Base resolution methylome profiling: considerations in platform selection, data preprocessing and analysis

Next-generation sequencing in cancer diagnosis and treatment: clinical applications and future directions

Next-generation sequencing (NGS) has emerged as a pivotal technology in the field of oncology, transforming the approach to cancer diagnosis and treatment. This paper provides a comprehensive overview of the integration of NGS into clinical settings, emphasizing its significant contributions to precision medicine. NGS enables detailed genomic profiling of tumors, identifying genetic alterations that drive cancer progression and facilitating personalized treatment plans targeting specific mutations, thereby improving patient outcomes. This capability facilitates the development of personalized treatment plans targeting specific mutations, leading to improved patient outcomes and the potential for better prognosis. The application of NGS extends beyond identifying actionable mutations; it is instrumental in detecting hereditary cancer syndromes, thus aiding in early diagnosis and preventive strategies. Furthermore, NGS plays a crucial role in monitoring minimal residual disease, offering a sensitive method to detect cancer recurrence at an early stage. Its use in guiding immunotherapy by identifying biomarkers that predict response to treatment is also highlighted. Ethical issues related to genetic testing, such as concerns around patient consent and data privacy, are also important considerations that need to be addressed for the broader implementation of NGS. These include the complexities of data interpretation, the need for robust bioinformatics support, cost considerations, and ethical issues related to genetic testing. Addressing these challenges is essential for the widespread adoption of NGS. Looking forward, advancements such as single-cell sequencing and liquid biopsies promise to further enhance the precision of cancer diagnostics and treatment. This review emphasizes the transformative impact of NGS in oncology and advocates for its incorporation into routine clinical practice to promote molecularly driven cancer care.

EpiAge: a next-generation sequencing-based ELOVL2 epigenetic clock for biological age assessment in saliva and blood across health and disease

This study introduces EpiAgePublic, a new method to estimate biological age using only three specific sites on the gene ELOVL2, known for its connection to aging. Unlike traditional methods that require complex and extensive data, our model uses a simpler approach that is well-suited for next-generation sequencing technology, which is a more advanced method of analyzing DNA methylation. This new model overcomes some of the common challenges found in older methods, such as errors due to sample quality and processing variations. We tested EpiAgePublic with a large and varied group of over 4,600 people to ensure its accuracy. It performed on par with, and sometimes better than, more complicated models that use much more data for age estimation. We examined its effectiveness in understanding how factors like HIV infection and stress affect aging, confirming its usefulness in real-world clinical settings. Our results prove that our simple yet effective model, EpiAgePublic, can capture the subtle signs of aging with high accuracy. We also used this model in a study involving patients with Alzheimer's Disease, demonstrating the practical benefits of next-generation sequencing in making precise age-related assessments. This study lays the groundwork for future research on aging mechanisms and assessing how different interventions might impact the aging process using this clock.

Genomic context determines the effect of DNA methylation on gene expression in the gut epithelium of Atlantic salmon (Salmo salar)

The canonical view of DNA methylation, a pivotal epigenetic regulation mechanism in eukaryotes, dictates its role as a suppressor of gene activity, particularly within promoter regions. However, this view is being challenged as it is becoming increasingly evident that the connection between DNA methylation and gene expression varies depending on the genomic location and is therefore more complex than initially thought. We examined DNA methylation levels in the gut epithelium of Atlantic salmon (Salmo salar) using whole-genome bisulfite sequencing, which we correlated with gene expression data from RNA sequencing of the same gut tissue sample (RNA-seq). Assuming epigenetic signals might be pronounced between distinctive phenotypes, we compared large and small fish, finding 22 significant associations between 22 differentially methylated regions and 21 genes. We did not detect significant methylation differences between large and small fish. However, we observed a consistent signal of methylation levels around the transcription start sites (TSS), being negatively correlated with the expression levels of those genes. We found both negative and positive associations of methylation levels with gene expression further upstream or downstream of the TSS, revealing a more unpredictable pattern. The 21 genes showing significant methylation-expression correlations were involved in biological processes related to salmon health, such as growth and immune responses. Deciphering how DNA methylation affects the expression of such genes holds great potential for future applications. For instance, our results suggest the importance of genomic context in targeting epigenetic modifications to improve the welfare of aquaculture species like Atlantic salmon.

Circulating tumor DNA methylation detection as biomarker and its application in tumor liquid biopsy: advances and challenges

Circulating tumor DNA (ctDNA) methylation, an innovative liquid biopsy biomarker, has emerged as a promising tool in early cancer diagnosis, monitoring, and prognosis prediction. As a noninvasive approach, liquid biopsy overcomes the limitations of traditional tissue biopsy. Among various biomarkers, ctDNA methylation has garnered significant attention due to its high specificity and early detection capability across diverse cancer types. Despite its immense potential, the clinical application of ctDNA methylation faces substantial challenges pertaining to sensitivity, specificity, and standardization. In this review, we begin by introducing the basic biology and common detection techniques of ctDNA methylation. We then explore recent advancements and the challenges faced in the clinical application of ctDNA methylation in liquid biopsies. This includes progress in early screening and diagnosis, identification of clinical molecular subtypes, monitoring of recurrence and minimal residual disease (MRD), prediction of treatment response and prognosis, assessment of tumor burden, and determination of tissue origin. Finally, we discuss the future perspectives and challenges of ctDNA methylation detection in clinical applications. This comprehensive overview underscores the vital role of ctDNA methylation in enhancing cancer diagnostic accuracy, personalizing treatments, and effectively monitoring disease progression, providing valuable insights for future research and clinical practice.

Discovery and Validation of Methylation Signatures in Circulating Cell-Free DNA for the Detection of Colorectal Cancer

This study was conducted with the primary objective of assessing the performance of cfDNA methylation in the detection of colorectal cancer (CRC). Five tumor tissue, 20 peripheral blood leucocyte, and 169 cfDNA samples were collected for whole-genome bisulfite sequencing (WGBS) analysis. Bioinformatic analysis was conducted to identify differentially methylated regions (DMRs) and their functional characteristics. Quantitative methylation-specific PCR (qMSP) was used to validate the methylation levels of DMRs in the tissues and leucocytes. cfDNA samples from CRC patients and healthy controls were used to evaluate the performance of the DMR analysis. WGBS analysis revealed a decrease in DNA methylation levels in the CpG context in CRC tumor tissues compared with adjacent normal tissues. A total of 132 DMRs in cfDNA were identified as potential markers for diagnosing CRC. In a cohort of 95 CRC patients and 74 healthy controls, a combination of the three DMRs (DAB1, PPP2R5C, and FAM19A5) yielded an AUC of 0.763, achieving 64.21% sensitivity and 78.38% specificity in discriminating CRC patients from healthy controls. This study provides insights into DNA methylation patterns in CRC and identifies a set of DMRs in cfDNA with potential diagnostic value for CRC. These DMRs hold promise as biomarkers for CRC detection, offering promise for non-invasive CRC diagnosis. Further research is warranted to validate these findings in larger cohorts.

Genome-wide 5'-C-phosphate-G-3' methylation patterns reveal the effect of heat stress on the altered semen quality in Bubalus bubalis

Semen production and quality are closely correlated with different environmental factors in bovines, particularly for the buffalo (Bubalus bubalis) bulls reared under tropical and sub-tropical conditions. Factors including DNA methylation patterns, an intricate process in sperm cells, have an impact on the production of quality semen in buffalo bulls under abiotic stress conditions. The present study was conducted to identify DNA methylome signatures for semen quality in Murrah buffalo bulls, acclaimed as a major dairy breed globally, under summer heat stress. Based on semen quality parameters that significantly varied between the two groups over the seasons, the breeding bulls were classified into seasonally affected (SA = 6) and seasonally non-affected (SNA = 6) categories. DNA was isolated from purified sperm cells and sequenced using the RRBS (Reduced Representation Bisulfite Sequencing) technique for genome-wide methylome data generation. During the hot summer months, the physiological parameters such as scrotal surface temperature, rectal temperature, and respiration rate for both the SA and SNA bulls were significantly higher in the afternoon than in the morning. Whereas, the global CpG% of SA bulls was positively correlated with the afternoon's scrotal surface and rectal temperature. The RRBS results conveyed differentially methylated cytosines in the promoter region of the genes encoding the channels responsible for Ca2+ exchange, NPTN, Ca2+ activated chloride channels, ANO1, and a few structure-related units such as septins (SEPT4 and SEPT6), SPATA, etc. Additionally, the hypermethylated set of genes in SA was significantly enriched for pathways such as the FOXO signaling pathway and oocyte meiosis. The methylation patterns suggest promoter methylation in the genes regulating the sperm structure as well as surface transporters, which could contribute to the reduced semen quality in the Murrah buffalo bulls during the season-related heat stress.

Cell-free DNA methylation in the clinical management of lung cancer

The clinical use of cell-free DNA (cfDNA) methylation in managing lung cancer depends on its ability to differentiate between malignant and healthy cells, assign methylation changes to specific tissue sources, and elucidate opportunities for targeted therapy. From a technical standpoint, cfDNA methylation analysis is primed as a potential clinical tool for lung cancer screening, early diagnosis, prognostication, and treatment, pending the outcome of elaborate validation studies. Here, we discuss the current state of the art in cfDNA methylation analysis, examine the unique features and limitations of these new methods in a clinical context, propose two models for applying cfDNA methylation data for lung cancer screening, and discuss future research directions.

Whole-genome bisulfite sequencing identifies stage- and subtype-specific DNA methylation signatures in pancreatic cancer

In pancreatic ductal adenocarcinoma (PDAC), no recurrent metastasis-specific mutation has been found, suggesting that epigenetic mechanisms, such as DNA methylation, are the major contributors of late-stage disease progression. Here, we performed the first whole-genome bisulfite sequencing (WGBS) on mouse and human PDAC organoid models to identify stage-specific and molecular subtype-specific DNA methylation signatures. With this approach, we identified thousands of differentially methylated regions (DMRs) that can distinguish between the stages and molecular subtypes of PDAC. Stage-specific DMRs are associated with genes related to nervous system development and cell-cell adhesions, and are enriched in promoters and bivalent enhancers. Subtype-specific DMRs showed hypermethylation of GATA6 foregut endoderm transcriptional networks in the squamous subtype and hypermethylation of EMT transcriptional networks in the progenitor subtype. These results indicate that aberrant DNA methylation contributes to both PDAC progression and subtype differentiation, resulting in significant and reoccurring DNA methylation patterns with diagnostic and prognostic potential.

Mutations in human DNA methyltransferase DNMT1 induce specific genome-wide epigenomic and transcriptomic changes in neurodevelopment

DNA methyltransferase type 1 (DNMT1) is a major enzyme involved in maintaining the methylation pattern after DNA replication. Mutations in DNMT1 have been associated with autosomal dominant cerebellar ataxia, deafness and narcolepsy (ADCA-DN). We used fibroblasts, induced pluripotent stem cells (iPSCs) and induced neurons (iNs) generated from patients with ADCA-DN and controls, to explore the epigenomic and transcriptomic effects of mutations in DNMT1. We show cell type-specific changes in gene expression and DNA methylation patterns. DNA methylation and gene expression changes were negatively correlated in iPSCs and iNs. In addition, we identified a group of genes associated with clinical phenotypes of ADCA-DN, including PDGFB and PRDM8 for cerebellar ataxia, psychosis and dementia and NR2F1 for deafness and optic atrophy. Furthermore, ZFP57, which is required to maintain gene imprinting through DNA methylation during early development, was hypomethylated in promoters and exhibited upregulated expression in patients with ADCA-DN in both iPSC and iNs. Our results provide insight into the functions of DNMT1 and the molecular changes associated with ADCA-DN, with potential implications for genes associated with related phenotypes.

An ecologist's guide for studying DNA methylation variation in wild vertebrates

The field of molecular biology is advancing fast with new powerful technologies, sequencing methods and analysis software being developed constantly. Commonly used tools originally developed for research on humans and model species are now regularly used in ecological and evolutionary research. There is also a growing interest in the causes and consequences of epigenetic variation in natural populations. Studying ecological epigenetics is currently challenging, especially for vertebrate systems, because of the required technical expertise, complications with analyses and interpretation, and limitations in acquiring sufficiently high sample sizes. Importantly, neglecting the limitations of the experimental setup, technology and analyses may affect the reliability and reproducibility, and the extent to which unbiased conclusions can be drawn from these studies. Here, we provide a practical guide for researchers aiming to study DNA methylation variation in wild vertebrates. We review the technical aspects of epigenetic research, concentrating on DNA methylation using bisulfite sequencing, discuss the limitations and possible pitfalls, and how to overcome them through rigid and reproducible data analysis. This review provides a solid foundation for the proper design of epigenetic studies, a clear roadmap on the best practices for correct data analysis and a realistic view on the limitations for studying ecological epigenetics in vertebrates. This review will help researchers studying the ecological and evolutionary implications of epigenetic variation in wild populations.

Simultaneous detection of DNA variation and methylation at HLA class II locus and immune gene promoters using targeted SureSelect Methyl-Sequencing

The Human Leukocyte Antigen (HLA) locus associates with a variety of complex diseases, particularly autoimmune and inflammatory conditions. The HLA-DR15 haplotype, for example, confers the major risk for developing Multiple Sclerosis in Caucasians, pinpointing an important role in the etiology of this chronic inflammatory disease of the central nervous system. In addition to the protein-coding variants that shape the functional HLA-antigen-T cell interaction, recent studies suggest that the levels of HLA molecule expression, that are epigenetically controlled, also play a role in disease development. However, deciphering the exact molecular mechanisms of the HLA association has been hampered by the tremendous genetic complexity of the locus and a lack of robust approaches to investigate it. Here, we developed a method to specifically enrich the genomic DNA from the HLA class II locus (chr6:32,426,802-34,167,129) and proximal promoters of 2,157 immune-relevant genes, utilizing the Agilent RNA-based SureSelect Methyl-Seq Capture related method, followed by sequencing to detect genetic and epigenetic variation. We demonstrated successful simultaneous detection of the genetic variation and quantification of DNA methylation levels in HLA locus. Moreover, by the detection of differentially methylated positions in promoters of immune-related genes, we identified relevant pathways following stimulation of cells. Taken together, we present a method that can be utilized to study the interplay between genetic variance and epigenetic regulation in the HLA class II region, potentially, in a wide disease context.

Evaluation of circulating tumor DNA by electropherogram analysis and methylome profiling in high-risk neuroblastomas

Background

Liquid biopsy has emerged as a promising, non-invasive diagnostic approach in oncology because the analysis of circulating tumor DNA (ctDNA) reflects the precise status of the disease at diagnosis, progression, and response to treatment. DNA methylation profiling is also a potential solution for sensitive and specific detection of many cancers. The combination of both approaches, DNA methylation analysis from ctDNA, provides an extremely useful and minimally invasive tool with high relevance in patients with childhood cancer. Neuroblastoma is an extracranial solid tumor most common in children and responsible for up to 15% of cancer-related deaths. This high death rate has prompted the scientific community to search for new therapeutic targets. DNA methylation also offers a new source for identifying these molecules. However, the limited blood sample size which can be obtained from children with cancer and the fact that ctDNA content may occasionally be diluted by non-tumor cell-free DNA (cfDNA) complicate optimal quantities of material for high-throughput sequencing studies.

Methods

In this article, we present an improved method for ctDNA methylome studies of blood-derived plasma from high-risk neuroblastoma patients. We assessed the electropherogram profiles of ctDNA-containing samples suitable for methylome studies, using 10 ng of plasma-derived ctDNA from 126 samples of 86 high-risk neuroblastoma patients, and evaluated several bioinformatic approaches to analyze DNA methylation sequencing data.

Results

We demonstrated that enzymatic methyl-sequencing (EM-seq) outperformed bisulfite conversion-based method, based on the lower proportion of PCR duplicates and the higher percentage of unique mapping reads, mean coverage, and genome coverage. The analysis of the electropherogram profiles revealed the presence of nucleosomal multimers, and occasionally high molecular weight DNA. We established that 10% content of the mono-nucleosomal peak is sufficient ctDNA for successful detection of copy number variations and methylation profiles. Quantification of mono-nucleosomal peak also showed that samples at diagnosis contained a higher amount of ctDNA than relapse samples.

Conclusions

Our results refine the use of electropherogram profiles to optimize sample selection for subsequent high-throughput analysis and support the use of liquid biopsy followed by enzymatic conversion of unmethylated cysteines to assess the methylomes of neuroblastoma patients.

High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias

Aberrant DNA methylation at CpG dinucleotides is a cancer hallmark that is associated with the emergence of resistance to anti cancer treatment, though molecular mechanisms and biological significance remain elusive. Genome scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG rich regions (CpG islands). We report the first high coverage whole-genome map in cancer using the long read nanopore technology, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, after chemotherapy. Long read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution, and showed that the relapse methylome is characterized by hypermethylation at both CpG islands and sparse CpGs regions. Most differentially methylated genes, however, were not differentially expressed nor enriched for chemoresistance genes. A small fraction of under-expressed and hyper-methylated genes at sparse CpGs, in the gene body, was significantly enriched in transcription factors (TFs). Remarkably, these few TFs supported large gene-regulatory networks including 50% of all differentially expressed genes in the relapsed AMLs and highly-enriched in chemoresistance genes. Notably, hypermethylated regions at sparse CpGs were poorly conserved in the relapsed AMLs, under-represented at their genomic positions and showed higher methylation entropy, as compared to CpG islands. Analyses of available datasets confirmed TF binding to their target genes and conservation of the same gene-regulatory networks in large patient cohorts. Relapsed AMLs carried few patient specific structural variants and DNA mutations, apparently not involved in drug resistance. Thus, drug resistance in AMLs can be mainly ascribed to the selection of random epigenetic alterations at sparse CpGs of a few transcription factors, which then induce reprogramming of the relapsing phenotype, independently of clonal genomic evolution.

Genomic, epigenomic, and transcriptomic signatures of prostate cancer between African American and European American patients

Prostate cancer is the second most common cancer in men in the United States, and racial disparities are greatly observed in the disease. Specifically, African American (AA) patients have 60% higher incidence and mortality rates, in addition to higher grade and stage prostate tumors, than European American (EA) patients. In order to narrow the gap between clinical outcomes for these two populations, genetic and molecular signatures contributing to this disparity have been characterized. Over the past decade, profiles of prostate tumor samples from different ethnic groups have been developed using molecular and functional assays coupled with next generation sequencing or microarrays. Comparative genome-wide analyses of genomic, epigenomic, and transcriptomic profiles from prostate tumor samples have uncovered potential race-specific mutations, copy number alterations, DNA methylation, and gene expression patterns. In this study, we reviewed over 20 published studies that examined the aforementioned molecular contributions to racial disparities in AA and EA prostate cancer patients. The reviewed genomic studies revealed mutations, deletions, amplifications, duplications, or fusion genes differentially enriched in AA patients relative to EA patients. Commonly reported genomic alterations included mutations or copy number alterations of FOXA1, KMT2D, SPOP, MYC, PTEN, TP53, ZFHX3, and the TMPRSS2-ERG fusion. The reviewed epigenomic studies identified that CpG sites near the promoters of PMEPA1, RARB, SNRPN, and TIMP3 genes were differentially methylated between AA and EA patients. Lastly, the reviewed transcriptomic studies identified genes (e.g. CCL4, CHRM3, CRYBB2, CXCR4, GALR1, GSTM3, SPINK1) and signaling pathways dysregulated between AA and EA patients. The most frequently found dysregulated pathways were involved in immune and inflammatory responses and neuroactive ligand signaling. Overall, we observed that the genomic, epigenomic, and transcriptomic alterations evaluated between AA and EA prostate cancer patients varied between studies, highlighting the impact of using different methods and sample sizes. The reported genomic, epigenomic, and transcriptomic alterations do not only uncover molecular mechanisms of tumorigenesis but also provide researchers and clinicians valuable resources to identify novel biomarkers and treatment modalities to improve the disparity of clinical outcomes between AA and EA patients.

A Clinician's Guide to Bioinformatics for Next-Generation Sequencing

Next-generation sequencing (NGS) technologies are high-throughput methods for DNA sequencing and have become a widely adopted tool in cancer research. The sheer amount and variety of data generated by NGS assays require sophisticated computational methods and bioinformatics expertise. In this review, we provide background details of NGS technology and basic bioinformatics concepts for the clinician investigator interested in cancer research applications, with a focus on DNA-based approaches. We introduce the general principles of presequencing library preparation, postsequencing alignment, and variant calling. We also highlight the common variant annotations and NGS applications for other molecular data types. Finally, we briefly discuss the revealed utility of NGS methods in NSCLC research and study design considerations for research studies that aim to leverage NGS technologies for clinical care.

DNA Methylation Analysis Using Bisulfite Pyrosequencing

Pyrosequencing is a DNA sequencing-by-synthesis technique that can quantitatively detect single-nucleotide polymorphisms (SNPs). With pyrosequencing, the level of DNA methylation can be calculated according to the ratio of artificial cytosine/thymine SNPs produced by bisulfite conversion at each CpG site. This analysis method provides a reproducible and accurate measurement of methylation levels at CpG sites near sequencing primers with high quantitative resolution. DNA methylation plays an important role in mammalian development and cellular physiology; alterations in DNA methylation patterns have been implicated in several common diseases as well as cancers and imprinting disorders. Evaluating DNA methylation levels via pyrosequencing is useful for identifying biomarkers that could help with the diagnosis, prognosis, treatment selection, and onset risk assessment for several diseases. We describe the principles of pyrosequencing and detail a bisulfite pyrosequencing protocol based on our experience and the PyroMark Q24 User Manual.

Genome-wide alternation and effect of DNA methylation in the impairments of steroidogenesis and spermatogenesis after PM2.5 exposure

The effects of ambient fine particles on male reproductive health have raised widespread concern. The particular underlying mechanisms of the damage remain largely unclear and demand more research in new directions. Previous research has revealed that DNA methylation plays an important role in male reproductive development and is also vulnerable to environmental influences. However, there hasn't been enough investigation into the involvement of DNA methylation in PM_2.5-induced male reproductive toxicity. Here, we establish a real-time PM_2.5 exposure model and revealed that PM_2.5 exposure could lead to testicular dysfunction including spermatogenesis impairment and steroid hormone dysfunction. In particular, the decrease in the testicular global level of 5-methylcytosine (5mC) indicated a possible association of DNA methylation with testicular injury induced by PM_2.5 exposure. Further genome-wide methylation analysis revealed genomic hypomethylation of testicular DNA and identified more than 1000 differentially methylated regions in both CAP and UA versus FA, indicating that PM_2.5 exposure, even low-dose, could modulate the testicular methylome. Furthermore, integrated analysis of methylome and transcriptome identified some key methylated genes and networks, which may be involved in spermatogenesis and synthesis of steroid hormone. The testicular methylation levels of key genes especially Cyp11a1 and Pax8 raised, and their consequent reduced expression may impair the testosterone and sperm production process. Our research provides fundamental knowledge as well as novel insights into the possible involvement of DNA methylation in PM_2.5-induced male reproductive harm.

Comparative analysis of sperm DNA methylation supports evolutionary acquired epigenetic plasticity for organ speciation

Aim: To perform a comparative epigenomic analysis of DNA methylation in spermatozoa from humans, mice, rats and mini-pigs. Materials & methods: Genome-wide DNA methylation analysis was used to compare the methylation profiles of orthologous CpG sites. Transcription profiles of early embryo development were analyzed to provide insight into the association between sperm methylation and gene expression programming. Results: We identified DNA methylation variation near genes related to the central nervous system and signal transduction. Gene expression dynamics at different time points of preimplantation stages were modestly associated with spermatozoal DNA methylation at the nearest promoters. Conclusion: Conserved genomic regions subject to epigenetic variation across different species were associated with specific organ functions, suggesting their potential contribution to organ speciation and long-term adaptation to the environment.

Benchmarking DNA Methylation Analysis of 14 Alignment Algorithms for Whole Genome Bisulfite Sequencing in Mammals

Whole genome bisulfite sequencing (WGBS) is an essential technique for methylome studies. Although a series of tools have been developed to overcome the mapping challenges caused by bisulfite treatment, the latest available tools have not been evaluated on the performance of reads mapping as well as on biological insights in multiple mammals. Herein, based on the real and simulated WGBS data of 14.77 billion reads, we undertook 936 mappings to benchmark and evaluate 14 wildly utilized alignment algorithms from reads mapping to biological interpretation in humans, cattle and pigs: Bwa-meth, BSBolt, BSMAP, Walt, Abismal, Batmeth2, Hisat_3n, Hisat_3n_repeat, Bismark-bwt2-e2e, Bismark-his2, BSSeeker2-bwt, BSSeeker2-soap2, BSSeeker2-bwt2-e2e and BSSeeker2-bwt2-local. Specifically, Bwa-meth, BSBolt, BSMAP, Bismark-bwt2-e2e and Walt exhibited higher uniquely mapped reads, mapped precision, recall and F1 score than other nine alignment algorithms, and the influences of distinct alignment algorithms on the methylomes varied considerably at the numbers and methylation levels of CpG sites, the calling of differentially methylated CpGs (DMCs) and regions (DMRs). Moreover, we reported that BSMAP showed the highest accuracy at the detection of CpG coordinates and methylation levels, the calling of DMCs, DMRs, DMR-related genes and signaling pathways. These results suggested that careful selection of algorithms to profile the genome-wide DNA methylation is required, and our works provided investigators with useful information on the choice of alignment algorithms to effectively improve the DNA methylation detection accuracy in mammals.

Comparison of DNA methylation measurements from EPIC BeadChip and SeqCap targeted bisulphite sequencing in PON1 and nine additional candidate genes

Epigenome-wide association studies (EWAS) are widely implemented in epidemiology, and the Illumina HumanMethylationEPIC BeadChip (EPIC) DNA microarray is the most-used technology. Recently, next-generation sequencing (NGS)-based methods, which assess DNA methylation at single-base resolution, have become more affordable and technically feasible. While the content of microarray technology is fixed, NGS-based approaches, such as the Roche Nimblegen, SeqCap Epi Enrichment System (SeqCap), offer the flexibility of targeting most CpGs in a gene. With the current usage of microarrays and emerging NGS-based technologies, it is important to establish whether data generated from the two platforms are comparable. We harnessed 112 samples from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) birth cohort study and compared DNA methylation between the EPIC microarray and SeqCap for PON1 and nine additional candidate genes, by evaluating epigenomic coverage and correlations. We conducted multivariable linear regression and principal component analyses to assess the ability of the EPIC array and SeqCap to detect biological differences in gene methylation by the PON1_-108 single nucleotide polymorphism. We found an overall high concordance (r = 0.84) between SeqCap and EPIC DNA methylation, among highly methylated and minimally methylated regions. However, substantial disagreement was present between the two methods in moderately methylated regions, with SeqCap measurements exhibiting greater within-site variation. Additionally, SeqCap did not capture PON1 SNP associated differences in DNA methylation that were evident with the EPIC array. Our findings indicate that microarrays perform well for analysing DNA methylation in large cohort studies but with limited coverage.

Examining the association between adiposity and DNA methylation: A systematic review and meta-analysis

Obesity is associated with widespread differential DNA methylation (DNAm) patterns, though there have been limited overlap in the obesity-associated cytosine-guanine nucleotide pair (CpG) sites that have been identified in the literature. We systematically searched four databases for studies published until January 2020. Eligible studies included cross-sectional, longitudinal, or intervention studies examining adiposity and genome-wide DNAm in non-pregnant adults aged 18-75 in all tissue types. Study design and results were extracted in the descriptive review. Blood-based DNAm results in body mass index (BMI) and waist circumference (WC) were meta-analyzed using weighted sum of Z-score meta-analysis. Of the 10,548 studies identified, 46 studies were included in the systematic review with 18 and nine studies included in the meta-analysis of BMI and WC, respectively. In the blood, 77 and four CpG sites were significant in three or more studies of BMI and WC, respectively. Using a genome-wide threshold for significance, 52 blood-based CpG sites were significantly associated with BMI. These sites have previously been associated with many obesity-related diseases including type 2 diabetes, cardiovascular disease, Crohn's disease, and depression. Our study shows that DNAm at 52 CpG sites represent potential mediators of obesity-associated chronic diseases and may be novel intervention or therapeutic targets to protect against obesity-associated chronic diseases.

DNA methylation detection technology and plasma-based methylation biomarkers in screening of gastrointestinal carcinoma

DNA methylation is of paramount importance for the evolution of human cancers. Its high sensitivity and specificity make it a potential biomarker for early cancer screening in the context of an increasing global burden of gastrointestinal (GI) carcinoma. More DNA methylation biomarkers are emerging with the development of liquid biopsy and sensitive DNA methylation detection technology. This review provides an overview of DNA methylation, focusing on the presentation and comparison of 5-methylcytosine detection technologies, and introduces the promising plasma-based cell-free DNA (cfDNA) methylation biomarkers published in recent years for early screening of GI carcinoma. Finally, we summarize and discuss the future of plasma cfDNA methylation markers detection as a clinical tool for early screening of GI carcinoma.

Perinatal exposure to nicotine alters spermatozoal DNA methylation near genes controlling nicotine action

Perinatal smoke/nicotine exposure alters lung development and causes asthma in exposed offspring, transmitted transgenerationally. The mechanism underlying the transgenerational inheritance of perinatal smoke/nicotine-induced asthma remains unknown, but germline epigenetic modulations may play a role. Using a well-established rat model of perinatal nicotine-induced asthma, we determined the DNA methylation pattern of spermatozoa of F1 rats exposed perinatally to nicotine in F0 gestation. To identify differentially methylated regions (DMRs), reduced representation bisulfite sequencing was performed on spermatozoa of F1 litters. The top regulated gene body and promoter DMRs were tested for lung gene expression levels, and key proteins involved in lung development and repair were determined. The overall CpG methylation in F1 sperms across gene bodies, promoters, 5'-UTRs, exons, introns, and 3'-UTRs was not affected by nicotine exposure. However, the methylation levels were different between the different genomic regions. Eighty one CpG sites, 16 gene bodies, and 3 promoter regions were differentially methylated. Gene enrichment analysis of DMRs revealed pathways involved in oxidative stress, nicotine response, alveolar and brain development, and cellular signaling. Among the DMRs, Dio1 and Nmu were the most hypermethylated and hypomethylated genes, respectively. Gene expression analysis showed that the mRNA expression and DNA methylation were incongruous. Key proteins involved in lung development and repair were significantly different (FDR < 0.05) between the nicotine and placebo-treated groups. Our data show that DNA methylation is remodeled in offspring spermatozoa upon perinatal nicotine exposure. These epigenetic alterations may play a role in transgenerational inheritance of perinatal smoke/nicotine induced asthma.

ABCA1, TCF7, NFATC1, PRKCZ, and PDGFA DNA methylation as potential epigenetic-sensitive targets in acute coronary syndrome via network analysis

Acute coronary syndrome (ACS) is the most severe clinical manifestation of coronary heart disease.We performed an epigenome-wide analysis of circulating CD4⁺ and CD8⁺ T cells isolated from ACS patients and healthy subjects (HS), enrolled in the DIANA clinical trial, by reduced-representation bisulphite sequencing (RRBS). In CD4⁺ T cells, we identified 61 differentially methylated regions (DMRs) associated with 57 annotated genes (53% hyper- and 47% hypo-methylated) by comparing ACS patients vs HS. In CD8⁺ T cells, we identified 613 DMRs associated with 569 annotated genes (28% hyper- and 72% hypo-methylated) in ACS patients as compared to HS. In CD4⁺ vs CD8⁺ T cells of ACS patients we identified 175 statistically significant DMRs associated with 157 annotated genes (41% hyper- and 59% hypo-methylated). From pathway analyses, we selected six differentially methylated hub genes (NFATC1, TCF7, PDGFA, PRKCB, PRKCZ, ABCA1) and assessed their expression levels by q-RT-PCR. We found an up-regulation of selected genes in ACS patients vs HS (P < 0.001). ABCA1, TCF7, PDGFA, and PRKCZ gene expression was positively associated with CK-MB serum concentrations (r = 0.75, P = 0.03; r = 0.760, P = 0.029; r = 0.72, P = 0.044; r = 0.74, P = 0.035, respectively).This pilot study is the first single-base resolution map of DNA methylome by RRBS in CD4⁺ and CD8⁺ T cells and provides specific methylation signatures to clarify the role of aberrant methylation in ACS pathogenesis, thus supporting future research for novel epigenetic-sensitive biomarkers in the prevention and early diagnosis of this pathology.

DDR1 methylation is associated with bipolar disorder and the isoform expression and methylation of myelin genes

Aim: To investigate DDR1 methylation in the brains of bipolar disorder (BD) patients and its association with DDR1 mRNA levels and comethylation with myelin genes. Materials & methods: Genome-wide profiling of DNA methylation (Infinium MethylationEPIC BeadChip) corrected for glial composition and DDR1 gene expression analysis in the occipital cortices of individuals with BD (n = 15) and healthy controls (n = 15) were conducted. Results: DDR1 5-methylcytosine levels were increased and directly associated with DDR1b mRNA expression in the brains of BD patients. We also observed that DDR1 was comethylated with a group of myelin genes. Conclusion: DDR1 is hypermethylated in BD brain tissue and is associated with isoform expression. Additionally, DDR1 comethylation with myelin genes supports the role of this receptor in myelination.

Clinical epigenomics for cardiovascular disease: Diagnostics and therapies

The study of epigenomics has advanced in recent years to span the regulation of a single genetic locus to the structure and orientation of entire chromosomes within the nucleus. In this review, we focus on the challenges and opportunities of clinical epigenomics in cardiovascular disease. As an integrator of genetic and environmental inputs, and because of advances in measurement techniques that are highly reproducible and provide sequence information, the epigenome is a rich source of potential biosignatures of cardiovascular health and disease. Most of the studies to date have focused on the latter, and herein we discuss observations on epigenomic changes in human cardiovascular disease, examining the role of protein modifiers of chromatin, noncoding RNAs and DNA modification. We provide an overview of cardiovascular epigenomics, discussing the challenges of data sovereignty, data analysis, doctor-patient ethics and innovations necessary to implement precision health.

Hybrid genome de novo assembly with methylome analysis of the anaerobic thermophilic subsurface bacterium Thermanaerosceptrum fracticalcis strain DRI-13T

BACKGROUND

There is a dearth of sequenced and closed microbial genomes from environments that exceed > 500 m below level terrestrial surface. Coupled with even fewer cultured isolates, study and understanding of how life endures in the extreme oligotrophic subsurface environments is greatly hindered. Using a de novo hybrid assembly of Illumina and Oxford Nanopore sequences we produced a circular genome with corresponding methylome profile of the recently characterized thermophilic, anaerobic, and fumarate-respiring subsurface bacterium, Thermanaerosceptrum fracticalcis, strain DRI-13T to understand how this microorganism survives the deep subsurface.

RESULTS

The hybrid assembly produced a single circular genome of 3.8 Mb in length with an overall GC content of 45%. Out of the total 4022 annotated genes, 3884 are protein coding, 87 are RNA encoding genes, and the remaining 51 genes were associated with regulatory features of the genome including riboswitches and T-box leader sequences. Approximately 24% of the protein coding genes were hypothetical. Analysis of strain DRI-13T genome revealed: 1) energy conservation by bifurcation hydrogenase when growing on fumarate, 2) four novel bacterial prophages, 3) methylation profile including 76.4% N6-methyladenine and 3.81% 5-methylcytosine corresponding to novel DNA methyltransferase motifs. As well a cluster of 45 genes of unknown protein families that have enriched DNA mCpG proximal to the transcription start sites, and 4) discovery of a putative core of bacteriophage exclusion (BREX) genes surrounded by hypothetical proteins, with predicted functions as helicases, nucleases, and exonucleases.

CONCLUSIONS

The de novo hybrid assembly of strain DRI-13T genome has provided a more contiguous and accurate view of the subsurface bacterium T. fracticalcis, strain DRI-13T. This genome analysis reveals a physiological focus supporting syntrophy, non-homologous double stranded DNA repair, mobility/adherence/chemotaxis, unique methylome profile/recognized motifs, and a BREX defense system. The key to microbial subsurface survival may not rest on genetic diversity, but rather through specific syntrophy niches and novel methylation strategies.

Hairpin-Bisulfite PCR

Ligation of a hairpin oligonucleotide to genomic DNA prior to bisulfite conversion and PCR amplification physically links the two complementary DNA strands. This additional step in the conversion procedure overcomes the limitations of conventional bisulfite sequencing where information of the cytosine methylation status is only obtained from one of the two strands of an individual DNA molecule. Sequences derived from hairpin bisulfite PCR products reveal the dynamics of this epigenetic memory system on both strands of individual DNA molecules. The chapter describes a reliable step-by-step procedure to generate hairpin-linked DNA. It also provides a guide for efficient bisulfite conversion that is suitable for both conventional and hairpin bisulfite sequencing approaches.

DNA Methylation Regulates Transcription Factor-Specific Neurodevelopmental but Not Sexually Dimorphic Gene Expression Dynamics in Zebra Finch Telencephalon

Song learning in zebra finches (Taeniopygia guttata) is a prototypical example of a complex learned behavior, yet knowledge of the underlying molecular processes is limited. Therefore, we characterized transcriptomic (RNA-sequencing) and epigenomic (RRBS, reduced representation bisulfite sequencing; immunofluorescence) dynamics in matched zebra finch telencephalon samples of both sexes from 1 day post hatching (1 dph) to adulthood, spanning the critical period for song learning (20 and 65 dph). We identified extensive transcriptional neurodevelopmental changes during postnatal telencephalon development. DNA methylation was very low, yet increased over time, particularly in song control nuclei. Only a small fraction of the massive differential expression in the developing zebra finch telencephalon could be explained by differential CpG and CpH DNA methylation. However, a strong association between DNA methylation and age-dependent gene expression was found for various transcription factors (i.e., OTX2, AR, and FOS) involved in neurodevelopment. Incomplete dosage compensation, independent of DNA methylation, was found to be largely responsible for sexually dimorphic gene expression, with dosage compensation increasing throughout life. In conclusion, our results indicate that DNA methylation regulates neurodevelopmental gene expression dynamics through steering transcription factor activity, but does not explain sexually dimorphic gene expression patterns in zebra finch telencephalon.

Machine learning for deciphering cell heterogeneity and gene regulation

Epigenetics studies inheritable and reversible modifications of DNA that allow cells to control gene expression throughout their development and in response to environmental conditions. In computational epigenomics, machine learning is applied to study various epigenetic mechanisms genome wide. Its aim is to expand our understanding of cell differentiation, that is their specialization, in health and disease. Thus far, most efforts focus on understanding the functional encoding of the genome and on unraveling cell-type heterogeneity. Here, we provide an overview of state-of-the-art computational methods and their underlying statistical concepts, which range from matrix factorization and regularized linear regression to deep learning methods. We further show how the rise of single-cell technology leads to new computational challenges and creates opportunities to further our understanding of epigenetic regulation.

Koala methylomes reveal divergent and conserved DNA methylation signatures of X chromosome regulation

X chromosome inactivation (XCI) mediated by differential DNA methylation between sexes is an iconic example of epigenetic regulation. Although XCI is shared between eutherians and marsupials, the role of DNA methylation in marsupial XCI remains contested. Here, we examine genome-wide signatures of DNA methylation across fives tissues from a male and female koala (Phascolarctos cinereus), and present the first whole-genome, multi-tissue marsupial ‘methylome atlas’. Using these novel data, we elucidate divergent versus common features of representative marsupial and eutherian DNA methylation. First, tissue-specific differential DNA methylation in koalas primarily occurs in gene bodies. Second, females show significant global reduction (hypomethylation) of X chromosome DNA methylation compared to males. We show that this pattern is also observed in eutherians. Third, on average, promoter DNA methylation shows little difference between male and female koala X chromosomes, a pattern distinct from that of eutherians. Fourth, the sex-specific DNA methylation landscape upstream of Rsx, the primary lncRNA associated with marsupial XCI, is consistent with the epigenetic regulation of female-specific (and presumably inactive X chromosome-specific) expression. Finally, we use the prominent female X chromosome hypomethylation and classify 98 previously unplaced scaffolds as X-linked, contributing an additional 14.6 Mb (21.5%) to genomic data annotated as the koala X chromosome. Our work demonstrates evolutionarily divergent pathways leading to functionally conserved patterns of XCI in two deep branches of mammals.

Epigenetic Landscape of Liquid Biopsy in Colorectal Cancer

Colorectal cancer (CRC) is one of the most common malignancies and is a major cause of cancer-related deaths worldwide. Thus, there is a clinical need to improve early detection of CRC and personalize therapy for patients with this disease. In the era of precision oncology, liquid biopsy has emerged as a major approach to characterize the circulating tumor elements present in body fluids, including cell-free DNA and RNA, circulating tumor cells, and extracellular vesicles. This non-invasive tool has allowed the identification of relevant molecular alterations in CRC patients, including some indicating the disruption of epigenetic mechanisms. Epigenetic alterations found in solid and liquid biopsies have shown great utility as biomarkers for early detection, prognosis, monitoring, and evaluation of therapeutic response in CRC patients. Here, we summarize current knowledge of the most relevant epigenetic mechanisms associated with cancer development and progression, and the implications of their deregulation in cancer cells and liquid biopsy of CRC patients. In particular, we describe the methodologies used to analyze these epigenetic alterations in circulating tumor material, and we focus on the clinical utility of epigenetic marks in liquid biopsy as tumor biomarkers for CRC patients. We also discuss the great challenges and emerging opportunities of this field for the diagnosis and personalized management of CRC patients.

A novel computational strategy for DNA methylation imputation using mixture regression model (MRM)

BACKGROUND

DNA methylation is an important heritable epigenetic mark that plays a crucial role in transcriptional regulation and the pathogenesis of various human disorders. The commonly used DNA methylation measurement approaches, e.g., Illumina Infinium HumanMethylation-27 and -450 BeadChip arrays (27 K and 450 K arrays) and reduced representation bisulfite sequencing (RRBS), only cover a small proportion of the total CpG sites in the human genome, which considerably limited the scope of the DNA methylation analysis in those studies.

RESULTS

We proposed a new computational strategy to impute the methylation value at the unmeasured CpG sites using the mixture of regression model (MRM) of radial basis functions, integrating information of neighboring CpGs and the similarities in local methylation patterns across subjects and across multiple genomic regions. Our method achieved a better imputation accuracy over a set of competing methods on both simulated and empirical data, particularly when the missing rate is high. By applying MRM to an RRBS dataset from subjects with low versus high bone mineral density (BMD), we recovered methylation values of ~ 300 K CpGs in the promoter regions of chromosome 17 and identified some novel differentially methylated CpGs that are significantly associated with BMD.

CONCLUSIONS

Our method is well applicable to the numerous methylation studies. By expanding the coverage of the methylation dataset to unmeasured sites, it can significantly enhance the discovery of novel differential methylation signals and thus reveal the mechanisms underlying various human disorders/traits.

Comparison of methylation capture sequencing and Infinium MethylationEPIC array in peripheral blood mononuclear cells

Background

Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium MethylationEPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price.

Methods

Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000 ng), medium (300–1000 ng), and low (150 ng–300 ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array.

Results

After quality control, an average of 3,708,550 CpG sites per sample were detected by MC-seq with DNA quantity > 1000 ng. Reproducibility of DNA methylation in MC-seq-detected CpG sites was high among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98–0.99). However, methylation for a small proportion of CpGs (N = 235) differed significantly between the two platforms, with differences in beta values of greater than 0.5.

Conclusions

Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.

Detect differentially methylated regions using non-homogeneous hidden Markov model for bisulfite sequencing data

DNA methylation plays an important role in many biological processes and diseases. With the rise of the whole genome bisulfite sequencing technique, aberrant methylation patterns can now be detected by comparing paired normal and disease samples at the single nucleotide level. We develop a novel Bayesian method for detecting differentially methylated regions from paired bisulfite sequencing data, and implement it as a R package called BSDMR. Based on a non-homogeneous hidden Markov model, BSDMR provides a better modeling strategy for the spatial correlation between CpG sites and takes into consideration the relationship between methylation signals from normal and disease samples. Simulations show that BSDMR performs well even under low read depth and has a smaller false discovery rates than existing methods. We also apply BSDMR to the colon cancer data from Gene Expression Omnibus. The detected DMRs are well supported by existing biomedical literatures.

A DNA methylation signature discriminates between excellent and non-response to lithium in patients with bipolar disorder type 1

Lithium (Li) is the cornerstone maintenance treatment for bipolar disorders (BD), but response rates are highly variable. To date, no clinical or biological marker is available to reliably define eligibility criteria for a maintenance treatment with Li. We examined whether the prophylactic response to Li (assessed retrospectively) is associated with distinct blood DNA methylation profiles. Bisulfite-treated total blood DNA samples from individuals with BD type 1 (15 excellent-responders (LiERs) versus 11 non-responders (LiNRs)) were used for targeted enrichment of CpG rich genomic regions followed by high-resolution next-generation sequencing to identify differentially methylated regions (DMRs). After controlling for potential confounders we identified 111 DMRs that significantly differ between LiERs and LiNRs with a significant enrichment in neuronal cell components. Logistic regression and receiver operating curves identified a combination of 7 DMRs with a good discriminatory power for response to Li (Area Under the Curve 0.806). Annotated genes associated with these DMRs include Eukaryotic Translation Initiation Factor 2B Subunit Epsilon (EIF2B5), Von Willebrand Factor A Domain Containing 5B2 (VWA5B2), Ral GTPase Activating Protein Catalytic Alpha Subunit 1 (RALGAPA1). Although preliminary and deserving replication, these results suggest that biomarkers of response to Li may be identified through peripheral epigenetic measures.

Application of Next-Generation Sequencing in Neurodegenerative Diseases: Opportunities and Challenges

Genetic factors (gene mutations) lead to various rare and prevalent neurological diseases. Identification of underlying mutations in neurodegenerative diseases is of paramount importance due to the heterogeneous nature of the genome and different clinical manifestations. An early and accurate molecular diagnosis are cardinal for neurodegenerative patients to undergo proper therapeutic regimens. The next-generation sequencing (NGS) method examines up to millions of sequences at a time. As a result, the rare molecular diagnoses, previously presented with "unknown causes", are now possible in a short time. This method generates a large amount of data that can be utilized in patient management. Since each person has a unique genome, the NGS has transformed diagnostic and therapeutic strategies into sequencing and individual genomic mapping. However, this method has disadvantages like other diagnostic methods. Therefore, in this review, we aimed to briefly summarize the NGS method and correlated studies to unravel the genetic causes of neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, epilepsy, and MS. Finally, we discuss the NGS challenges and opportunities in neurodegenerative diseases.

Quantitative comparison of within-sample heterogeneity scores for DNA methylation data

DNA methylation is an epigenetic mark with important regulatory roles in cellular identity and can be quantified at base resolution using bisulfite sequencing. Most studies are limited to the average DNA methylation levels of individual CpGs and thus neglect heterogeneity within the profiled cell populations. To assess this within-sample heterogeneity (WSH) several window-based scores that quantify variability in DNA methylation in sequencing reads have been proposed. We performed the first systematic comparison of four published WSH scores based on simulated and publicly available datasets. Moreover, we propose two new scores and provide guidelines for selecting appropriate scores to address cell-type heterogeneity, cellular contamination and allele-specific methylation. Most of the measures were sensitive in detecting DNA methylation heterogeneity in these scenarios, while we detected differences in susceptibility to technical bias. Using recently published DNA methylation profiles of Ewing sarcoma samples, we show that DNA methylation heterogeneity provides information complementary to the DNA methylation level. WSH scores are powerful tools for estimating variance in DNA methylation patterns and have the potential for detecting novel disease-associated genomic loci not captured by established statistics. We provide an R-package implementing the WSH scores for integration into analysis workflows.

Performance of Mapping Approaches for Whole-Genome Bisulfite Sequencing Data in Crop Plants

DNA methylation is involved in many different biological processes in the development and well-being of crop plants such as transposon activation, heterosis, environment-dependent transcriptome plasticity, aging, and many diseases. Whole-genome bisulfite sequencing is an excellent technology for detecting and quantifying DNA methylation patterns in a wide variety of species, but optimized data analysis pipelines exist only for a small number of species and are missing for many important crop plants. This is especially important as most existing benchmark studies have been performed on mammals with hardly any repetitive elements and without CHG and CHH methylation. Pipelines for the analysis of whole-genome bisulfite sequencing data usually consists of four steps: read trimming, read mapping, quantification of methylation levels, and prediction of differentially methylated regions (DMRs). Here we focus on read mapping, which is challenging because un-methylated cytosines are transformed to uracil during bisulfite treatment and to thymine during the subsequent polymerase chain reaction, and read mappers must be capable of dealing with this cytosine/thymine polymorphism. Several read mappers have been developed over the last years, with different strengths and weaknesses, but their performances have not been critically evaluated. Here, we compare eight read mappers: Bismark, BismarkBwt2, BSMAP, BS-Seeker2, Bwameth, GEM3, Segemehl, and GSNAP to assess the impact of the read-mapping results on the prediction of DMRs. We used simulated data generated from the genomes of Arabidopsis thaliana, Brassica napus, Glycine max, Solanum tuberosum, and Zea mays, monitored the effects of the bisulfite conversion rate, the sequencing error rate, the maximum number of allowed mismatches, as well as the genome structure and size, and calculated precision, number of uniquely mapped reads, distribution of the mapped reads, run time, and memory consumption as features for benchmarking the eight read mappers mentioned above. Furthermore, we validated our findings using real-world data of Glycine max and showed the influence of the mapping step on DMR calling in WGBS pipelines. We found that the conversion rate had only a minor impact on the mapping quality and the number of uniquely mapped reads, whereas the error rate and the maximum number of allowed mismatches had a strong impact and leads to differences of the performance of the eight read mappers. In conclusion, we recommend BSMAP which needs the shortest run time and yields the highest precision, and Bismark which requires the smallest amount of memory and yields precision and high numbers of uniquely mapped reads.

A Novel Application of Mixed Effects Models for Reconciling Base-Pair Resolution 5-Methylcytosine and 5-Hydroxymethylcytosine Data in Neuroepigenetics

Epigenetic marks operate at multiple chromosomal levels to regulate gene expression, from direct covalent modification of DNA to three-dimensional chromosomal structure. Research has shown that 5-methylcytosine (5-mC) and its oxidized form, 5-hydroxymethylcytosine (5-hmC), are stable epigenetic marks with distinct genomic distributions and separate regulatory functions. In addition, recent data indicate that 5-hmC plays a critical regulatory role in the mammalian brain, emphasizing the importance of considering this alternative DNA modification in the context of neuroepigenetics. Traditional bisulfite (BS) treatment-based methods to measure the methylome are not able to distinguish between 5-mC and 5-hmC, meaning much of the existing literature does not differentiate these two DNA modifications. Recently developed methods, including Tet-assisted bisulfite treatment and oxidative bisulfite treatment, allow for differentiation of 5-hmC and/or 5-mC levels at base-pair resolution when combined with next-generation sequencing or methylation arrays. Despite these technological advances, there remains a lack of clarity regarding the appropriate statistical methods for integration of 5-mC and 5-hmC data. As a result, it can be difficult to determine the effects of an experimental treatment on 5-mC and 5-hmC dynamics. Here, we propose a statistical approach involving mixed effects to simultaneously model paired 5-mC and 5-hmC data as repeated measures. We tested this approach using publicly available BS/oxidative bisulfite-450K array data and showed that our new approach detected far more CpG probes with paired changes in 5-mC and 5-hmC by Alzheimer’s disease status (n = 14,183 probes) compared with the overlapping differential probes generated from separate models for each epigenetic mark (n = 68). Of note, all 68 of the overlapping probe IDs from the separate models were also significant in our new modeling approach, supporting the sensitivity of our new analysis method. Using the proposed approach, it will be possible to determine the effects of an experimental treatment on both 5-mC and 5-hmC at the base-pair level.

Battle of epigenetic proportions: comparing Illumina's EPIC methylation microarrays and TruSeq targeted bisulfite sequencing

DNA methylation microarrays have been the platform of choice for epigenome-wide association studies in epidemiology, but declining costs have rendered targeted bisulphite sequencing a feasible alternative. Nonetheless, the literature for researchers seeking guidance on which platform to choose is sparse. To fill this gap, we conducted a comparison study in which we processed cord blood samples from four newborns in duplicates using both the Illumina HumanMethylationEPIC BeadChip and the Illumina TruSeq Methyl Capture EPIC Kit, and evaluated both platforms in regard to coverage, reproducibility, and identification of differential methylation. We conclude that with current analytic goals microarrays still outperform bisulphite sequencing for precise quantification of DNA methylation.

Umap and Bismap: quantifying genome and methylome mappability

Short-read sequencing enables assessment of genetic and biochemical traits of individual genomic regions, such as the location of genetic variation, protein binding and chemical modifications. Every region in a genome assembly has a property called 'mappability', which measures the extent to which it can be uniquely mapped by sequence reads. In regions of lower mappability, estimates of genomic and epigenomic characteristics from sequencing assays are less reliable. These regions have increased susceptibility to spurious mapping from reads from other regions of the genome with sequencing errors or unexpected genetic variation. Bisulfite sequencing approaches used to identify DNA methylation exacerbate these problems by introducing large numbers of reads that map to multiple regions. Both to correct assumptions of uniformity in downstream analysis and to identify regions where the analysis is less reliable, it is necessary to know the mappability of both ordinary and bisulfite-converted genomes. We introduce the Umap software for identifying uniquely mappable regions of any genome. Its Bismap extension identifies mappability of the bisulfite-converted genome. A Umap and Bismap track hub for human genome assemblies GRCh37/hg19 and GRCh38/hg38, and mouse assemblies GRCm37/mm9 and GRCm38/mm10 is available at https://bismap.hoffmanlab.org for use with genome browsers.

Redefining the IBDs using genome-scale molecular phenotyping

The IBDs, Crohn's disease and ulcerative colitis, are chronic inflammatory conditions of the gastrointestinal tract resulting from an aberrant immune response to enteric microbiota in genetically susceptible individuals. Disease presentation and progression within and across IBDs, especially Crohn's disease, are highly heterogeneous in location, severity of inflammation and other phenotypes. Current clinical classifications fail to accurately predict disease course and response to therapies. Genome-wide association studies have identified >240 loci that confer risk of IBD, but the clinical utility of these findings remains unclear, and mechanisms by which the genetic variants contribute to disease are largely unknown. In the past 5 years, the profiling of genome-wide gene expression, epigenomic features and gut microbiota composition in intestinal tissue and faecal samples has uncovered distinct molecular signatures that define IBD subtypes, including within Crohn's disease and ulcerative colitis. In this Review, we summarize studies in both adult and paediatric patients that have identified different IBD subtypes, which in some cases have been associated with distinct clinical phenotypes. We posit that genome-scale molecular phenotyping in large cohorts holds great promise not only to further our understanding of the diverse molecular causes of IBD but also for improving clinical trial design to develop more personalized disease management and treatment.

An Epigenome-Wide DNA Methylation Map of Testis in Pigs for Study of Complex Traits

Epigenetic changes are important for understanding complex trait variation and inheritance in pigs that are also a valuable biomedical model for human health research. Testis is the main organ for reproduction and boar taint in pigs; however, there have been no studies to-date on adult pig testis epigenome. The main objective of this study was to establish a genome-wide DNA methylation map of pig testis that would help identify candidate epigenetic biomarkers and methylated genes for complex traits such as male reproduction, fertility or boar taint. Reduced Representation Bisulfite Sequencing (RRBS) was used to study methylation levels of cytosine in nine pig testis samples. The results showed that genome-wide methylation status of nine samples overlapped greatly and their variation among pigs were low. The methylation levels of promoter, exon, intron, cytosine and guanine dinucleotide (CpG) islands and CpG island shores regions were 0.15, 0.47, 0.55, 0.39, and 0.53, respectively. Cytosines binding to CpG islands showed different methylation levels between exon and intron regions. All methylation levels of CpG islands were lower than CpG island shores in different genic features. The distribution of 12,738 differentially methylated cytosines (DMCs) within CpG islands, CpG island shores and other regions was 36.86, 21.65, and 41.49%, respectively, and was 0.33, 1.71, 5.95, and 92.01% in promoter, exon, intron and intergenic regions, respectively. Methylation levels of DMCs in promoter, exon and intron regions were significantly different between CpG islands and CpG island shores (P < 0.05). A total of 898 genes with 2089 DMCs were enriched in 112 Gene Ontology (GO) terms. Fifteen methylated genes from our study were associated with fertility or boar taint traits. Our analysis revealed the methylation patterns in different genic features and CpG island regions of testis in pigs, and summarized several candidate genes associated with DMCs and the involved GO terms. These findings are helpful to understand the relationship between DNA methylation and genic CpG islands, to provide candidate epigenetic regions or biomarkers for pig production and welfare and for translational epigenomic studies that use pigs as an animal model for human research.

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.

Statistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data

High-throughput bisulfite methylation sequencing such as reduced representation bisulfite sequencing (RRBS), Agilent SureSelect Human Methyl-Seq (Methyl-seq) or whole-genome bisulfite sequencing is commonly used for base resolution methylome research. These data are represented either by the ratio of methylated cytosine versus total coverage at a CpG site or numbers of methylated and unmethylated cytosines. Multiple statistical methods can be used to detect differentially methylated CpGs (DMCs) between conditions, and these methods are often the base for the next step of differentially methylated region identification. The ratio data have a flexibility of fitting to many linear models, but the raw count data take consideration of coverage information. There is an array of options in each datatype for DMC detection; however, it is not clear which is an optimal statistical method. In this study, we systematically evaluated four statistic methods on methylation ratio data and four methods on count-based data and compared their performances with regard to type I error control, sensitivity and specificity of DMC detection and computational resource demands using real RRBS data along with simulation. Our results show that the ratio-based tests are generally more conservative (less sensitive) than the count-based tests. However, some count-based methods have high false-positive rates and should be avoided. The beta-binomial model gives a good balance between sensitivity and specificity and is preferred method. Selection of methods in different settings, signal versus noise and sample size estimation are also discussed.

Applying circulating tumor DNA methylation in the diagnosis of lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. Low dose computed tomography (LDCT) is commonly used for disease screening, with identified candidate cancerous regions further diagnosed using tissue biopsy. However, existing techniques are all invasive and unavoidably cause multiple complications. In contrast, liquid biopsy is a noninvasive, ideal surrogate for tissue biopsy that can identify circulating tumor DNA (ctDNA) containing tumorigenic signatures. It has been successfully implemented to assist treatment decisions and disease outcome prediction. ctDNA methylation, a type of lipid biopsy that profiles critical epigenetic alterations occurring during carcinogenesis, has gained increasing attention. Indeed, aberrant ctDNA methylation occurs at early stages in lung malignancy and therefore can be used as an alternative for the early diagnosis of lung cancer. In this review, we give a brief synopsis of the biological basis and detecting techniques of ctDNA methylation. We then summarize the latest progress in use of ctDNA methylation as a diagnosis biomarker. Lastly, we discuss the major issues that limit application of ctDNA methylation in the clinic, and propose possible solutions to enhance its usage.

DNA methylation correlates of PTSD: Recent findings and technical challenges

There is increasing evidence that epigenetic factors play a critical role in posttraumatic stress disorder (PTSD), by mediating the impact of environmental exposures to trauma on the regulation of gene expression. DNA methylation is one epigenetic process that has been highly studied in PTSD. This review will begin by providing an overview of DNA methylation (DNAm) methods, and will then highlight two major biological systems that have been identified in the epigenetic regulation in PTSD: (a) the immune system and (b) the stress response system. In addition to candidate gene approaches, we will review novel strategies to study epigenome-wide PTSD-related effects, including epigenome-wide algorithms that distill information from many loci into a single summary score (e.g., measures of "epigenetic age" which have been associated with PTSD). This review will also cover recent epigenome wide association studies (EWAS) of PTSD, and biological pathway models used to identify gene sets enriched in PTSD. Finally, we address technical and methodological advances and challenges to the field, and highlight exciting directions for future research.

Computational and Statistical Analysis of Array-Based DNA Methylation Data

The characterization of aberrant DNA methylation is emerging as a key part of the study of cancer development and phenotype. The technical advancements and decreasing costs of methods for high-throughput profiling of DNA methylation have brought about a high interest in the use of such methods in disease association studies. Here we discuss the principles for DNA methylation analysis using data from the Infinium DNA methylation BeadChip assays and describe the computational steps and statistical considerations going from processing of the raw array data to analysis of differential methylation. Moreover, we provide detailed guidelines on how to perform tumor subtype classification based on DNA methylation signatures.

Advances in detection and quantification of methylcytosine and its derivatives

Methylation of the fifth carbon atom in cytosine is an epigenetic modification of deoxyribonucleic acid that plays important roles in numerous cellular processes and disease pathogenesis. Three additional states of cytosine, that is, 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxylcytosine, have been identified and associated with the diagnosis and/or prognosis of diseases. However, accurate measurement of those intermediates is a challenge since their global levels are relatively low. A number of innovative methods have been developed to detect and quantify these compounds in biological samples, such as blood, tissue and urine, etc. This review focuses on recent advancement in detection and quantification of four cytosine modifications, based on which, the development, diagnosis, and prognosis of diseases could be monitored through non-invasive procedures.