Pruning and thresholding approach for methylation risk scores in multi-ancestry populations.

Recent efforts have focused on developing methylation risk scores (MRS), a weighted sum of the individual's DNA methylation (DNAm) values of pre-selected CpG sites. Most of the current MRS approaches that utilize Epigenome-wide association studies (EWAS) summary statistics only include genome-wide significant CpG sites and do not consider co-methylation. New methods that relax the p-value threshold to include more CpG sites and account for the inter-correlation of DNAm might improve the predictive performance of MRS. We paired informed co-methylation pruning with P-value thresholding to generate pruning and thresholding (P+T) MRS and evaluated its performance among multi-ancestry populations. Through simulation studies and real data analyses, we demonstrated that pruning provides an improvement over simple thresholding methods for prediction of phenotypes. We demonstrated that European-derived summary statistics can be used to develop P+T MRS among other populations such as African populations. However, the prediction accuracy of P+T MRS may differ across multi-ancestry population due to environmental/cultural/social differences.

A systematic evaluation of normalization methods and probe replicability using infinium EPIC methylation data.

BACKGROUND: The Infinium EPIC array measures the methylation status of > 850,000 CpG sites. The EPIC BeadChip uses a two-array design: Infinium Type I and Type II probes. These probe types exhibit different technical characteristics which may confound analyses. Numerous normalization and pre-processing methods have been developed to reduce probe type bias as well as other issues such as background and dye bias. METHODS: This study evaluates the performance of various normalization methods using 16 replicated samples and three metrics: absolute beta-value difference, overlap of non-replicated CpGs between replicate pairs, and effect on beta-value distributions. Additionally, we carried out Pearson's correlation and intraclass correlation coefficient (ICC) analyses using both raw and SeSAMe 2 normalized data. RESULTS: The method we define as SeSAMe 2, which consists of the application of the regular SeSAMe pipeline with an additional round of QC, pOOBAH masking, was found to be the best performing normalization method, while quantile-based methods were found to be the worst performing methods. Whole-array Pearson's correlations were found to be high. However, in agreement with previous studies, a substantial proportion of the probes on the EPIC array showed poor reproducibility (ICC < 0.50). The majority of poor performing probes have beta values close to either 0 or 1, and relatively low standard deviations. These results suggest that probe reliability is largely the result of limited biological variation rather than technical measurement variation. Importantly, normalizing the data with SeSAMe 2 dramatically improved ICC estimates, with the proportion of probes with ICC values > 0.50 increasing from 45.18% (raw data) to 61.35% (SeSAMe 2).

A variability in response of osteoclasts to zoledronic acid is mediated by smoking-associated modification in the DNA methylome.

BACKGROUND: Clinical trials have shown zoledronic acid as a potent bisphosphonate in preventing bone loss, but with varying potency between patients. Human osteoclasts ex vivo reportedly displayed a variable sensitivity to zoledronic acid > 200-fold, determined by the half-maximal inhibitory concentration (IC50), with cigarette smoking as one of the reported contributors to this variation. To reveal the molecular basis of the smoking-mediated variation on treatment sensitivity, we performed a DNA methylome profiling on whole blood cells from 34 healthy female blood donors. Multiple regression models were fitted to associate DNA methylation with ex vivo determined IC50 values, smoking, and their interaction adjusting for age and cell compositions. RESULTS: We identified 59 CpGs displaying genome-wide significance (p < 1e-08) with a false discovery rate (FDR) < 0.05 for the smoking-dependent association with IC50. Among them, 3 CpGs have p < 1e-08 and FDR < 2e-03. By comparing with genome-wide association studies, 15 significant CpGs were locally enriched (within < 50,000 bp) by SNPs associated with bone and body size measures. Furthermore, through a replication analysis using data from a published multi-omics association study on bone mineral density (BMD), we could validate that 29 out of the 59 CpGs were in close vicinity of genomic sites significantly associated with BMD. Gene Ontology (GO) analysis on genes linked to the 59 CpGs displaying smoking-dependent association with IC50, detected 18 significant GO terms including cation:cation antiporter activity, extracellular matrix conferring tensile strength, ligand-gated ion channel activity, etc. CONCLUSIONS: Our results suggest that smoking mediates individual sensitivity to zoledronic acid treatment through epigenetic regulation. Our novel findings could have important clinical implications since DNA methylation analysis may enable personalized zoledronic acid treatment.

Target-enriched enzymatic methyl sequencing: Flexible, scalable and inexpensive hybridization capture for quantifying DNA methylation.

The increasing interest in studying DNA methylation to understand how traits or diseases develop requires new and flexible approaches for quantifying DNA methylation in a diversity of organisms. In particular, we need efficient yet cost-effective ways to measure CpG methylation states over large and complete regions of the genome. Here, we develop TEEM-Seq (target-enriched enzymatic methyl sequencing), a method that combines enzymatic methyl sequencing with a custom-designed hybridization capture bait set that can be scaled to reactions including large numbers of samples in any species for which a reference genome is available. Using DNA from a passerine bird, the superb starling (Lamprotornis superbus), we show that TEEM-Seq is able to quantify DNA methylation states similarly well to the more traditional approaches of whole-genome and reduced-representation sequencing. Moreover, we demonstrate its reliability and repeatability, as duplicate libraries from the same samples were highly correlated. Importantly, the downstream bioinformatic analysis for TEEM-Seq is the same as for any sequence-based approach to studying DNA methylation, making it simple to incorporate into a variety of workflows. We believe that TEEM-Seq could replace traditional approaches for studying DNA methylation in candidate genes and pathways, and be effectively paired with other whole-genome or reduced-representation sequencing approaches to increase project sample sizes. In addition, TEEM-Seq can be combined with mRNA sequencing to examine how DNA methylation in promoters or other regulatory regions is related to the expression of individual genes or gene networks. By maximizing the number of samples in the hybridization reaction, TEEM-Seq is an inexpensive and flexible sequence-based approach for quantifying DNA methylation in species where other capture-based methods are unavailable or too expensive, particularly for non-model organisms.

Influence of methyl donor nutrients as epigenetic regulators in colorectal cancer: A systematic review of observational studies.

BACKGROUND: Dietary methyl donors might influence DNA methylation during carcinogenesis of colorectal cancer (CRC). However, whether the influence of methyl donor intake is modified by polymorphisms in such epigenetic regulators is still unclear. AIM: To improve the current understanding of the molecular basis of CRC. METHODS: A literature search in the Medline database, Reference Citation Analysis (https:// www.referencecitationanalysis.com/), and manual reference screening were performed to identify observational studies published from inception to May 2022. RESULTS: A total of fourteen case-control studies and five cohort studies were identified. These studies included information on dietary methyl donors, dietary components that potentially modulate the bioavailability of methyl groups, genetic variants of methyl metabolizing enzymes, and/or markers of CpG island methylator phenotype and/or microsatellite instability, and their possible interactions on CRC risk. CONCLUSION: Several studies have suggested interactions between methylenetetrahydrofolate reductase polymorphisms, methyl donor nutrients (such as folate) and alcohol on CRC risk. Moreover, vitamin B6, niacin, and alcohol may affect CRC risk through not only genetic but also epigenetic regulation. Identification of specific mechanisms in these interactions associated with CRC may assist in developing targeted prevention strategies for individuals at the highest risk of developing CRC.

DNA methylation patterns at birth predict health outcomes in young adults born very low birthweight.

BACKGROUND: Individuals born very low birthweight (VLBW) are at increased risk of impaired cardiovascular and respiratory function in adulthood. To identify markers to predict future risk for VLBW individuals, we analyzed DNA methylation at birth and at 28 years in the New Zealand (NZ) VLBW cohort (all infants born < 1500 g in NZ in 1986) compared with age-matched, normal birthweight controls. Associations between neonatal methylation and cardiac structure and function (echocardiography), vascular function and respiratory outcomes at age 28 years were documented. RESULTS: Genomic DNA from archived newborn heel-prick blood (n = 109 VLBW, 51 controls) and from peripheral blood at ~ 28 years (n = 215 VLBW, 96 controls) was analyzed on Illumina Infinium MethylationEPIC 850 K arrays. Following quality assurance and normalization, methylation levels were compared between VLBW cases and controls at both ages by linear regression, with genome-wide significance set to p < 0.05 adjusted for false discovery rate (FDR, Benjamini-Hochberg). In neonates, methylation at over 16,400 CpG methylation sites differed between VLBW cases and controls and the canonical pathway most enriched for these CpGs was Cardiac Hypertrophy Signaling (p = 3.44E-11). The top 20 CpGs that differed most between VLBW cases and controls featured clusters in ARID3A, SPATA33, and PLCH1 and these 3 genes, along with MCF2L, TRBJ2-1 and SRC, led the list of 15,000 differentially methylated regions (DMRs) reaching FDR-adj significance. Fifteen of the 20 top CpGs in the neonate EWAS showed associations between methylation at birth and adult cardiovascular traits (particularly LnRHI). In 28-year-old adults, twelve CpGs differed between VLBW cases and controls at FDR-adjusted significance, including hypermethylation in EBF4 (four CpGs), CFI and UNC119B and hypomethylation at three CpGs in HIF3A and one in KCNQ1. DNA methylation GrimAge scores at 28 years were significantly greater in VLBW cases versus controls and weakly associated with cardiovascular traits. Four CpGs were identified where methylation differed between VLBW cases and controls in both neonates and adults, three reversing directions with age (two CpGs in EBF4, one in SNAI1 were hypomethylated in neonates, hypermethylated in adults). Of these, cg16426670 in EBF4 at birth showed associations with several cardiovascular traits in adults. CONCLUSIONS: These findings suggest that methylation patterns in VLBW neonates may be informative about future adult cardiovascular and respiratory outcomes and have value in guiding early preventative care to improve adult health.

An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review.

The prediction of chronological age from methylation-based biomarkers represents one of the most promising applications in the field of forensic sciences. Age-prediction models developed so far are not easily applicable for forensic caseworkers. Among the several attempts to pursue this objective, the formulation of single-locus models might represent a good strategy. The present work aimed to develop an accurate single-locus model for age prediction exploiting ELOVL2, a gene for which epigenetic alterations are most highly correlated with age. We carried out a systematic review of different published pyrosequencing datasets in which methylation of the ELOVL2 promoter was analysed to formulate age prediction models. Nine of these, with available datasets involving 2298 participants, were selected. We found that irrespective of which model was adopted, a very strong relationship between ELOVL2 methylation levels and age exists. In particular, the model giving the best age-prediction accuracy was the gradient boosting regressor with a prediction error of about 5.5 years. The findings reported here strongly support the use of ELOVL2 for the formulation of a single-locus epigenetic model, but the inclusion of additional, non-redundant markers is a fundamental requirement to apply a molecular model to forensic applications with more robust results.

Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging.

BACKGROUND: Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown. RESULT: We propose a novel computational method, Data-driven Identification and Classification of Nonlinear Aging Patterns (DICNAP), that is based on functional data analysis to identify biomarkers for aging and potential patterns of change during aging in a data-driven manner. We applied the proposed method to large-scale, public DNA methylation data to explore the potential patterns of age-related changes in methylation intensity. The results showed that not only linear, but also nonlinear changes in DNA methylation patterns exist. A monotonous demethylation pattern during aging, with its rate decreasing at around age 60, was identified as the candidate stable nonlinear pattern. We also analyzed the age-related changes in methylation variability. The results showed that the variability of methylation intensity tends to increase with age at age-associated sites. The representative variability pattern is a monotonically increasing pattern that accelerates after middle age. CONCLUSION: DICNAP was able to identify the potential patterns of the changes in the landscape of DNA methylation during aging. It contributes to an improvement in our theoretical understanding of the aging process.

Cross-tissue correlations of genome-wide DNA methylation in Japanese live human brain and blood, saliva, and buccal epithelial tissues.

Neuroepigenetics considers genetic sequences and the interplay with environmental influences to elucidate vulnerability risk for various neurological and psychiatric disorders. However, evaluating DNA methylation of brain tissue is challenging owing to the issue of tissue specificity. Consequently, peripheral surrogate tissues were used, resulting in limited progress compared with other epigenetic studies, such as cancer research. Therefore, we developed databases to establish correlations between the brain and peripheral tissues in the same individuals. Four tissues, resected brain tissue, blood, saliva, and buccal mucosa (buccal), were collected from 19 patients (aged 13-73 years) who underwent neurosurgery. Moreover, their genome-wide DNA methylation was assessed using the Infinium HumanMethylationEPIC BeadChip arrays to determine the cross-tissue correlation of each combination. These correlation analyses were conducted with all methylation sites and with variable CpGs, and with when these were adjusted for cellular proportions. For the averaged data for each CpG across individuals, the saliva-brain correlation (r = 0.90) was higher than that for blood-brain (r = 0.87) and buccal-brain (r = 0.88) comparisons. Among individual CpGs, blood had the highest proportion of CpGs correlated to the brain at nominally significant levels (19.0%), followed by saliva (14.4%) and buccal (9.8%). These results were similar to the previous IMAGE-CpG results; however, cross-database correlations of the correlation coefficients revealed a relatively low (brain vs. blood: r = 0.27, saliva: r = 0.18, and buccal: r = 0.24). To the best of our knowledge, this is the fifth study in the literature initiating the development of databases for correlations between the brain and peripheral tissues in the same individuals. We present the first database developed from an Asian population, specifically Japanese samples (AMAZE-CpG), which would contribute to interpreting individual epigenetic study results from various Asian populations.

MORF and MOZ acetyltransferases target unmethylated CpG islands through the winged helix domain.

Human acetyltransferases MOZ and MORF are implicated in chromosomal translocations associated with aggressive leukemias. Oncogenic translocations involve the far amino terminus of MOZ/MORF, the function of which remains unclear. Here, we identified and characterized two structured winged helix (WH) domains, WH1 and WH2, in MORF and MOZ. WHs bind DNA in a cooperative manner, with WH1 specifically recognizing unmethylated CpG sequences. Structural and genomic analyses show that the DNA binding function of WHs targets MORF/MOZ to gene promoters, stimulating transcription and H3K23 acetylation, and WH1 recruits oncogenic fusions to HOXA genes that trigger leukemogenesis. Cryo-EM, NMR, mass spectrometry and mutagenesis studies provide mechanistic insight into the DNA-binding mechanism, which includes the association of WH1 with the CpG-containing linker DNA and binding of WH2 to the dyad of the nucleosome. The discovery of WHs in MORF and MOZ and their DNA binding functions could open an avenue in developing therapeutics to treat diseases associated with aberrant MOZ/MORF acetyltransferase activities.

A new blood based epigenetic age predictor for adolescents and young adults.

Children have special rights for protection compared to adults in our society. However, more than 1/4 of children globally have no documentation of their date of birth. Hence, there is a pressing need to develop biological methods for chronological age prediction, robust to differences in genetics, psychosocial events and physical living conditions. At present, DNA methylation is the most promising biological biomarker applied for age assessment. The human genome contains around 28 million DNA methylation sites, many of which change with age. Several epigenetic clocks accurately predict chronological age using methylation levels at age associated GpG-sites. However, variation in DNA methylation increases with age, and there is no epigenetic clock specifically designed for adolescents and young adults. Here we present a novel age Predictor for Adolescents and Young Adults (PAYA), using 267 CpG methylation sites to assess the chronological age of adolescents and young adults. We compared different preprocessing approaches and investigated the effect on prediction performance of the epigenetic clock. We evaluated performance using an independent validation data set consisting of 18-year-old individuals, where we obtained a median absolute deviation of just below 0.7 years. This tool may be helpful in age assessment of adolescents and young adults. However, there is a need to investigate the robustness of the age predictor across geographical and disease populations as well as environmental effects.

DNA-Methylation Signatures of Tobacco Smoking in a High Cardiovascular Risk Population: Modulation by the Mediterranean Diet.

Biomarkers based on DNA methylation are relevant in the field of environmental health for precision health. Although tobacco smoking is one of the factors with a strong and consistent impact on DNA methylation, there are very few studies analyzing its methylation signature in southern European populations and none examining its modulation by the Mediterranean diet at the epigenome-wide level. We examined blood methylation smoking signatures on the EPIC 850 K array in this population (n = 414 high cardiovascular risk subjects). Epigenome-wide methylation studies (EWASs) were performed analyzing differential methylation CpG sites by smoking status (never, former, and current smokers) and the modulation by adherence to a Mediterranean diet score was explored. Gene-set enrichment analysis was performed for biological and functional interpretation. The predictive value of the top differentially methylated CpGs was analyzed using receiver operative curves. We characterized the DNA methylation signature of smoking in this Mediterranean population by identifying 46 differentially methylated CpGs at the EWAS level in the whole population. The strongest association was observed at the cg21566642 (p = 2.2 × 10-32) in the 2q37.1 region. We also detected other CpGs that have been consistently reported in prior research and discovered some novel differentially methylated CpG sites in subgroup analyses. In addition, we found distinct methylation profiles based on the adherence to the Mediterranean diet. Particularly, we obtained a significant interaction between smoking and diet modulating the cg5575921 methylation in the AHRR gene. In conclusion, we have characterized biomarkers of the methylation signature of tobacco smoking in this population, and suggest that the Mediterranean diet can increase methylation of certain hypomethylated sites.

Dual stimulation by autoantigen and CpG fosters the proliferation of exhausted rheumatoid factor-specific CD21low B cells in hepatitis C virus-cured mixed cryoglobulinemia.

Introduction: Hepatitis C virus (HCV) causes mixed cryoglobulinemia (MC) by driving clonal expansion of B cells expressing B cell receptors (BCRs), often encoded by the VH1-69 variable gene, endowed with both rheumatoid factor (RF) and anti-HCV specificity. These cells display an atypical CD21low phenotype and functional exhaustion evidenced by unresponsiveness to BCR and Toll-like receptor 9 (TLR9) stimuli. Although antiviral therapy is effective on MC vasculitis, pathogenic B cell clones persist long thereafter and can cause virus-independent disease relapses. Methods: Clonal B cells from patients with HCV-associated type 2 MC or healthy donors were stimulated with CpG or heath-aggregated IgG (as surrogate immune complexes) alone or in combination; proliferation and differentiation were then evaluated by flow cytometry. Phosphorylation of AKT and of the p65 NF-kB subunit were measured by flow cytometry. TLR9 was quantified by qPCR and by intracellular flow cytometry, and MyD88 isoforms were analyzed using RT-PCR. Discussion: We found that dual triggering with autoantigen and CpG restored the capacity of exhausted VH1-69pos B cells to proliferate. The signaling mechanism for this BCR/TLR9 crosstalk remains elusive, since TLR9 mRNA and protein as well as MyD88 mRNA were normally expressed and CpG-induced phosphorylation of p65 NF-kB was intact in MC clonal B cells, whereas BCR-induced p65 NF-kB phosphorylation was impaired and PI3K/Akt signaling was intact. Our findings indicate that autoantigen and CpG of microbial or cellular origin may unite to foster persistence of pathogenic RF B cells in HCV-cured MC patients. BCR/TLR9 crosstalk might represent a more general mechanism enhancing systemic autoimmunity by the rescue of exhausted autoreactive CD21low B cells.

Analysis of Methylation and mRNA Expression of Lin28B Gene Promoter Region in the Hypothalamus of Dolang Sheep During Pubertal Initiation.

Lin28B plays an important role in puberty initiation in sheep. This study aimed to discuss the correlation between different growth periods and the methylation status of cytosine-guanine dinucleotide (CpG) islands in the promoter region of the Lin28B gene in the Dolang sheep's hypothalamus. In this study, the sequence of the Lin28B gene promoter region in Dolang sheep was obtained by cloning and sequencing, and methyl groups of the CpG island of the Lin28B gene promoter in the hypothalamus were detected by bisulfite sequencing PCR during the three periods of prepuberty, adolescence, and postpuberty in Dolang sheep. Lin28B expression in the Dolang sheep's hypothalamus was detected by fluorescence quantitative PCR at three stages: prepuberty, puberty, and postpuberty. In this experiment, the 2993-bp Lin28B promoter region was obtained, and it was predicted that there was a CpG island containing 15 transcription factor binding sites and 12 CpG sites, which may play a role in gene expression regulation. Overall, methylation levels increased from prepuberty to postpuberty, while Lin28B expression levels decreased, indicating that Lin28B expression was negatively correlated with promoter methylation levels. Variance analysis showed significant differences in the methylation status of CpG5, CpG7, and CpG9 between pre- and postpuberty (p < 0.05). Our data show that Lin28B expression is increased by demethylation of promoter CpG islands, with CpG5, CpG7, and CpG9 implicated as critical regulatory sites.

Principal component analysis- and tensor decomposition-based unsupervised feature extraction to select more suitable differentially methylated cytosines: Optimization of standard deviation versus state-of-the-art methods.

In contrast to RNA-seq analysis, which has various standard methods, no standard methods for identifying differentially methylated cytosines (DMCs) exist. To identify DMCs, we tested principal component analysis and tensor decomposition-based unsupervised feature extraction with optimized standard deviation, which has been shown to be effective for differentially expressed gene (DEG) identification. The proposed method outperformed certain conventional methods, including those that assume beta-binomial distribution for methylation as the proposed method does not require this, especially when applied to methylation profiles measured using high throughput sequencing. DMCs identified by the proposed method also significantly overlapped with various functional sites, including known differentially methylated regions, enhancers, and DNase I hypersensitive sites. The proposed method was applied to data sets retrieved from The Cancer Genome Atlas to identify DMCs using American Joint Committee on Cancer staging system edition labels. This suggests that the proposed method is a promising standard method for identifying DMCs.

DNA methylation entropy is associated with DNA sequence features and developmental epigenetic divergence.

Epigenetic information defines tissue identity and is largely inherited in development through DNA methylation. While studied mostly for mean differences, methylation also encodes stochastic change, defined as entropy in information theory. Analyzing allele-specific methylation in 49 human tissue sample datasets, we find that methylation entropy is associated with specific DNA binding motifs, regulatory DNA, and CpG density. Then applying information theory to 42 mouse embryo methylation datasets, we find that the contribution of methylation entropy to time- and tissue-specific patterns of development is comparable to the contribution of methylation mean, and methylation entropy is associated with sequence and chromatin features conserved with human. Moreover, methylation entropy is directly related to gene expression variability in development, suggesting a role for epigenetic entropy in developmental plasticity.

Epigenetic and Genetic Population Structure is Coupled in a Marine Invertebrate.

Delineating the relative influence of genotype and the environment on DNA methylation is critical for characterizing the spectrum of organism fitness as driven by adaptation and phenotypic plasticity. In this study, we integrated genomic and DNA methylation data for two distinct Olympia oyster (Ostrea lurida) populations while controlling for within-generation environmental influences. In addition to providing the first characterization of genome-wide DNA methylation patterns in the oyster genus Ostrea, we identified 3,963 differentially methylated loci between populations. Our results show a clear coupling between genetic and epigenetic patterns of variation, with 27% of variation in interindividual methylation differences explained by genotype. Underlying this association are both direct genetic changes in CpGs (CpG-SNPs) and genetic variation with indirect influence on methylation (mQTLs). When comparing measures of genetic and epigenetic population divergence at specific genomic regions this relationship surprisingly breaks down, which has implications for the methods commonly used to study epigenetic and genetic coupling in marine invertebrates.

A CpG island-encoded mechanism protects genes from premature transcription termination.

Transcription must be tightly controlled to regulate gene expression and development. However, our understanding of the molecular mechanisms that influence transcription and how these are coordinated in cells to ensure normal gene expression remains rudimentary. Here, by dissecting the function of the SET1 chromatin-modifying complexes that bind to CpG island-associated gene promoters, we discover that they play a specific and essential role in enabling the expression of low to moderately transcribed genes. Counterintuitively, this effect can occur independently of SET1 complex histone-modifying activity and instead relies on an interaction with the RNA Polymerase II-binding protein WDR82. Unexpectedly, we discover that SET1 complexes enable gene expression by antagonising premature transcription termination by the ZC3H4/WDR82 complex at CpG island-associated genes. In contrast, at extragenic sites of transcription, which typically lack CpG islands and SET1 complex occupancy, we show that the activity of ZC3H4/WDR82 is unopposed. Therefore, we reveal a gene regulatory mechanism whereby CpG islands are bound by a protein complex that specifically protects genic transcripts from premature termination, effectively distinguishing genic from extragenic transcription and enabling normal gene expression.

Interactive DNA Methylation Array Analysis with ShinyÉPICo.

Arrays provide a cost-effective platform for the analysis of human DNA methylation. ShinyÉPICo is an interactive, web-based, and graphical tool that allows the user to analyze Illumina DNA methylation arrays (450 k and EPIC), from the user's own computer or from a server. This tool covers the analysis entirely, from the raw data input to the final list of differentially methylated positions or regions. Here, we describe the steps of the analysis, the different parameters available, and useful information to understand and select the best options in each step.

DNA Methylation Data Analysis Using Msuite.

DNA methylation is a widespread epigenetic modification responsible for many biological regulation pathways. The development of various powerful biochemical assays, including conventional bisulfite treatment-based and emerging bisulfite-free techniques, has promised high-resolution DNA methylome profiling and significantly propelled the DNA methylation research field. However, the analysis of large-scale data generated from such assays is still complex and challenging. In this paper, we present a step-by-step protocol for using Msuite for whole-spectrum DNA methylation data analysis, from quality control, read alignment, to methylation call and data visualization. The Msuite package and a testing dataset are freely available at https://github.com/hellosunking/Msuite.