DNA methylation dynamics: identification and functional annotation

The CLASSY family controls tissue-specific DNA methylation patterns in Arabidopsis

DNA methylation shapes the epigenetic landscape of the genome, plays critical roles in regulating gene expression, and ensures transposon silencing. As is evidenced by the numerous defects associated with aberrant DNA methylation landscapes, establishing proper tissue-specific methylation patterns is critical. Yet, how such differences arise remains a largely open question in both plants and animals. Here we demonstrate that CLASSY1-4 (CLSY1-4), four locus-specific regulators of DNA methylation, also control tissue-specific methylation patterns, with the most striking pattern observed in ovules where CLSY3 and CLSY4 control DNA methylation at loci with a highly conserved DNA motif. On a more global scale, we demonstrate that specific clsy mutants are sufficient to shift the epigenetic landscape between tissues. Together, these findings reveal substantial epigenetic diversity between tissues and assign these changes to specific CLSY proteins, elucidating how locus-specific targeting combined with tissue-specific expression enables the CLSYs to generate epigenetic diversity during plant development.

CLASSY (CLSY) proteins regulate DNA methylation at specific loci in the Arabidopsis genome. Here the authors show that the CLSYs also control tissue-specific DNA methylation, including at siren loci in ovules, and that the lack of an individual CLSYs can shift the epigenetic landscape between tissues.

Epigenetic Regulation of Dental Pulp Stem Cell Fate

Epigenetic regulation, mainly involving DNA methylation, histone modification, and noncoding RNAs, affects gene expression without modifying the primary DNA sequence and modulates cell fate. Mesenchymal stem cells derived from dental pulp, also called dental pulp stem cells (DPSCs), exhibit multipotent differentiation capacity and can promote various biological processes, including odontogenesis, osteogenesis, angiogenesis, myogenesis, and chondrogenesis. Over the past decades, increased attention has been attracted by the use of DPSCs in the field of regenerative medicine. According to a series of studies, epigenetic regulation is essential for DPSCs to differentiate into specialized cells. In this review, we summarize the mechanisms involved in the epigenetic regulation of the fate of DPSCs.

DNA methylation changes in clonally propagated oil palm

Several hypomethylated sites within the Karma region of EgDEF1 and hotspot regions in chromosomes 1, 2, 3, and 5 may be associated with mantling. One of the main challenges faced by the oil palm industry is fruit abnormalities, such as the "mantled" phenotype that can lead to reduced yields. This clonal abnormality is an epigenetic phenomenon and has been linked to the hypomethylation of a transposable element within the EgDEF1 gene. To understand the epigenome changes in clones, methylomes of clonal oil palms were compared to methylomes of seedling-derived oil palms. Whole-genome bisulfite sequencing data from seedlings, normal, and mantled clones were analyzed to determine and compare the context-specific DNA methylomes. In seedlings, coding and regulatory regions are generally hypomethylated while introns and repeats are extensively methylated. Genes with a low number of guanines and cytosines in the third position of codons (GC₃-poor genes) were increasingly methylated towards their 3' region, while GC₃-rich genes remain demethylated, similar to patterns in other eukaryotic species. Predicted promoter regions were generally hypomethylated in seedlings. In clones, CG, CHG, and CHH methylation levels generally decreased in functionally important regions, such as promoters, 5' UTRs, and coding regions. Although random regions were found to be hypomethylated in clonal genomes, hypomethylation of certain hotspot regions may be associated with the clonal mantling phenotype. Our findings, therefore, suggest other hypomethylated CHG sites within the Karma of EgDEF1 and hypomethylated hotspot regions in chromosomes 1, 2, 3 and 5, are associated with mantling.

Sex-dependent pronociceptive role of spinal α5 -GABAA receptor and its epigenetic regulation in neuropathic rodents

Extrasynaptic α₅ -subunit containing GABA_A (α₅ -GABA_A ) receptors participate in chronic pain. Previously, we reported a sex difference in the action of α₅ -GABA_A receptors in dysfunctional pain. However, the underlying mechanisms remain unknown. The aim of this study was to examine this sexual dimorphism in neuropathic rodents and the mechanisms involved. Female and male Wistar rats or ICR mice were subjected to nerve injury followed by α₅ -GABA_A receptor inverse agonist intrathecal administration, L-655,708. The drug produced an antiallodynic effect in nerve-injured female rats and mice, and a lower effect in males. We hypothesized that changes in α₅ -GABA_A receptor, probably influenced by hormonal and epigenetic status, might underlie this sex difference. Thus, we performed qPCR and western blot. Nerve injury increased α₅ -GABA_A mRNA and protein in female dorsal root ganglia (DRG) and decreased them in DRG and spinal cord of males. To investigate the hormonal influence over α₅ -GABA_A receptor actions, we performed nerve injury to ovariectomized rats and reconstituted them with 17β-estradiol (E2). Ovariectomy abrogated L-655,708 antiallodynic effect and E2 restored it. Ovariectomy decreased α₅ -GABA_A receptor and estrogen receptor α protein in DRG of neuropathic female rats, while E2 enhanced them. Since DNA methylation might contribute to α₅ -GABA_A receptor down-regulation in males, we examined CpG island DNA methylation of α₅ -GABA_A receptor coding gene through pyrosequencing. Nerve injury increased methylation in male, but not female rats. Pharmacological inhibition of DNA methyltransferases increased α₅ -GABA_A receptor and enabled L-655,708 antinociceptive effect in male rats. These results suggest that α₅ -GABA_A receptor is a suitable target to treat chronic pain in females.

Gene-methylation interactions: discovering region-wise DNA methylation levels that modify SNP-associated disease risk

BACKGROUND

Current technology allows rapid assessment of DNA sequences and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals simultaneously. This has led to an increase in epigenome-wide association studies (EWAS) of complex traits, particularly those that are poorly explained by previous genome-wide association studies (GWAS). However, the genome and epigenome are intertwined, e.g., DNA methylation is known to affect gene expression through, for example, genomic imprinting. There is thus a need to go beyond single-omics data analyses and develop interaction models that allow a meaningful combination of information from EWAS and GWAS.

RESULTS

We present two new methods for genetic association analyses that treat offspring DNA methylation levels as environmental exposure. Our approach searches for statistical interactions between SNP alleles and DNA methylation (G ×Me) and between parent-of-origin effects and DNA methylation (PoO ×Me), using case-parent triads or dyads. We use summarized methylation levels over nearby genomic region to ease biological interpretation. The methods were tested on a dataset of parent-offspring dyads, with EWAS data on the offspring. Our results showed that methylation levels around a SNP can significantly alter the estimated relative risk. Moreover, we show how a control dataset can identify false positives.

CONCLUSIONS

The new methods, G ×Me and PoO ×Me, integrate DNA methylation in the assessment of genetic relative risks and thus enable a more comprehensive biological interpretation of genome-wide scans. Moreover, our strategy of condensing DNA methylation levels within regions helps overcome specific disadvantages of using sparse chip-based measurements. The methods are implemented in the freely available R package Haplin ( https://cran.r-project.org/package=Haplin ), enabling fast scans of multi-omics datasets.

Genome-wide analysis of aberrant methylation of enhancer DNA in human osteoarthritis

Background

Osteoarthritis is a chronic musculoskeletal disease characterized by age-related gradual thinning and a high risk in females. Recent studies have shown that DNA methylation plays important roles in osteoarthritis. However, the genome-wide pattern of methylation in enhancers in osteoarthritis remains unclear.

Methods

To explore the function of enhancers in osteoarthritis, we quantified CpG methylation in human enhancers based on a public dataset that included methylation profiles of 470,870 CpG probes in 108 samples from patients with hip and knee osteoarthritis and hip tissues from healthy individuals. Combining various bioinformatics analysis tools, we systematically analyzed aberrant DNA methylation of the enhancers throughout the genome in knee osteoarthritis and hip osteoarthritis.

Results

We identified 16,816 differentially methylated CpGs, and nearly half (8111) of them were from enhancers, suggesting major DNA methylation changes in both types of osteoarthritis in the enhancer regions. A detailed analysis of hip osteoarthritis identified 2426 differentially methylated CpGs in enhancers between male and female patients, and 84.5% of them were hypomethylated in female patients and enriched in phenotypes related to hip osteoarthritis in females. Next, we explored the enhancer methylation dynamics among patients with knee osteoarthritis and identified 280 differentially methylated enhancer CpGs that were enriched in the human phenotypes and disease ontologies related to osteoarthritis. Finally, a comparison of enhancer methylation between knee osteoarthritis and hip osteoarthritis revealed organ source-dependent differences in enhancer methylation.

Conclusion

Our findings indicate that aberrant methylation of enhancers is related to osteoarthritis phenotypes, and a comprehensive atlas of enhancer methylation is useful for further analysis of the epigenetic regulation of osteoarthritis and the development of clinical drugs for treatment of osteoarthritis.

Developing novel in vitro methods for the risk assessment of developmental and placental toxicants in the environment

During pregnancy, the placenta is critical for the regulation of maternal homeostasis and fetal growth and development. Exposures to environmental chemicals during pregnancy can be detrimental to the health of the placenta and therefore adversely impact maternal and fetal health. Though research on placental-derived developmental toxicity is expanding, testing is limited by the resources required for traditional test methods based on whole animal experimentation. Alternative strategies utilizing in vitro methods are well suited to contribute to more efficient screening of chemical toxicity and identification of biological mechanisms underlying toxicity outcomes. This review aims to summarize methods that can be used to evaluate toxicity resulting from exposures during the prenatal period, with a focus on newer in vitro methods centered on placental toxicity. The following key aspects are reviewed: (i) traditional test methods based on animal developmental toxicity testing, (ii) in vitro methods using monocultures and explant models, as well as more recently developed methods, including co-cultures, placenta-on-a-chip, and 3-dimensional (3D) cell models, (iii) endpoints that are commonly measured using in vitro designs, and (iv) the translation of in vitro methods into chemical evaluations and risk assessment applications. We conclude that findings from in vitro placental models can contribute to the screening of potentially hazardous chemicals, elucidation of chemical mechanism of action, incorporation into adverse outcome pathways, estimation of doses eliciting toxicity, derivation of extrapolation factors, and characterization of overall risk of adverse outcomes, representing key components of chemical regulation in the 21^st century.

Mechanisms of Antisense Transcription Initiation with Implications in Gene Expression, Genomic Integrity and Disease Pathogenesis

Non-coding antisense transcripts arise from the strand opposite the sense strand. Over 70% of the human genome generates non-coding antisense transcripts while less than 2% of the genome codes for proteins. Antisense transcripts and/or the act of antisense transcription regulate gene expression and genome integrity by interfering with sense transcription and modulating histone modifications or DNA methylation. Hence, they have significant pathological and physiological relevance. Indeed, antisense transcripts were found to be associated with various diseases including cancer, diabetes, cardiac and neurodegenerative disorders, and, thus, have promising potentials for prognostic and diagnostic markers and therapeutic development. However, it is not clearly understood how antisense transcription is initiated and epigenetically regulated. Such knowledge would provide new insights into the regulation of antisense transcription, and hence disease pathogenesis with therapeutic development. The recent studies on antisense transcription initiation and its epigenetic regulation, which are limited, are discussed here. Furthermore, we concisely describe how antisense transcription/transcripts regulate gene expression and genome integrity with implications in disease pathogenesis and therapeutic development.

Whole‑genome scale identification of methylation markers specific for cerebral palsy in monozygotic discordant twins

Cerebral palsy (CP) is a severe type of brain disease affecting movement and posture. Although CP has strong genetic and environmental components, considerable differences in the methylome between monozygotic (MZ) twins discordant for CP implicates epigenetic contributors as well. In order to determine the differences in methylation in patients with CP without interference of the interindividual genomic variation, four pairs of MZ twins discordant for CP were profiled for DNA methylation changes using reduced representation bisulfite sequencing on the genomic-scale. Similar DNA methylation patterns were observed in all samples. However, MZ twins demonstrated higher correlations and closer evolutionary associations compared with the other samples, indicating a stable methylome of MZ twins. A total of 190 differentially methylated genes (DMGs) were identified using Student's t-test, of which 37 genes were hypermethylated in the CP group while the remainders were hypomethylated compared with control group. The identified DMGs were enriched in several cerebral abnormalities, including cerebral cortical atrophy and cerebral atrophy, suggesting that the occurrence of CP may be associated with the methylation alterations. The neighboring genes of DMGs in the protein-protein interaction network were enriched in numerous important functions in essential processes. The results of the present study identified important genes that may epigenetically contribute to the occurrence and development of CP in MZ twins, suggesting that the different prevalence of CP in identical twins may be associated with DNA methylation alterations.

Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns

Despite numerous studies done on understanding the role of DNA methylation, limited work has focused on systems integration of cell type-specific interplay between DNA methylation and gene transcription. Through a genome-wide analysis of DNA methylation across 19 cell types with T-47D as reference, we identified 106,252 cell type-specific differentially-methylated CpGs categorized into 7,537 differentially (46.6% hyper- and 53.4% hypo-) methylated regions. We found 44% promoter regions and 75% CpG islands were T-47D cell type-specific methylated. Pyrosequencing experiments validated the cell type-specific methylation across three benchmark cell lines. Interestingly, these DMRs overlapped with 1,145 known tumor suppressor genes. We then developed a Bayesian Gaussian Regression model to measure the relationship among DNA methylation, genomic segment distribution, differential gene expression and tumor suppressor gene status. The model uncovered that 3′UTR methylation has much less impact on transcriptional activity than other regions. Integration of DNA methylation and 82 transcription factor binding information across the 19 cell types suggested diverse interplay patterns between the two regulators. Our integrative analysis reveals cell type-specific and genomic region-dependent regulatory patterns and provides a perspective for integrating hundreds of various omics-seq data together.