Bis-class: a new classification tool of methylation status using bayes classifier and local methylation information

Integrative approach for classifying male tumors based on DNA methylation 450K data

Malignancies such as bladder urothelial carcinoma, colon adenocarcinoma, liver hepatocellular carcinoma, lung adenocarcinoma and prostate adenocarcinoma significantly impact men's well-being. Accurate cancer classification is vital in determining treatment strategies and improving patient prognosis. This study introduced an innovative method that utilizes gene selection from high-dimensional datasets to enhance the performance of the male tumor classification algorithm. The method assesses the reliability of DNA methylation data to distinguish the five most prevalent types of male cancers from normal tissues by employing DNA methylation 450K data obtained from The Cancer Genome Atlas (TCGA) database. First, the chi-square test is used for dimensionality reduction and second, L1 penalized logistic regression is used for feature selection. Furthermore, the stacking ensemble learning technique was employed to integrate seven common multiclassification models. Experimental results demonstrated that the ensemble learning model utilizing multiple classification models outperformed any base classification model. The proposed ensemble model achieved an astonishing overall accuracy (ACC) of 99.2% in independent testing data. Moreover, it may present novel ideas and pathways for the early detection and treatment of future diseases.

CGGBP1-regulated cytosine methylation at CTCF-binding motifs resists stochasticity

Background

The human CGGBP1 binds to GC-rich regions and interspersed repeats, maintains homeostasis of stochastic cytosine methylation and determines DNA-binding of CTCF. Interdependence between regulation of cytosine methylation and CTCF occupancy by CGGBP1 remains unknown.

Results

By analyzing methylated DNA-sequencing data obtained from CGGBP1-depleted cells, we report that some transcription factor-binding sites, including CTCF, resist stochastic changes in cytosine methylation. By analysing CTCF-binding sites we show that cytosine methylation changes at CTCF motifs caused by CGGBP1 depletion resist stochastic changes. These CTCF-binding sites are positioned at locations where the spread of cytosine methylation in cis depends on the levels of CGGBP1.

Conclusion

Our findings suggest that CTCF occupancy and functions are determined by CGGBP1-regulated cytosine methylation patterns.

Distinct epigenomic and transcriptomic modifications associated with Wolbachia-mediated asexuality

Wolbachia are maternally transmitted intracellular bacteria that induce a range of pathogenic and fitness-altering effects on insect and nematode hosts. In parasitoid wasps of the genus Trichogramma, Wolbachia infection induces asexual production of females, thus increasing transmission of Wolbachia. It has been hypothesized that Wolbachia infection accompanies a modification of the host epigenome. However, to date, data on genome-wide epigenomic changes associated with Wolbachia are limited, and are often confounded by background genetic differences. Here, we took sexually reproducing Trichogramma free of Wolbachia and introgressed their genome into a Wolbachia-infected cytoplasm, converting them to Wolbachia-mediated asexuality. Wolbachia was then cured from replicates of these introgressed lines, allowing us to examine the genome-wide effects of wasps newly converted to asexual reproduction while controlling for genetic background. We thus identified gene expression and DNA methylation changes associated with Wolbachia-infection. We found no overlaps between differentially expressed genes and differentially methylated genes, indicating that Wolbachia-infection associated DNA methylation change does not directly modulate levels of gene expression. Furthermore, genes affected by these mechanisms exhibit distinct evolutionary histories. Genes differentially methylated due to the infection tended to be evolutionarily conserved. In contrast, differentially expressed genes were significantly more likely to be unique to the Trichogramma lineage, suggesting host-specific transcriptomic responses to infection. Nevertheless, we identified several novel aspects of Wolbachia-associated DNA methylation changes. Differentially methylated genes included those involved in oocyte development and chromosome segregation. Interestingly, Wolbachia-infection was associated with higher levels of DNA methylation. Additionally, Wolbachia infection reduced overall variability in gene expression, even after accounting for the effect of DNA methylation. We also identified specific cases where alternative exon usage was associated with DNA methylation changes due to Wolbachia infection. These results begin to reveal distinct genes and molecular pathways subject to Wolbachia induced epigenetic modification and/or host responses to Wolbachia-infection.

Wolbachia is an extremely common endosymbiotic infection of arthropods and nematodes. One of the reasons why Wolbachia can so successfully infect diverse species is the bacterium’s ability to profoundly alter the reproductive behavior of its host. It has been proposed that Wolbachia may modify host’s epigenetic programs to alter its reproductive behavior. However, it has been difficult to study how epigenetic programs change with Wolbachia infection, due to the confounding effects of genetic backgrounds. Here, we studied host transcriptome and epigenome changes associated with Wolbachia infection in a homogenous genetic background, by carrying out an innovative introgression scheme. By doing so, we show, for the first time, high-resolution molecular consequences of intracellular infection and offer insights into epigenetic and transcriptomic regulation of invertebrates.

Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species

DNA methylation is one of the most extensively studied epigenetic modifications of genomic DNA. In recent years, sequencing of bisulfite-converted DNA, particularly via next-generation sequencing technologies, has become a widely popular method to study DNA methylation. This method can be readily applied to a variety of species, dramatically expanding the scope of DNA methylation studies beyond the traditionally studied human and mouse systems. In parallel to the increasing wealth of genomic methylation profiles, many statistical tools have been developed to detect differentially methylated loci (DMLs) or differentially methylated regions (DMRs) between biological conditions. We discuss and summarize several key properties of currently available tools to detect DMLs and DMRs from sequencing of bisulfite-converted DNA. However, the majority of the statistical tools developed for DML/DMR analyses have been validated using only mammalian data sets, and less priority has been placed on the analyses of invertebrate or plant DNA methylation data. We demonstrate that genomic methylation profiles of non-mammalian species are often highly distinct from those of mammalian species using examples of honey bees and humans. We then discuss how such differences in data properties may affect statistical analyses. Based on these differences, we provide three specific recommendations to improve the power and accuracy of DML and DMR analyses of invertebrate data when using currently available statistical tools. These considerations should facilitate systematic and robust analyses of DNA methylation from diverse species, thus advancing our understanding of DNA methylation.

Cell type-specific epigenetic links to schizophrenia risk in the brain

BACKGROUND

The importance of cell type-specific epigenetic variation of non-coding regions in neuropsychiatric disorders is increasingly appreciated, yet data from disease brains are conspicuously lacking. We generate cell type-specific whole-genome methylomes (N = 95) and transcriptomes (N = 89) from neurons and oligodendrocytes obtained from brain tissue of patients with schizophrenia and matched controls.

RESULTS

The methylomes of the two cell types are highly distinct, with the majority of differential DNA methylation occurring in non-coding regions. DNA methylation differences between cases and controls are subtle compared to cell type differences, yet robust against permuted data and validated in targeted deep-sequencing analyses. Differential DNA methylation between control and schizophrenia tends to occur in cell type differentially methylated sites, highlighting the significance of cell type-specific epigenetic dysregulation in a complex neuropsychiatric disorder.

CONCLUSIONS

Our results provide novel and comprehensive methylome and transcriptome data from distinct cell populations within patient-derived brain tissues. This data clearly demonstrate that cell type epigenetic-differentiated sites are preferentially targeted by disease-associated epigenetic dysregulation. We further show reduced cell type epigenetic distinction in schizophrenia.

Genomic Landscape of Methylation Islands in Hymenopteran Insects

Recent genome-wide DNA methylation analyses of insect genomes accentuate an intriguing contrast compared with those in mammals. In mammals, most CpGs are heavily methylated, with the exceptions of clusters of hypomethylated sites referred to as CpG islands. In contrast, DNA methylation in insects is localized to a small number of CpG sites. Here, we refer to clusters of methylated CpGs as “methylation islands (MIs),” and investigate their characteristics in seven hymenopteran insects with high-quality bisulfite sequencing data. Methylation islands were primarily located within gene bodies. They were significantly overrepresented in exon–intron boundaries, indicating their potential roles in splicing. Methylated CpGs within MIs exhibited stronger evolutionary conservation compared with those outside of MIs. Additionally, genes harboring MIs exhibited higher and more stable levels of gene expression compared with those that do not harbor MIs. The effects of MIs on evolutionary conservation and gene expression are independent and stronger than the effect of DNA methylation alone. These results indicate that MIs may be useful to gain additional insights into understanding the role of DNA methylation in gene expression and evolutionary conservation in invertebrate genomes.

Particulate matter exposure is associated with inflammatory gene methylation in obese subjects

BACKGROUND

Overweight and obesity are becoming more widespread with alarming projections for the coming years. Obesity may increase susceptibility to the adverse effects of PM exposure, exacerbating the effects on cardiovascular diseases and altering the biomarkers of vascular inflammation. The associated biological mechanisms have not been fully understood yet; the common denominator in the pathogenesis of the co-morbidities of obesity is the presence of an active, low-grade inflammatory process. DNA methylation has been shown to regulate inflammatory pathways that are responsible for the development of cardiovascular diseases.

OBJECTIVES

The aim of the study was to investigate, in a population of overweight/obese subjects, the effects of PM on blood DNA methylation in genes associated to inflammatory response.

METHODS

Using bisulfite pyrosequencing, we measured DNA methylation in peripheral blood mononuclear cells from 186 overweighted/obese subjects. In particular, we quantified DNA methylation in a set of 3 candidate genes, including CD14, TLR4 and TNF-α, because of the important roles that these genes play in the inflammatory pathway. Personal exposure to PM₁₀ was estimated for each subject based on the local PM₁₀ concentrations, measured by monitoring stations at residential address. Repeated measure models were used to evaluate the association of PM10 with each genes, accounting for possible correlations among the genes that regulate the same inflammatory pathway.

RESULTS

We found an inverse association between the daily PM₁₀ exposure and the DNA methylation of inflammatory genes, measured in peripheral blood of healthy overweight/obese subjects. Considering different exposure time-windows, the effect on CD14 and TLR4 methylation was observed, respectively, in days 4-5-6, and days 6-7-8. TNF-α methylation was not associated to PM₁₀.

CONCLUSIONS

Our findings support a picture in which PM₁₀ exposure and transcriptional regulation of inflammatory gene pathway in obese subjects are associated.

Impacts of Chromatin States and Long-Range Genomic Segments on Aging and DNA Methylation

Understanding the fundamental dynamics of epigenome variation during normal aging is critical for elucidating key epigenetic alterations that affect development, cell differentiation and diseases. Advances in the field of aging and DNA methylation strongly support the aging epigenetic drift model. Although this model aligns with previous studies, the role of other epigenetic marks, such as histone modification, as well as the impact of sampling specific CpGs, must be evaluated. Ultimately, it is crucial to investigate how all CpGs in the human genome change their methylation with aging in their specific genomic and epigenomic contexts. Here, we analyze whole genome bisulfite sequencing DNA methylation maps of brain frontal cortex from individuals of diverse ages. Comparisons with blood data reveal tissue-specific patterns of epigenetic drift. By integrating chromatin state information, divergent degrees and directions of aging-associated methylation in different genomic regions are revealed. Whole genome bisulfite sequencing data also open a new door to investigate whether adjacent CpG sites exhibit coordinated DNA methylation changes with aging. We identified significant 'aging-segments', which are clusters of nearby CpGs that respond to aging by similar DNA methylation changes. These segments not only capture previously identified aging-CpGs but also include specific functional categories of genes with implications on epigenetic regulation of aging. For example, genes associated with development are highly enriched in positive aging segments, which are gradually hyper-methylated with aging. On the other hand, regions that are gradually hypo-methylated with aging ('negative aging segments') in the brain harbor genes involved in metabolism and protein ubiquitination. Given the importance of protein ubiquitination in proteome homeostasis of aging brains and neurodegenerative disorders, our finding suggests the significance of epigenetic regulation of this posttranslational modification pathway in the aging brain. Utilizing aging segments rather than individual CpGs will provide more comprehensive genomic and epigenomic contexts to understand the intricate associations between genomic neighborhoods and developmental and aging processes. These results complement the aging epigenetic drift model and provide new insights.