Bayesian functional regression, to tackle these challenges. Using simulations, we establish that DMCFB outperforms current methods and results in better smoothing and efficient imputation. We analyzed a dataset of patients with acute promyelocytic leukemia and control samples. With DMCFB, we discovered many new dmcs and, more importantly, exhibited enhanced consistency of differential methylation within islands and their adjacent shores. Additionally, we detected differential methylation at more of the binding sites of the fused gene involved in this cancer.

Depletion of Mettl3 in cholinergic neurons causes adult-onset neuromuscular degeneration

Motor neuron (MN) demise is a hallmark of several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Post-transcriptional gene regulation can control RNA's fate, and defects in RNA processing are critical determinants of MN degeneration. N6-methyladenosine (m6A) is a post-transcriptional RNA modification that controls diverse aspects of RNA metabolism. To assess the m6A requirement in MNs, we depleted the m6A methyltransferase-like 3 (METTL3) in cells and mice. METTL3 depletion in embryonic stem cell-derived MNs has profound and selective effects on survival and neurite outgrowth. Mice with cholinergic neuron-specific METTL3 depletion display a progressive decline in motor behavior, accompanied by MN loss and muscle denervation, culminating in paralysis and death. Reader proteins convey m6A effects, and their silencing phenocopies METTL3 depletion. Among the m6A targets, we identified transactive response DNA-binding protein 43 (TDP-43) and discovered that its expression is under epitranscriptomic control. Thus, impaired m6A signaling disrupts MN homeostasis and triggers neurodegeneration conceivably through TDP-43 deregulation.

DNA methylation analysis to differentiate reference, breed, and parent-of-origin effects in the bovine pangenome era

BACKGROUND

Most DNA methylation studies have used a single reference genome with little attention paid to the bias introduced due to the reference chosen. Reference genome artifacts and genetic variation, including single nucleotide polymorphisms (SNPs) and structural variants (SVs), can lead to differences in methylation sites (CpGs) between individuals of the same species. We analyzed whole-genome bisulfite sequencing data from the fetal liver of Angus (Bos taurus taurus), Brahman (Bos taurus indicus), and reciprocally crossed samples. Using reference genomes for each breed from the Bovine Pangenome Consortium, we investigated the influence of reference genome choice on the breed and parent-of-origin effects in methylome analyses.

RESULTS

Our findings revealed that ∼75% of CpG sites were shared between Angus and Brahman, ∼5% were breed specific, and ∼20% were unresolved. We demonstrated up to ∼2% quantification bias in global methylation when an incorrect reference genome was used. Furthermore, we found that SNPs impacted CpGs 13 times more than other autosomal sites (P < $5 \times {10}^{ - 324}$) and SVs contained 1.18 times (P < $5 \times {10}^{ - 324}$) more CpGs than non-SVs. We found a poor overlap between differentially methylated regions (DMRs) and differentially expressed genes (DEGs) and suggest that DMRs may be impacting enhancers that target these DEGs. DMRs overlapped with imprinted genes, of which 1, DGAT1, which is important for fat metabolism and weight gain, was found in the breed-specific and sire-of-origin comparisons.

CONCLUSIONS

This work demonstrates the need to consider reference genome effects to explore genetic and epigenetic differences accurately and identify DMRs involved in controlling certain genes.

ChroKit: a Shiny-based framework for interactive analysis, visualization and integration of genomic data

We developed ChroKit (the Chromatin toolKit), an interactive web-based framework written in R that enables intuitive exploration, multidimensional analyses, and visualization of genomic data from ChIP-Seq, DNAse-Seq or any other NGS experiment that reports the enrichment of aligned reads over genomic regions. This program takes preprocessed NGS data and performs operations on genomic regions of interest, including resetting their boundaries, their annotation based on proximity to genomic features, the association to gene ontologies, and signal enrichment calculations. Genomic regions can be further refined or subsetted by user-defined logical operations and unsupervised classification algorithms. ChroKit generates a full range of plots that are easily manipulated by point and click operations, thus allowing 'on the fly' re-analysis and fast exploration of the data. Working sessions can be exported for reproducibility, accountability, and easy sharing within the bioinformatics community. ChroKit is multiplatform and can be deployed on a server to enhance computational speed and provide simultaneous access by multiple users. ChroKit is a fast and intuitive genomic analysis tool suited for a wide range of users due to its architecture and its user-friendly graphical interface. ChroKit source code is available at https://github.com/ocroci/ChroKit and the Docker image at https://hub.docker.com/r/ocroci/chrokit.

Applications of bioinformatics in epigenetics

Epigenetic modifications such as DNA methylation, post-translational chromatin modifications and non-coding RNA-mediated mechanisms are responsible for epigenetic inheritance. Change in gene expression due to these epigenetic modifications are responsible for new traits in different organisms leading to various diseases including cancer, diabetic kidney disease (DKD), diabetic nephropathy (DN) and renal fibrosis. Bioinformatics is an effective approach for epigenomic profiling. These epigenomic data can be analyzed by a large number of bioinformatics tools and software. Many databases are available online, which comprises huge amount of information regarding these modifications. Recent methodologies include many sequencing and analytical techniques to extrapolate different types of epigenetic data. This data can be used to design drugs against diseases linked to epigenetic modifications. This chapter briefly highlights different epigenetics databases (MethDB, REBASE, Pubmeth, MethPrimerDB, Histone Database, ChromDB, MeInfoText database, EpimiR, Methylome DB, and dbHiMo), and tools (compEpiTools, CpGProD, MethBlAST, EpiExplorer, and BiQ analyzer), which are being utilized to retrieve the data and mechanistically analysis of epigenetics modifications.

Multiomics reveals glutathione metabolism as a driver of bimodality during stem cell aging

With age, skeletal muscle stem cells (MuSCs) activate out of quiescence more slowly and with increased death, leading to defective muscle repair. To explore the molecular underpinnings of these defects, we combined multiomics, single-cell measurements, and functional testing of MuSCs from young and old mice. The multiomics approach allowed us to assess which changes are causal, which are compensatory, and which are simply correlative. We identified glutathione (GSH) metabolism as perturbed in old MuSCs, with both causal and compensatory components. Contrary to young MuSCs, old MuSCs exhibit a population dichotomy composed of GSHhigh cells (comparable with young MuSCs) and GSHlow cells with impaired functionality. Mechanistically, we show that antagonism between NRF2 and NF-κB maintains this bimodality. Experimental manipulation of GSH levels altered the functional dichotomy of aged MuSCs. These findings identify a novel mechanism of stem cell aging and highlight glutathione metabolism as an accessible target for reversing MuSC aging.

Differences by origin in methylome suggest eco-phenotypes in the kelp Saccharina latissima

Most kelp species are of high ecological and economic importance worldwide, but are highly susceptible to rising ocean temperatures due to their sessile lifestyle. Due to interference with reproduction, development and growth, natural kelp forests have vanished in multiple regions after extreme summer heat waves. Furthermore, increasing temperatures are likely to decrease biomass production and, thus, reduce production security of farmed kelp. Epigenetic variation, and cytosine methylation as a heritable epigenetic trait, is a rapid means of acclimation and adaptation to environmental conditions, including temperature. While the first methylome of brown macroalgae has been recently described in the kelp Saccharina japonica, its functional relevance and contribution to environmental acclimation is currently unknown. The main objective of our study was to identify the importance of the methylome in the congener kelp species Saccharina latissima for temperature acclimation. Our study is the first to compare DNA methylation in kelp between wild populations of different latitudinal origin, and the first to investigate the effect of cultivation and rearing temperature on genome-wide cytosine methylation. Origin appears to determine many traits in kelp, but it is unknown to what extent the effects of thermal acclimation may be overruled by lab-related acclimation. Our results suggest that seaweed hatchery conditions have strong effects on the methylome and, thus, putatively on the epigenetically controlled characteristics of young kelp sporophytes. However, culture origin could best explain epigenetic differences in our samples suggesting that epigenetic mechanisms contribute to local adaptation of eco-phenotypes. Our study is a first step to understand whether DNA methylation marks (via their effect on gene regulation) may be used as biological regulators to enhance production security and kelp restoration success under rising temperatures, and highlights the importance to match hatchery conditions to origin.

The transcriptional co-repressor SEED DORMANCY 4-LIKE (AtSDR4L) promotes the embryonic-to-vegetative transition in Arabidopsis thaliana

Repression of embryonic traits during the seed-to-seedling phase transition requires the inactivation of master transcription factors associated with embryogenesis. How the timing of such inactivation is controlled is unclear. Here, we report on a novel transcriptional co-repressor, Arabidopsis thaliana SDR4L, that forms a feedback inhibition loop with the master transcription factors LEC1 and ABI3 to repress embryonic traits post-imbibition. LEC1 and ABI3 regulate their own expression by inducing AtSDR4L during mid to late embryogenesis. AtSDR4L binds to sites upstream of LEC1 and ABI4, and these transcripts are upregulated in Atsdr4l seedlings. Atsdr4l seedlings phenocopy a LEC1 overexpressor. The embryonic traits of Atsdr4l can be partially rescued by impairing LEC1 or ABI3. The penetrance and expressivity of the Atsdr4l phenotypes depend on both developmental and external cues, demonstrating the importance of AtSDR4L in seedling establishment under suboptimal conditions.

HRas and Myc synergistically induce cell cycle progression and apoptosis of murine cardiomyocytes

Aim

Adult mammalian cardiomyocytes are incapable of significant proliferation, limiting regeneration after myocardial injury. Overexpression of the transcription factor Myc has been shown to drive proliferation in the adult mouse heart, but only when combined with Cyclin T1. As constitutive HRas activity has been shown to stabilise Cyclin T1 in vivo, we aimed to establish whether Myc and HRas could also act cooperatively to induce proliferation in adult mammalian cardiomyocytes in vivo.

Methods and results

Using a genetically modified mouse model, we confirmed that constitutive HRas activity (HRas G 12 V ) increased Cyclin T1 expression. HRas G 12 V and constitutive Myc expression together co-operate to drive cell-cycle progression of adult mammalian cardiomyocytes. However, stimulation of endogenous cardiac proliferation by the ectopic expression of HRas G 12 V and Myc also induced cardiomyocyte death, while Myc and Cyclin T1 expression did not.

Conclusion

Co-expression of Cyclin T1 and Myc may be a therapeutically tractable approach for cardiomyocyte neo-genesis post injury, while cell death induced by HRas G 12 V and Myc expression likely limits this option as a regenerative therapeutic target.

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.

Dysfunction of histone demethylase IBM1 in Arabidopsis causes autoimmunity and reshapes the root microbiome

Root microbiota is important for plant growth and fitness. Little is known about whether and how the assembly of root microbiota may be controlled by epigenetic regulation, which is crucial for gene transcription and genome stability. Here we show that dysfunction of the histone demethylase IBM1 (INCREASE IN BONSAI METHYLATION 1) in Arabidopsis thaliana substantially reshaped the root microbiota, with the majority of the significant amplicon sequence variants (ASVs) being decreased. Transcriptome analyses of plants grown in soil and in sterile growth medium jointly disclosed salicylic acid (SA)-mediated autoimmunity and production of the defense metabolite camalexin in the ibm1 mutants. Analyses of genome-wide histone modifications and DNA methylation highlighted epigenetic modifications permissive for transcription at several important defense regulators. Consistently, ibm1 mutants showed increased resistance to the pathogen Pseudomonas syringae DC3000 with stronger immune responses. In addition, ibm1 showed substantially impaired plant growth promotion in response to beneficial bacteria; the impairment was partially mimicked by exogenous application of SA to wild-type plants, and by a null mutation of AGP19 that is important for cell expansion and that is repressed with DNA hypermethylation in ibm1. IBM1-dependent epigenetic regulation imposes strong and broad impacts on plant-microbe interactions and thereby shapes the assembly of root microbiota.

DNA methylation profiles in the blood of newborn term infants born to mothers with obesity

Maternal obesity is an important risk factor for childhood obesity and influences the prevalence of metabolic diseases in offspring. As childhood obesity is influenced by postnatal factors, it is critical to determine whether children born to women with obesity during pregnancy show alterations that are detectable at birth. Epigenetic mechanisms such as DNA methylation modifications have been proposed to mediate prenatal programming. We investigated DNA methylation signatures in male and female infants from mothers with a normal Body Mass Index (BMI 18.5-24.9 kg/m2) compared to mothers with obesity (BMI≥30 kg/m2). BMI was measured during the first prenatal visit from women recruited into the Ontario Birth Study (OBS) at Mount Sinai Hospital in Toronto, ON, Canada. DNA was extracted from neonatal dried blood spots collected from heel pricks obtained 24 hours after birth at term (total n = 40) from women with a normal BMI and women with obesity matched for parity, age, and neonatal sex. Reduced representation bisulfite sequencing was used to identify genomic loci associated with differentially methylated regions (DMRs) in CpG-dense regions most likely to influence gene regulation. DMRs were predominantly localized to intergenic regions and gene bodies, with only 9% of DMRs localized to promoter regions. Genes associated with DMRs were compared to those from a large publicly available cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC; total n = 859). Hypergeometric tests revealed a significant overlap in genes associated with DMRs in the OBS and ALSPAC cohorts. PTPRN2, a gene involved in insulin secretion, and MAD1L1, which plays a role in the cell cycle and tumor suppression, contained DMRs in males and females in both cohorts. In males, KEGG pathway analysis revealed significant overrepresentation of genes involved in endocytosis and pathways in cancer, including IGF1R, which was previously shown to respond to diet-induced metabolic stress in animal models and in lymphocytes in the context of childhood obesity. These preliminary findings are consistent with Developmental Origins of Health and Disease paradigm, which posits that adverse prenatal exposures set developmental health trajectories.

Polycomb group ring finger protein 6 suppresses Myc-induced lymphomagenesis

Max dimerizes with Mga to form the repressive complex PRC1.6; another PRC1.6 subunit, Pcgf6, suppresses Myc-induced lymphomagenesis but, unexpectedly, does so in a Mga- and PRC1.6-independent manner.

Max is an obligate dimerization partner for the Myc transcription factors and for several repressors, such as Mnt, Mxd1-4, and Mga, collectively thought to antagonize Myc function in transcription and oncogenesis. Mga, in particular, is part of the variant Polycomb group repressive complex PRC1.6. Here, we show that ablation of the distinct PRC1.6 subunit Pcgf6–but not Mga–accelerates Myc-induced lymphomagenesis in Eµ-myc transgenic mice. Unexpectedly, however, Pcgf6 loss shows no significant impact on transcriptional profiles, in neither pre-tumoral B-cells, nor lymphomas. Altogether, these data unravel an unforeseen, Mga- and PRC1.6-independent tumor suppressor activity of Pcgf6.

Analysis of Bisulfite Sequencing Data Using Bismark and DMRcaller to Identify Differentially Methylated Regions

The mechanism of the addition of a methyl group to cytosine has been identified as one of several heritable epigenetic mechanisms. In plants, DNA methylation is involved in mediating response to stress, plant development, polyploidy, and domestication through regulation of gene expression. The correlation of epigenetic variation to phenotypic traits expands our understanding toward plant evolution, and provides new source for targeted manipulation in crop improvement. To address the increasing interest to map methylation landscape in plant species, this chapter describes methods to analyze bisulfite sequencing data and identify epigenetic variation between samples. We also detailed guidelines to highlight possible optimizations, as well as ways to tailor parameters according to data and biological variability.

Whole-Genome DNA Methylation Dynamics of Sheep Preimplantation Embryo Investigated by Single-Cell DNA Methylome Sequencing

The early stages of mammalian embryonic development involve the participation and cooperation of numerous complex processes, including nutritional, genetic, and epigenetic mechanisms. However, in embryos cultured in vitro, a developmental block occurs that affects embryo development and the efficiency of culture. Although the block period is reported to involve the transcriptional repression of maternal genes and transcriptional activation of zygotic genes, how epigenetic factors regulate developmental block is still unclear. In this study, we systematically analyzed whole-genome methylation levels during five stages of sheep oocyte and preimplantation embryo development using single-cell level whole genome bisulphite sequencing (SC-WGBS) technology. Then, we examined several million CpG sites in individual cells at each evaluated developmental stage to identify the methylation changes that take place during the development of sheep preimplantation embryos. Our results showed that two strong waves of methylation changes occurred, namely, demethylation at the 8-cell to 16-cell stage and methylation at the 16-cell to 32-cell stage. Analysis of DNA methylation patterns in different functional regions revealed a stable hypermethylation status in 3'UTRs and gene bodies; however, significant differences were observed in intergenic and promoter regions at different developmental stages. Changes in methylation at different stages of preimplantation embryo development were also compared to investigate the molecular mechanisms involved in sheep embryo development at the methylation level. In conclusion, we report a detailed analysis of the DNA methylation dynamics during the development of sheep preimplantation embryos. Our results provide an explanation for the complex regulatory mechanisms underlying the embryo developmental block based on changes in DNA methylation levels.

Identification of DNA Methylation and Transcriptomic Profiles Associated With Fruit Mealiness in Prunus persica (L.) Batsch

Peach (Prunus persica) fruits have a fast ripening process and a shelf-life of days, presenting a challenge for long-distance consuming markets. To prolong shelf-life, peach fruits are stored at low temperatures (0 to 7 °C) for at least two weeks, which can lead to the development of mealiness, a physiological disorder that reduces fruit quality and decreases consumer acceptance. Several studies have been made to understand this disorder, however, the molecular mechanisms underlying mealiness are not fully understood. Epigenetic factors, such as DNA methylation, modulate gene expression according to the genetic background and environmental conditions. In this sense, the aim of this work was to identify differentially methylated regions (DMRs) that could affect gene expression in contrasting individuals for mealiness. Peach flesh was studied at harvest time (E1 stage) and after cold storage (E3 stage) for 30 days. The distribution of DNA methylations within the eight chromosomes of P. persica showed higher methylation levels in pericentromeric regions and most differences between mealy and normal fruits were at Chr1, Chr4, and Chr8. Notably, differences in Chr4 co-localized with previous QTLs associated with mealiness. Additionally, the number of DMRs was higher in CHH cytosines of normal and mealy fruits at E3; however, most DMRs were attributed to mealy fruits from E1, increasing at E3. From RNA-Seq data, we observed that differentially expressed genes (DEGs) between normal and mealy fruits were associated with ethylene signaling, cell wall modification, lipid metabolism, oxidative stress and iron homeostasis. When integrating the annotation of DMRs and DEGs, we identified a CYP450 82A and an UDP-ARABINOSE 4 EPIMERASE 1 gene that were downregulated and hypermethylated in mealy fruits, coinciding with the co-localization of a transposable element (TE). Altogether, this study indicates that genetic differences between tolerant and susceptible individuals is predominantly affecting epigenetic regulation over gene expression, which could contribute to a metabolic alteration from earlier stages of development, resulting in mealiness at later stages. Finally, this epigenetic mark should be further studied for the development of new molecular tools in support of breeding programs.

Integrated requirement of non-specific and sequence-specific DNA binding in Myc-driven transcription

Eukaryotic transcription factors recognize specific DNA sequence motifs, but are also endowed with generic, non-specific DNA-binding activity. How these binding modes are integrated to determine select transcriptional outputs remains unresolved. We addressed this question by site-directed mutagenesis of the Myc transcription factor. Impairment of non-specific DNA backbone contacts caused pervasive loss of genome interactions and gene regulation, associated with increased intra-nuclear mobility of the Myc protein in murine cells. In contrast, a mutant lacking base-specific contacts retained DNA-binding and mobility profiles comparable to those of the wild-type protein, but failed to recognize its consensus binding motif (E-box) and could not activate Myc-target genes. Incidentally, this mutant gained weak affinity for an alternative motif, driving aberrant activation of different genes. Altogether, our data show that non-specific DNA binding is required to engage onto genomic regulatory regions; sequence recognition in turn contributes to transcriptional activation, acting at distinct levels: stabilization and positioning of Myc onto DNA, and-unexpectedly-promotion of its transcriptional activity. Hence, seemingly pervasive genome interaction profiles, as detected by ChIP-seq, actually encompass diverse DNA-binding modalities, driving defined, sequence-dependent transcriptional responses.

Differential Transcriptomes and Methylomes of Trophoblast Stem Cells From Naturally-Fertilized and Somatic Cell Nuclear-Transferred Embryos

Trophoblast stem cells (TSCs) are critical to mammalian embryogenesis by providing the cell source of the placenta. TSCs can be derived from trophoblast cells. However, the efficiency of TSC derivation from somatic cell nuclear transfer (NT) blastocysts is low. The regulatory mechanisms underlying transcription dynamics and epigenetic landscape remodeling during TSC derivation remain elusive. Here, we derived TSCs from the blastocysts by natural fertilization (NF), NT, and a histone deacetylase inhibitor Scriptaid-treated NT (SNT). Profiling of the transcriptomes across the stages of TSC derivation revealed that fibroblast growth factor 4 (FGF4) treatment resulted in many differentially expressed genes (DEGs) at outgrowth and initiated transcription program for TSC formation. We identified 75 transcription factors (TFs) that are continuously upregulated during NF TSC derivation, whose transcription profiles can infer the time course of NF not NT TSC derivation. Most DEGs in NT outgrowth are rescued in SNT outgrowth. The correct time course of SNT TSC derivation is inferred accordingly. Moreover, these TFs comprise an interaction network important to TSC stemness. Profiling of DNA methylation dynamics showed an extremely low level before FGF4 treatment and gradual increases afterward. FGF4 treatment results in a distinct DNA methylation remodeling process committed to TSC formation. We further identified 1,293 CpG islands (CGIs) whose DNA methylation difference is more than 0.25 during NF TSC derivation. The majority of these CGIs become highly methylated upon FGF4 treatment and remain in high levels. This may create a barrier for lineage commitment to restrict embryonic development, and ensure TSC formation. There exist hundreds of aberrantly methylated CGIs during NT TSC derivation, most of which are corrected during SNT TSC derivation. More than half of the aberrantly methylated CGIs before NT TSC formation are inherited from the donor genome. In contrast, the aberrantly methylated CGIs upon TSC formation are mainly from the highly methylated CGIs induced by FGF4 treatment. Functional annotation indicates that the aberrantly highly methylated CGIs play a role in repressing placenta development genes, etc., related to post-implantation development and maintaining TSC pluripotency. Collectively, our findings provide novel insights into the transcription dynamics, DNA methylation remodeling, and the role of FGF4 during TSC derivation.

Bioinformatic tools for DNA methylation and histone modification: A survey

Epigenetic inheritance occurs due to different mechanisms such as chromatin and histone modifications, DNA methylation and processes mediated by non-coding RNAs. It leads to changes in gene expressions and the emergence of new traits in different organisms in many diseases such as cancer. Recent advances in experimental methods led to the identification of epigenetic target sites in various organisms. Computational approaches have enabled us to analyze mass data produced by these methods. Next-generation sequencing (NGS) methods have been broadly used to identify these target sites and their patterns. By using these patterns, the emergence of diseases could be prognosticated. In this study, target site prediction tools for two major epigenetic mechanisms comprising histone modification and DNA methylation are reviewed. Publicly accessible databases are reviewed as well. Some suggestions regarding the state-of-the-art methods and databases have been made, including examining patterns of epigenetic changes that are important in epigenotypes detection.

DNA methylome signatures of prenatal exposure to synthetic glucocorticoids in hippocampus and peripheral whole blood of female guinea pigs in early life

Synthetic glucocorticoids (sGC) are administered to women at risk of preterm delivery, approximately 10% of all pregnancies. In animal models, offspring exposed to elevated glucocorticoids, either by administration of sGC or endogenous glucocorticoids as a result of maternal stress, show increased risk of developing behavioral, endocrine, and metabolic dysregulation. DNA methylation may play a critical role in long-lasting programming of gene regulation underlying these phenotypes. However, peripheral tissues such as blood are often the only accessible source of DNA for epigenetic analyses in humans. Here, we examined the hypothesis that prenatal sGC administration alters DNA methylation signatures in guinea pig offspring hippocampus and whole blood. We compared these signatures across the two tissue types to assess epigenetic biomarkers of common molecular pathways affected by sGC exposure. Guinea pigs were treated with sGC or saline in late gestation. Genome-wide modifications of DNA methylation were analyzed at single nucleotide resolution using reduced representation bisulfite sequencing in juvenile female offspring. Results indicate that there are tissue-specific as well as common methylation signatures of prenatal sGC exposure. Over 90% of the common methylation signatures associated with sGC exposure showed the same directionality of change in methylation. Among differentially methylated genes, 134 were modified in both hippocampus and blood, of which 61 showed methylation changes at identical CpG sites. Gene pathway analyses indicated that prenatal sGC exposure alters the methylation status of gene clusters involved in brain development. These data indicate concordance across tissues of epigenetic programming in response to alterations in glucocorticoid signaling.

Single-base cytosine methylation analysis in fruits of three Capsicum species

Single-base cytosine methylation analysis across fruits of Capsicum annuum, C. chinense and C. frutescens showed global average methylation ranging from 82.8-89.1%, 77.6-83.9%, and 22.4-25% at CG, CHG and CHH contexts, respectively. High gene-body methylation at CG and CHG was observed across Capsicum species. The C. annuum showed the highest proportion (>80%) of mCs at different genomic regions compared to C. chinense and C. frutescens. Cytosine methylation for transposable-elements were lower in C. frutescens compared to C. annuum and C. chinense. A total of 510,165 CG, 583112 CHG and 277,897 CHH DMRs were identified across three Capsicum species. The differentially methylated regions (DMRs) distribution analysis revealed C. frutescens as more hypo-methylated compared to C. annuum and C. chinense, and also the presence of more intergenic DMRs in Capsicum genome. At CG and CHG context, gene expression and promoter methylation showed inverse correlations. Furthermore, the observed correlation between methylation and expression of genes suggested the potential role of methylation in Capsicum fruit development/ripening.

Reactivation of Myc transcription in the mouse heart unlocks its proliferative capacity

It is unclear why some tissues are refractory to the mitogenic effects of the oncogene Myc. Here we show that Myc activation induces rapid transcriptional responses followed by proliferation in some, but not all, organs. Despite such disparities in proliferative response, Myc is bound to DNA at open elements in responsive (liver) and non-responsive (heart) tissues, but fails to induce a robust transcriptional and proliferative response in the heart. Using heart as an exemplar of a non-responsive tissue, we show that Myc-driven transcription is re-engaged in mature cardiomyocytes by elevating levels of the positive transcription elongation factor (P-TEFb), instating a large proliferative response. Hence, P-TEFb activity is a key limiting determinant of whether the heart is permissive for Myc transcriptional activation. These data provide a greater understanding of how Myc transcriptional activity is determined and indicate modification of P-TEFb levels could be utilised to drive regeneration of adult cardiomyocytes for the treatment of heart myopathies.

Computational Oncology in the Multi-Omics Era: State of the Art

Cancer is the quintessential complex disease. As technologies evolve faster each day, we are able to quantify the different layers of biological elements that contribute to the emergence and development of malignancies. In this multi-omics context, the use of integrative approaches is mandatory in order to gain further insights on oncological phenomena, and to move forward toward the precision medicine paradigm. In this review, we will focus on computational oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings; classification, diagnosis, and prognosis; and the development of models in the research setting, including their use for therapeutic target identification. We will discuss the machine learning and network approaches as two of the most promising emerging paradigms, in computational oncology. These approaches provide a foundation on how to integrate different layers of biological description into coherent frameworks that allow advances both in the basic and clinical settings.

EpiMOLAS: an intuitive web-based framework for genome-wide DNA methylation analysis

BACKGROUND

DNA methylation is a crucial epigenomic mechanism in various biological processes. Using whole-genome bisulfite sequencing (WGBS) technology, methylated cytosine sites can be revealed at the single nucleotide level. However, the WGBS data analysis process is usually complicated and challenging.

RESULTS

To alleviate the associated difficulties, we integrated the WGBS data processing steps and downstream analysis into a two-phase approach. First, we set up the required tools in Galaxy and developed workflows to calculate the methylation level from raw WGBS data and generate a methylation status summary, the mtable. This computation environment is wrapped into the Docker container image DocMethyl, which allows users to rapidly deploy an executable environment without tedious software installation and library dependency problems. Next, the mtable files were uploaded to the web server EpiMOLAS_web to link with the gene annotation databases that enable rapid data retrieval and analyses.

CONCLUSION

To our knowledge, the EpiMOLAS framework, consisting of DocMethyl and EpiMOLAS_web, is the first approach to include containerization technology and a web-based system for WGBS data analysis from raw data processing to downstream analysis. EpiMOLAS will help users cope with their WGBS data and also conduct reproducible analyses of publicly available data, thereby gaining insights into the mechanisms underlying complex biological phenomenon. The Galaxy Docker image DocMethyl is available at https://hub.docker.com/r/lsbnb/docmethyl/. EpiMOLAS_web is publicly accessible at http://symbiosis.iis.sinica.edu.tw/epimolas/.

A genomic and epigenomic atlas of prostate cancer in Asian populations

Prostate cancer is the second most common cancer in men worldwide¹. Over the past decade, large-scale integrative genomics efforts have enhanced our understanding of this disease by characterizing its genetic and epigenetic landscape in thousands of patients^2,3. However, most tumours profiled in these studies were obtained from patients from Western populations. Here we produced and analysed whole-genome, whole-transcriptome and DNA methylation data for 208 pairs of tumour tissue samples and matched healthy control tissue from Chinese patients with primary prostate cancer. Systematic comparison with published data from 2,554 prostate tumours revealed that the genomic alteration signatures in Chinese patients were markedly distinct from those of Western cohorts: specifically, 41% of tumours contained mutations in FOXA1 and 18% each had deletions in ZNF292 and CHD1. Alterations of the genome and epigenome were correlated and were predictive of disease phenotype and progression. Coding and noncoding mutations, as well as epimutations, converged on pathways that are important for prostate cancer, providing insights into this devastating disease. These discoveries underscore the importance of including population context in constructing comprehensive genomic maps for disease.

Impact of ex vivo Sample Handling on DNA Methylation Profiles in Human Cord Blood and Neonatal Dried Blood Spots

The profiling of DNA methylation modifications in peripheral blood has significant potential to determine risk factors for human disease. Little is known concerning the sensitivity of DNA methylation profiles to ex vivo sample handling. Here, we studied typical conditions prior to sample storage associated with cord blood samples obtained from clinical investigations using reduced representation bisulfite sequencing. We examined both whole blood collected shortly after birth and dried blood spots, a potentially important source of neonatal blood for investigation of the DNA methylome and the Developmental Origins of Health and Disease in human cohorts because they are routinely collected during clinical care. Samples were matched across different time conditions, as they were from the same cord blood samples obtained from the same individuals. Maintaining whole blood ex vivo up to 24 h (4°C) or dried blood spots up to 7 days (room temp.) had little effect on DNA methylation profiles. Minimal differences were detected between cord blood immediately frozen and dried blood spots. Our results indicate that DNA methylation profiles are resilient to ex vivo sample handling conditions prior to storage. These data will help guide future human studies focused toward determination of DNA methylation modifications in whole blood.

A dual role of dLsd1 in oogenesis: regulating developmental genes and repressing transposons

The histone demethylase LSD1 is a key chromatin regulator that is often deregulated in cancer. Its ortholog, dLsd1 plays a crucial role in Drosophila oogenesis; however, our knowledge of dLsd1 function is insufficient to explain its role in the ovary. Here, we have performed genome-wide analysis of dLsd1 binding in the ovary, and we document that dLsd1 is preferentially associated to the transcription start site of developmental genes. We uncovered an unanticipated interplay between dLsd1 and the GATA transcription factor Serpent and we report an unexpected role for Serpent in oogenesis. Besides, our transcriptomic data show that reducing dLsd1 levels results in ectopic transposable elements (TE) expression correlated with changes in H3K4me2 and H3K9me2 at TE loci. In addition, our results suggest that dLsd1 is required for Piwi dependent TE silencing. Hence, we propose that dLsd1 plays crucial roles in establishing specific gene expression programs and in repressing transposons during oogenesis.

Dormant but Active: Chilling Accumulation Modulates the Epigenome and Transcriptome of Prunus avium During Bud Dormancy

Temperate deciduous fruit tree species like sweet cherry (Prunus avium) require long periods of low temperatures to trigger dormancy release and flowering. In addition to sequence-based genetic diversity, epigenetic variation may contribute to different chilling requirements among varieties. For the low chill variety 'Royal Dawn' and high chill variety 'Kordia', we studied the methylome of floral buds during chilling accumulation using MethylC-seq to identify differentially methylated regions (DMRs) during chilling hours (CH) accumulation, followed by transcriptome analysis to correlate changes in gene expression with DNA methylation. We found that during chilling accumulation, DNA methylation increased from 173 CH in 'Royal Dawn' and 443 CH in 'Kordia' and was mostly associated with the CHH context. In addition, transcriptional changes were observed from 443 CH in 'Kordia' with 1,210 differentially expressed genes, increasing to 4,292 genes at 1,295 CH. While 'Royal Dawn' showed approximately 5,000 genes differentially expressed at 348 CH and 516 CH, showing a reprogramming that was specific for each genotype. From conserved upregulated genes that overlapped with hypomethylated regions and downregulated genes that overlapped with hypermethylated regions in both varieties, we identified genes related to cold-sensing, cold-signaling, oxidation-reduction process, metabolism of phenylpropanoids and lipids, and a MADS-box SVP-like gene. As a complementary analysis, we used conserved and non-conserved DEGs that presented a negative correlation between DNA methylations and mRNA levels across all chilling conditions, obtaining Gene Ontology (GO) categories related to abiotic stress, metabolism, and oxidative stress. Altogether, this data indicates that changes in DNA methylation precedes transcript changes and may occur as an early response to low temperatures to increase the cold tolerance in the endodormancy period, contributing with the first methylome information about the effect of environmental cues over two different genotypes of sweet cherry.

Method for Bisulfite Sequencing Data Analysis for Whole-Genome Level DNA Methylation Detection in Legumes

Methylation of cytosines in DNA is the most stable type of epigenetic modification that is established and maintained by different enzymes. In plants, DNA methylation is inherited from one generation to another leaving an epigenetic mark as a memory of previous state, which may include encounter with stress or pathogen. Advancement in the next generation sequencing technologies has enabled the profiling of methylation marks. Whole-genome bisulfite sequencing (WGBS) has the potential to unravel the patterns of DNA methylation at single-base resolution. Though the sequencing technologies have evolved drastically, analysis of WGBS data still remains challenging. Here, we provide a methodology for performing WGBS data analysis along with critical steps for identification of methylation marks in plant genomes including legumes.

Gene set analysis methods for the functional interpretation of non-mRNA data—Genomic range and ncRNA data

Gene set analysis (GSA) is one of the methods of choice for analyzing the results of current omics studies; however, it has been mainly developed to analyze mRNA (microarray, RNA-Seq) data. The following review includes an update regarding general methods and resources for GSA and then emphasizes GSA methods and tools for non-mRNA omics datasets, specifically genomic range data (ChIP-Seq, SNP and methylation) and ncRNA data (miRNAs, lncRNAs and others). In the end, the state of the GSA field for non-mRNA datasets is discussed, and some current challenges and trends are highlighted, especially the use of network approaches to face complexity issues.

An early Myc-dependent transcriptional program orchestrates cell growth during B-cell activation

Upon activation, lymphocytes exit quiescence and undergo substantial increases in cell size, accompanied by activation of energy-producing and anabolic pathways, widespread chromatin decompaction, and elevated transcriptional activity. These changes depend upon prior induction of the Myc transcription factor, but how Myc controls them remains unclear. We addressed this issue by profiling the response to LPS stimulation in wild-type and c-myc-deleted primary mouse B-cells. Myc is rapidly induced, becomes detectable on virtually all active promoters and enhancers, but has no direct impact on global transcriptional activity. Instead, Myc contributes to the swift up- and down-regulation of several hundred genes, including many known regulators of the aforementioned cellular processes. Myc-activated promoters are enriched for E-box consensus motifs, bind Myc at the highest levels, and show enhanced RNA Polymerase II recruitment, the opposite being true at down-regulated loci. Remarkably, the Myc-dependent signature identified in activated B-cells is also enriched in Myc-driven B-cell lymphomas: hence, besides modulation of new cancer-specific programs, the oncogenic action of Myc may largely rely on sustained deregulation of its normal physiological targets.

DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts

DNA methylation has been associated with transcriptional repression and detection of differential methylation is important in understanding the underlying causes of differential gene expression. Bisulfite-converted genomic DNA sequencing is the current gold standard in the field for building genome-wide maps at a base pair resolution of DNA methylation. Here we systematically investigate the underlying features of detecting differential DNA methylation in CpG and non-CpG contexts, considering both the case of mammalian systems and plants. In particular, we introduce DMRcaller, a highly efficient R/Bioconductor package, which implements several methods to detect differentially methylated regions (DMRs) between two samples. Most importantly, we show that different algorithms are required to compute DMRs and the most appropriate algorithm in each case depends on the sequence context and levels of methylation. Furthermore, we show that DMRcaller outperforms other available packages and we propose a new method to select the parameters for this tool and for other available tools. DMRcaller is a comprehensive tool for differential methylation analysis which displays high sensitivity and specificity for the detection of DMRs and performs entire genome wide analysis within a few hours.

DNA methylation dynamics during embryonic development and postnatal maturation of the mouse auditory sensory epithelium

The inner ear is a complex structure responsible for hearing and balance, and organ pathology is associated with deafness and balance disorders. To evaluate the role of epigenomic dynamics, we performed whole genome bisulfite sequencing at key time points during the development and maturation of the mouse inner ear sensory epithelium (SE). Our single-nucleotide resolution maps revealed variations in both general characteristics and dynamics of DNA methylation over time. This allowed us to predict the location of non-coding regulatory regions and to identify several novel candidate regulatory factors, such as Bach2, that connect stage-specific regulatory elements to molecular features that drive the development and maturation of the SE. Constructing in silico regulatory networks around sites of differential methylation enabled us to link key inner ear regulators, such as Atoh1 and Stat3, to pathways responsible for cell lineage determination and maturation, such as the Notch pathway. We also discovered that a putative enhancer, defined as a low methylated region (LMR), can upregulate the GJB6 gene and a neighboring non-coding RNA. The study of inner ear SE methylomes revealed novel regulatory regions in the hearing organ, which may improve diagnostic capabilities, and has the potential to guide the development of therapeutics for hearing loss by providing multiple intervention points for manipulation of the auditory system.

Dynamics of promoter bivalency and RNAP II pausing in mouse stem and differentiated cells

Background

Mammalian embryonic stem cells display a unique epigenetic and transcriptional state to facilitate pluripotency by maintaining lineage-specification genes in a poised state. Two epigenetic and transcription processes involved in maintaining poised state are bivalent chromatin, characterized by the simultaneous presence of activating and repressive histone methylation marks, and RNA polymerase II (RNAPII) promoter proximal pausing. However, the dynamics of histone modifications and RNAPII at promoters in diverse cellular contexts remains underexplored.

Results

We collected genome wide data for bivalent chromatin marks H3K4me3 and H3K27me3, and RNAPII (8WG16) occupancy together with expression profiling in eight different cell types, including ESCs, in mouse. The epigenetic and transcription profiles at promoters grouped in over thirty clusters with distinct functional identities and transcription control.

Conclusion

The clustering analysis identified distinct bivalent clusters where genes in one cluster retained bivalency across cell types while in the other were mostly cell type specific, but neither showed a high RNAPII pausing. We noted that RNAPII pausing is more associated with active genes than bivalent genes in a cell type, and was globally reduced in differentiated cell types compared to multipotent.

Electronic supplementary material

The online version of this article (10.1186/s12861-018-0163-7) contains supplementary material, which is available to authorized users.

Genome-wide DNA methylation analysis reveals that mouse chemical iPSCs have closer epigenetic features to mESCs than OSKM-integrated iPSCs

Induced pluripotent stem cells can be derived from somatic cells through ectopic expression of transcription factors or chemical cocktails. Chemical iPSCs (C-iPSCs) and OSKM-iPSCs (4F-iPSCs) have been suggested to have similar characteristics to mouse embryonic stem cells (mESCs). However, their epigenetic equivalence remains incompletely understood throughout the genome. In this study, we have generated mouse C-iPSCs and 4F-iPSCs, and further compared the genome-wide DNA methylomes of C-iPSCs, 4F-iPSCs, and mESCs that were maintained in 2i and LIF. Three pluripotent stem cells tend to be low methylated overall, however, DNA methylations in some specific regions (such as retrotransposons) are cell type-specific. Importantly, C-iPSCs are more hypomethylated than 4F-iPSCs. Bisulfite sequencing indicated that DNA methylation status in several known imprinted clusters, such as: Dlk1-Dio3 and Peg12-Ube3a, in C-iPSCs are closer to those of mESCs than 4F-iPSCs. Overall, our data demonstrate the reprogramming methods-dependent epigenetic differences of C-iPSCs and 4F-iPSCs and reveal that C-iPSCs are more hypomethylated than OSKM-integrated iPSCs.

Analysis of DNA modifications in aging research

As geroscience research extends into the role of epigenetics in aging and age-related disease, researchers are being confronted with unfamiliar molecular techniques and data analysis methods that can be difficult to integrate into their work. In this review, we focus on the analysis of DNA modifications, namely cytosine methylation and hydroxymethylation, through next-generation sequencing methods. While older techniques for modification analysis performed relative quantitation across regions of the genome or examined average genome levels, these analyses lack the desired specificity, rigor, and genomic coverage to firmly establish the nature of genomic methylation patterns and their response to aging. With recent methodological advances, such as whole genome bisulfite sequencing (WGBS), bisulfite oligonucleotide capture sequencing (BOCS), and bisulfite amplicon sequencing (BSAS), cytosine modifications can now be readily analyzed with base-specific, absolute quantitation at both cytosine-guanine dinucleotide (CG) and non-CG sites throughout the genome or within specific regions of interest by next-generation sequencing. Additional advances, such as oxidative bisulfite conversion to differentiate methylation from hydroxymethylation and analysis of limited input/single-cells, have great promise for continuing to expand epigenomic capabilities. This review provides a background on DNA modifications, the current state-of-the-art for sequencing methods, bioinformatics tools for converting these large data sets into biological insights, and perspectives on future directions for the field.

msgbsR: An R package for analysing methylation-sensitive restriction enzyme sequencing data

Genotyping-by-sequencing (GBS) or restriction-site associated DNA marker sequencing (RAD-seq) is a practical and cost-effective method for analysing large genomes from high diversity species. This method of sequencing, coupled with methylation-sensitive enzymes (often referred to as methylation-sensitive restriction enzyme sequencing or MRE-seq), is an effective tool to study DNA methylation in parts of the genome that are inaccessible in other sequencing techniques or are not annotated in microarray technologies. Current software tools do not fulfil all methylation-sensitive restriction sequencing assays for determining differences in DNA methylation between samples. To fill this computational need, we present msgbsR, an R package that contains tools for the analysis of methylation-sensitive restriction enzyme sequencing experiments. msgbsR can be used to identify and quantify read counts at methylated sites directly from alignment files (BAM files) and enables verification of restriction enzyme cut sites with the correct recognition sequence of the individual enzyme. In addition, msgbsR assesses DNA methylation based on read coverage, similar to RNA sequencing experiments, rather than methylation proportion and is a useful tool in analysing differential methylation on large populations. The package is fully documented and available freely online as a Bioconductor package (https://bioconductor.org/packages/release/bioc/html/msgbsR.html).

Identification of Differentially Methylated Regions in the Genome of Arabidopsis thaliana

DNA methylation profiling in the epigenome of Arabidopsis thaliana (Arabidopsis) has provided great insights in the role of this epigenetic mark for the regulation of transcription in plants, and is often based on high-throughput sequencing. The analysis of these data involves a series of steps including quality checks, filtering, alignment, identification of methyl-cytosines, and the identification of differentially methylated regions. This chapter outlines the computational methodology required to profile genome-wide differential methylation patterns based on publicly available Arabidopsis base-resolution bisulfite sequencing data. The methylPipe Bioconductor package is adopted for the identification of the differentially methylated regions, and all the steps from the raw data to the required input are described in detail.

Integrated DNA methylome and transcriptome analysis reveals the ethylene-induced flowering pathway genes in pineapple

Ethylene has long been used to promote flowering in pineapple production. Ethylene-induced flowering is dose dependent, with a critical threshold level of ethylene response factors needed to trigger flowering. The mechanism of ethylene-induced flowering is still unclear. Here, we integrated isoform sequencing (iso-seq), Illumina short-reads sequencing and whole-genome bisulfite sequencing (WGBS) to explore the early changes of transcriptomic and DNA methylation in pineapple following high-concentration ethylene (HE) and low-concentration ethylene (LE) treatment. Iso-seq produced 122,338 transcripts, including 26,893 alternative splicing isoforms, 8,090 novel transcripts and 12,536 candidate long non-coding RNAs. The WGBS results suggested a decrease in CG methylation and increase in CHH methylation following HE treatment. The LE and HE treatments induced drastic changes in transcriptome and DNA methylome, with LE inducing the initial response to flower induction and HE inducing the subsequent response. The dose-dependent induction of FLOWERING LOCUS T-like genes (FTLs) may have contributed to dose-dependent flowering induction in pineapple by ethylene. Alterations in DNA methylation, lncRNAs and multiple genes may be involved in the regulation of FTLs. Our data provided a landscape of the transcriptome and DNA methylome and revealed a candidate network that regulates flowering time in pineapple, which may promote further studies.

Integrating DNA Methylation and Hydroxymethylation Data with the Mint Pipeline

DNA methylation (5mC) plays important roles in mammalian development, oncogenesis, treatment response, and responses to the environment. DNA hydroxymethylation (5hmC) is also an informative epigenetic mark with distinct roles in regulation and cancer. Gold-standard, widely used technologies (bisulfite conversion, followed by deep sequencing) cannot distinguish between 5mC and 5hmC. Therefore, additional experiments are required to differentiate the two marks, and in silico methods are needed to analyze, integrate, and interpret these data. We developed the Methylation INTegration (mint) pipeline to support the comprehensive analysis of bisulfite conversion and immunoprecipitation-based methylation and hydroxymethylation assays, with additional steps toward integration, visualization, and interpretation. The pipeline is available as both a command line and a Galaxy graphical user interface tool. Both implementations require minimal configuration while remaining flexible to experiment specific needs. Cancer Res; 77(21); e27-30. ©2017 AACR.

Genome-wide profiling of nardilysin target genes reveals its role in epigenetic regulation and cell cycle progression

Post-translational histone modifications, such as acetylation and methylation, are prerequisites for transcriptional regulation. The metalloendopeptidase nardilysin (Nrdc) is a H3K4me2-binding protein that controls thermoregulation and β-cell functions through its transcriptional coregulator function. We herein combined high-throughput ChIP-seq and RNA-seq to achieve the first genome-wide identification of Nrdc target genes. A ChIP-seq analysis of immortalized mouse embryo fibroblasts (iMEF) identified 4053 Nrdc-binding sites, most of which were located in proximal promoter sites (2587 Nrdc-binding genes). Global H3K4me2 levels at Nrdc-binding promoters slightly increased, while H3K9ac levels decreased in the absence of Nrdc. Among Nrdc-binding genes, a comparative RNA-seq analysis identified 448 candidates for Nrdc target genes, among which cell cycle-related genes were significantly enriched. We confirmed decreased mRNA and H3K9ac levels at the promoters of individual genes in Nrdc-deficient iMEF, which were restored by the ectopic introduction of Nrdc. Reduced mRNA levels, but not H3K9ac levels were fully restored by the reintroduction of the peptidase-dead mutant of Nrdc. Furthermore, Nrdc promoted cell cycle progression at multiple stages, which enhanced cell proliferation in vivo. Collectively, our integrative studies emphasize the importance of Nrdc for maintaining a proper epigenetic status and cell growth.

Whole Genome DNA Methylation Analysis Using Next-Generation Sequencing (BS-seq)

Plant methylation is widely evident and has played crucial roles ranging in defining the epi-genome variations during abiotic and biotic stress. Variations in epi-genomic level has observed not only in the symmetrical as well as the non-symmetrical sequences. Plethora of these epi-genomic variations have been widely also demonstrated at the flowering, tissue-specific, and also at developmental stages revealing a strong association of the observed epi-alleles to the physiological state. In the present chapter, epi-genomic analysis of the s has been described with functional workflow and illustrated methodology.

TEA: the epigenome platform for Arabidopsis methylome study

Background

Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task.

Results

We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits.

Conclusions

TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data.

TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw.

Successful transmission and transcriptional deployment of a human chromosome via mouse male meiosis

Most human aneuploidies originate maternally, due in part to the presence of highly stringent checkpoints during male meiosis. Indeed, male sterility is common among aneuploid mice used to study chromosomal abnormalities, and male germline transmission of exogenous DNA has been rarely reported. Here we show that, despite aberrant testis architecture, males of the aneuploid Tc1 mouse strain produce viable sperm and transmit human chromosome 21 to create aneuploid offspring. In these offspring, we mapped transcription, transcriptional initiation, enhancer activity, non-methylated DNA, and transcription factor binding in adult tissues. Remarkably, when compared with mice derived from female passage of human chromosome 21, the chromatin condensation during spermatogenesis and the extensive epigenetic reprogramming specific to male germline transmission resulted in almost indistinguishable patterns of transcriptional deployment. Our results reveal an unexpected tolerance of aneuploidy during mammalian spermatogenesis, and the surprisingly robust ability of mouse developmental machinery to accurately deploy an exogenous chromosome, regardless of germline transmission.

Profiling genome-wide DNA methylation

DNA methylation is an epigenetic modification that plays an important role in regulating gene expression and therefore a broad range of biological processes and diseases. DNA methylation is tissue-specific, dynamic, sequence-context-dependent and trans-generationally heritable, and these complex patterns of methylation highlight the significance of profiling DNA methylation to answer biological questions. In this review, we surveyed major methylation assays, along with comparisons and biological examples, to provide an overview of DNA methylation profiling techniques. The advances in microarray and sequencing technologies make genome-wide profiling possible at a single-nucleotide or even a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, genomic region coverage, and bioinformatics analysis, and selecting a feasible method requires knowledge of these methods. We first introduce the biological background of DNA methylation and its pattern in plants, animals and fungi. We present an overview of major experimental approaches to profiling genome-wide DNA methylation and hydroxymethylation and then extend to the single-cell methylome. To evaluate these methods, we outline their strengths and weaknesses and perform comparisons across the different platforms. Due to the increasing need to compute high-throughput epigenomic data, we interrogate the computational pipeline for bisulfite sequencing data and also discuss the concept of identifying differentially methylated regions (DMRs). This review summarizes the experimental and computational concepts for profiling genome-wide DNA methylation, followed by biological examples. Overall, this review provides researchers useful guidance for the selection of a profiling method suited to specific research questions.