Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Strengths and limitations of reduced representation bisulfite sequencing (RRBS) in the perspective of DNA methylation analysis in fish: a case-study on rainbow trout spermatozoa

DNA methylation in CpG dinucleotides is an important epigenetic mark in fish spermatozoa since it has been shown that some sperm methylome features are transmitted to the offspring. Reduced representation bisulfite sequencing (RRBS) is one genome-scale methods developed to assess DNA methylation at CpG sites. It allows the sequencing of a reduced fraction of the genome expected to be enriched in CpGs. The aim of this study is to characterize the extent of the CpG sites that can be identified in the RRBS-reduced sequenced fraction of rainbow trout spermatozoa, in order to evaluate the potential of RRBS for sperm DNA methylation studies. We observed that RRBS did provide a reduced amount of genomic data, the sum of the CpGs analyzed on 12 males spanning 9% of the total genomic CpGs. CpGs were only slightly enriched in the RRBS data (×1.7 times the sequenced nucleotides), the possible causes being linked to trout genome structure and sequenced fragments size. All genomic functional features were represented in our CpG dataset, with a noticeable enrichment in exons but, strikingly, not in promoters. The number of CpGs shared between biological replicates was low, but this proportion reached workable values from six biological replicates (46% of the analyzed cytosines) on. The choices that are to be made regarding fragment size selection and the options during bioinformatic data processing are discussed. In all, RRBS is a relevant first-approach method to scan the CpG DNA methylation status of spermatozoa along rainbow trout genome, although in a very reduced pattern among biological replicates.

DNA hypomethylation promotes the expression of CASPASE-4 which exacerbates inflammation and amyloid-β deposition in Alzheimer's disease

Alzheimer's disease (AD) is the sixth leading cause of death in the USA. It is established that neuroinflammation contributes to the synaptic loss, neuronal death, and symptomatic decline of AD patients. Accumulating evidence suggests a critical role for microglia, innate immune phagocytes of the brain. For instance, microglia release pro-inflammatory products such as IL-1β which is highly implicated in AD pathobiology. The mechanisms underlying the transition of microglia to proinflammatory promoters of AD remain largely unknown. To address this gap, we performed reduced representation bisulfite sequencing (RRBS) to profile global DNA methylation changes in human AD brains compared to no disease controls. We identified differential DNA methylation of CASPASE-4 (CASP4), which when expressed promotes the generation of IL-1β and is predominantly expressed in immune cells. DNA upstream of the CASP4 transcription start site was hypomethylated in human AD brains, which was correlated with increased expression of CASP4. Furthermore, microglia from a mouse model of AD (5xFAD) express increased levels of CASP4 compared to wild-type (WT) mice. To study the role of CASP4 in AD, we developed a novel mouse model of AD lacking the mouse ortholog of CASP4 and CASP11, which is encoded by mouse Caspase-4 (5xFAD/Casp4-/-). The expression of CASP11 was associated with increased accumulation of pathologic protein aggregate amyloid-β (Aβ) and increased microglial production of IL-1β in 5xFAD mice. Utilizing RNA-sequencing, we determined that CASP11 promotes unique transcriptomic phenotypes in 5xFAD mouse brains, including alterations of neuroinflammatory and chemokine signaling pathways. Notably, in vitro, CASP11 promoted generation of IL-1β from macrophages in response to cytosolic Aβ through cleavage of downstream effector Gasdermin D (GSDMD). Therefore, here we unravel the role for CASP11 and GSDMD in the generation of IL-1β in response to Aβ and the progression of pathologic inflammation in AD. Overall, our results demonstrate that overexpression of CASP4 due to differential DNA methylation in AD microglia contributes to the progression of AD pathobiology. Thus, we identify CASP4 as a potential target for immunotherapies for the treatment and prevention of AD.

A novel principal component based method for identifying differentially methylated regions in Illumina Infinium MethylationEPIC BeadChip data

Differentially methylated regions (DMRs) are genomic regions with methylation patterns across multiple CpG sites that are associated with a phenotype. In this study, we proposed a Principal Component (PC) based DMR analysis method for use with data generated using the Illumina Infinium MethylationEPIC BeadChip (EPIC) array. We obtained methylation residuals by regressing the M-values of CpGs within a region on covariates, extracted PCs of the residuals, and then combined association information across PCs to obtain regional significance. Simulation-based genome-wide false positive (GFP) rates and true positive rates were estimated under a variety of conditions before determining the final version of our method, which we have named DMRPC. Then, DMRPC and another DMR method, coMethDMR, were used to perform epigenome-wide analyses of several phenotypes known to have multiple associated methylation loci (age, sex, and smoking) in a discovery and a replication cohort. Among regions that were analysed by both methods, DMRPC identified 50% more genome-wide significant age-associated DMRs than coMethDMR. The replication rate for the loci that were identified by only DMRPC was higher than the rate for those that were identified by only coMethDMR (90% for DMRPC vs. 76% for coMethDMR). Furthermore, DMRPC identified replicable associations in regions of moderate between-CpG correlation which are typically not analysed by coMethDMR. For the analyses of sex and smoking, the advantage of DMRPC was less clear. In conclusion, DMRPC is a new powerful DMR discovery tool that retains power in genomic regions with moderate correlation across CpGs.

Coordinated alternation of DNA methylation and alternative splicing of PBRM1 affect bovine sperm structure and motility

DNA methylation and gene alternative splicing drive spermatogenesis. In screening DNA methylation markers and transcripts related to sperm motility, semen from three pairs of full-sibling Holstein bulls with high and low motility was subjected to reduced representation bisulphite sequencing. A total of 948 DMRs were found in 874 genes (gDMRs). Approximately 89% of gDMR-related genes harboured alternative splicing events, including SMAD2, KIF17, and PBRM1. One DMR in exon 29 of PBRM1 with the highest 5mC ratio was found, and hypermethylation in this region was related to bull sperm motility. Furthermore, alternative splicing events at exon 29 of PBRM1 were found in bull testis, including PBRM1-complete, PBRM1-SV1 (exon 28 deletion), and PBRM1-SV2 (exons 28-29 deletion). PBRM1-SV2 exhibited significantly higher expression in adult bull testes than in newborn bull testes. In addition, PBRM1 was localized to the redundant nuclear membrane of bull sperm, which might be related to sperm motility caused by sperm tail breakage. Therefore, the hypermethylation of exon 29 may be associated with the production of PBRM1-SV2 in spermatogenesis. These findings indicated that DNA methylation alteration at specific loci could regulate gene splicing and expression and synergistically alter sperm structure and motility.

Broodstock nutritional programming differentially affects the hepatic transcriptome and genome-wide DNA methylome of farmed gilthead sea bream (Sparus aurata) depending on genetic background

BACKGROUND

Broodstock nutritional programming improves the offspring utilization of plant-based diets in gilthead sea bream through changes in hepatic metabolism. Attention was initially focused on fatty acid desaturases, but it can involve a wide range of processes that remain largely unexplored. How all this can be driven by a different genetic background is hardly underlined, and the present study aimed to assess how broodstock nutrition affects differentially the transcriptome and genome-wide DNA methylome of reference and genetically selected fish within the PROGENSA® selection program.

RESULTS

After the stimulus phase with a low fish oil diet, two offspring subsets of each genetic background received a control or a FUTURE-based diet. This highlighted a different hepatic transcriptome (RNA-seq) and genome-wide DNA methylation (MBD-seq) pattern depending on the genetic background. The number of differentially expressed transcripts following the challenge phase varied from 323 in reference fish to 2,009 in genetically selected fish. The number of discriminant transcripts, and associated enriched functions, were also markedly higher in selected fish. Moreover, correlation analysis depicted a hyper-methylated and down-regulated gene expression state in selected fish with the FUTURE diet, whereas the opposite pattern appeared in reference fish. After filtering for highly represented functions in selected fish, 115 epigenetic markers were retrieved in this group. Among them, lipid metabolism genes (23) were the most reactive following ordering by fold-change in expression, rendering a final list of 10 top markers with a key role on hepatic lipogenesis and fatty acid metabolism (cd36, pitpna, cidea, fasn, g6pd, lipt1, scd1a, acsbg2, acsl14, acsbg2).

CONCLUSIONS

Gene expression profiles and methylation signatures were dependent on genetic background in our experimental model. Such assumption affected the magnitude, but also the type and direction of change. Thus, the resulting epigenetic clock of reference fish might depict an older phenotype with a lower methylation for the epigenetically responsive genes with a negative methylation-expression pattern. Therefore, epigenetic markers will be specific of each genetic lineage, serving the broodstock programming in our selected fish to prevent and mitigate later in life the risk of hepatic steatosis through changes in hepatic lipogenesis and fatty acid metabolism.

Integrated analysis of DNA methylome and transcriptome reveals SFRP1 and LIPG as potential drivers of ovarian cancer metastasis

OBJECTIVE

More than 75% of ovarian cancer patients are diagnosed at advanced stages and die of tumor cell metastasis. This study aimed to identify new epigenetic and transcriptomic alterations associated with ovarian cancer metastasis.

METHODS

Two cell sublines with low- and high-metastasis potentials were derived from the ovarian cancer cell line A2780. Genome-wide DNA methylome and transcriptome profiling were carried out in these two sublines by Reduced Representation Bisulfite Sequencing and RNA-seq technologies. Cell-based assays were conducted to support the clinical findings.

RESULTS

There are distinct DNA methylation and gene expression patterns between the two cell sublines with low- and high-metastasis potentials. Integrated analysis identified 33 methylation-induced genes potentially involved in ovarian cancer metastasis. The DNA methylation patterns of two of them (i.e., SFRP1 and LIPG) were further validated in human specimens, indicating that they were hypermethylated and downregulated in peritoneal metastatic ovarian carcinoma compared to primary ovarian carcinoma. Patients with lower SFRP1 and LIPG expression tend to have a worse prognosis. Functionally, knockdown of SFRP1 and LIPG promoted cell growth and migration, whereas their overexpression resulted in the opposite effects. In particular, knockdown of SFRP1 could phosphorylate GSK3β and increase β-catenin expression, leading to deregulated activation of the Wnt/β-catenin signaling.

CONCLUSION

Many systemic and important epigenetic and transcriptomic alterations occur in the progression of ovarian cancer. In particular, epigenetic silencing of SFRP1 and LIPG is a potential driver event in ovarian cancer metastasis. They can be used as prognostic biomarkers and therapeutic targets for ovarian cancer patients.

DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues

Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3-9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the beta value-based linear support vector (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68).

DNA methylation markers in the detection of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and has a poor prognosis. Epigenetic modification has been shown to be deregulated during HCC development by dramatically impacting the differentiation, proliferation, and function of cells. One important epigenetic modification is DNA methylation during which methyl groups are added to cytosines without changing the DNA sequence itself. Studies found that methylated DNA markers can be specific for detection of HCC. On the basis of these findings, the utility of methylated DNA markers as novel biomarkers for early-stage HCC has been measured in blood, and indeed superior sensitivity and specificity have been found in several studies when compared to current surveillance methods. However, a variety of factors currently limit the immediate application of these exciting biomarkers. In this review, we provide a detailed rationalisation of the approach and basis for the use of methylation biomarkers for HCC detection and summarise recent studies on methylated DNA markers in HCC focusing on the importance of the aetiological cause of liver disease in the mechanisms leading to cancer.

DNA hypomethylation promotes the expression of CASPASE-4 which exacerbates neuroinflammation and amyloid-β deposition in Alzheimer's disease The Ohio State University College of Medicine

Alzheimer's Disease (AD) is the 6th leading cause of death in the US. It is established that neuroinflammation contributes to the synaptic loss, neuronal death, and symptomatic decline of AD patients. Accumulating evidence suggests a critical role for microglia, innate immune phagocytes of the brain. For instance, microglia release proinflammatory products such as IL-1β which is highly implicated in AD pathobiology. The mechanisms underlying the transition of microglia to proinflammatory promoters of AD remain largely unknown. To address this gap, we performed Reduced Representation Bisulfite Sequencing (RRBS) to profile global DNA methylation changes in human AD brains compared to no disease controls. We identified differential DNA methylation of CASPASE-4 (CASP4), which when expressed, can be involved in generation of IL-1β and is predominantly expressed in immune cells. DNA upstream of the CASP4 transcription start site was hypomethylated in human AD brains, which was correlated with increased expression of CASP4. Furthermore, microglia from a mouse model of AD (5xFAD) express increased levels of CASP4 compared to wild-type (WT) mice. To study the role of CASP4 in AD, we developed a novel mouse model of AD lacking the mouse ortholog of CASP4, CASP11, which is encoded by mouse Caspase-4 (5xFAD/Casp4-/-). The expression of CASP11 was associated with increased accumulation of pathologic protein aggregate amyloid-β (Aβ) and increased microglial production of IL-1β in 5xFAD mice. Utilizing RNA sequencing, we determined that CASP11 promotes unique transcriptomic phenotypes in 5xFAD mouse brains, including alterations of neuroinflammatory and chemokine signaling pathways. Notably, in vitro, CASP11 promoted generation of IL-1β from macrophages in response to cytosolic Aβ through cleavage of downstream effector Gasdermin D (G SDMD). We describe a role for CASP11 and GSDMD in the generation of IL-1β in response to Aβ and the progression of pathologic inflammation in AD. Overall, our results demonstrate that overexpression of CASP4 due to differential methylation in AD microglia contributes to the progression of AD pathobiology, thus identifying CASP4 as a potential target for immunotherapies for the treatment of AD.

E-value: a superior alternative to P-value and its adjustments in DNA methylation studies

DNA methylation plays a crucial role in transcriptional regulation. Reduced representation bisulfite sequencing (RRBS) is a technique of increasing use for analyzing genome-wide methylation profiles. Many computational tools such as Metilene, MethylKit, BiSeq and DMRfinder have been developed to use RRBS data for the detection of the differentially methylated regions (DMRs) potentially involved in epigenetic regulations of gene expression. For DMR detection tools, as for countless other medical applications, P-values and their adjustments are among the most standard reporting statistics used to assess the statistical significance of biological findings. However, P-values are coming under increasing criticism relating to their questionable accuracy and relatively high levels of false positive or negative indications. Here, we propose a method to calculate E-values, as likelihood ratios falling into the null hypothesis over the entire parameter space, for DMR detection in RRBS data. We also provide the R package 'metevalue' as a user-friendly interface to implement E-value calculations into various DMR detection tools. To evaluate the performance of E-values, we generated various RRBS benchmarking datasets using our simulator 'RRBSsim' with eight samples in each experimental group. Our comprehensive benchmarking analyses showed that using E-values not only significantly improved accuracy, area under ROC curve and power, over that of P-values or adjusted P-values, but also reduced false discovery rates and type I errors. In applications using real RRBS data of CRL rats and a clinical trial on low-salt diet, the use of E-values detected biologically more relevant DMRs and also improved the negative association between DNA methylation and gene expression.

Identification and validation of a DNA methylation-driven gene-based prognostic model for clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with heterogeneous morphology and poor prognosis. This study aimed to establish a DNA methylation (DNAm)-driven gene-based prognostic model for ccRCC.

METHODS

Reduced representation bisulfite sequencing (RRBS) was performed on the DNA extracts from ccRCC patients. We analyzed the RRBS data from 10 pairs of patient samples to screen the candidate CpG sites, then trained and validated an 18-CpG site model, and integrated the clinical characters to establish a Nomogram model for the prognosis or risk evaluation of ccRCC.

RESULTS

We identified 2261 DMRs in the promoter region. After DMR selection, 578 candidates were screened, and was correspondence with 408 CpG dinucleotides in the 450 K array. We collected the DNAm profiles of 478 ccRCC samples from TCGA dataset. Using the training set with 319 samples, a prognostic panel of 18 CpGs was determined by univariate Cox regression, LASSO regression, and multivariate Cox proportional hazards regression analyses. We constructed a prognostic model by combining the clinical signatures. In the test set (159 samples) and whole set (478 samples), the Kaplan-Meier plot showed significant differences; and the ROC curve and survival analyses showed AUC greater than 0.7. The Nomogram integrated with clinicopathological characters and methylation risk score had better performance, and the decision curve analyses also showed a beneficial effect.

CONCLUSIONS

This work provides insight into the role of hypermethylation in ccRCC. The targets identified might serve as biomarkers for early ccRCC diagnosis and prognosis biomarkers for ccRCC. We believe our findings have implications for better risk stratification and personalized management of this disease.

Targeting the ADPKD methylome using nanoparticle-mediated combination therapy

DNA methylation aberrancies are found in autosomal dominant polycystic kidney disease (ADPKD), which suggests the methylome to be a promising therapeutic target. However, the impact of combining DNA methylation inhibitors (DNMTi) and ADPKD drugs in treating ADPKD and on disease-associated methylation patterns has not been fully explored. To test this, ADPKD drugs, metformin and tolvaptan (MT), were delivered in combination with DNMTi 5-aza-2'-deoxycytidine (Aza) to 2D or 3D cystic Pkd1 heterozygous renal epithelial cells (PKD1-Het cells) as free drugs or within nanoparticles to enable direct delivery for future in vivo applications. We found Aza synergizes with MT to reduce cell viability and cystic growth. Reduced representation bisulfite sequencing (RRBS) was performed across four groups: PBS, Free-Aza (Aza), Free-Aza+MT (F-MTAza), and Nanoparticle-Aza+MT (NP-MTAza). Global methylation patterns showed that while Aza alone induces a unimodal intermediate methylation landscape, Aza+MT recovers the bimodality reminiscent of somatic methylomes. Importantly, site-specific methylation changes associated with F-MTAza and NP-MTAza were largely conserved including hypomethylation at ADPKD-associated genes. Notably, we report hypomethylation of cancer-associated genes implicated in ADPKD pathogenesis as well as new target genes that may provide additional therapeutic effects. Overall, this study motivates future work to further elucidate the regulatory mechanisms of observed drug synergy and apply these combination therapies in vivo.

Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species

Methylation of cytosines is a prototypic epigenetic modification of the DNA. It has been implicated in various regulatory mechanisms across the animal kingdom and particularly in vertebrates. We mapped DNA methylation in 580 animal species (535 vertebrates, 45 invertebrates), resulting in 2443 genome-scale DNA methylation profiles of multiple organs. Bioinformatic analysis of this large dataset quantified the association of DNA methylation with the underlying genomic DNA sequence throughout vertebrate evolution. We observed a broadly conserved link with two major transitions-once in the first vertebrates and again with the emergence of reptiles. Cross-species comparisons focusing on individual organs supported a deeply conserved association of DNA methylation with tissue type, and cross-mapping analysis of DNA methylation at gene promoters revealed evolutionary changes for orthologous genes. In summary, this study establishes a large resource of vertebrate and invertebrate DNA methylomes, it showcases the power of reference-free epigenome analysis in species for which no reference genomes are available, and it contributes an epigenetic perspective to the study of vertebrate evolution.

A Guide to MethylationToActivity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors

Genome-wide DNA methylomes have contributed greatly to tumor detection and subclassification. However, interpreting the biological impact of the DNA methylome at the individual gene level remains a challenge. MethylationToActivity (M2A) is a pipeline that uses convolutional neural networks to infer H3K4me3 and H3K27ac enrichment from DNA methylomes and thus infer promoter activity. It was shown to be highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers. The following will present a user-friendly guide through the model pipeline.

A Cautionary Tale of Sexing by Methylation: Hybrid Bisulfite-Conversion Sequencing of Immunoprecipitated Methylated DNA in Chrysemys picta Turtles with Temperature-Dependent Sex Determination Reveals Contrasting Patterns of Somatic and Gonadal Methylation, but No Unobtrusive Sex Diagnostic

Background: The gonads of Chrysemys picta, a turtle with temperature-dependent sex determination (TSD), exhibit differential DNA methylation between males and females, but whether the same is true in somatic tissues remains unknown. Such differential DNA methylation in the soma would provide a non-lethal sex diagnostic for TSD turtle hatchings who lack visually detectable sexual dimorphism when young. Methods: Here, we tested multiple approaches to study DNA methylation in tail clips of Chrysemys picta hatchlings, to identify differentially methylated candidate regions/sites that could serve as molecular sex markers To detect global differential methylation in the tails we used methylation-sensitive ELISA, and to test for differential local methylation we developed a novel hybrid method by sequencing immunoprecipitated and bisulfite converted DNA (MeDIP-BS-seq) followed by PCR validation of candidate regions/sites after digestion with a methylation-sensitive restriction enzyme. Results: We detected no global differences in methylation between males and females via ELISA. While we detected inter-individual variation in DNA methylation in the tails, this variation was not sexually dimorphic, in contrast with hatchling gonads. Conclusions: Results highlight that differential DNA methylation is tissue-specific and plays a key role in gonadal formation (primary sexual development) and maintenance post-hatching, but not in the somatic tail tissue.

Isogenic Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes Reveal Activation of Wnt Signaling Pathways Underlying Intrinsic Cardiac Abnormalities in Rett Syndrome

Rett syndrome (RTT) is a severe neurodevelopmental disorder caused by MeCP2 mutations. Nonetheless, the pathophysiological roles of MeCP2 mutations in the etiology of intrinsic cardiac abnormality and sudden death remain unclear. In this study, we performed a detailed functional studies (calcium and electrophysiological analysis) and RNA-sequencing-based transcriptome analysis of a pair of isogenic RTT female patient-specific induced pluripotent stem-cell-derived cardiomyocytes (iPSC-CMs) that expressed either MeCP2^wildtype or MeCP2^mutant allele and iPSC-CMs from a non-affected female control. The observations were further confirmed by additional experiments, including Wnt signaling inhibitor treatment, siRNA-based gene silencing, and ion channel blockade. Compared with MeCP2^wildtype and control iPSC-CMs, MeCP2^mutant iPSC-CMs exhibited prolonged action potential and increased frequency of spontaneous early after polarization. RNA sequencing analysis revealed up-regulation of various Wnt family genes in MeCP2^mutant iPSC-CMs. Treatment of MeCP2^mutant iPSC-CMs with a Wnt inhibitor XAV939 significantly decreased the β-catenin protein level and CACN1AC expression and ameliorated their abnormal electrophysiological properties. In summary, our data provide novel insight into the contribution of activation of the Wnt/β-catenin signaling cascade to the cardiac abnormalities associated with MeCP2 mutations in RTT.

An evaluation of the genome-wide false positive rates of common methods for identifying differentially methylated regions using illumina methylation arrays

Differentially methylated regions (DMRs) are genomic regions with specific methylation patterns across multiple loci that are associated with a phenotype. We examined the genome-wide false positive (GFP) rates of five widely used DMR methods: comb-p, Bumphunter, DMRcate, mCSEA and coMethDMR using both Illumina HumanMethylation450 (450 K) and MethylationEPIC (EPIC) data and simulated continuous and dichotomous null phenotypes (i.e., generated independently of methylation data). coMethDMR provided well-controlled GFP rates (~5%) except when analysing skewed continuous phenotypes. DMRcate generally had well-controlled GFP rates when applied to 450 K data except for the skewed continuous phenotype and EPIC data only for the normally distributed continuous phenotype. GFP rates for mCSEA were at least 0.096 and comb-p yielded GFP rates above 0.34. Bumphunter had high GFP rates of at least 0.35 across conditions, reaching as high as 0.95. Analysis of the performance of these methods in specific regions of the genome found that regions with higher correlation across loci had higher regional false positive rates on average across methods. Based on the false positive rates, coMethDMR is the most recommended analysis method, and DMRcate had acceptable performance when analysing 450 K data. However, as both could display higher levels of FPs for skewed continuous distributions, a normalizing transformation of skewed continuous phenotypes is suggested. This study highlights the importance of genome-wide simulations when evaluating the performance of DMR-analysis methods.

Comparison and imputation-aided integration of five commercial platforms for targeted DNA methylome analysis

Targeted bisulfite sequencing (TBS) has become the method of choice for the cost-effective, targeted analysis of the human methylome at base-pair resolution. In this study, we benchmarked five commercially available TBS platforms-three hybridization capture-based (Agilent, Roche and Illumina) and two reduced-representation-based (Diagenode and NuGen)-across 11 samples. Two samples were also compared with whole-genome DNA methylation sequencing with the Illumina and Oxford Nanopore platforms. We assessed workflow complexity, on/off-target performance, coverage, accuracy and reproducibility. Although all platforms produced robust and reproducible data, major differences in the number and identity of the CpG sites covered make it difficult to compare datasets generated on different platforms. To overcome this limitation, we applied imputation and show that it improves interoperability from an average of 10.35% (0.8 million) to 97% (7.6 million) common CpG sites. Our study provides guidance on which TBS platform to use for different methylome features and offers an imputation-based harmonization solution that allows comparative, integrative analysis.

DNA methylation and expression profiles of placenta and umbilical cord blood reveal the characteristics of gestational diabetes mellitus patients and offspring

BACKGROUND

Gestational diabetes mellitus (GDM) is a common pregnancy-specific disease and is growing at an alarming rate worldwide, which can negatively affect the health of pregnant women and fetuses. However, most studies are limited to one tissue, placenta or umbilical cord blood, usually with one omics assay. It is thus difficult to systematically reveal the molecular mechanism of GDM and the key influencing factors on pregnant women and offspring.

RESULTS

We recruited a group of 21 pregnant women with GDM and 20 controls without GDM. For each pregnant woman, reduced representation bisulfite sequencing and RNA-seq were performed using the placenta and paired neonatal umbilical cord blood specimens. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were identified with body mass index as a covariate. Through the comparison of GDM and control samples, 2779 and 141 DMRs, 1442 and 488 DEGs were identified from placenta and umbilical cord blood, respectively. Functional enrichment analysis showed that the placenta methylation and expression profiles of GDM women mirrored the molecular characteristics of "type II diabetes" and "insulin resistance." Methylation-altered genes in umbilical cord blood were associated with pathways "type II diabetes" and "cholesterol metabolism." Remarkably, both DMRs and DEGs illustrated significant overlaps among placenta and umbilical cord blood samples. The overlapping DMRs were associated with "cholesterol metabolism." The top-ranking pathways enriched in the shared DEGs include "growth hormone synthesis, secretion and action" and "type II diabetes mellitus."

CONCLUSIONS

Our research demonstrated the epigenetic and transcriptomic alternations of GDM women and offspring. Our findings emphasized the importance of epigenetic modifications in the communication between pregnant women with GDM and offspring, and provided a reference for the prevention, control, treatment, and intervention of perinatal deleterious events of GDM and neonatal complications.

Genome-wide DNA methylation patterns reveal clinically relevant predictive and prognostic subtypes in human osteosarcoma

Aberrant methylation of genomic DNA has been reported in many cancers. Specific DNA methylation patterns have been shown to provide clinically useful prognostic information and define molecular disease subtypes with different response to therapy and long-term outcome. Osteosarcoma is an aggressive malignancy for which approximately half of tumors recur following standard combined surgical resection and chemotherapy. No accepted prognostic factor save tumor necrosis in response to adjuvant therapy currently exists, and traditional genomic studies have thus far failed to identify meaningful clinical associations. We studied the genome-wide methylation state of primary tumors and tested how they predict patient outcomes. We discovered relative genomic hypomethylation to be strongly predictive of response to standard chemotherapy. Recurrence and survival were also associated with genomic methylation, but through more site-specific patterns. Furthermore, the methylation patterns were reproducible in three small independent clinical datasets. Downstream transcriptional, in vitro, and pharmacogenomic analysis provides insight into the clinical translation of the methylation patterns. Our findings suggest the assessment of genomic methylation may represent a strategy for stratifying patients for the application of alternative therapies.

Genome-Wide DNA Methylation Protocol for Epigenetics Studies

Epigenetic modification are heritable changes in gene expression not encoded by the DNA sequence therefore playing a significant role in a broad range of biological processes and diseases.A key player of the epigenetic modifications is the DNA methylation, a process involving the covalent transfer of a methyl group to the C-5 position of the cytosine ring of DNA forming 5-methylcytosine (5mC), catalyzed by DNA methyltransferases. Altering the structure of the chromatin, DNA methylation has the potential to down-regulate gene expression.The here presented protocol shows a method to obtain DNA samples ready for NGS sequencing for genome-wide methylation analysis.

Dietary omega-3 fatty acid intake impacts peripheral blood DNA methylation -anti-inflammatory effects and individual variability in a pilot study

Omega-3 or n-3 polyunsaturated fatty acids (PUFAs) are widely studied for health benefits that may relate to anti-inflammatory activity. However, mechanisms mediating an anti-inflammatory response to n-3 PUFA intake are not fully understood. Of interest is the emerging role of fatty acids to impact DNA methylation (DNAm) and thereby modulate mediating inflammatory processes. In this pilot study, we investigated the impact of n-3 PUFA intake on DNAm in inflammation-related signaling pathways in peripheral blood mononuclear cells (PBMCs) of women at high risk of breast cancer. PBMCs of women at high risk of breast cancer (n=10) were obtained at baseline and after 6 months of n-3 PUFA (5 g/d EPA+DHA dose arm) intake in a previously reported dose finding trial. DNA methylation of PBMCs was assayed by reduced representation bisulfite sequencing (RRBS) to obtain genome-wide methylation profiles at the single nucleotide level. We examined the impact of n-3 PUFA on genome-wide DNAm and focused upon a set of candidate genes associated with inflammation signaling pathways and breast cancer. We identified 24,842 differentially methylated CpGs (DMCs) in gene promoters of 5507 genes showing significant enrichment for hypermethylation in both the candidate gene and genome-wide analyses. Pathway analysis identified significantly hypermethylated signaling networks after n-3 PUFA treatment, such as the Toll-like Receptor inflammatory pathway. The DNAm pattern in individuals and the response to n-3 PUFA intake are heterogeneous. PBMC DNAm profiling suggests a mechanism whereby n-3 PUFAs may impact inflammatory cascades associated with disease processes including carcinogenesis.

Childhood adversity correlates with stable changes in DNA methylation trajectories in children and converges with epigenetic signatures of prenatal stress

Childhood maltreatment (CM) is an established major risk factor for a number of negative health outcomes later in life. While epigenetic mechanisms, such as DNA methylation (DNAm), have been proposed as a means of embedding this environmental risk factor, little is known about its timing and trajectory, especially in very young children. It is also not clear whether additional environmental adversities, often experienced by these children, converge on similar DNAm changes. Here, we calculated a cumulative adversity score, which additionally to CM includes socioeconomic status (SES), other life events, parental psychopathology and epigenetic biomarkers of prenatal smoking and alcohol consumption. We investigated the effects of CM alone as well as the adversity score on longitudinal DNAm trajectories in the Berlin Longitudinal Child Study. This is a cohort of 173 children aged 3-5 years at baseline of whom 86 were exposed to CM. These children were followed-up for 2 years with extensive psychometric and biological assessments as well as saliva collection at 5 time points providing genome-wide DNAm levels. Overall, only a few DNAm patterns were stable over this timeframe, but less than 10 DNAm regions showed significant changes. At baseline, neither CM nor the adversity score associated with DNAm changes. However, in 6 differentially methylated regions (DMRs), CM and the adversity score significantly moderated DNAm trajectories over time. A number of these DMRs have previously been associated with adverse prenatal exposures. In our study, children exposed to CM also presented with epigenetic signatures indicative of increased prenatal exposure to tobacco and alcohol, as compared to non-CM exposed children. These epigenetic signatures of prenatal exposure strongly correlate with DNAm regions associated with CM and the adversity score. Finally, weighted correlation network analysis revealed a module of CpGs exclusively associated with CM. While our study identifies DNAm loci specifically associated with CM, especially within long non-coding RNAs, the majority of associations were found with the adversity score with convergent association with indicators of adverse prenatal exposures. This study highlights the importance of mapping not only of the epigenome but also the exposome and extending the observational timeframe to well before birth.

Integration of Epigenetic Mechanisms into Non-Genotoxic Carcinogenicity Hazard Assessment: Focus on DNA Methylation and Histone Modifications

Epigenetics involves a series of mechanisms that entail histone and DNA covalent modifications and non-coding RNAs, and that collectively contribute to programing cell functions and differentiation. Epigenetic anomalies and DNA mutations are co-drivers of cellular dysfunctions, including carcinogenesis. Alterations of the epigenetic system occur in cancers whether the initial carcinogenic events are from genotoxic (GTxC) or non-genotoxic (NGTxC) carcinogens. NGTxC are not inherently DNA reactive, they do not have a unifying mode of action and as yet there are no regulatory test guidelines addressing mechanisms of NGTxC. To fil this gap, the Test Guideline Programme of the Organisation for Economic Cooperation and Development is developing a framework for an integrated approach for the testing and assessment (IATA) of NGTxC and is considering assays that address key events of cancer hallmarks. Here, with the intent of better understanding the applicability of epigenetic assays in chemical carcinogenicity assessment, we focus on DNA methylation and histone modifications and review: (1) epigenetic mechanisms contributing to carcinogenesis, (2) epigenetic mechanisms altered following exposure to arsenic, nickel, or phenobarbital in order to identify common carcinogen-specific mechanisms, (3) characteristics of a series of epigenetic assay types, and (4) epigenetic assay validation needs in the context of chemical hazard assessment. As a key component of numerous NGTxC mechanisms of action, epigenetic assays included in IATA assay combinations can contribute to improved chemical carcinogen identification for the better protection of public health.

A panel of DNA methylation markers for the classification of consensus molecular subtypes 2 and 3 in patients with colorectal cancer

Consensus molecular subtypes (CMSs) can guide precision treatment of colorectal cancer (CRC). We aim to identify methylation markers to distinguish between CMS2 and CMS3 in patients with CRC, for which an easy test is currently lacking. To this aim, fresh‐frozen tumor tissue of 239 patients with stage I‐III CRC was analyzed. Methylation profiles were obtained using the Infinium HumanMethylation450 BeadChip. We performed adaptive group‐regularized logistic ridge regression with post hoc group‐weighted elastic net marker selection to build prediction models for classification of CMS2 and CMS3. The Cancer Genome Atlas (TCGA) data were used for validation. Group regularization of the probes was done based on their location either relative to a CpG island or relative to a gene present in the CMS classifier, resulting in two different prediction models and subsequently different marker panels. For both panels, even when using only five markers, accuracies were > 90% in our cohort and in the TCGA validation set. Our methylation marker panel accurately distinguishes between CMS2 and CMS3. This enables development of a targeted assay to provide a robust and clinically relevant classification tool for CRC patients.

DNA methylation QTL analysis identifies new regulators of human longevity

Human longevity is a complex trait influenced by both genetic and environmental factors, whose interaction is mediated by epigenetic mechanisms like DNA methylation. Here, we generated genome-wide whole-blood methylome data from 267 individuals, of which 71 were long-lived (90–104 years), by applying reduced representation bisulfite sequencing. We followed a stringent two-stage analysis procedure using discovery and replication samples to detect differentially methylated sites (DMSs) between young and long-lived study participants. Additionally, we performed a DNA methylation quantitative trait loci analysis to identify DMSs that underlie the longevity phenotype. We combined the DMSs results with gene expression data as an indicator of functional relevance. This approach yielded 21 new candidate genes, the majority of which are involved in neurophysiological processes or cancer. Notably, two candidates (PVRL2, ERCC1) are located on chromosome 19q, in close proximity to the well-known longevity- and Alzheimer’s disease-associated loci APOE and TOMM40. We propose this region as a longevity hub, operating on both a genetic (APOE, TOMM40) and an epigenetic (PVRL2, ERCC1) level. We hypothesize that the heritable methylation and associated gene expression changes reported here are overall advantageous for the LLI and may prevent/postpone age-related diseases and facilitate survival into very old age.

DNA methylation analysis reveals epimutation hotspots in patients with dilated cardiomyopathy-associated laminopathies

BACKGROUND

Mutations in LMNA, encoding lamin A/C, lead to a variety of diseases known as laminopathies including dilated cardiomyopathy (DCM) and skeletal abnormalities. Though previous studies have investigated the dysregulation of gene expression in cells from patients with DCM, the role of epigenetic (gene regulatory) mechanisms, such as DNA methylation, has not been thoroughly investigated. Furthermore, the impact of family-specific LMNA mutations on DNA methylation is unknown. Here, we performed reduced representation bisulfite sequencing on ten pairs of fibroblasts and their induced pluripotent stem cell (iPSC) derivatives from two families with DCM due to distinct LMNA mutations, one of which also induces brachydactyly.

RESULTS

Family-specific differentially methylated regions (DMRs) were identified by comparing the DNA methylation landscape of patient and control samples. Fibroblast DMRs were found to enrich for distal regulatory features and transcriptionally repressed chromatin and to associate with genes related to phenotypes found in tissues affected by laminopathies. These DMRs, in combination with transcriptome-wide expression data and lamina-associated domain (LAD) organization, revealed the presence of inter-family epimutation hotspots near differentially expressed genes, most of which were located outside LADs redistributed in LMNA-related DCM. Comparison of DMRs found in fibroblasts and iPSCs identified regions where epimutations were persistent across both cell types. Finally, a network of aberrantly methylated disease-associated genes revealed a potential molecular link between pathways involved in bone and heart development.

CONCLUSIONS

Our results identified both shared and mutation-specific laminopathy epimutation landscapes that were consistent with lamin A/C mutation-mediated epigenetic aberrancies that arose in somatic and early developmental cell stages.

Characterizing the properties of bisulfite sequencing data: maximizing power and sensitivity to identify between-group differences in DNA methylation

BACKGROUND

The combination of sodium bisulfite treatment with highly-parallel sequencing is a common method for quantifying DNA methylation across the genome. The power to detect between-group differences in DNA methylation using bisulfite-sequencing approaches is influenced by both experimental (e.g. read depth, missing data and sample size) and biological (e.g. mean level of DNA methylation and difference between groups) parameters. There is, however, no consensus about the optimal thresholds for filtering bisulfite sequencing data with implications for the reproducibility of findings in epigenetic epidemiology.

RESULTS

We used a large reduced representation bisulfite sequencing (RRBS) dataset to assess the distribution of read depth across DNA methylation sites and the extent of missing data. To investigate how various study variables influence power to identify DNA methylation differences between groups, we developed a framework for simulating bisulfite sequencing data. As expected, sequencing read depth, group size, and the magnitude of DNA methylation difference between groups all impacted upon statistical power. The influence on power was not dependent on one specific parameter, but reflected the combination of study-specific variables. As a resource to the community, we have developed a tool, POWEREDBiSeq, which utilizes our simulation framework to predict study-specific power for the identification of DNAm differences between groups, taking into account user-defined read depth filtering parameters and the minimum sample size per group.

CONCLUSIONS

Our data-driven approach highlights the importance of filtering bisulfite-sequencing data by minimum read depth and illustrates how the choice of threshold is influenced by the specific study design and the expected differences between groups being compared. The POWEREDBiSeq tool, which can be applied to different types of bisulfite sequencing data (e.g. RRBS, whole genome bisulfite sequencing (WGBS), targeted bisulfite sequencing and amplicon-based bisulfite sequencing), can help users identify the level of data filtering needed to optimize power and aims to improve the reproducibility of bisulfite sequencing studies.

An integrated epigenomic-transcriptomic landscape of lung cancer reveals novel methylation driver genes of diagnostic and therapeutic relevance

Background: Aberrant DNA methylation occurs commonly during carcinogenesis and is of clinical value in human cancers. However, knowledge of the impact of DNA methylation changes on lung carcinogenesis and progression remains limited.

Methods: Genome-wide DNA methylation profiles were surveyed in 18 pairs of tumors and adjacent normal tissues from non-small cell lung cancer (NSCLC) patients using Reduced Representation Bisulfite Sequencing (RRBS). An integrated epigenomic-transcriptomic landscape of lung cancer was depicted using the multi-omics data integration method.

Results: We discovered a large number of hypermethylation events pre-marked by poised promoter in embryonic stem cells, being a hallmark of lung cancer. These hypermethylation events showed a high conservation across cancer types. Eight novel driver genes with aberrant methylation (e.g., PCDH17 and IRX1) were identified by integrated analysis of DNA methylome and transcriptome data. Methylation level of the eight genes measured by pyrosequencing can distinguish NSCLC patients from lung tissues with high sensitivity and specificity in an independent cohort. Their tumor-suppressive roles were further experimentally validated in lung cancer cells, which depend on promoter hypermethylation. Similarly, 13 methylation-driven ncRNAs (including 8 lncRNAs and 5 miRNAs) were identified, some of which were co-regulated with their host genes by the same promoter hypermethylation. Finally, by analyzing the transcription factor (TF) binding motifs, we uncovered sets of TFs driving the expression of epigenetically regulated genes and highlighted the epigenetic regulation of gene expression of TCF21 through DNA methylation of EGR1 binding motifs.

Conclusions: We discovered several novel methylation driver genes of diagnostic and therapeutic relevance in lung cancer. Our findings revealed that DNA methylation in TF binding motifs regulates target gene expression by affecting the binding ability of TFs. Our study also provides a valuable epigenetic resource for identifying DNA methylation-based diagnostic biomarkers, developing cancer drugs for epigenetic therapy and studying cancer pathogenesis.

DNA hypomethylating agents increase activation and cytolytic activity of CD8+ T cells

We demonstrate that DNA hypomethylating agent (HMA) treatment can directly modulate the anti-tumor response and effector function of CD8⁺ T cells. In vivo HMA treatment promotes CD8⁺ T cell tumor infiltration and suppresses tumor growth via CD8⁺ T cell-dependent activity. Ex vivo, HMAs enhance primary human CD8⁺ T cell activation markers, effector cytokine production, and anti-tumor cytolytic activity. Epigenomic and transcriptomic profiling shows that HMAs vastly regulate T cell activation-related transcriptional networks, culminating with over-activation of NFATc1 short isoforms. Mechanistically, demethylation of an intragenic CpG island immediately downstream to the 3' UTR of the short isoform was associated with antisense transcription and alternative polyadenylation of NFATc1 short isoforms. High-dimensional single-cell mass cytometry analyses reveal a selective effect of HMAs on a subset of human CD8⁺ T cell subpopulations, increasing both the number and abundance of a granzyme B^high, perforin^high effector subpopulation. Overall, our findings support the use of HMAs as a therapeutic strategy to boost anti-tumor immune response.

Differential DNA Methylation Landscape in Skin Fibroblasts from African Americans with Systemic Sclerosis

The etiology and reasons underlying the ethnic disparities in systemic sclerosis (SSc) remain unknown. African Americans are disproportionally affected by SSc and yet are underrepresented in research. The aim of this study was to comprehensively investigate the association of DNA methylation levels with SSc in dermal fibroblasts from patients of African ancestry. Reduced representation bisulfite sequencing (RRBS) was performed on primary dermal fibroblasts from 15 SSc patients and 15 controls of African ancestry, and over 3.8 million CpG sites were tested for differential methylation patterns between cases and controls. The dermal fibroblasts from African American patients exhibited widespread reduced DNA methylation. Differentially methylated CpG sites were most enriched in introns and intergenic regions while depleted in 5' UTR, promoters, and CpG islands. Seventeen genes and eleven promoters showed significant differential methylation, mostly in non-coding RNA genes and pseudogenes. Gene set enrichment analysis (GSEA) and gene ontology (GO) analyses revealed an enrichment of pathways related to interferon signaling and mesenchymal differentiation. The hypomethylation of DLX5 and TMEM140 was accompanied by these genes' overexpression in patients but underexpression for lncRNA MGC12916. These data show that differential methylation occurs in dermal fibroblasts from African American patients with SSc and identifies novel coding and non-coding genes.

MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors

Although genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities based on H3K4me3 and H3K27ac enrichment, from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

Flanking sequence preference modulates de novo DNA methylation in the mouse genome

Mammalian de novo DNA methyltransferases (DNMT) are responsible for the establishment of cell-type-specific DNA methylation in healthy and diseased tissues. Through genome-wide analysis of de novo methylation activity in murine stem cells we uncover that DNMT3A prefers to methylate CpGs followed by cytosines or thymines, while DNMT3B predominantly methylates CpGs followed by guanines or adenines. These signatures are further observed at non-CpG sites, resembling methylation context observed in specialised cell types, including neurons and oocytes. We further show that these preferences result from structural differences in the catalytic domains of the two de novo DNMTs and are not a consequence of differential recruitment to the genome. Molecular dynamics simulations suggest that, in case of human DNMT3A, the preference is due to favourable polar interactions between the flexible Arg836 side chain and the guanine that base-pairs with the cytosine following the CpG. By exchanging arginine to a lysine, the corresponding side chain in DNMT3B, the sequence preference is reversed, confirming the requirement for arginine at this position. This context-dependent enzymatic activity provides additional insights into the complex regulation of DNA methylation patterns.

Changes in DNA methylation profiles of myalgic encephalomyelitis/chronic fatigue syndrome patients reflect systemic dysfunctions

BACKGROUND

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a lifelong debilitating disease with a complex pathology not yet clearly defined. Susceptibility to ME/CFS involves genetic predisposition and exposure to environmental factors, suggesting an epigenetic association. Epigenetic studies with other ME/CFS cohorts have used array-based technology to identify differentially methylated individual sites. Changes in RNA quantities and protein abundance have been documented in our previous investigations with the same ME/CFS cohort used for this study.

RESULTS

DNA from a well-characterised New Zealand cohort of 10 ME/CFS patients and 10 age-/sex-matched healthy controls was isolated from peripheral blood mononuclear (PBMC) cells, and used to generate reduced genome-scale DNA methylation maps using reduced representation bisulphite sequencing (RRBS). The sequencing data were analysed utilising the DMAP analysis pipeline to identify differentially methylated fragments, and the MethylKit pipeline was used to quantify methylation differences at individual CpG sites. DMAP identified 76 differentially methylated fragments and Methylkit identified 394 differentially methylated cytosines that included both hyper- and hypo-methylation. Four clusters were identified where differentially methylated DNA fragments overlapped with or were within close proximity to multiple differentially methylated individual cytosines. These clusters identified regulatory regions for 17 protein encoding genes related to metabolic and immune activity. Analysis of differentially methylated gene bodies (exons/introns) identified 122 unique genes. Comparison with other studies on PBMCs from ME/CFS patients and controls with array technology showed 59% of the genes identified in this study were also found in one or more of these studies. Functional pathway enrichment analysis identified 30 associated pathways. These included immune, metabolic and neurological-related functions differentially regulated in ME/CFS patients compared to the matched healthy controls.

CONCLUSIONS

Major differences were identified in the DNA methylation patterns of ME/CFS patients that clearly distinguished them from the healthy controls. Over half found in gene bodies with RRBS in this study had been identified in other ME/CFS studies using the same cells but with array technology. Within the enriched functional immune, metabolic and neurological pathways, a number of enriched neurotransmitter and neuropeptide reactome pathways highlighted a disturbed neurological pathophysiology within the patient group.

A comprehensive evaluation of computational tools to identify differential methylation regions using RRBS data

DNA methylation plays a vital role in transcription regulation. Reduced representation bisulfite sequencing (RRBS) is becoming common for analyzing genome-wide methylation profiles at the single nucleotide level. A major goal of RRBS studies is to detect differentially methylated regions (DMRs) between different biological conditions. The previous tools to predict DMRs lack consistency. Here, we simulated RRBS datasets with significant attributes of real sequencing data under a wide range of scenarios, and systematically evaluated seven DMR detection tools in terms of type I error rate, precision/recall (PR), and area under ROC curve (AUC) using different methylation levels, sequencing coverage depth, length of DMRs, read length, and sample sizes. DMRfinder, methylSig, and methylKit were our preferred tools for RRBS data analysis, in terms of their AUC and PR curves. Our comparison highlights the different applicability of DMR detection tools and provides information to guide researchers towards the advancement of sequence-based DMR analysis.

Non-invasive early detection of cancer four years before conventional diagnosis using a blood test

Early detection has the potential to reduce cancer mortality, but an effective screening test must demonstrate asymptomatic cancer detection years before conventional diagnosis in a longitudinal study. In the Taizhou Longitudinal Study (TZL), 123,115 healthy subjects provided plasma samples for long-term storage and were then monitored for cancer occurrence. Here we report the preliminary results of PanSeer, a noninvasive blood test based on circulating tumor DNA methylation, on TZL plasma samples from 605 asymptomatic individuals, 191 of whom were later diagnosed with stomach, esophageal, colorectal, lung or liver cancer within four years of blood draw. We also assay plasma samples from an additional 223 cancer patients, plus 200 primary tumor and normal tissues. We show that PanSeer detects five common types of cancer in 88% (95% CI: 80-93%) of post-diagnosis patients with a specificity of 96% (95% CI: 93-98%), We also demonstrate that PanSeer detects cancer in 95% (95% CI: 89-98%) of asymptomatic individuals who were later diagnosed, though future longitudinal studies are required to confirm this result. These results demonstrate that cancer can be non-invasively detected up to four years before current standard of care.

Epigenetic Modifications in T Cells: The Role of DNA Methylation in Salt-Sensitive Hypertension

The SS (Dahl salt sensitive) rat is an established model of hypertension and renal damage that is accompanied with immune system activation in response to a high-salt diet. Investigations into the effects of sodium-independent and dependent components of the diet were shown to affect the disease phenotype with SS/MCW (JrHsdMcwi) rats maintained on a purified diet (AIN-76A) presenting with a more severe phenotype relative to grain-fed SS/CRL (JrHsdMcwiCrl) rats. Since contributions of the immune system, environment, and diet are documented to alter this phenotype, this present study examined the epigenetic profile of T cells isolated from the periphery and the kidney from these colonies. T cells isolated from kidneys of the 2 colonies revealed that transcriptomic and functional differences may contribute to the susceptibility of hypertension and renal damage. In response to high-salt challenge, the methylome of T cells isolated from the kidney of SS/MCW exhibit a significant increase in differentially methylated regions with a preference for hypermethylation compared with the SS/CRL kidney T cells. Circulating T cells exhibited similar methylation profiles between colonies. Utilizing transcriptomic data from T cells isolated from the same animals upon which the DNA methylation analysis was performed, a predominant negative correlation was observed between gene expression and DNA methylation in all groups. Lastly, inhibition of DNA methyltransferases blunted salt-induced hypertension and renal damage in the SS/MCW rats providing a functional role for methylation. This study demonstrated the influence of epigenetic modifications to immune cell function, highlighting the need for further investigations.

Genome-wide DNA methylation data from adult brain following prenatal immune activation and dietary intervention

DNA methylation is a dynamic epigenetic mark regulating gene function and are implicated in the pathophysiology of schizophrenia and autism. Environmental exposures such as inflammation and diet modify the epigenome and may explain why prenatal exposure to inflammation increase risk of neurodevelopmental disorders. This manuscript presents genome-wide DNA methylation data (GSE102942) generated from adult offspring brain prenatally exposed to Maternal Immune Activation (MIA). Methylome of the adult brain supplemented with omega-3 polyunsaturated fatty acids (PUFA) is also described. DNA methylation across gene regulatory regions were measured using MSP-I digestion and Reduced Representation Bisulfite Sequencing (RRBS) method.

Persistent changes in liver methylation and microbiome composition following reversal of diet-induced non-alcoholic-fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a metabolic liver disease that is thought to be reversible by changing the diet. To examine the impact of dietary changes on progression and cure of NAFLD, we fed mice a high-fat diet (HFD) or high-fructose diet (HFrD) for 9 weeks, followed by an additional 9 weeks, where mice were given normal chow diet. As predicted, the diet-induced NAFLD elicited changes in glucose tolerance, serum cholesterol, and triglyceride levels in both diet groups. Moreover, the diet-induced NAFLD phenotype was reversed, as measured by the recovery of glucose intolerance and high cholesterol levels when mice were given normal chow diet. However, surprisingly, the elevated serum triglyceride levels persisted. Metagenomic analysis revealed dietary-induced changes of microbiome composition, some of which remained altered even after reversing the diet to normal chow, as illustrated by species of the Odoribacter genus. Genome-wide DNA methylation analysis revealed a "priming effect" through changes in DNA methylation in key liver genes. For example, the lipid-regulating gene Apoa4 remained hypomethylated in both groups even after introduction to normal chow diet. Our results support that dietary change, in part, reverses the NAFLD phenotype. However, some diet-induced effects remain, such as changes in microbiome composition, elevated serum triglyceride levels, and hypomethylation of key liver genes. While the results are correlative in nature, it is tempting to speculate that the dietary-induced changes in microbiome composition may in part contribute to the persistent epigenetic modifications in the liver.

Contribution of DNA methylation in chronic stress-induced cardiac remodeling and arrhythmias in mice

It is recognized that stress can induce cardiac dysfunction, but the underlying mechanisms are not well understood. The present study aimed to test the hypothesis that chronic negative stress leads to alterations in DNA methylation of certain cardiac genes, which in turn contribute to pathologic remodeling of the heart. We found that mice that were exposed to chronic restraint stress (CRS) for 4 wk exhibited cardiac remodeling toward heart failure, as characterized by ventricular chamber dilatation, wall thinning, and decreased contractility. CRS also induced cardiac arrhythmias, including intermittent sinus tachycardia and bradycardia, frequent premature ventricular contraction, and sporadic atrioventricular conduction block. Circulating levels of stress hormones were elevated, and the cardiac expression of tyrosine hydroxylase, a marker of sympathetic innervation, was increased in CRS mice. Using reduced representation bisulfite sequencing, we found that although CRS did not lead to global changes in DNA methylation in the murine heart, it nevertheless altered methylation at specific genes that are associated with the dilated cardiomyopathy (DCM) (e.g., desmin) and adrenergic signaling of cardiomyocytes (ASPC) (e.g., adrenergic receptor-α1) pathways. We conclude that CRS induces cardiac remodeling and arrhythmias, potentially through altered methylation of myocardial genes associated with the DCM and ASPC pathways.-Zhang, P., Li, T., Liu, Y.-Q., Zhang, H., Xue, S.-M., Li, G., Cheng, H.-Y.M., Cao, J.-M. Contribution of DNA methylation in chronic stress-induced cardiac remodeling and arrhythmias in mice.

The Intricate Interplay between Epigenetic Events, Alternative Splicing and Noncoding RNA Deregulation in Colorectal Cancer

Colorectal cancer (CRC) results from a transformation of colonic epithelial cells into adenocarcinoma cells due to genetic and epigenetic instabilities, alongside remodelling of the surrounding stromal tumour microenvironment. Epithelial-specific epigenetic variations escorting this process include chromatin remodelling, histone modifications and aberrant DNA methylation, which influence gene expression, alternative splicing and function of non-coding RNA. In this review, we first highlight epigenetic modulators, modifiers and mediators in CRC, then we elaborate on causes and consequences of epigenetic alterations in CRC pathogenesis alongside an appraisal of the complex feedback mechanisms realized through alternative splicing and non-coding RNA regulation. An emphasis in our review is put on how this intricate network of epigenetic and post-transcriptional gene regulation evolves during the initiation, progression and metastasis formation in CRC.

Methylation analysis of plasma DNA informs etiologies of Epstein-Barr virus-associated diseases

Epstein-Barr virus (EBV) is associated with a number of diseases, including malignancies. Currently, it is not known whether patients with different EBV-associated diseases have different methylation profiles of circulating EBV DNA. Through whole-genome methylation analysis of plasma samples from patients with nasopharyngeal carcinoma (NPC), EBV-associated lymphoma and infectious mononucleosis, we demonstrate that EBV DNA methylation profiles exhibit a disease-associated pattern. This observation implies a significant potential for the development of methylation analysis of plasma EBV DNA for NPC diagnostics. We further analyse the plasma EBV DNA methylome of NPC and non-NPC subjects from a prospective screening cohort. Plasma EBV DNA fragments demonstrate differential methylation patterns between NPC and non-NPC subjects. Combining such differential methylation patterns with the fractional concentration (count) and size of plasma EBV DNA, population screening of NPC is performed with an improved positive predictive value of 35.1%, compared to a count- and size-based only protocol.

Epstein-Barr virus (EBV) is associated with different malignant diseases and circulating EBV DNA is a biomarker for nasopharyngeal carcinoma (NPC). Here, the authors report that plasma EBV DNA methylation profiles show disease-associated patterns and can help to distinguish NPC and non-NPC subjects.

A non-randomized procedure for large-scale heterogeneous multiple discrete testing based on randomized tests

In the analysis of next-generation sequencing technology, massive discrete data are generated from short read counts with varying biological coverage. Conducting conditional hypothesis testing such as Fisher's Exact Test at every genomic region of interest thus leads to a heterogeneous multiple discrete testing problem. However, most existing multiple testing procedures for controlling the false discovery rate (FDR) assume that test statistics are continuous and become conservative for discrete tests. To overcome the conservativeness, in this article, we propose a novel multiple testing procedure for better FDR control on heterogeneous discrete tests. Our procedure makes decisions based on the marginal critical function (MCF) of randomized tests, which enables achieving a powerful and non-randomized multiple testing procedure. We provide upper bounds of the positive FDR (pFDR) and the positive false non-discovery rate (pFNR) corresponding to our procedure. We also prove that the set of detections made by our method contains every detection made by a naive application of the widely-used q-value method. We further demonstrate the improvement of our method over other existing multiple testing procedures by simulations and a real example of differentially methylated region (DMR) detection using whole-genome bisulfite sequencing (WGBS) data.

Developmental Dieldrin Exposure Alters DNA Methylation at Genes Related to Dopaminergic Neuron Development and Parkinson's Disease in Mouse Midbrain

Human and animal studies have shown that exposure to the organochlorine pesticide dieldrin is associated with increased risk of Parkinson's disease (PD). Despite previous work showing a link between developmental dieldrin exposure and increased neuronal susceptibility to MPTP toxicity in male C57BL/6 mice, the mechanism mediating this effect has not been identified. Here, we tested the hypothesis that developmental exposure to dieldrin increases neuronal susceptibility via genome-wide changes in DNA methylation. Starting at 8 weeks of age and prior to mating, female C57BL/6 mice were exposed to 0.3 mg/kg dieldrin by feeding (every 3 days) throughout breeding, gestation, and lactation. At 12 weeks of age, pups were sacrificed and ventral mesencephalon, containing primarily substantia nigra, was microdissected. DNA was isolated and dieldrin-related changes in DNA methylation were assessed via reduced representation bisulfite sequencing. We identified significant, sex-specific differentially methylated CpGs (DMCs) and regions (DMRs) by developmental dieldrin exposure (false discovery rate < 0.05), including DMCs at the Nr4a2 and Lmx1b genes, which are involved in dopaminergic neuron development and maintenance. Developmental dieldrin exposure had distinct effects on the male and female epigenome. Together, our data suggest that developmental dieldrin exposure establishes sex-specific poised epigenetic states early in life. These poised epigenomes may mediate sensitivity to subsequent toxic stimuli and contribute to the development of late-life neurodegenerative disease, including PD.

Direct measurement of the mechanical properties of a chromatin analog and the epigenetic effects of para-sulphonato-calix[4]arene

By means of Silicon Nano Tweezers (SNTs) the effects on the mechanical properties of λ-phage DNA during interaction with calf thymus nucleosome to form an artificial chromatin analog were measured. At a concentration of 100 nM, a nucleosome solution induced a strong stiffening effect on DNA (1.1 N m-1). This can be compared to the effects of the histone proteins, H1, H2A, H3 where no changes in the mechanical properties of DNA were observed and the complex of the H3/H4 proteins where a smaller increase in the stiffness is observed (0.2 N m-1). Para-sulphonato-calix[4]arene, SC4, known for epigenetic activity by interacting specifically with the lysine groups of histone proteins, was studied for its effect on an artificial chromatin. Using a microfluidic SNT device, SC4 was titrated against the artificial chromatin, at a concentration of 1 mM in SC4 a considerable increase in stiffness, 15 N m-1, was observed. Simultaneously optical microscopy showed a physical change in the DNA structure between the tips of the SNT device. Electronic and Atomic Force microscopy confirmed this structural re-arrangement. Negative control experiments confirmed that these mechanical and physical effects were induced neither by the acidity of SC4 nor through nonspecific interactions of SC4 on DNA.

A survey of the approaches for identifying differential methylation using bisulfite sequencing data

DNA methylation is an important epigenetic mechanism that plays a crucial role in cellular regulatory systems. Recent advancements in sequencing technologies now enable us to generate high-throughput methylation data and to measure methylation up to single-base resolution. This wealth of data does not come without challenges, and one of the key challenges in DNA methylation studies is to identify the significant differences in the methylation levels of the base pairs across distinct biological conditions. Several computational methods have been developed to identify differential methylation using bisulfite sequencing data; however, there is no clear consensus among existing approaches. A comprehensive survey of these approaches would be of great benefit to potential users and researchers to get a complete picture of the available resources. In this article, we present a detailed survey of 22 such approaches focusing on their underlying statistical models, primary features, key advantages and major limitations. Importantly, the intrinsic drawbacks of the approaches pointed out in this survey could potentially be addressed by future research.

Analysis of DNA Methylation at Specific Loci in Stool Samples Detects Colorectal Cancer and High-Grade Dysplasia in Patients With Inflammatory Bowel Disease

BACKGROUND & AIMS

Patients with inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn's disease, are at increased risk for colorectal cancer (CRC). Analyses of DNA methylation patterns in stool samples have been reported to detect CRC in patients with IBD. We sought to validate these findings in larger cohorts and assess the accuracy of analysis of DNA methylation patterns in stool for detection of CRC and high-grade dysplasia (HGD) normalized to methylation level at ZDHHC1.

METHODS

We obtained buffered, frozen stool samples from a US case-control study and from 2 European surveillance cohorts (referral or population based) of patients with chronic ulcerative colitis (n = 248), Crohn's disease (n = 82), indeterminate colitis (n = 2), or IBD with primary sclerosing cholangitis (n = 38). Stool samples were collected before bowel preparation for colonoscopy or at least 1 week after colonoscopy. Among the study samples, stools from individuals with IBD but without neoplasia were used as controls (n = 291). DNA was isolated from stool, exposed to bisulfite, and then assayed by multiplex quantitative allele-specific real-time target and signal amplification. We analyzed methylation levels of BMP3, NDRG4, VAV3, and SFMBT2 relative to the methylation level of ZDHHC1, and compared these between patients with CRC or HGD and controls.

RESULTS

Levels of methylation at BMP3 and VAV3, relative to ZDHHC1 methylation, identified patients with CRC and HGD with an area under the curve value of 0.91 (95% CI, 0.77-1.00). Methylation levels at specific promotor regions of these genes identified 11 of the 12 patients with CRC and HGD, with 92% sensitivity (95% CI, 60%-100%) and 90% specificity (95% CI, 86%-93%). The proportion of false-positive results did not differ significantly among the case-control, referral cohort, and population cohort studies (P = .60) when the 90% specificity cut-off from the whole sample set was applied.

CONCLUSIONS

In an analysis of stool samples from 3 independent studies of 332 patients with IBD, we associated levels of methylation at 2 genes (BMP3 and VAV3), relative to level of methylation at ZDHHC1, with detection of CRC and HGD. These methylation patterns identified patients with CRC and HGD with more than 90% specificity, and might be used in CRC surveillance.