Genome-wide DNA methylation profiling

Methylation and transcriptomic expression profiles of HUVEC in the oxygen and glucose deprivation model and its clinical implications in AMI patients

The obstructed coronary artery undergoes a series of pathological changes due to ischemic-hypoxic shocks during acute myocardial infarction (AMI). However, the altered DNA methylation levels in endothelial cells under these conditions and their implication for the etiopathology of AMI have not been investigated in detail. This study aimed to explore the relationship between DNA methylation and pathologically altered gene expression profile in human umbilical vein endothelial cells (HUVECs) subjected to oxygen-glucose deprivation (OGD), and its clinical implications in AMI patients. The Illumina Infinium MethylationEPIC BeadChip assay was used to explore the genome-wide DNA methylation profile using the Novaseq6000 platform for mRNA sequencing in 3 pairs of HUVEC-OGD and control samples. GO and KEGG pathway enrichment analyses, as well as correlation, causal inference test (CIT), and protein-protein interaction (PPI) analyses identified 22 hub genes that were validated by MethylTarget sequencing as well as qRT-PCR. ELISA was used to detect four target molecules associated with the progression of AMI. A total of 2,524 differentially expressed genes (DEGs) and 22,148 differentially methylated positions (DMPs) corresponding to 6,642 differentially methylated genes (DMGs) were screened (|Δβ|>0.1 and detection p < 0.05). After GO, KEGG, correlation, CIT, and PPI analyses, 441 genes were filtered. qRT-PCR confirmed the overexpression of VEGFA, CCL2, TSP-1, SQSTM1, BCL2L11, and TIMP3 genes, and downregulation of MYC, CD44, BDNF, GNAQ, RUNX1, ETS1, NGFR, MME, SEMA6A, GNAI1, IFIT1, and MEIS1. DNA fragments BDNF_1_ (r = 0.931, p < 0.0001) and SQSTM1_2_NEW (r = 0.758, p = 0.0043) were positively correlated with the expressions of corresponding genes, and MYC_1_ (r = -0.8245, p = 0.001) was negatively correlated. Furthermore, ELISA confirmed TNFSF10 and BDNF were elevated in the peripheral blood of AMI patients (p = 0.0284 and p = 0.0142, respectively). Combined sequencing from in vitro cellular assays with clinical samples, aiming to establish the potential causal chain of the causal factor (DNA methylation) - mediator (mRNA)-cell outcome (endothelial cell ischemic-hypoxic injury)-clinical outcome (AMI), our study identified promising OGD-specific genes, which provided a solid basis for screening fundamental diagnostic and prognostic biomarkers of coronary endothelial cell injury of AMI. Moreover, it furnished the first evidence that during ischemia and hypoxia, the expression of BNDF was regulated by DNA methylation in endothelial cells and elevated in peripheral blood.

AtSAMS regulates floral organ development by DNA methylation and ethylene signaling pathway

S-adenosylmethionine synthase is the key enzyme involved in the biosynthesis of S-adenosylmethionine, which serves as the universal methyl group donor and a common precursor for the biosynthesis of ethylene and polyamines. However, little is known about how SAMS controls plant development. Here, we report that the abnormal floral organ development in the AtSAMS-overexpressing plants is caused by DNA demethylation and ethylene signaling. The whole-genome DNA methylation level decreased, and ethylene content increased in SAMOE. Wild-type plants treated with DNA methylation inhibitor mimicked the phenotypes and the ethylene levels in SAMOE, suggesting that DNA demethylation enhanced ethylene biosynthesis, which led to abnormal floral organ development. DNA demethylation and elevated ethylene resulted in changes in the expression of ABCE genes, which is essential for floral organ development. Furthermore, the transcript levels of ACE genes were highly correlated to their methylation levels, except for the down-regulation of the B gene, which might have resulted from demethylation-independent ethylene signaling. SAMS-mediated methylation and ethylene signaling might create crosstalk in the process of floral organ development. Together, we provide evidence that AtSAMS regulates floral organ development by DNA methylation and ethylene signaling pathway.

Relationships between the maternal prenatal diet and epigenetic state in infants: a systematic review of human studies

Most human studies investigating the relationship between maternal diet in pregnancy and infant epigenetic state have focused on macro- and micro-nutrient intake, rather than the whole diet. This makes it difficult to translate the evidence into practical prenatal dietary recommendations.To review the evidence on how the prenatal diet relates to the epigenetic state of infants measured in the first year of life via candidate gene or genome-wide approaches.Following the PRISMA guidelines, this systematic literature search was completed in August 2020, and updated in August 2021 and April 2022. Studies investigating dietary supplementation were excluded. Risk of bias was assessed, and the certainty of results was analysed with consideration of study quality and validity.Seven studies were included, encompassing 6852 mother-infant dyads. One study was a randomised controlled trial and the remaining six were observational studies. There was heterogeneity in dietary exposure measures. Three studies used an epigenome-wide association study (EWAS) design and four focused on candidate genes from cord blood samples. All studies showed inconsistent associations between maternal dietary measures and DNA methylation in infants. Effect sizes of maternal diet on DNA methylation ranged from very low (< 1%) to high (> 10%). All studies had limitations and were assessed as having moderate to high risk of bias.The evidence presented here provides very low certainty that dietary patterns in pregnancy relate to epigenetic state in infants. We recommend that future studies maximise sample sizes and optimise and harmonise methods of dietary measurement and pipelines of epigenetic analysis.

Epigenetic Studies for Evaluation of NPS Toxicity: Focus on Synthetic Cannabinoids and Cathinones

In the recent decade, numerous new psychoactive substances (NPSs) have been added to the illicit drug market. These are synthetized to mimic the effects of classic drugs of abuse (i.e., cannabis, cocaine, etc.), with the purpose of bypassing substance legislations and increasing the pharmacotoxicological effects. To date, research into the acute pharmacological effects of new NPSs is ongoing and necessary in order to provide an appropriate contribution to public health. In fact, multiple examples of NPS-related acute intoxication and mortality have been recorded in the literature. Accordingly, several in vitro and in vivo studies have investigated the pharmacotoxicological profiles of these compounds, revealing that they can cause adverse effects involving various organ systems (i.e., cardiovascular, respiratory effects) and highlighting their potential increased consumption risks. In this sense, NPSs should be regarded as a complex issue that requires continuous monitoring. Moreover, knowledge of long-term NPS effects is lacking. Because genetic and environmental variables may impact NPS responses, epigenetics may aid in understanding the processes behind the harmful events induced by long-term NPS usage. Taken together, “pharmacoepigenomics” may provide a new field of combined study on genetic differences and epigenetic changes in drug reactions that might be predictive in forensic implications.

DNA methylation-based diagnostic, prognostic, and predictive biomarkers in colorectal cancer

DNA methylation is an epigenetic mechanism regulating gene expression. Changes in DNA methylation were suggested to be useful biomarkers for diagnosis, and for the determination of prognosis and treatment response. Here, we provide an overview of methylation-based biomarkers in colorectal cancer. First, we start with the two methylation-based diagnostic biomarkers already approved for colorectal cancer, SEPT9 and the combination of NDRG4 and BMP3. Then, we provide a list-based overview of new biomarker candidates depending on the sample source including plasma, stool, urine, and surgically removed tumor tissues. The most often identified markers like SDC2, VIM, APC, MGMT, SFRP1, SFRP2, and NDRG4 have distinct functions previously linked to tumor progression. Although numerous studies have identified tumor-specific methylation changes, most of these alterations were observed in a single study only. The lack of validation in independent samples means low reproducibility and is a major limitation. The genome-wide determination of methylation status (methylome) can provide data to solve these issues. In the third section of the review, methylome studies focusing on different aspects related to CRC, including precancerous lesions, CRC-specific changes, molecular subtypes, aging, and chemotherapy response are summarized. Notably, techniques simultaneously analyzing a large set of regions can also uncover epigenetic regulation of genes which have not yet been associated with tumorigenesis previously. A remaining constraint of studies published to date is the low patient number utilized in these preventing the identification of clinically valuable biomarker candidates. Either future large-scale studies or the integration of already available methylome-level data will be necessary to uncover biomarkers sufficiently robust for clinical application.

Characterization of the Illumina EPIC Array for Optimal Applications in Epigenetic Research Targeting Diverse Human Populations

The Illumina EPIC array is widely used for high-throughput profiling of DNA cytosine modifications in human samples, covering more than 850,000 modification sites across various genomic features. The application of this platform is expected to provide novel insights into the epigenetic contribution to human complex traits and diseases. Considering the diverse inter-population genetic and epigenetic variation, it will benefit the research community with a comprehensive characterization of this platform for its applicability to major global populations. Specifically, we mapped 866,836 CpG probes from the EPIC array to the human genome reference. We detected 91,034 CpG probes that did not align reliably to the human genome reference. In addition, 21,256 CpG probes were found to ambiguously map to multiple loci in the human genome, and 448 probes showing inaccurate genomic information from the original Illumina annotations. We further characterized those uniquely mapped CpG probes in terms of whether they contained common genetic variants, i.e., single nucleotide polymorphisms (SNPs), in major global populations, by utilizing the 1000 Genomes Project data. A list of optimal CpG probes on the EPIC array was generated for major global populations, with the aim of providing a resource to facilitate future studies of diverse human populations. In conclusion, our analysis indicated that studies of diverse human populations using the EPIC array would be benefited by taking into account of the technical features of this platform.

Differential analysis of RNA methylation regulators in gastric cancer based on TCGA data set and construction of a prognostic model

Background

Methylation is one of the common forms of RNA modification, which mainly include N6-methyladenosine (m6A), C5-methylcytidine (m5C), and N1-methyladenosine (m1A). Numerous studies have shown that RNA methylation is associated with tumor development. We aim to construct prognostic models of gastric cancer based on RNA methylation regulators.

Methods

The transcriptome and clinical data of gastric cancer and normal samples were obtained from the National Cancer Institute Genome Data Commons (NCI-GDC). Use Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to construct risk models for different types of RNA methylation. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive efficiency of risk characteristics. Cluster heat maps are used to assess the correlation with clinical information. Univariate and multivariate Cox analyses were used to analyze prognostic effects of risk scores. Gene Set Enrichment Analysis (GSEA) analyzes the functional enrichment of RNA methylation genes. And make a separate analysis of the data of Asians.

Results

The expression of most of the 30 RNA methylation regulators were significantly different in cancer and paracancerous tissues (P<0.05). Three methylated genes (FTO, ALKBH5, and RBM15) were screened from m6A by LASSO Cox regression analysis. Five methylated genes (FTO, ALKBH5, TRMT61B, RBM15, and YXB1) were selected from the population, and were used to construct two risk ratio models. Survival analysis showed that the survival rate of patients in the low-risk group was significantly higher than that in the high-risk group (P<0.05). All ROC curves indicated that the predictive efficiency of risk characteristics was good [area under the ROC curve (AUC): 0.6-1].Cluster analysis reveals differences in clinical data between the two groups. Univariate and multivariate Cox regression results show that the risk score has independent prognostic value. GSEA showed that pathways such as cell cycle were significantly enriched in the low-risk group, while pathways such as calcium signaling pathway were significantly enriched in the high-risk group. In addition, three methylation models that can predict the prognosis of Asian gastric cancer patients were obtained.

Conclusions

The methylation prognosis model constructed in this study can effectively predict the prognosis of gastric cancer patients.

Cardioinformatics: the nexus of bioinformatics and precision cardiology

Cardiovascular disease (CVD) is the leading cause of death worldwide, causing over 17 million deaths per year, which outpaces global cancer mortality rates. Despite these sobering statistics, most bioinformatics and computational biology research and funding to date has been concentrated predominantly on cancer research, with a relatively modest footprint in CVD. In this paper, we review the existing literary landscape and critically assess the unmet need to further develop an emerging field at the multidisciplinary interface of bioinformatics and precision cardiovascular medicine, which we refer to as 'cardioinformatics'.

Identifying Regulatory Elements via Deep Learning

Deep neural networks have been revolutionizing the field of machine learning for the past several years. They have been applied with great success in many domains of the biomedical data sciences and are outperforming extant methods by a large margin. The ability of deep neural networks to pick up local image features and model the interactions between them makes them highly applicable to regulatory genomics. Instead of an image, the networks analyze DNA and RNA sequences and additional epigenomic data. In this review, we survey the successes of deep learning in the field of regulatory genomics. We first describe the fundamental building blocks of deep neural networks, popular architectures used in regulatory genomics, and their training process on molecular sequence data. We then review several key methods in different gene regulation domains. We start with the pioneering method DeepBind and its successors, which were developed to predict protein–DNA binding. We then review methods developed to predict and model epigenetic information, such as histone marks and nucleosome occupancy. Following epigenomics, we review methods to predict protein–RNA binding with its unique challenge of incorporating RNA structure information. Finally, we provide our overall view of the strengths and weaknesses of deep neural networks and prospects for future developments.

Practical guide to genetic screening for inherited eye diseases

Genetic eye diseases affect around one in 1000 people worldwide for which the molecular aetiology remains unknown in the majority. The identification of disease-causing gene variant(s) allows a better understanding of the disorder and its inheritance. There is now an approved retinal gene therapy for autosomal recessive RPE65-retinopathy, and numerous ocular gene/mutation-targeted clinical trials underway, highlighting the importance of establishing a genetic diagnosis so patients can fully access the latest research developments and treatment options. In this review, we will provide a practical guide to managing patients with these conditions including an overview of inheritance patterns, required pre- and post-test genetic counselling, different types of cytogenetic and genetic testing available, with a focus on next generation sequencing using targeted gene panels, whole exome and genome sequencing. We will expand on the pros and cons of each modality, variant interpretation and options for family planning for the patient and their family. With the advent of genomic medicine, genetic screening will soon become mainstream within all ophthalmology subspecialties for prevention of disease and provision of precision therapeutics.

PDX models recapitulate the genetic and epigenetic landscape of pediatric T-cell leukemia

We compared 24 primary pediatric T‐cell acute lymphoblastic leukemias (T‐ALL) collected at the time of initial diagnosis and relapse from 12 patients and 24 matched patient‐derived xenografts (PDXs). DNA methylation profile was preserved in PDX mice in 97.5% of the promoters (ρ = 0.99). Similarly, the genome‐wide chromatin accessibility (ATAC‐Seq) was preserved remarkably well (ρ = 0.96). Interestingly, both the ATAC regions, which showed a significant decrease in accessibility in PDXs and the regions hypermethylated in PDXs, were associated with immune response, which might reflect the immune deficiency of the mice and potentially the incomplete interaction between murine cytokines and human receptors. The longitudinal approach of this study allowed an observation that samples collected from patients who developed a type 1 relapse (clonal mutations maintained at relapse) preserved their genomic composition; whereas in patients who developed a type 2 relapse (subset of clonal mutations lost at relapse), the preservation of the leukemia's composition was more variable. In sum, this study underlines the remarkable genomic stability, and for the first time documents the preservation of the epigenomic landscape in T‐ALL‐derived PDX models.

Downregulation of RdDM during strawberry fruit ripening

Background

Recently, DNA methylation was proposed to regulate fleshy fruit ripening. Fleshy fruits can be distinguished by their ripening process as climacteric fruits, such as tomatoes, or non-climacteric fruits, such as strawberries. Tomatoes undergo a global decrease in DNA methylation during ripening, due to increased expression of a DNA demethylase gene. The dynamics and biological relevance of DNA methylation during the ripening of non-climacteric fruits are unknown.

Results

Here, we generate single-base resolution maps of the DNA methylome in immature and ripe strawberry. We observe an overall loss of DNA methylation during strawberry fruit ripening. Thus, ripening-induced DNA hypomethylation occurs not only in climacteric fruit, but also in non-climacteric fruit. Application of a DNA methylation inhibitor causes an early ripening phenotype, suggesting that DNA hypomethylation is important for strawberry fruit ripening. The mechanisms underlying DNA hypomethylation during the ripening of tomato and strawberry are distinct. Unlike in tomatoes, DNA demethylase genes are not upregulated during the ripening of strawberries. Instead, genes involved in RNA-directed DNA methylation are downregulated during strawberry ripening. Further, ripening-induced DNA hypomethylation is associated with decreased siRNA levels, consistent with reduced RdDM activity. Therefore, we propose that a downregulation of RdDM contributes to DNA hypomethylation during strawberry ripening.

Conclusions

Our findings provide new insight into the DNA methylation dynamics during the ripening of non-climacteric fruit and suggest a novel function of RdDM in regulating an important process in plant development.

Electronic supplementary material

The online version of this article (10.1186/s13059-018-1587-x) contains supplementary material, which is available to authorized users.

DNA methylation profiling in nonfunctioning pituitary adenomas

Nonfunctioning pituitary adenomas (NFPAs) are among the most frequent intracranial tumors but their molecular background, including changes in epigenetic regulation, remains poorly understood. We performed genome-wide DNA methylation profiling of 34 NFPAs and normal pituitary samples. Methylation status of the selected genomic regions and expression level of corresponding genes were assessed in a group of 75 patients. NFPAs exhibited distinct global methylation profile as compared to normal pituitary. Aberrant DNA methylation appears to contribute to deregulation of the cancer-related pathways as shown by preliminary functional analysis. Promoter hypermethylation and decreased expression level of SFN, STAT5A, DUSP1, PTPRE and FGFR2 was confirmed in the enlarged group of NFPAs. Difference in the methylation profiles between invasive and non-invasive NFPAs is very slight. Nevertheless, invasiveness-related aberrant epigenetic deregulation of the particular genes was found including upregulation of ITPKB and downregulation CNKSR1 in invasive tumors.

Guidelines for whole genome bisulphite sequencing of intact and FFPET DNA on the Illumina HiSeq X Ten

Background

Comprehensive genome-wide DNA methylation profiling is critical to gain insights into epigenetic reprogramming during development and disease processes. Among the different genome-wide DNA methylation technologies, whole genome bisulphite sequencing (WGBS) is considered the gold standard for assaying genome-wide DNA methylation at single base resolution. However, the high sequencing cost to achieve the optimal depth of coverage limits its application in both basic and clinical research. To achieve 15× coverage of the human methylome, using WGBS, requires approximately three lanes of 100-bp-paired-end Illumina HiSeq 2500 sequencing. It is important, therefore, for advances in sequencing technologies to be developed to enable cost-effective high-coverage sequencing.

Results

In this study, we provide an optimised WGBS methodology, from library preparation to sequencing and data processing, to enable 16–20× genome-wide coverage per single lane of HiSeq X Ten, HCS 3.3.76. To process and analyse the data, we developed a WGBS pipeline (METH10X) that is fast and can call SNPs. We performed WGBS on both high-quality intact DNA and degraded DNA from formalin-fixed paraffin-embedded tissue. First, we compared different library preparation methods on the HiSeq 2500 platform to identify the best method for sequencing on the HiSeq X Ten. Second, we optimised the PhiX and genome spike-ins to achieve higher quality and coverage of WGBS data on the HiSeq X Ten. Third, we performed integrated whole genome sequencing (WGS) and WGBS of the same DNA sample in a single lane of HiSeq X Ten to improve data output. Finally, we compared methylation data from the HiSeq 2500 and HiSeq X Ten and found high concordance (Pearson r > 0.9×).

Conclusions

Together we provide a systematic, efficient and complete approach to perform and analyse WGBS on the HiSeq X Ten. Our protocol allows for large-scale WGBS studies at reasonable processing time and cost on the HiSeq X Ten platform.

Electronic supplementary material

The online version of this article (10.1186/s13072-018-0194-0) contains supplementary material, which is available to authorized users.

Bisulfite Sequencing for DNA Methylation Analysis of Primary Muscle Stem Cells

In skeletal muscle, DNA methylation contributes to the suppression of gene expression in several biological processes and diseases. A protocol for the detection of methylated cytosine was thus established based on methylation-sensitive enzymes, immunoprecipitation, and bisulfite conversion. DNA methylation analysis, with bisulfite conversion and sequencing, enables the quantification of methylation at each single base position. Here, we describe a basic method of bisulfite sequencing that can be used to analyze local DNA methylation status to confirm genome-wide DNA methylation analysis or correlation of gene expression regulatory mechanisms.

Towards understanding the breast cancer epigenome: a comparison of genome-wide DNA methylation and gene expression data

Until recently, an elevated disease risk has been ascribed to a genetic predisposition, however, exciting progress over the past years has discovered alternate elements of inheritance that involve epigenetic regulation. Epigenetic changes are heritably stable alterations that include DNA methylation, histone modifications and RNA-mediated silencing. Aberrant DNA methylation is a common molecular basis for a number of important human diseases, including breast cancer. Changes in DNA methylation profoundly affect global gene expression patterns. What is emerging is a more dynamic and complex association between DNA methylation and gene expression than previously believed. Although many tools have already been developed for analyzing genome-wide gene expression data, tools for analyzing genome-wide DNA methylation have not yet reached the same level of refinement.

Here we provide an in-depth analysis of DNA methylation in parallel with gene expression data characteristics and describe the particularities of low-level and high-level analyses of DNA methylation data. Low-level analysis refers to pre-processing of methylation data (i.e. normalization, transformation and filtering), whereas high-level analysis is focused on illustrating the application of the widely used class comparison, class prediction and class discovery methods to DNA methylation data. Furthermore, we investigate the influence of DNA methylation on gene expression by measuring the correlation between the degree of CpG methylation and the level of expression and to explore the pattern of methylation as a function of the promoter region.

Aberrant methylation of CDH13 can be a diagnostic biomarker for lung adenocarcinoma

Background: Aberrant methylation of CpG islands in tumor cells in promoter regions is a critical event in non-small cell lung carcinoma (NSCLC) tumorigenesis and can be a potential diagnostic biomarker for NSCLC patients. The present study systemically and quantitatively reviewed the diagnostic ability of CDH13 methylation in NSCLC as well as in its subsets. Eligible studies were identified through searching PubMed, Web of Science, Cochrane Library and Embase. The pooled odds of CDH13 promoter methylation in lung cancer tissues versus normal controls were calculated by meta-analysis method. Simultaneously, four independent DNA methylation datasets of NSCLC from TCGA and GEO database were downloaded and analyzed to validate the results from meta-analysis. Results: Thirteen studies, including 1850 samples were included in this meta-analysis. The pooled odds ratio of CDH13 promoter methylation in cancer tissues was 7.41 (95% CI: 5.34 to 10.29, P < 0.00001) compared with that in controls under fixed-effect model. In validation stage, 126 paired samples from TCGA were analyzed and 5 out of the 6 CpG sites in the CpG island of CDH13 were significantly hypermethylated in lung adenocarcinoma tissues but none of the 6 CpG sites was hypermethylated in squamous cell carcinoma tissues. Concordantly, the results from other three datasets, which were subsequently obtained from GEO database consisting of 568 tumors and 256 normal tissues, also consisted with those from TCGA dataset. Conclusion: The pooled data showed that the methylation status of the CDH13 promoter is strongly associated with lung adenocarcinoma. The CDH13 methylation status could be a promising diagnostic biomarker for diagnosis of lung adenocarcinoma.

Understanding the genetic liability to schizophrenia through the neuroepigenome

The Psychiatric Genomics Consortium-Schizophrenia Workgroup (PGC-SCZ) recently identified 108 loci associated with increased risk for schizophrenia (SCZ). The vast majority of these variants reside within non-coding sequences of the genome and are predicted to exert their effects by affecting the mechanism of action of cis regulatory elements (CREs), such as promoters and enhancers. Although a number of large-scale collaborative efforts (e.g. ENCODE) have achieved a comprehensive mapping of CREs in human cell lines or tissue homogenates, it is becoming increasingly evident that many risk-associated variants are enriched for expression Quantitative Trait Loci (eQTLs) and CREs in specific tissues or cells. As such, data derived from previous research endeavors may not capture fully cell-type and/or region specific changes associated with brain diseases. Coupling recent technological advances in genomics with cell-type specific methodologies, we are presented with an unprecedented opportunity to better understand the genetics of normal brain development and function and, in turn, the molecular basis of neuropsychiatric disorders. In this review, we will outline ongoing efforts towards this goal and will discuss approaches with the potential to shed light on the mechanism(s) of action of cell-type specific cis regulatory elements and their putative roles in disease, with particular emphasis on understanding the manner in which the epigenome and CREs influence the etiology of SCZ.

DNA methylation profiling of esophageal adenocarcinoma using Methylation Ligation-dependent Macroarray (MLM)

Most types of cancer cells are characterized by aberrant methylation of promoter genes. In this study, we described a rapid, reproducible, and relatively inexpensive approach allowing the detection of multiple human methylated promoter genes from many tissue samples, without the need of bisulfite conversion. The Methylation Ligation-dependent Macroarray (MLM), an array-based analysis, was designed in order to measure methylation levels of 58 genes previously described as putative biomarkers of cancer. The performance of the design was proven by screening the methylation profile of DNA from esophageal cell lines, as well as microdissected formalin-fixed and paraffin-embedded (FFPE) tissues from esophageal adenocarcinoma (EAC). Using the MLM approach, we identified 32 (55%) hypermethylated promoters in EAC, and not or rarely methylated in normal tissues. Among them, 21promoters were found aberrantly methylated in more than half of tumors. Moreover, seven of them (ADAMTS18, APC, DKK2, FOXL2, GPX3, TIMP3 and WIF1) were found aberrantly methylated in all or almost all the tumor samples, suggesting an important role for these genes in EAC. In addition, dysregulation of the Wnt pathway with hypermethylation of several Wnt antagonist genes was frequently observed. MLM revealed a homogeneous pattern of methylation for a majority of tumors which were associated with an advanced stage at presentation and a poor prognosis. Interestingly, the few tumors presenting less methylation changes had a lower pathological stage. In conclusion, this study demonstrated the feasibility and accuracy of MLM for DNA methylation profiling of FFPE tissue samples.

DNA methylation profiling: comparison of genome-wide sequencing methods and the Infinium Human Methylation 450 Bead Chip

AIMS

To compare the performance of four sequence-based and one microarray methods for DNA methylation profiling.

METHODS

DNA from two cell lines were profiled by reduced representation bisulfite sequencing, methyl capture sequencing (SS-Meth Seq), NimbleGen SeqCapEpi CpGiant(Nimblegen MethSeq), methylated DNA immunoprecipitation (MeDIP) and the Human Methylation 450 Bead Chip (Meth450K).

RESULTS & CONCLUSION

Despite differences in genome-wide coverage, high correlation and concordance were observed between different methods. Significant overlap of differentially methylated regions was identified between sequenced-based platforms. MeDIP provided the best coverage for the whole genome and gene body regions, while RRBS and Nimblegen MethSeq were superior for CpGs in CpG islands and promoters. Methylation analyses can be achieved by any of the five methods but understanding their differences may better address the research question being posed.

Mycoplasma CG- and GATC-specific DNA methyltransferases selectively and efficiently methylate the host genome and alter the epigenetic landscape in human cells

Aberrant DNA methylation is frequently observed in disease, including many cancer types, yet the underlying mechanisms remain unclear. Because germline and somatic mutations in the genes that are responsible for DNA methylation are infrequent in malignancies, additional mechanisms must be considered. Mycoplasmas spp., including Mycoplasma hyorhinis, efficiently colonize human cells and may serve as a vehicle for delivery of enzymatically active microbial proteins into the intracellular milieu. Here, we performed, for the first time, genome-wide and individual gene mapping of methylation marks generated by the M. hyorhinis CG- and GATC-specific DNA cytosine methyltransferases (MTases) in human cells. Our results demonstrated that, upon expression in human cells, MTases readily translocated to the cell nucleus. In the nucleus, MTases selectively and efficiently methylated the host genome at the DNA sequence sites free from pre-existing endogenous methylation, including those in a variety of cancer-associated genes. We also established that mycoplasma is widespread in colorectal cancers, suggesting that either the infection contributed to malignancy onset or, alternatively, that tumors provide a favorable environment for mycoplasma growth. In the human genome, ∼ 11% of GATC sites overlap with CGs (e.g., CGAT(m)CG); therefore, the methylated status of these sites can be perpetuated by human DNMT1. Based on these results, we now suggest that the GATC-specific methylation represents a novel type of infection-specific epigenetic mark that originates in human cells with a previous exposure to infection. Overall, our findings unveil an entirely new panorama of interactions between the human microbiome and epigenome with a potential impact in disease etiology.

Genome-wide assays that identify and quantify modified cytosines in human disease studies

The number of different assays that has been published to study DNA methylation is extensive, complemented by recently described assays that test modifications of cytosine other than the most abundant 5-methylcytosine (5mC) variant. In this review, we describe the considerations involved in choosing how to study 5mC throughout the genome, with an emphasis on the common application of testing for epigenetic dysregulation in human disease. While microarray studies of 5mC continue to be commonly used, these lack the additional qualitative information from sequencing-based approaches that is increasingly recognized to be valuable. When we test the representation of functional elements in the human genome by several current assay types, we find that no survey approach interrogates anything more than a small minority of the nonpromoter cis-regulatory sites where DNA methylation variability is now appreciated to influence gene expression and to be associated with human disease. However, whole-genome bisulphite sequencing (WGBS) adds a substantial representation of loci at which DNA methylation changes are unlikely to be occurring with transcriptional consequences. Our assessment is that the most effective approach to DNA methylation studies in human diseases is to use targeted bisulphite sequencing of the cis-regulatory loci in a cell type of interest, using a capture-based or comparable system, and that no single design of a survey approach will be suitable for all cell types.

TAGLN expression is upregulated in NF1-associated malignant peripheral nerve sheath tumors by hypomethylation in its promoter and subpromoter regions

Neurofibromatosis type 1 (NF1) caused by NF1 gene mutation is a commonly inherited autosomal dominant disorder. Malignant peripheral nerve sheath tumors (MPNSTs), a type of aggressive sarcoma, are a major cause of mortality in NF1 patients. The malignant transformation of benign plexiform neurofibromas (PNs) to MPNSTs is a marked peculiarity in NF1 patients, yet the pathogenesis remains poorly understood. We found that an actin-associated protein transgelin (SM22) was highly expressed in NF1-deficient MPNST tissues compared to NF1-deficient PN tissues using immunohistological staining and primary cultured MPNST cells in western blot analysis. We further found that this transgelin upregulation was caused by increased transcriptional expression of the TAGLN gene encoding transgelin. Comparison of DNA methylation values in the promoter and subpromoter regions of the TAGLN gene in three types of NF1-deficient primary-cultured cells, derived from an NF1 patient's normal phenotype, a benign PN and MPNST tissues, revealed that the TAGLN gene was hypomethylated in the MPNST cells. Next, to determine the functional role of transgelin in MPNST pathogenesis, we manipulated the TAGLN gene expression and investigated the alteration of the RAS-mitogen-activated protein kinase (MAPK) signaling pathway in the normal-phenotypic and malignant tumor cells. The downregulation of TAGLN expression in NF1-deficient MPNST tumor cells through the treatment of the small interfering RNA resulted in a decrease in the RAS activation (GTP-RAS) and the downstream ERK1/2 activation (phosphorylated ERK1/2), while the overexpression of TAGLN in normal-phenotypic NF1-deficient cells caused an increase in RAS and ERK1/2 activation. These results indicate that upregulation of transgelin caused by hypomethylation of the TAGLN gene is closely involved in tumor progression in NF1.

Phenotype prediction based on genome-wide DNA methylation data

Background

DNA methylation (DNAm) has important regulatory roles in many biological processes and diseases. It is the only epigenetic mark with a clear mechanism of mitotic inheritance and the only one easily available on a genome scale. Aberrant cytosine-phosphate-guanine (CpG) methylation has been discussed in the context of disease aetiology, especially cancer. CpG hypermethylation of promoter regions is often associated with silencing of tumour suppressor genes and hypomethylation with activation of oncogenes.

Supervised principal component analysis (SPCA) is a popular machine learning method. However, in a recent application to phenotype prediction from DNAm data SPCA was inferior to the specific method EVORA.

Results

We present Model-Selection-SPCA (MS-SPCA), an enhanced version of SPCA. MS-SPCA applies several models that perform well in the training data to the test data and selects the very best models for final prediction based on parameters of the test data.

We have applied MS-SPCA for phenotype prediction from genome-wide DNAm data. CpGs used for prediction are selected based on the quantification of three features of their methylation (average methylation difference, methylation variation difference and methylation-age-correlation). We analysed four independent case–control datasets that correspond to different stages of cervical cancer: (i) cases currently cytologically normal, but will later develop neoplastic transformations, (ii, iii) cases showing neoplastic transformations and (iv) cases with confirmed cancer. The first dataset was split into several smaller case–control datasets (samples either Human Papilloma Virus (HPV) positive or negative). We demonstrate that cytology normal HPV+ and HPV- samples contain DNAm patterns which are associated with later neoplastic transformations. We present evidence that DNAm patterns exist in cytology normal HPV- samples that (i) predispose to neoplastic transformations after HPV infection and (ii) predispose to HPV infection itself. MS-SPCA performs significantly better than EVORA.

Conclusions

MS-SPCA can be applied to many classification problems. Additional improvements could include usage of more than one principal component (PC), with automatic selection of the optimal number of PCs. We expect that MS-SPCA will be useful for analysing recent larger DNAm data to predict future neoplastic transformations.

DNA methylation and cancer development: molecular mechanism

DNA methylation is a significant regulator of gene expression, and its role in carcinogenesis recently has been a subject of remarkable interest. The aim of this review is to analyze the mechanism and cell regulatory effects of both hypo- and hyper-DNA methylation on cancer. In this review, we report new developments and their implications regarding the effects of DNA methylation on cancer development. Indeed, alteration of the pattern of DNA methylation has been a constant finding in cancer cells of the same type and differences in the pattern of DNA methylation not only occur in a variety of tumor types, but also in developmental processes Furthermore, the pattern of histone modification appears to be a predicator of the risk of recurrence of human cancers. It is well known that hypermethylation represses transcription of the promoter sections of tumor-suppressor genes leading to gene silencing. However, hypomethylation also has been identified as a cause of oncogenesis. Furthermore, experiments concerning the mechanism of methylation and its control have led to the discovery of many regulatory enzymes and proteins. This review reports on methods developed for the detection of 5-hydroxymethylcytosine methylation at the 5-methylcytosine of protein domains in the CpG context compared to non-methylated DNA, histone modification, and microRNA change.

Characterization of HPV DNA methylation of contiguous CpG sites by bisulfite treatment and massively parallel sequencing-the FRAGMENT approach

Invasive cervix cancer (ICC) is the third most common malignant tumor in women and human papillomavirus 16 (HPV16) causes more than 50% of ICC. DNA methylation is a covalent modification predominantly occurring at CpG dinucleotides and increased methylation across the HPV16 genome is strongly associated with ICC development. Next generation (Next Gen) sequencing has been proposed as a novel approach to determine DNA methylation. However, utilization of this method to survey CpG methylation in the HPV16 genome is not well described. Moreover, it provides additional information on methylation “haplotypes.” In the current study, we chose 12 random samples, amplified multiple segments in the HPV16 bisulfite treated genome with specific barcodes, inspected the methylation ratio at 31 CpG sites for all samples using Illumina sequencing, and compared the results with quantitative pyrosequencing. Most of the CpG sites were highly consistent between the two approaches (overall correlation, r = 0.92), thus verifying that Next Gen sequencing is an accurate and convenient method to survey HPV16 methylation and thus can be used in clinical samples for risk assessment. Moreover, the CpG methylation patterns (methylation haplotypes) in single molecules identified an excess of complete-and non-methylated molecules and a substantial amount of partial-methylated ones, thus indicating a complex dynamic for the mechanisms of HPV16 CpG methylation. In summary, the advantages of Next Gen sequencing compared to pyrosequencing for HPV genome methylation analyses include higher throughput, increased resolution, and improved efficiency of time and resources.

DNA methylation in mammals

DNA methylation is one of the best characterized epigenetic modifications. In mammals it is involved in various biological processes including the silencing of transposable elements, regulation of gene expression, genomic imprinting, and X-chromosome inactivation. This article describes how DNA methylation serves as a cellular memory system and how it is dynamically regulated through the action of the DNA methyltransferase (DNMT) and ten eleven translocation (TET) enzymes. Its role in the regulation of gene expression, through its interplay with histone modifications, is also described, and its implication in human diseases discussed. The exciting areas of investigation that will likely become the focus of research in the coming years are outlined in the summary.

Accessing epigenetic variation in the plant methylome

Cytosine DNA methylation is the addition of a methyl group to the 5' position of a cytosine, which plays a crucial role in plant development and gene silencing. Genome-wide profiling of DNA methylation is now possible using various techniques and strategies. Using these technologies, we are beginning to elucidate the extent and impact of variation in DNA methylation between individuals and/or tissues. Here, we review the different techniques used to analyze the methylomes at the whole-genome level and their applications to better understand epigenetic variations in plants.

Global analysis of DNA methylation changes during progression of oral cancer

OBJECTIVES

Earlier studies involving a priori gene selection have identified promoter regions deregulated by DNA methylation changes in oral squamous cell cancers (OSCCs) and precancers. Interrogation of global DNA methylation patterns for such specimens has not been reported, though such analyses are needed to uncover novel molecular factors driving disease.

MATERIALS AND METHODS

We evaluated global DNA methylation patterns for 30 biopsies obtained from 10 patients undergoing surgical removal of an OSCC or carcinoma in situ (CIS). From a disease field in each patient, we collected (i) dysplastic, (ii) CIS or OSCC, and (iii) adjacent normal biopsies. DNA isolated from each biopsy was profiled for methylation status using the Illumina HumanMethylation27K platform.

RESULTS

Our data demonstrate that aberrant methylation of promoter CpG islands exists across oral precancer and OSCC genomes. Non-hierarchical clustering of all methylation data revealed distinct methylation patterns between the normal and the CIS/OSCC tissues (with results for dysplastic biopsies split between groups). Multiple genes exhibiting recurrent aberrant DNA methylation were found for both dysplastic and CIS/OSCC groups, and included enrichment for genes found in the WNT and MAPK signaling pathways.

CONCLUSION

In identifying aberrant DNA methylation at the earliest stages of oral precancer and finding recurring epigenetic disruption of specific genes/pathways across our analyzed cohort, we see evidence that CpG methylation changes may play a role in oral cancer progression and that global DNA methylation analyses may have significant utility in wider studies that seek to derive biomarkers or potentially druggable targets to improve oral cancer outcomes.

Age-associated epigenetic drift: implications, and a case of epigenetic thrift?

It is now well established that the genomic landscape of DNA methylation (DNAm) gets altered as a function of age, a process we here call ‘epigenetic drift’. The biological, functional, clinical and evolutionary significance of this epigenetic drift, however, remains unclear. We here provide a brief review of epigenetic drift, focusing on the potential implications for ageing, stem cell biology and disease risk prediction. It has been demonstrated that epigenetic drift affects most of the genome, suggesting a global deregulation of DNAm patterns with age. A component of this drift is tissue-specific, allowing remarkably accurate age-predictive models to be constructed. Another component is tissue-independent, targeting stem cell differentiation pathways and affecting stem cells, which may explain the observed decline of stem cell function with age. Age-associated increases in DNAm target developmental genes, overlapping those associated with environmental disease risk factors and with disease itself, notably cancer. In particular, cancers and precursor cancer lesions exhibit aggravated age DNAm signatures. Epigenetic drift is also influenced by genetic factors. Thus, drift emerges as a promising biomarker for premature or biological ageing, and could potentially be used in geriatrics for disease risk prediction. Finally, we propose, in the context of human evolution, that epigenetic drift may represent a case of epigenetic thrift, or bet-hedging. In summary, this review demonstrates the growing importance of the ‘ageing epigenome’, with potentially far-reaching implications for understanding the effect of age on stem cell function and differentiation, as well as for disease prevention.

Combined methylation mapping of 5mC and 5hmC during early embryonic stages in bovine

Background

It was recently established that changes in methylation during development are dynamic and involve both methylation and demethylation processes. Yet, which genomic sites are changing and what are the contributions of methylation (5mC) and hydroxymethylation (5hmC) to this epigenetic remodeling is still unknown. When studying early development, options for methylation profiling are limited by the unavailability of sufficient DNA material from these scarce samples and limitations are aggravated in non-model species due to the lack of technological platforms. We therefore sought to obtain a representation of differentially 5mC or 5hmC loci during bovine early embryo stages through the use of three complementary methods, based on selective methyl-sensitive restriction and enrichment by ligation-mediated PCR or on subtractive hybridization. Using these strategies, libraries of putative methylation and hydroxymethylated sites were generated from Day-7 and Day-12 bovine embryos.

Results

Over 1.2 million sequencing reads were analyzed, resulting in 151,501 contigs, of which 69,136 were uniquely positioned on the genome. A total of 101,461 putative methylated sites were identified. The output of the three methods differed in genomic coverage as well as in the nature of the identified sites. The classical MspI/HpaII combination of restriction enzymes targeted CpG islands whereas the other methods covered 5mC and 5hmC sites outside of these regions. Data analysis suggests a transition of these methylation marks between Day-7 and Day-12 embryos in specific classes of repeat-containing elements.

Conclusions

Our combined strategy offers a genomic map of the distribution of cytosine methylation/hydroxymethylation during early bovine embryo development. These results support the hypothesis of a regulatory phase of hypomethylation in repeat sequences during early embryogenesis.

Bi-PROF: bisulfite profiling of target regions using 454 GS FLX Titanium technology

The use of next generation sequencing has expanded our view on whole mammalian methylome patterns. In particular, it provides a genome-wide insight of local DNA methylation diversity at single nucleotide level and enables the examination of single chromosome sequence sections at a sufficient statistical power. We describe a bisulfite-based sequence profiling pipeline, Bi-PROF, which is based on the 454 GS-FLX Titanium technology that allows to obtain up to one million sequence stretches at single base pair resolution without laborious subcloning. To illustrate the performance of the experimental workflow connected to a bioinformatics program pipeline (BiQ Analyzer HT) we present a test analysis set of 68 different epigenetic marker regions (amplicons) in five individual patient-derived xenograft tissue samples of colorectal cancer and one healthy colon epithelium sample as a control. After the 454 GS-FLX Titanium run, sequence read processing and sample decoding, the obtained alignments are quality controlled and statistically evaluated. Comprehensive methylation pattern interpretation (profiling) assessed by analyzing 10 (2)-10 (4) sequence reads per amplicon allows an unprecedented deep view on pattern formation and methylation marker heterogeneity in tissues concerned by complex diseases like cancer.

Mapping and significance of the mRNA methylome

Internal methylation of eukaryotic mRNAs in the form of N6-methyladenosine (m(6)A) and 5-methylcytidine (m(5)C) has long been known to exist, but progress in understanding its role was hampered by difficulties in identifying individual sites. This was recently overcome by high-throughput sequencing-based methods that mapped thousands of sites for both modifications throughout mammalian transcriptomes, with most sites found in mRNAs. The topology of m(6)A in mouse and human revealed both conserved and variable sites as well as plasticity in response to extracellular cues. Within mRNAs, m(5)C and m(6)A sites were relatively depleted in coding sequences and enriched in untranslated regions, suggesting functional interactions with post-transcriptional gene control. Finer distribution analyses and preexisting literature point toward roles in the regulation of mRNA splicing, translation, or decay, through an interplay with RNA-binding proteins and microRNAs. The methyltransferase (MTase) METTL3 'writes' m(6)A marks on mRNA, whereas the demethylase FTO can 'erase' them. The RNA:m(5)C MTases NSUN2 and TRDMT1 have roles in tRNA methylation but they also act on mRNA. Proper functioning of these enzymes is important in development and there are clear links to human disease. For instance, a common variant of FTO is a risk allele for obesity carried by 1 billion people worldwide and mutations cause a lethal syndrome with growth retardation and brain deficits. NSUN2 is linked to cancer and stem cell biology and mutations cause intellectual disability. In this review, we summarize the advances, open questions, and intriguing possibilities in this emerging field that might be called RNA modomics or epitranscriptomics.

A variational Bayes beta mixture model for feature selection in DNA methylation studies

An increasing number of studies are using beadarrays to measure DNA methylation on a genome-wide basis. The purpose is to identify novel biomarkers in a wide range of complex genetic diseases including cancer. A common difficulty encountered in these studies is distinguishing true biomarkers from false positives. While statistical methods aimed at improving the feature selection step have been developed for gene expression, relatively few methods have been adapted to DNA methylation data, which is naturally beta-distributed. Here we explore and propose an innovative application of a recently developed variational Bayesian beta-mixture model (VBBMM) to the feature selection problem in the context of DNA methylation data generated from a highly popular beadarray technology. We demonstrate that VBBMM offers significant improvements in inference and feature selection in this type of data compared to an Expectation-Maximization (EM) algorithm, at a significantly reduced computational cost. We further demonstrate the added value of VBBMM as a feature selection and prioritization step in the context of identifying prognostic markers in breast cancer. A variational Bayesian approach to feature selection of DNA methylation profiles should thus be of value to any study undergoing large-scale DNA methylation profiling in search of novel biomarkers.

Single-molecule, genome-scale analyses of DNA modifications: exposing the epigenome with next-generation technologies

DNA modifications represent an integral part of the epigenome and they have a pivotal role in regulation of genome function. Despite the wide variety of analytical techniques that have been developed to detect DNA modifications, their investigation at the single-genome level is only beginning to emerge. In contrast to population-averaged analyses, single-molecule approaches potentially allow the mapping of epigenetic linkage between distantly located genomic regions, the locus-specific analysis of repetitive DNA elements, as well as determination of allele-specific DNA modification patterns. In this article, the properties of current single-molecule analyses of DNA modifications will be discussed and compared. In addition, the possible biomedical and discovery research applications of single-molecule epigenomics will be highlighted.

A comparison of the whole genome approach of MeDIP-seq to the targeted approach of the Infinium HumanMethylation450 BeadChip(®) for methylome profiling

DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.

Cytosine methylation and hydroxymethylation mark DNA for elimination in Oxytricha trifallax

BACKGROUND

Cytosine methylation of DNA is conserved across eukaryotes and plays important functional roles regulating gene expression during differentiation and development in animals, plants and fungi. Hydroxymethylation was recently identified as another epigenetic modification marking genes important for pluripotency in embryonic stem cells.

RESULTS

Here we describe de novo cytosine methylation and hydroxymethylation in the ciliate Oxytricha trifallax. These DNA modifications occur only during nuclear development and programmed genome rearrangement. We detect methylcytosine and hydroxymethylcytosine directly by high-resolution nano-flow UPLC mass spectrometry, and indirectly by immunofluorescence, methyl-DNA immunoprecipitation and bisulfite sequencing. We describe these modifications in three classes of eliminated DNA: germline-limited transposons and satellite repeats, aberrant DNA rearrangements, and DNA from the parental genome undergoing degradation. Methylation and hydroxymethylation generally occur on the same sequence elements, modifying cytosines in all sequence contexts. We show that the DNA methyltransferase-inhibiting drugs azacitidine and decitabine induce demethylation of both somatic and germline sequence elements during genome rearrangements, with consequent elevated levels of germline-limited repetitive elements in exconjugant cells.

CONCLUSIONS

These data strongly support a functional link between cytosine DNA methylation/hydroxymethylation and DNA elimination. We identify a motif strongly enriched in methylated/hydroxymethylated regions, and we propose that this motif recruits DNA modification machinery to specific chromosomes in the parental macronucleus. No recognizable methyltransferase enzyme has yet been described in O. trifallax, raising the possibility that it might employ a novel cytosine methylation machinery to mark DNA sequences for elimination during genome rearrangements.

Molecular genomic research designs

Genetic and genomic research approaches have the capability to expand our understanding of the complex pathophysiology of disease susceptibility, susceptibility to complications related to disease, trajectory of recovery from acquired injuries and infections, patient response to interventions and therapeutics, as well as informing diagnoses and prognoses. Nurse scientists are actively involved in all of these fields of inquiry, and the goal of this chapter is to assist with incorporation of genetic and genomic trajectories into their research and facilitate the design and execution of these studies. New studies that are going to embark on recruitment, phenotyping, and sample collection will benefit from forethought about research design to ensure that it addresses the research questions or hypotheses being tested. Studies that will use existing data or samples will also benefit from forethought about research design for the same reason but will also address the fact that some designs may not be feasible with the available data or samples. This chapter discusses candidate gene association, genome-wide association, candidate gene expression, global gene expression, and epigenetic/epigenomic study designs. Information provided includes rationale for selecting an appropriate study design, important methodology considerations for each design, key technologies available to accomplish each type of study, and online resources available to assist in executing each type of study design.

DNA methylation in peripheral blood: a potential biomarker for cancer molecular epidemiology

Aberrant DNA methylation is associated with cancer development and progression. There are several types of specimens from which DNA methylation pattern can be measured and evaluated as an indicator of disease status (from normal biological process to pathologic condition) and even of pharmacologic response to therapy. Blood-based specimens such as cell-free circulating nucleic acid and DNA extracted from leukocytes in peripheral blood may be a potential source of noninvasive cancer biomarkers. In this article, we describe the characteristics of blood-based DNA methylation from different biological sources, detection methods, and the factors affecting DNA methylation. We provide a comprehensive literature review of blood-based DNA methylation as a cancer biomarker and focus on the study of DNA methylation using peripheral blood leukocytes. Although DNA methylation patterns measured in peripheral blood have great potential to be useful and informative biomarkers of cancer risk and prognosis, large systematic and unbiased prospective studies that consider biological plausibility and data analysis issues will be needed in order to develop a clinically feasible blood-based assay.

Make way for the 'next generation': application and prospects for genome-wide, epigenome-specific technologies in endocrine research

Epigenetic changes, which target DNA and associated histones, can be described as a pivotal mechanism of interaction between genes and the environment. The field of epigenomics aims to detect and interpret epigenetic modifications at the whole genome level. These approaches have the potential to increase resolution of epigenetic changes to the single base level in multiple disease states or across a population of individuals. Identification and comparison of the epigenomic landscape has challenged our understanding of the regulation of phenotype. Additionally, inclusion of these marks as biomarkers in the early detection or progression monitoring of disease is providing novel avenues for future biomedical research. Cells of the endocrine organs, which include pituitary, thyroid, thymus, pancreas ovary and testes, have been shown to be susceptible to epigenetic alteration, leading to both local and systemic changes often resulting in life-threatening metabolic disease. As with other cell types and populations, endocrine cells are susceptible to tumour development, which in turn may have resulted from aberration of epigenetic control. Techniques including high-throughput sequencing and array-based analysis to investigate these changes have rapidly emerged and are continually evolving. Here, we present a review of these methods and their promise to influence our studies on the epigenome for endocrine research and perhaps to uncover novel therapeutic options in disease states.

Human dedifferentiated adipocytes show similar properties to bone marrow-derived mesenchymal stem cells

Mature adipocytes are generally considered terminally differentiated because they have lost their proliferative abilities. Here, we studied the gene expression and functional properties of mature adipocytes isolated from human omental and subcutaneous fat tissues. We also focused on dedifferentiated adipocytes in culture and their morphologies and functional changes with respect to mature adipocytes, stromal-vascular fraction (SVF)-derived mesenchymal stem cells (MSCs) and bone marrow (BM)-derived MSCs. Isolated mature adipocytes expressed stem cell and reprogramming genes. They replicated in culture after assuming a fibroblast-like shape and expanded similarly to SVF- and BM-derived MSCs. During the dedifferentiation process, mature adipocytes lost their lineage gene expression profile, assumed the typical mesenchymal morphology and immunophenotype, expressed stem cell genes and differentiated into multilineage cells. Moreover, during the dedifferentiation process, we showed changes in the epigenetic status of mature adipocytes, which led dedifferentiated adipocytes to display a similar DNA methylation condition to BM-derived MSCs. Like SVF- and BM-derived MSCs, dedifferentiated adipocytes were able to inhibit the proliferation of stimulated lymphocytes in coculture while mature adipocytes stimulated their growth. Furthermore, dedifferentiated adipocytes maintained the survival and complete differentiation characteristic of hematopoietic stem cells. This is the first study that in addition to characterizing isolated and dedifferentiated adipocytes also reports on the immunoregulatory and hematopoietic supporting functions of these cells. This structural and functional characterization might have clinical applications of both mature and dedifferentiated adipocytes in such fields, as regenerative medicine.

Methylomic analysis identifies frequent DNA methylation of zinc finger protein 582 (ZNF582) in cervical neoplasms

Background

Despite of the trend that the application of DNA methylation as a biomarker for cancer detection is promising, clinically applicable genes are few. Therefore, we looked for novel hypermethylated genes for cervical cancer screening.

Methods and Findings

At the discovery phase, we analyzed the methylation profiles of human cervical carcinomas and normal cervixes by methylated DNA immunoprecipitation coupled to promoter tiling arrays (MeDIP-on-chip). Methylation-specific PCR (MSP), quantitative MSP and bisulfite sequencing were used to verify the methylation status in cancer tissues and cervical scrapings from patients with different severities. Immunohistochemical staining of a cervical tissue microarray was used to confirm protein expression. We narrowed to three candidate genes: DBC1, PDE8B, and ZNF582; their methylation frequencies in tumors were 93%, 29%, and 100%, respectively. At the pre-validation phase, the methylation frequency of DBC1 and ZNF582 in cervical scraping correlated significantly with disease severity in an independent cohort (n = 330, both P<0.001). For the detection of cervical intraepithelial neoplasia 3 (CIN3) and worse, the area under the receiver operating characteristic curve (AUC) of ZNF582 was 0.82 (95% confidence interval  = 0.76–0.87).

Conclusions

Our study shows ZNF582 is frequently methylated in CIN3 and worse lesions, and it is demonstrated as a potential biomarker for the molecular screening of cervical cancer.

SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips

DNA methylation is the most widely studied epigenetic mark and is known to be essential to normal development and frequently disrupted in disease. The Illumina HumanMethylation450 BeadChip assays the methylation status of CpGs at 485,577 sites across the genome. Here we present Subset-quantile Within Array Normalization (SWAN), a new method that substantially improves the results from this platform by reducing technical variation within and between arrays. SWAN is available in the minfi Bioconductor package.

Genomics of DNA cytosine methylation in Escherichia coli reveals its role in stationary phase transcription

DNA cytosine methylation regulates gene expression in mammals. In bacteria, its role in gene expression and genome architecture is less understood. Here we perform high-throughput sequencing of bisulfite-treated genomic DNA from Escherichia coli K12 to describe, for the first time, the extent of cytosine methylation of bacterial DNA at single-base resolution. Whereas most target sites (C(m)CWGG) are fully methylated in stationary phase cells, many sites with an extended CC(m)CWGG motif are only partially methylated in exponentially growing cells. We speculate that these partially methylated sites may be selected, as these are slightly correlated with the risk of spontaneous, non-synonymous conversion of methylated cytosines to thymines. Microarray analysis in a cytosine methylation-deficient mutant of E. coli shows increased expression of the stress response sigma factor RpoS and many of its targets in stationary phase. Thus, DNA cytosine methylation is a regulator of stationary phase gene expression in E. coli.

Methylation-mediated molecular dysregulation in clinical oral malignancy

Herein we provide a concise review of the state of methylation research as it pertains to clinical oral cancerous and precancerous tissues. We provide context for ongoing research efforts in this field and describe technologies that are presently being applied to analyze clinical specimens. We also discuss the various recurrent methylation changes that have been reported for oral malignancy (including those genes frequently silenced by promoter methylation and the small RNAs with activity modulated by methylation changes) and describe surrogate disease markers identified via epigenetic analysis of saliva and blood specimens from patients with oral cancer.

A comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform

Background

The 27k Illumina Infinium Methylation Beadchip is a popular high-throughput technology that allows the methylation state of over 27,000 CpGs to be assayed. While feature selection and classification methods have been comprehensively explored in the context of gene expression data, relatively little is known as to how best to perform feature selection or classification in the context of Illumina Infinium methylation data. Given the rising importance of epigenomics in cancer and other complex genetic diseases, and in view of the upcoming epigenome wide association studies, it is critical to identify the statistical methods that offer improved inference in this novel context.

Results

Using a total of 7 large Illumina Infinium 27k Methylation data sets, encompassing over 1,000 samples from a wide range of tissues, we here provide an evaluation of popular feature selection, dimensional reduction and classification methods on DNA methylation data. Specifically, we evaluate the effects of variance filtering, supervised principal components (SPCA) and the choice of DNA methylation quantification measure on downstream statistical inference. We show that for relatively large sample sizes feature selection using test statistics is similar for M and β-values, but that in the limit of small sample sizes, M-values allow more reliable identification of true positives. We also show that the effect of variance filtering on feature selection is study-specific and dependent on the phenotype of interest and tissue type profiled. Specifically, we find that variance filtering improves the detection of true positives in studies with large effect sizes, but that it may lead to worse performance in studies with smaller yet significant effect sizes. In contrast, supervised principal components improves the statistical power, especially in studies with small effect sizes. We also demonstrate that classification using the Elastic Net and Support Vector Machine (SVM) clearly outperforms competing methods like LASSO and SPCA. Finally, in unsupervised modelling of cancer diagnosis, we find that non-negative matrix factorisation (NMF) clearly outperforms principal components analysis.

Conclusions

Our results highlight the importance of tailoring the feature selection and classification methodology to the sample size and biological context of the DNA methylation study. The Elastic Net emerges as a powerful classification algorithm for large-scale DNA methylation studies, while NMF does well in the unsupervised context. The insights presented here will be useful to any study embarking on large-scale DNA methylation profiling using Illumina Infinium beadarrays.

Evaluation of the Infinium Methylation 450K technology

AIMS

Studies of DNA methylomes hold enormous promise for biomedicine but are hampered by the technological challenges of analyzing many samples cost-effectively. Recently, a major extension of the previous Infinium HumanMethylation27 BeadChip® (Illumina, Inc. CA, USA), called Infinium HumanMethylation450 (Infinium Methylation 450K; Illumina, Inc. CA, USA) was developed. This upgraded technology is a hybrid of two different chemical assays, the Infinium I and Infinium II assays, allowing (for 12 samples in parallel) assessment of the methylation status of more than 480,000 cytosines distributed over the whole genome. In this article, we evaluate Infinium Methylation 450K on cell lines and tissue samples, highlighting some of its advantages but also some of its limitations. In particular, we compare the methylation values of the Infinium I and Infinium II assays.

MATERIALS & METHODS

We used Infinium Methylation 450K to profile: first, the well-characterized HCT116 wild-type and double-knockout cell lines and then, 16 breast tissue samples (including eight normal and eight primary tumor samples). Absolute methylation values (β-values) were extracted with the GenomeStudio™ software and then subjected to detailed analysis.

RESULTS

While this technology appeared highly robust as previously shown, we noticed a divergence between the β-values retrieved from the type I and type II Infinium assays. Specifically, the β-values obtained from Infinium II probes were less accurate and reproducible than those obtained from Infinium I probes. This suggests that data from the type I and type II assays should be considered separately in any downstream bioinformatic analysis. To be able to deal with the Infinium I and Infinium II data together, we developed and tested a new correction technique, which we called 'peak-based correction'. The idea was to rescale the Infinium II data on the basis of the Infinium I data. While this technique should be viewed as an approximation method, it significantly improves the quality of Infinium II data.

CONCLUSION

Infinium 450K is a powerful technique in terms of reagent costs, time of labor, sample throughput and coverage. It holds great promise for the better understanding of the epigenetic component in health and disease. Yet, due to the nature of its design comprising two different chemical assays, analysis of the whole set of data is not as easy as initially anticipated. Correction strategies, such as the peak-based approach proposed here, are a step towards adequate output data analysis.

Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation

Background

Recently, it has been proposed that epigenetic variation may contribute to the risk of complex genetic diseases like cancer. We aimed to demonstrate that epigenetic changes in normal cells, collected years in advance of the first signs of morphological transformation, can predict the risk of such transformation.

Methods

We analyzed DNA methylation (DNAm) profiles of over 27,000 CpGs in cytologically normal cells of the uterine cervix from 152 women in a prospective nested case-control study. We used statistics based on differential variability to identify CpGs associated with the risk of transformation and a novel statistical algorithm called EVORA (Epigenetic Variable Outliers for Risk prediction Analysis) to make predictions.

Results

We observed many CpGs that were differentially variable between women who developed a non-invasive cervical neoplasia within 3 years of sample collection and those that remained disease-free. These CpGs exhibited heterogeneous outlier methylation profiles and overlapped strongly with CpGs undergoing age-associated DNA methylation changes in normal tissue. Using EVORA, we demonstrate that the risk of cervical neoplasia can be predicted in blind test sets (AUC = 0.66 (0.58 to 0.75)), and that assessment of DNAm variability allows more reliable identification of risk-associated CpGs than statistics based on differences in mean methylation levels. In independent data, EVORA showed high sensitivity and specificity to detect pre-invasive neoplasia and cervical cancer (AUC = 0.93 (0.86 to 1) and AUC = 1, respectively).

Conclusions

We demonstrate that the risk of neoplastic transformation can be predicted from DNA methylation profiles in the morphologically normal cell of origin of an epithelial cancer. Having profiled only 0.1% of CpGs in the human genome, studies of wider coverage are likely to yield improved predictive and diagnostic models with the accuracy needed for clinical application.

Trial registration

The ARTISTIC trial is registered with the International Standard Randomised Controlled Trial Number ISRCTN25417821.