Enzymatic methyl sequencing detects DNA methylation at single-base resolution from picograms of DNA

TET-mediated 5hmC in breast cancer: mechanism and clinical potential

Breast cancer is the most common cancer among women, with differences in clinical features due to its distinct molecular subtypes. Current studies have demonstrated that epigenetic modifications play a crucial role in regulating the progression of breast cancer. Among these mechanisms, DNA demethylation and its reverse process have been studied extensively for their roles in activating or silencing cancer related gene expression. Specifically, Ten-Eleven Translocation (TET) enzymes are involved in the conversion process from 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), which results in a significant difference in the global level of 5hmC in breast cancer compared with normal tissues. In this review, we summarize the functions of TET proteins and the regulated 5hmC levels in the pathogenesis of breast cancer. Discussions on the clinical values of 5hmC in early diagnosis and the prediction of prognosis are also mentioned.

Normal bronchial field basal cells show persistent methylome-wide impact of tobacco smoking, including in known cancer genes

Lung carcinogenesis is causally linked to cigarette smoking, in part by epigenetic changes. We tested whether accumulated epigenetic change in smokers is apparent in bronchial basal cells as cells of origin of squamous cell carcinoma. Using an EM-seq platform covering 53.8 million CpGs (96% of the entire genome) at an average of 7.5 sequencing reads per CpG site at a single base resolution, we evaluated cytology-normal basal cells bronchoscopically brushed from the in situ tobacco smoke-exposed 'bronchial epithelial field' and isolated by short-term primary culture from 54 human subjects. We found that mean methylation was globally lower in ever (former and current) smokers versus never smokers (p = 0.0013) across promoters, CpG shores, exons, introns, 3'-UTRs, and intergenic regions, but not in CpG islands. Among 6mers with dinucleotides flanking CpG, those containing CGCG showed no effect from smoking, while those flanked with TT and AA displayed the strongest effects. At the gene level, smoking-related differences in methylation level were observed in CDKL1, ARTN, EDC3, CYP1B1, FAM131A, and MAGI2. Among candidate cancer genes, smoking reduced the methylation level in KRAS, ROS1, CDKN1A, CHRNB4, and CADM1. We conclude that smoking reduces long-term epigenome-wide methylation in bronchial stem cells, is impacted by the flanking sequence, and persists indefinitely beyond smoking cessation.

Evolution of genome-wide methylation profiling technologies

In this mini-review, we explore the advancements in genome-wide DNA methylation profiling, tracing the evolution from traditional methods such as methylation arrays and whole-genome bisulfite sequencing to the cutting-edge single-molecule profiling enabled by long-read sequencing (LRS) technologies. We highlight how LRS is transforming clinical and translational research, particularly by its ability to simultaneously measure genetic and epigenetic information, providing a more comprehensive understanding of complex disease mechanisms. We discuss current challenges and future directions in the field, emphasizing the need for innovative computational tools and robust, reproducible approaches to fully harness the capabilities of LRS in molecular diagnostics.

Accurate cross-species 5mC detection for Oxford Nanopore sequencing in plants with DeepPlant

Nanopore sequencing enables comprehensive detection of 5-methylcytosine (5mC), particularly in repeat regions. However, CHH methylation detection in plants is limited by the scarcity of high-methylation positive samples, reducing generalization across species. Dorado, the only tool for plant 5mC detection on the R10.4 platform, lacks extensive species testing. Here, we develop DeepPlant, a deep learning model incorporating both Bi-LSTM and Transformer architectures, which significantly improves CHH detection accuracy and performs well for CpG and CHG motifs. We address the scarcity of methylation-positive CHH training samples through screening species with abundant high-methylation CHH sites using bisulfite-sequencing and generate datasets that cover diverse 9-mer motifs for training and testing DeepPlant. Evaluated across nine species, DeepPlant achieves high whole-genome methylation frequency correlations (0.705-0.838) with BS-seq data on CHH, improved by 23.4- 117.6% compared to Dorado. DeepPlant also demonstrates superior single-molecule accuracy and F1 score, offering strong generalization for plant epigenetics research.

Epigenetics factors in schizophrenia: future directions for etiologic and therapeutic study approaches

Schizophrenia is a complex, heterogeneous, and highly disabling severe mental disorder whose pathogenesis has not yet been fully elucidated. Epigenetics, as a bridge between genetic and environmental factors, plays an important role in the pathophysiology of schizophrenia. Over the past decade, epigenetic-wide association studies have rapidly become an important branch of psychiatric research, especially in deciphering the molecular mechanisms of schizophrenia. This review systematically analyzes recent advances in epigenome-wide association studies (EWAS) of schizophrenia, focusing on technological developments. We synthesize findings from large-scale EWAS alongside emerging evidence on DNA methylation patterns, histone modifications, and regulatory networks, emphasizing their roles in disease mechanisms and treatment responses. In addition, this review provides a prospective outlook, evaluating the impact that technological developments may have on future studies of schizophrenia. With the continuous advancement of high-throughput sequencing technology and the increasing maturity of big data analysis methods, epigenetics is expected to have a significant impact on the early diagnosis, prognosis assessment and even personalized treatment of schizophrenia.

Comparative performance evaluation of bisulfite- and enzyme-based DNA conversion methods

BACKGROUND

Bisulfite conversion (BC) has been the gold standard in DNA methylation profiling for decades. During this chemical process, non-methylated cytosines are converted into uracils, while methylated cytosines remain intact. Despite its popularity, BC has major drawbacks when used for sensitive applications with low-quality and -quantity DNA samples, such as the required large amount of DNA input, the caused DNA fragmentation and loss, and the resulting reduced sequence complexity. Lately, to account for BC-related disadvantages the first commercial enzymatic conversion (EC) kit was launched. While EC follows the same conversion principle as BC it uses two enzymatic steps instead of one chemical step with BC. In this study, we validated and compared the conversion performance of the most widely used BC and EC kits using a multiplex qPCR assay (qBiCo) we recently developed, which provides several indexes: conversion efficiency, converted DNA recovery and fragmentation.

RESULTS

Firstly, we implemented and standardized both DNA conversion methods. Secondly, using qBiCo, we performed a developmental validation for both conversion approaches, including testing the following parameters: repeatability, reproducibility, sensitivity and robustness. Regarding conversion efficiency, both methods performed similarly, with the limit of reproducible conversion being 5 ng and 10 ng for BC and EC, respectively. The recovery, however, is structurally overestimated for BC: 2.3 ± 0.7 and 0.7 ± 0.2 for EC. In contrast, degraded DNA input resulted in high fragmentation values after BC and low-medium values for EC (14.4 ± 1.2 and 3.3 ± 0.4, respectively). Finally, we converted 10 ng of 22 genomic DNA samples using both methods. We observed an overestimation of the BC DNA recovery (130%) and a low recovery for EC (40%).

CONCLUSIONS

Our findings indicate that both DNA conversion methods have strengths and weaknesses. BC shows a high recovery, whereas EC does not cause extensive fragmentation that is characteristic to BC. EC is, therefore, more robust to the analysis of degraded DNA such as forensic-type or cell-free DNA, at least for the genomic DNA inputs tested here. We believe that the low recovery of EC could be improved by further optimizing and automating the bead-based cleanup steps. Overall, our study provides the first independent benchmarking of bisulfite- and enzyme-based conversion kits.

Developmental epigenetic programming by Tet1/3 determines peripheral CD8 T cell fate

In response to infections, naive CD8 T cells give rise to effector and memory T cells. However, eliciting long-lived memory CD8 T cells remains a challenge for many infections. DNA demethylation of cytosines within CpG dinucleotides by Tet enzymes is a key epigenetic mechanism that regulates short- and long-term transcriptional programs in cells. Currently, their roles in modulating CD8 T-cell effector and memory differentiation are unclear. Here, we report that developing CD8 T cells lacking Tet1/3 preferentially differentiate into short-lived effector and effector memory cells following acute infection. Using genome-wide analyses, mice in which Tet1/3 were ablated during T-cell development and mature CD8 T cells, respectively, we show that Tet1/3 regulates these cell fates by licensing the chromatin landscape of genes downstream of T-cell receptor activation during thymic T-cell maturation. However, in mature CD8 T cells, Tet1/3 are dispensable for effector and memory cell fates. These findings unveil context-specific roles of DNA demethylation, which are essential for defining pathways that contribute to CD8 memory T-cell generation in response to infections.

Assessing the virological response to direct-acting antiviral therapies in the HBV cure programme

Hepatitis B virus (HBV) is a global health problem with over 250 million people affected worldwide. Nucleos(t)ide analogues remain the standard of care and suppress production of progeny virions; however, they have limited effect on the viral transcriptome and long-term treatment is associated with off-target toxicities. Promising results are emerging from clinical trials and several drug classes have been evaluated, including capsid assembly modulators and RNA interfering agents. Whilst peripheral biomarkers are used to monitor responses and define treatment endpoints, they fail to reflect the full reservoir of infected hepatocytes. Given these limitations, consideration should be given to the merits of sampling liver tissue, especially in the context of clinical trials. In this review article, we will discuss methods for profiling HBV in liver tissue and their value to the HBV cure programme.

Noninvasive Multicancer Detection Using DNA Hypomethylation of LINE-1 Retrotransposons

PURPOSE

The detection of ctDNA, which allows noninvasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge.

EXPERIMENTAL DESIGN

We implemented a new, highly sensitive strategy to detect bp resolution methylation patterns from plasma DNA and assessed the potential of hypomethylation of long interspersed nuclear element-1 retrotransposons as a noninvasive multicancer detection biomarker. The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method targets 30 to 40,000 young long interspersed nuclear element-1 retrotransposons scattered throughout the genome, covering about 100,000 CpG sites and is based on a reference-free analysis pipeline.

RESULTS

Resulting machine learning-based classifiers showed powerful correct classification rates discriminating healthy and tumor plasmas from six types of cancers (colorectal, breast, lung, ovarian, and gastric cancers and uveal melanoma, including localized stages) in two independent cohorts (AUC = 88%-100%, N = 747). The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method can also be used to perform copy number alteration analysis that improves cancer detection.

CONCLUSIONS

This should lead to the development of more efficient noninvasive diagnostic tests adapted to all patients with cancer, based on the universality of these factors. See related commentary by Szymanski et al., p. 1179.

Pig and quail CpG methylation datasets from short and long read sequencing technologies

CpG methylation, a key epigenetic mark involved in gene regulation, development, and other biological processes, is commonly analyzed using Whole-Genome Bisulfite Sequencing (WGBS). However, bisulfite treatment causes significant DNA degradation. Enzymatic Methyl-seq (EM-seq) offers a short-read alternative that preserves DNA integrity but requires conversion steps, limiting its compatibility with downstream analyses. Third-generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and PacBio, enable direct detection of DNA modifications without altering the DNA, providing simultaneous genome and epigenome information. This work presents a comprehensive dataset combining long- and short-read sequencing data, including ONT, PacBio, Enzymatic Methyl-seq, and WGBS, for two agronomically relevant species: pig (Sus scrofa) and quail (Coturnix japonica). Data quality evaluation reveals high nucleotide quality scores for PacBio and short reads, robust alignment rates for long reads, and inter-method correlations in CpG methylation calling ranging from 0.76 to 0.99. This dataset is a valuable resource for training methylation callers and represents the first combined methylation dataset for these species, providing an essential benchmark for assessing emerging sequencing technologies.

Computational analysis of DNA methylation from long-read sequencing

DNA methylation is a critical epigenetic mechanism in numerous biological processes, including gene regulation, development, ageing and the onset of various diseases such as cancer. Studies of methylation are increasingly using single-molecule long-read sequencing technologies to simultaneously measure epigenetic states such as DNA methylation with genomic variation. These long-read data sets have spurred the continuous development of advanced computational methods to gain insights into the roles of methylation in regulating chromatin structure and gene regulation. In this Review, we discuss the computational methods for calling methylation signals, contrasting methylation between samples, analysing cell-type diversity and gaining additional genomic insights, and then further discuss the challenges and future perspectives of tool development for DNA methylation research.

Prospective, multicenter validation of a platform for rapid molecular profiling of central nervous system tumors

Molecular data integration plays a central role in central nervous system (CNS) tumor diagnostics but currently used assays pose limitations due to technical complexity, equipment and reagent costs, as well as lengthy turnaround times. We previously reported the development of Rapid-CNS2, an adaptive-sampling-based nanopore sequencing workflow. Here we comprehensively validated and further developed Rapid-CNS2 for intraoperative use. It now offers real-time methylation classification and DNA copy number information within a 30-min intraoperative window, followed by comprehensive molecular profiling within 24 h, covering the complete spectrum of diagnostically and therapeutically relevant information for the respective entity. We validated Rapid-CNS2 in a multicenter setting on 301 archival and prospective samples including 18 samples sequenced intraoperatively. To broaden the utility of methylation-based CNS tumor classification, we developed MNP-Flex, a platform-agnostic methylation classifier encompassing 184 classes. MNP-Flex achieved 99.6% accuracy for methylation families and 99.2% accuracy for methylation classes with clinically applicable thresholds across a global validation cohort of more than 78,000 frozen and formalin-fixed paraffin-embedded samples spanning five different technologies. Integration of these tools has the potential to advance CNS tumor diagnostics by providing broad access to rapid, actionable molecular insights crucial for personalized treatment strategies.

Sperm DNA methylation landscape and its links to male fertility in a non-model teleost using EM-seq

Differential DNA methylation due to epigenetic phenomena is crucial in regulating gene expression. Understanding the consequences of such differential expression on sperm quality parameters may provide insights into the underlying mechanisms of male reproductive success. Nonetheless, male fertility in fish remains understudied despite its critical importance to overall reproductive success in nature and captivity. This study investigated the DNA methylation landscape in spermatozoa of domesticated Arctic charr (Salvelinus alpinus) and its associations with sperm quality parameters. Computer assisted-semen analysis (CASA) was performed in 47 sperm samples of farmed Arctic charr, followed by enzymatic methylation sequencing (EM-seq). Our results showed that the DNA of Arctic charr sperm is highly methylated (mean value of ~86%), though variations were observed in genomic features involved in gene regulation. Methylation at variable CpG sites exhibited regional correlation decaying by physical distance, while methylation similarities among individuals were strongly coupled with genetic variation and mirrored pedigree structure. Comethylation network analyses for promoters, CpG islands and first introns revealed genomic modules significantly correlated with sperm quality traits (p < 0.05; Bonferroni adjusted), with distinct patterns suggesting a resource trade-off between sperm concentration and kinematics. Furthermore, annotation and gene-set enrichment analysis highlighted biological mechanisms related to spermatogenesis, cytoskeletal regulation, and mitochondrial function, all vital to sperm physiology. These findings suggest that DNA methylation is a critical and fundamental factor influencing male fertility in Arctic charr, providing insights into the underlying mechanisms of male reproductive success.

Variable performance of widely used bisulfite sequencing methods and read mapping software for DNA methylation

DNA methylation (DNAm) is the most commonly studied marker in ecological epigenetics, yet the performance of popular library preparation strategies and bioinformatic tools is seldom assessed and compared in genetically variable natural populations. We profiled DNAm using reduced representation bisulfite sequencing (RRBS) and whole genome bisulfite sequencing (WGBS), including technical and biological replicates from lab-reared and wild-caught threespine stickleback ( Gasterosteus aculeatus ). We then compared how the most commonly used read mapper and methylation caller (Bismark) performed relative to two alternative pipelines (BWA mem or BWA meth read mappers analyzed with MethyDackel). BWA meth provided 50% higher mapping efficiency than BWA mem and 45% higher efficiency than Bismark. Despite differences in mapping efficiency, BWA meth and Bismark produced highly similar methylation profiles, while BWA mem systematically discarded unmethylated cytosines. Sequencing depth filters had large impacts on CpG sites recovered across multiple individuals, with the largest impact on WGBS data. Notably, the prevalence of CpG sites with intermediate methylation levels is greatly reduced in RRBS data compared to WGBS, which may have important consequences for functional interpretations. We conclude by discussing how library construction and bisulfite alignment wrappers can influence SNP filtering, genomic coverage, and the abundance and reliability of data available for downstream analysis. Our analyses suggest that researchers studying genetically variable populations may prioritize filtering SNPs by constructing RRBS libraries with small insert sizes and paired end reads, which is counter to conventional wisdom.

Methylation pseudotime analysis for label-free profiling of the temporal chromatin landscape with long-read sequencing

Faithful epigenetic inheritance across cell divisions is essential to maintaining cell identity and involves numerous epigenetic modifications, whose roles in establishing chromatin architecture are less understood. Technological approaches to temporally order epigenetic modifications throughout the cell cycle often face limitations in sequence resolution and rely on potentially damaging mitotic labeling or conversion steps. Herein, we present M ethylation P seudotime A nalysis T hrough read-level H eterogeneity (MPATH), a label- and conversion-free method to infer post-replication DNA strand maturity from methylation patterns across single molecules. We use MPATH to temporally order hydroxymethylation throughout mitotic inheritance, revealing that CpGs within cis-regulatory elements undergo transitions between methylation states at sub-cell-cycle timescales. When applied to long reads generated by NOMe-seq, MPATH uncovered relationships between nucleosome occupancy and DNA maturity. Finally, extension of MPATH to phased reads reveals allele-specific trends in pseudotime distribution associated with X chromosome activity. Our findings suggest that when coupled with multimodal sequencing strategies, MPATH could provide valuable insights into chromatin restoration dynamics.

Novel Tet3 enzymes for next-generation epigenetic sequencing

Epigenetic regulation of gene expression is essential for cellular development and differentiation processes in higher eukaryotes. Modifications of cytosine, in particular 5-methylcytosine (5mdC), in DNA play a central role through impacting chromatin structure, repressing transposons, and regulating transcription. DNA methylation is actively installed by DNA methyltransferases and reversed through Tet-dioxygenase-mediated oxidation of 5mdC to 5-hydroxylmethylcytosine (5hmdC), 5-formylcytosine (5fdC), and 5-carboxycytosine (5cadC). It is crucial to understand the role of these epigenetic DNA modifications in cellular differentiation and developmental processes, as well as in disease state mapping and tracing of 5mdC and its oxidized forms. In bisulfite sequencing, which has been the benchmark for mapping 5mdC for the last few decades, degradation of the majority of genetic material occurs through harsh chemical treatment. Alternative sequencing methods often utilize Tet-enzyme-mediated oxidation of 5mdC to locate 5mdC and 5hmdC in genomic DNA. Herein, we report the development of novel Tet3-variants for oxidation-based bisulfite-free 5mdC- sequencing.

Genomic and fragmentomic landscapes of cell-free DNA for early cancer detection

Genomic analyses of cell-free DNA (cfDNA) in plasma are enabling noninvasive blood-based biomarker approaches to cancer detection and disease monitoring. Current approaches for identification of circulating tumour DNA typically use targeted tumour-specific mutations or methylation analyses. An emerging approach is based on the recognition of altered genome-wide cfDNA fragmentation in patients with cancer. Recent studies have revealed a multitude of characteristics that can affect the compendium of cfDNA fragments across the genome, collectively called the 'cfDNA fragmentome'. These changes result from genomic, epigenomic, transcriptomic and chromatin states of an individual and affect the size, position, coverage, mutation, structural and methylation characteristics of cfDNA. Identifying and monitoring these changes has the potential to improve early detection of cancer, especially using highly sensitive multi-feature machine learning approaches that would be amenable to broad use in populations at increased risk. This Review highlights the rapidly evolving field of genome-wide analyses of cfDNA characteristics, their comparison to existing cfDNA methods, and recent related innovations at the intersection of large-scale sequencing and artificial intelligence. As the breadth of clinical applications of cfDNA fragmentome methods have enormous public health implications for cancer screening and personalized approaches for clinical management of patients with cancer, we outline the challenges and opportunities ahead.

Microplastic exposure is associated with epigenomic effects in the model organism Pimephales promelas (fathead minnow)

Microplastics have evolutionary and ecological impacts across species, affecting organisms' development, reproduction, and behavior along with contributing to genotoxicity and stress. As plastic pollution is increasing and ubiquitous, gaining a better understanding of organismal responses to microplastics is necessary. Epigenetic processes such as DNA methylation are heritable forms of molecular regulation influenced by environmental conditions. Therefore, determining such epigenetic responses to microplastics will reveal potential chronic consequences of this environmental pollutant. We performed an experiment across two generations of fathead minnows (Pimephales promelas) to elucidate the transgenerational epigenetic effects of microplastic exposure. We exposed the first generation of fish to four different treatments of microplastics: two concentrations of each of pre-consumer polyethylene (PE) and PE collected from Lake Ontario. We then raised the first filial generation with no microplastic exposure. We used enzymatic methylation sequencing on adult liver tissue and homogenized larvae to evaluate DNA methylation differences among treatments, sexes, and generations. Our findings show the origin of the plastic had a larger effect in female minnows whereas the effect of concentration was stronger in the males. We also observed transgenerational effects, highlighting a mechanism in which parents can pass on the effects of microplastic exposure to their offspring. Many of the genes found within differentially methylated regions in our analyses are known to interact with estrogenic chemicals associated with plastic and are related to metabolism. This study highlights the persistent and potentially serious impacts of microplastic pollution on gene regulation in freshwater systems.

Feeling the force from within - new tools and insights into nuclear mechanotransduction

The ability of cells to sense and respond to mechanical signals is essential for many biological processes that form the basis of cell identity, tissue development and maintenance. This process, known as mechanotransduction, involves crucial feedback between mechanical force and biochemical signals, including epigenomic modifications that establish transcriptional programs. These programs, in turn, reinforce the mechanical properties of the cell and its ability to withstand mechanical perturbation. The nucleus has long been hypothesized to play a key role in mechanotransduction due to its direct exposure to forces transmitted through the cytoskeleton, its role in receiving cytoplasmic signals and its central function in gene regulation. However, parsing out the specific contributions of the nucleus from those of the cell surface and cytoplasm in mechanotransduction remains a substantial challenge. In this Review, we examine the latest evidence on how the nucleus regulates mechanotransduction, both via the nuclear envelope (NE) and through epigenetic and transcriptional machinery elements within the nuclear interior. We also explore the role of nuclear mechanotransduction in establishing a mechanical memory, characterized by a mechanical, epigenetic and transcriptomic cell state that persists after mechanical stimuli cease. Finally, we discuss current challenges in the field of nuclear mechanotransduction and present technological advances that are poised to overcome them.

A streamlined workflow for long-read DNA methylation analysis with NanoMethViz and Bioconductor

Long-read sequencing technologies have transformed the field of epigenetics by enabling direct, single-base resolution detection of DNA modifications, such as methylation. This produces novel opportunities for studying the role of DNA methylation in gene regulation, imprinting, and disease. However, the unique characteristics of long-read data, including the modBAM format and extended read lengths, necessitate the development of specialised software tools for effective analysis. The NanoMethViz package provides a suite of tools for loading in long-read methylation data, visualising data at various data resolutions. It can convert the data for use with other Bioconductor software such as bsseq, DSS, dmrseq and edgeR to discover differentially methylated regions (DMRs). In this workflow article, we demonstrate the process of converting modBAM files into formats suitable for comprehensive downstream analysis. We leverage NanoMethViz to conduct an exploratory analysis, visually summarizing differences between samples, examining aggregate methylation profiles across gene and CpG islands, and investigating methylation patterns within specific regions at the single-read level. Additionally, we illustrate the use of dmrseq for identifying DMRs and show how to integrate these findings into gene-level visualization plots. Our analysis is applied to a triplicate dataset of haplotyped long-read methylation data from mouse neural stem cells, allowing us to visualize and compare the characteristics of the parental alleles on chromosome 7. By applying DMR analysis, we recover DMRs associated with known imprinted genes and visualise the methylation patterns of these genes summarised at single-read resolution. Through DMR analysis, we identify DMRs associated with known imprinted genes and visualize their methylation patterns at single-read resolution. This streamlined workflow is adaptable to common experimental designs and offers flexibility in the choice of upstream data sources and downstream statistical analysis tools.

Scalable Screening of Ternary-Code DNA Methylation Dynamics Associated with Human Traits

Epigenome-wide association studies (EWAS) are transforming our understanding of the interplay between epigenetics and complex human traits and phenotypes. We introduce the Methylation Screening Array (MSA), a new iteration of the Infinium technology for scalable and quantitative screening of trait associations of nuanced ternary-code cytosine modifications in larger, more inclusive, and stratified human populations. MSA integrates EWAS, single-cell, and cell-type-resolved methylome profiles, covering diverse human traits and diseases. Our first MSA applications yield multiple biological insights: we revealed a previously unappreciated role of 5-hydroxymethylcytosine (5hmC) in trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5-methylcytosines (5mCs) in defining tissues and cells' epigenetic identities. In-depth analyses highlighted the cell type context of EWAS and GWAS hits. Using this platform, we conducted a comprehensive human 5hmC aging EWAS, discovering tissue-invariant and tissue-specific aging dynamics, including distinct tissue-specific rates of mitotic hyper- and hypomethylation rates. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Epigenetic regulation of vascular smooth muscle cell phenotypes in atherosclerosis

Vascular smooth muscle cells (VSMCs) in adult arteries maintain substantial phenotypic plasticity, which allows for the reversible cell state changes that enable vascular remodelling and homeostasis. In atherosclerosis, VSMCs dedifferentiate in response to lipid accumulation and inflammation, resulting in loss of their characteristic contractile state. Recent studies showed that individual, pre-existing VSMCs expand clonally and can acquire many different phenotypes in atherosclerotic lesions. The changes in gene expression underlying this phenotypic diversity are mediated by epigenetic modifications which affect transcription factor access and thereby gene expression dynamics. Additionally, epigenetic mechanisms can maintain cellular memory, potentially facilitating reversion to the contractile state. While technological advances have provided some insight, a comprehensive understanding of how VSMC phenotypes are governed in disease remains elusive. Here we review current literature in light of novel insight from studies at single-cell resolution. We also discuss how lessons from epigenetic studies of cellular regulation in other fields could help in translating the potential of targeting VSMC phenotype conversion into novel therapies in cardiovascular disease.

Rapid human oogonia-like cell specification via transcription factor-directed differentiation

The generation of germline cells from human induced pluripotent stem cells (hiPSCs) represents a milestone toward in vitro gametogenesis. Methods to recapitulate germline development beyond primordial germ cells in vitro have relied on long-term cell culture, such as 3-dimensional organoid co-culture for ~four months. Using a pipeline with highly parallelized screening, this study identifies combinations of TFs that directly and rapidly convert hiPSCs to induced oogonia-like cells (iOLCs). We demonstrate that co-expression of five TFs - namely, ZNF281, LHX8, SOHLH1, ZGLP1, and ANHX, induces high efficiency DDX4-positive iOLCs in only four days in a feeder-free monolayer culture condition. We also show improved production of human primordial germ cell-like cells (hPGCLCs) from hiPSCs by expression of DLX5, HHEX, and FIGLA. We characterize these TF-based iOLCs and hPGCLCs via gene and protein expression analyses and demonstrate their similarity to in vivo and in vitro-derived oogonia and primordial germ cells. Together, these results identify new regulatory factors that enhance human germ cell specification in vitro, and further establish unique computational and experimental tools for human in vitro oogenesis research.

DNA methylation-based age prediction and sex-specific epigenetic aging in a lizard with female-biased longevity

Sex differences in life span are widespread across animal taxa, but their causes remain unresolved. Alterations to the epigenome are hypothesized to contribute to vertebrate aging, and DNA methylation-based aging clocks allow for quantitative estimation of biological aging trajectories. Here, we investigate the influence of age, sex, and their interaction on genome-wide DNA methylation patterns in the brown anole (Anolis sagrei), a lizard with pronounced female-biased survival and longevity. We develop a series of age predictor models and find that, contrary to our predictions, rates of epigenetic aging were not slower in female lizards. However, methylation states at loci acquiring age-associated changes appear to be more "youthful" in young females, suggesting that female DNA methylomes are preemptively fortified in early life in opposition to the direction of age-related drift. Collectively, our findings provide insights into epigenetic aging in reptiles and suggest that early-life epigenetic profiles may be more informative than rates of change for predicting sex biases in longevity.

Thermodynamic principles link in vitro transcription factor affinities to single-molecule chromatin states in cells

The molecular details governing transcription factor (TF) binding and the formation of accessible chromatin are not yet quantitatively understood - including how sequence context modulates affinity, how TFs search DNA, the kinetics of TF occupancy, and how motif grammars coordinate binding. To resolve these questions for a human TF, erythroid Krüppel-like factor (eKLF/KLF1), we quantitatively compare, in high throughput, in vitro TF binding rates and affinities with in vivo single molecule TF and nucleosome occupancies across engineered DNA sequences. We find that 40-fold flanking sequence effects on affinity are consistent with distal flanks tuning TF search parameters and captured by a linear energy model. Motif recognition probability, rather than time in the bound state, drives affinity changes, and in vitro and in nuclei measurements exhibit consistent, minutes-long TF residence times. Finally, pairing in vitro biophysical parameters with thermodynamic models accurately predicts in vivo single-molecule chromatin states for unseen motif grammars.

methylGrapher: genome-graph-based processing of DNA methylation data from whole genome bisulfite sequencing

Genome graphs, including the recently released draft human pangenome graph, can represent the breadth of genetic diversity and thus transcend the limits of traditional linear reference genomes. However, there are no genome-graph-compatible tools for analyzing whole genome bisulfite sequencing (WGBS) data. To close this gap, we introduce methylGrapher, a tool tailored for accurate DNA methylation analysis by mapping WGBS data to a genome graph. Notably, methylGrapher can reconstruct methylation patterns along haplotype paths precisely and efficiently. To demonstrate the utility of methylGrapher, we analyzed the WGBS data derived from five individuals whose genomes were included in the first Human Pangenome draft as well as WGBS data from ENCODE (EN-TEx). Along with standard performance benchmarking, we show that methylGrapher fully recapitulates DNA methylation patterns defined by classic linear genome analysis approaches. Importantly, methylGrapher captures a substantial number of CpG sites that are missed by linear methods, and improves overall genome coverage while reducing alignment reference bias. Thus, methylGrapher is a first step toward unlocking the full potential of Human Pangenome graphs in genomic DNA methylation analysis.

Exercise intensity and training alter the innate immune cell type and chromosomal origins of circulating cell-free DNA in humans

Exercising regularly promotes health, but these benefits are complicated by acute inflammation induced by exercise. A potential source of inflammation is cell-free DNA (cfDNA), yet the cellular origins, molecular causes, and immune system interactions of exercise-induced cfDNA are unclear. To study these, 10 healthy individuals were randomized to a 12-wk exercise program of either high-intensity tactical training (HITT) or traditional moderate-intensity training (TRAD). Blood plasma was collected pre- and postexercise at weeks 0 and 12 and after 4 wk of detraining upon program completion. Whole-genome enzymatic methylation sequencing (EM-seq) with cell-type proportion deconvolution was applied to cfDNA obtained from the 50 plasma samples and paired to concentration measurements for 90 circulating cytokines. Acute exercise increased the release of cfDNA from neutrophils, dendritic cells (DCs), and macrophages proportional to exercise intensity. Exercise training reduced cfDNA released in HITT participants but not TRAD and from DCs and macrophages but not neutrophils. For most participants, training lowered mitochondrial cfDNA at rest, even after detraining. Using a sequencing analysis approach we developed, we concluded that rapid ETosis, a process of cell death where cells release DNA extracellular traps, was the likely source of cfDNA, demonstrated by enrichment of nuclear DNA. Further, several cytokines were induced by acute exercise, such as IL-6, IL-10, and IL-16, and training attenuated the induction of only IL-6 and IL-17F. Cytokine levels were not associated with cfDNA induction, suggesting that these cytokines are not the main cause of exercise-induced cfDNA. Overall, exercise intensity and training modulated cfDNA release and cytokine responses, contributing to the anti-inflammatory effects of regular exercise.

Integration of CRISPR/dCas9-Based methylation editing with guide positioning sequencing identifies dynamic changes of mrDEGs in breast cancer progression

Dynamic changes in DNA methylation are prevalent during the progression of breast cancer. However, critical alterations in aberrant methylation and gene expression patterns have not been thoroughly characterized. Here, we utilized guide positioning sequencing (GPS) to conduct whole-genome DNA methylation analysis in a unique human breast cancer progression model: MCF10 series of cell lines (representing benign/normal, atypical hyperplasia, and metastatic carcinoma). By integrating with mRNA-seq and matched clinical expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), six representative methylation-related differentially expressed genes (mrDEGs) were identified, including CAVIN2, ARL4D, DUSP1, TENT5B, P3H2, and MMP28. To validate our findings, we independently developed and optimized the dCas9-DNMT3L-DNMT3A system, achieving a high efficiency with a 98% increase in methylation at specific sites. DNA methylation levels significantly increased for the six genes, with CAVIN2 at 67.75 ± 1.05%, ARL4D at 53.29 ± 6.32%, DUSP1 at 57.63 ± 8.46%, TENT5B at 44.00 ± 5.09%, P3H2 at 58.50 ± 3.90%, and MMP28 at 49.60 ± 5.84%. RT-qPCR confirmed an inverse correlation between increased DNA methylation and gene expression. Most importantly, we mimicked tumor progression in vitro, demonstrating that transcriptional silencing of the TENT5B promotes cell proliferation in MCF10A cells owing to the crosstalk between hypermethylation and histone deacetylation. This study unveils the practical implications of DNA methylation dynamics of mrDEGs in reshaping epigenomic features during breast cancer malignant progression through integrated data analysis of the methylome and transcriptome. The application of the CRISPR/dCas9-based methylation editing technique elucidates the regulatory mechanisms and functional roles of individual genes within the DNA methylation signature, providing valuable insights for understanding breast cancer pathogenesis and facilitating potential therapeutic approaches in epigenome editing for patients with breast cancer.

Increased local DNA methylation disorder in AMLs with DNMT3A-destabilizing variants and its clinical implication

The mechanistic link between the complex mutational landscape of de novo methyltransferase DNMT3A and the pathology of acute myeloid leukemia (AML) has not been clearly elucidated so far. Motivated by a recent discovery of the significance of DNMT3A-destabilizing mutations (DNMT3AINS) in AML, we here investigate the common characteristics of DNMT3AINS AML methylomes through computational analyses. We present that methylomes of DNMT3AINS AMLs are considerably different from those of DNMT3AR882 AMLs in that they exhibit increased intratumor DNA methylation heterogeneity in bivalent chromatin domains. This epigenetic heterogeneity was associated with the transcriptional variability of developmental and membrane-associated factors shaping stem cell niche, and also was a predictor of the response of AML cells to hypomethylating agents, implying that the survival of AML cells depends on stochastic DNA methylations at bivalent domains. Altogether, our work provides a novel mechanistic model suggesting the genomic origin of the aberrant epigenomic heterogeneity in disease conditions.

Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

The analysis of circulating tumour DNA (ctDNA) through minimally invasive liquid biopsies is promising for early multi-cancer detection and monitoring minimal residual disease. Most existing methods focus on targeted deep sequencing, but few integrate multiple data modalities. Here, we develop a methodology for ctDNA detection using deep (80x) whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive approach than bisulphite sequencing, which permits the simultaneous analysis of genomic and methylomic data. We conduct a diagnostic accuracy study across multiple cancer types in symptomatic patients, achieving 94.9% sensitivity and 88.8% specificity. Matched tumour biopsies are used for validation, not for guiding the analysis, imitating an early detection scenario. Furthermore, in silico validation demonstrates strong discrimination (86% AUC) at ctDNA fractions as low as 0.7%. Additionally, we successfully track tumour burden and ctDNA shedding from precancerous lesions post-treatment without requiring matched tumour biopsies. This pipeline is ready for further clinical evaluation to extend cancer screening and improve patient triage and monitoring.

Atlas-scale single-cell DNA methylation profiling with sciMETv3

Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity. We showcase the throughput of sciMETv3 by producing a >140,000 cell library from human middle frontal gyrus split across four multiplexed individuals using both Illumina and Ultima sequencing instrumentation. Finally, we introduce sciMET+ATAC to enable high-throughput exploration of the interplay between chromatin accessibility and DNA methylation within the same cell.

DNA methylation modulates nucleosome retention in sperm and H3K4 methylation deposition in early mouse embryos

In the germ line and during early embryogenesis, DNA methylation (DNAme) undergoes global erasure and re-establishment to support germ cell and embryonic development. While DNAme acquisition during male germ cell development is essential for setting genomic DNA methylation imprints, other intergenerational roles for paternal DNAme in defining embryonic chromatin are unknown. Through conditional gene deletion of the de novo DNA methyltransferases Dnmt3a and/or Dnmt3b, we observe that DNMT3A primarily safeguards against DNA hypomethylation in undifferentiated spermatogonia, while DNMT3B catalyzes de novo DNAme during spermatogonial differentiation. Failing de novo DNAme in Dnmt3a/Dnmt3b double deficient spermatogonia is associated with increased nucleosome occupancy in mature sperm, preferentially at sites with higher CpG content, supporting the model that DNAme modulates nucleosome retention in sperm. To assess the impact of altered sperm chromatin in formatting embryonic chromatin, we measure H3K4me3 occupancy at paternal and maternal alleles in 2-cell embryos using a transposon-based tagging approach. Our data show that reduced DNAme in sperm renders paternal alleles permissive for H3K4me3 establishment in early embryos, independently of possible paternal inheritance of sperm born H3K4me3. Together, this study provides evidence that paternally inherited DNAme directs chromatin formation during early embryonic development.

Whole Genome Methylation Sequencing via Enzymatic Conversion (EM-seq): Protocol, Data Processing, and Analysis

Whole genome bisulfite sequencing (WGBS) has been the gold standard technique for base resolution analysis of DNA methylation for the last 15 years. It has been, however, associated with technical biases, which lead to overall overestimation of global and regional methylation values, and significant artifacts in extreme cytosine-rich DNA sequence contexts. Enzymatic conversion of cytosine is the newest approach, set to replace entirely the use of the damaging bisulfite conversion of DNA. The EM-seq technique utilizes TET2, T4-BGT, and APOBEC in a two-step conversion process, where the modified cytosines are first protected by oxidation and glucosylation, followed by deamination of all unmodified cytosines to uracil. As a result, EM-seq is degradation-free and bias-free, requires low DNA input, and produces high library yields with longer reads, little batch variation, less duplication, uniform genomic coverage, accurate methylation over a larger number of captured CpGs, and no sequence-specific artifacts.

Simultaneous single-cell analysis of 5mC and 5hmC with SIMPLE-seq

Dynamic 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications to DNA regulate gene expression in a cell-type-specific manner and are associated with various biological processes, but the two modalities have not yet been measured simultaneously from the same genome at the single-cell level. Here we present SIMPLE-seq, a scalable, base resolution method for joint analysis of 5mC and 5hmC from thousands of single cells. Based on orthogonal labeling and recording of 'C-to-T' mutational signals from 5mC and 5hmC sites, SIMPLE-seq detects these two modifications from the same molecules in single cells and enables unbiased DNA methylation dynamics analysis of heterogeneous biological samples. We applied this method to mouse embryonic stem cells, human peripheral blood mononuclear cells and mouse brain to give joint epigenome maps at single-cell and single-molecule resolution. Integrated analysis of these two cytosine modifications reveals distinct epigenetic patterns associated with divergent regulatory programs in different cell types as well as cell states.

Mapping epigenetic modifications by sequencing technologies

The "epigenetics" concept was first described in 1942. Thus far, chemical modifications on histones, DNA, and RNA have emerged as three important building blocks of epigenetic modifications. Many epigenetic modifications have been intensively studied and found to be involved in most essential biological processes as well as human diseases, including cancer. Precisely and quantitatively mapping over 100 [1], 17 [2], and 160 [3] different known types of epigenetic modifications in histone, DNA, and RNA is the key to understanding the role of epigenetic modifications in gene regulation in diverse biological processes. With the rapid development of sequencing technologies, scientists are able to detect specific epigenetic modifications with various quantitative, high-resolution, whole-genome/transcriptome approaches. Here, we summarize recent advances in epigenetic modification sequencing technologies, focusing on major histone, DNA, and RNA modifications in mammalian cells.

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.

Reduced Representation Bisulfite Sequencing Library Preparation for Sperm DNA Methylation Analyses: Manual and Automated Methods

Among epigenetic modifications, DNA methylation is extensively studied in sperm, and variations in sperm DNA methylation patterns have been associated with fertility, sperm quality, and in vitro fertilization outcomes in several species. Reduced representation bisulfite sequencing (RRBS) is a cost-effective method that has been successfully applied to sperm. However, RRBS library preparation remains sensitive and labor-intensive and can be subjected to diverse sources of technical variation. In order to improve RRBS library preparation performance, as well as its reproducibility, we adapted the reference protocol and implemented it on a Hamilton pipetting automaton.

Profiling the epigenome using long-read sequencing

The advent of single-molecule, long-read sequencing (LRS) technologies by Oxford Nanopore Technologies and Pacific Biosciences has revolutionized genomics, transcriptomics and, more recently, epigenomics research. These technologies offer distinct advantages, including the direct detection of methylated DNA and simultaneous assessment of DNA sequences spanning multiple kilobases along with their modifications at the single-molecule level. This has enabled the development of new assays for analyzing chromatin states and made it possible to integrate data for DNA methylation, chromatin accessibility, transcription factor binding and histone modifications, thereby facilitating comprehensive epigenomic profiling. Owing to recent advancements, alternative, nascent and translating transcripts can be detected using LRS approaches. This Review discusses LRS-based experimental and computational strategies for characterizing chromatin states and highlights their advantages over short-read sequencing methods. Furthermore, we demonstrate how various long-read methods can be integrated to design multi-omics studies to investigate the relationship between chromatin states and transcriptional dynamics.

Integrating multi-omics features enables non-invasive early diagnosis and treatment response prediction of diffuse large B-cell lymphoma

BACKGROUND

Multi-omics features of cell-free DNA (cfDNA) can effectively improve the performance of non-invasive early diagnosis and prognosis of cancer. However, multimodal characterization of cfDNA remains technically challenging.

METHODS

We developed a comprehensive multi-omics solution (COMOS) to specifically obtain an extensive fragmentomics landscape, presented by breakpoint characteristics of nucleosomes, CpG islands, DNase clusters and enhancers, besides typical methylation, copy number alteration of cfDNA. The COMOS was tested on 214 plasma samples of diffuse large B-cell lymphoma (DLBCL) and matched healthy controls.

RESULTS

For early diagnosis, COMOS improved the area under the curve (AUC) value to .993 compared with the individual omics model, with a sensitivity of 95% at 98% specificity. Detection sensitivity achieved 91% at 99% specificity in early-stage patients, while the AUC values of the individual omics model were 0.942, 0.968, 0.989, 0.935, 0.921, 0.781 and 0.917, respectively, with lower sensitivity and specificity. In the treatment response cohort, COMOS yielded a superior sensitivity of 88% at 86% specificity (AUC, 0.903). COMOS has achieved excellent performance in early diagnosis and treatment response prediction.

CONCLUSIONS

Our study provides an effectively improved approach with high accuracy for the diagnosis and prognosis of DLBCL, showing great potential for future clinical application.

KEY POINTS

A comprehensive multi-omics solution to specifically obtain an extensive fragmentomics landscape, presented by breakpoint characteristics of nucleosomes, CpG islands, DNase clusters and enhancers, besides typical methylation, copy number alteration of cfDNA. Integrated model of cfDNA multi-omics could be used for non-invasive early diagnosis of DLBCL. Integrated model of cfDNA multi-omics could effectively evaluate the efficacy of R-CHOP before DLBCL treatment.

DNA methylation in mammalian development and disease

The DNA methylation field has matured from a phase of discovery and genomic characterization to one seeking deeper functional understanding of how this modification contributes to development, ageing and disease. In particular, the past decade has seen many exciting mechanistic discoveries that have substantially expanded our appreciation for how this generic, evolutionarily ancient modification can be incorporated into robust epigenetic codes. Here, we summarize the current understanding of the distinct DNA methylation landscapes that emerge over the mammalian lifespan and discuss how they interact with other regulatory layers to support diverse genomic functions. We then review the rising interest in alternative patterns found during senescence and the somatic transition to cancer. Alongside advancements in single-cell and long-read sequencing technologies, the collective insights made across these fields offer new opportunities to connect the biochemical and genetic features of DNA methylation to cell physiology, developmental potential and phenotype.

Bisulfite-Free and Quantitative Detection of DNA Methylation at Single-Base Resolution by eROS1-seq

5-Methylcytosine (5mC) is the most significant DNA modification present in mammalian genomes. Understanding the roles of 5mC in diverse biological processes requires quantitative detection at single-base resolution. In this study, we engineered the repressor of the silencing 1 (ROS1) protein derived from Arabidopsis thaliana to enhance its 5mC glycosylase/lyase activity, resulting in the creation of the engineered ROS1 (eROS1) protein. Leveraging the unique properties of eROS1, we introduced a method termed engineered ROS1 sequencing (eROS1-seq) for bisulfite-free and quantitative detection of 5mC in DNA at single-base resolution. In eROS1-seq, the eROS1 protein selectively cleaves 5mC while leaving unmodified cytosine (C) intact, followed by the incorporation of dTTP, which subsequently results in sequencing as thymine (T). This method effectively differentiates between C and 5mC. Unlike conventional bisulfite sequencing (BS-seq), which predominantly converts cytosines, eROS1-seq specifically transforms 5mC into T, thereby avoiding potential imbalances in the nucleobase composition of the sequencing library. Using eROS1-seq, we successfully achieved quantitative and site-specific detection of 5mC in the genomic DNA of lung cancer tissue. Overall, the eROS1-seq approach is bisulfite-free and straightforward, making it a valuable tool for the quantitative detection of 5mC at single-base resolution.

Shedding light on DNA methylation and its clinical implications: the impact of long-read-based nanopore technology

DNA methylation is an essential epigenetic mechanism for regulation of gene expression, through which many physiological (X-chromosome inactivation, genetic imprinting, chromatin structure and miRNA regulation, genome defense, silencing of transposable elements) and pathological processes (cancer and repetitive sequences-associated diseases) are regulated. Nanopore sequencing has emerged as a novel technique that can analyze long strands of DNA (long-read sequencing) without chemically treating the DNA. Interestingly, nanopore sequencing can also extract epigenetic status of the nucleotides (including both 5-Methylcytosine and 5-hydroxyMethylcytosine), and a large variety of bioinformatic tools have been developed for improving its detection properties. Out of all genomic regions, long read sequencing provides advantages in studying repetitive elements, which are difficult to characterize through other sequencing methods. Transposable elements are repetitive regions of the genome that are silenced and usually display high levels of DNA methylation. Their demethylation and activation have been observed in many cancers. Due to their repetitive nature, it is challenging to accurately estimate DNA methylation levels within transposable elements using short sequencing technologies. The advantage to sequence native DNA (without PCR amplification biases or harsh bisulfite treatment) and long and ultra long reads coupled with epigenetic states of the DNA allows to accurately estimate DNA methylation levels in transposable elements. This is a big step forward for epigenomic studies, and unsolved questions regarding gene expression and transposable elements silencing through DNA methylation can now be answered.

Robust Bisulfite-Free Single-Molecule Real-Time Sequencing of Methyldeoxycytidine Based on a Novel hpTet3 Enzyme

In addition to the four canonical nucleosides dA, dG, dC and T, genomic DNA contains the additional base 5-methyldeoxycytidine (mdC). The presence of this methylated cytidine nucleoside in promoter regions or gene bodies significantly affects the transcriptional activity of the corresponding gene. Consequently, the methylation patterns of genes are crucial for either silencing or activating genes. Sequencing the positions of mdC in the genome is therefore of paramount importance for early cancer diagnostics as it helps determine incorrect gene expression. Currently, the bisulfite method is the gold standard for mdC-sequencing. However, this method has the drawback that the majority of the input DNA is degraded during the bisulfite treatment. Additionally, bisulfite sequencing is prone to errors. Here, we report a benign, bisulfite-free mdC sequencing method termed EMox-seq, which is based on third-generation single-molecule SMRT sequencing. The foundation of this technology is a new Tet3 enzyme that efficiently oxidizes mdCs to 5-carboxycytidine (cadC). In turn, cadC provides an excellent readout by SMRT sequencing using specially trained AI-based algorithms.

Exploring the Epigenetic Landscape of Spermatozoa: Impact of Oxidative Stress and Antioxidant Supplementation on DNA Methylation and Hydroxymethylation

Reproductive success is dependent on gamete integrity, and oxidative stress alters male nuclei, meaning that no DNA repair is possible due to chromatin compaction. The composition of sperm makes it highly sensitive to reactive oxygen species (ROS) but, at the same time, ROS are needed for sperm physiology. Over the past 30 years, much attention has been paid to the consequences of oxidative stress on sperm properties and the protective effects of antioxidant formulations to help fertility. Spermatozoa also carry epigenetic marks, critical for embryo development and the health of offspring. As DNA oxidative damage may disturb the sperm epigenome, we used an established mouse model of post-testicular sperm DNA oxidation to investigate sperm DNA methylation and hydroxymethylation. We also analyzed the potential corrective effect of oral antioxidant supplementation, proven to reduce sperm DNA oxidative damage, on sperm DNA methyl/hydroxymethyl marks. We show that sperm DNA oxidation is associated with a significant increase in overall hydroxymethylation. Oral antioxidant supplementation led to unexpected mild epigenetic changes. Antioxidant supplementation should not be proposed without proper clinical evaluation as it may alter sperm epigenetic marks, leading to a risk of paternally inherited epigenetic alterations.

Decoding epigenetic markers: implications of traits and genes through DNA methylation in resilience and susceptibility to mastitis in dairy cows

Cattle farming faces challenges linked to intensive exploitation and climate change, requiring the reinforcement of animal resilience in response to these dynamic environments. Currently, genetic selection is used to enhance resilience by identifying animals resistant to specific diseases; however, certain diseases, such as mastitis, pose difficulties in genetic prediction. This study introduced the utilization of enzymatic methyl sequencing (EM-seq) of the blood genomic DNA from twelve dairy cows to identify DNA methylation biomarkers, with the aim of predicting resilience and susceptibility to mastitis. The analysis uncovered significant differences between cows resilient and susceptible to mastitis, with 196,275 differentially methylated cytosines (DMCs) and 1,227 Differentially Methylated Regions (DMRs). Key genes associated with the immune response and morphological traits, including ENOPH1, MYL10 and KIR2DL5A, were identified by our analysis. Quantitative trait loci (QTL) were also highlighted and the body weight trait was the most targeted by DMCs and DMRs. Based on our results, the risk of developing mastitis can potentially be estimated with as few as fifty methylation biomarkers, paving the way for early animal selection. This research sets the stage for improved animal health management and economic yields within the framework of agricultural sustainability through early selection based on the epigenetic status of animals.

Role of epigenetic mechanisms in the pathogenesis of chronic respiratory diseases and response to inhaled exposures: From basic concepts to clinical applications

Epigenetic modifications are chemical groups in our DNA (and chromatin) that determine which genes are active and which are shut off. Importantly, they integrate environmental signals to direct cellular function. Upon chronic environmental exposures, the epigenetic signature of lung cells gets altered, triggering aberrant gene expression programs that can lead to the development of chronic lung diseases. In addition to driving disease, epigenetic marks can serve as attractive lung disease biomarkers, due to early onset, disease specificity, and stability, warranting the need for more epigenetic research in the lung field. Despite substantial progress in mapping epigenetic alterations (mostly DNA methylation) in chronic lung diseases, the molecular mechanisms leading to their establishment are largely unknown. This review is meant as a guide for clinicians and lung researchers interested in epigenetic regulation with a focus on DNA methylation. It provides a short introduction to the main epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNA) and the machinery responsible for their establishment and removal. It presents examples of epigenetic dysregulation across a spectrum of chronic lung diseases and discusses the current state of epigenetic therapies. Finally, it introduces the concept of epigenetic editing, an exciting novel approach to dissecting the functional role of epigenetic modifications. The promise of this emerging technology for the functional study of epigenetic mechanisms in cells and its potential future use in the clinic is further discussed.

Enriched Methylomes of Low-input and Fragmented DNA Using Fragment Ligation EXclusive Methylation Sequencing (FLEXseq)

Methylome profiling is an emerging clinical tool for tumor classification and liquid biopsies. Here, we developed FLEXseq, a genome-wide methylation profiler that enriches and sequences the fragments of DNA flanking the CCGG motif. FLEXseq strongly correlates (Pearson's r = 0.97) with whole genome bisulfite sequencing (WGBS) while enriching 18-fold. To demonstrate the broad applicability of FLEXseq, we verified its usage across cells, body fluids, and formalin-fixed paraffin-embedded (FFPE) tissues. DNA dilutions down to 250 pg decreased CpG coverage, but bias in methylation remained low (Pearson's r ≥ 0.90) compared to a 10 ng input. FLEXseq offers a cost-efficient, base-pair resolution methylome with potential as a diagnostic tool for tissue and liquid biopsies.

Single-molecule states link transcription factor binding to gene expression

The binding of multiple transcription factors (TFs) to genomic enhancers drives gene expression in mammalian cells1. However, the molecular details that link enhancer sequence to TF binding, promoter state and transcription levels remain unclear. Here we applied single-molecule footprinting2,3 to measure the simultaneous occupancy of TFs, nucleosomes and other regulatory proteins on engineered enhancer-promoter constructs with variable numbers of TF binding sites for both a synthetic TF and an endogenous TF involved in the type I interferon response. Although TF binding events on nucleosome-free DNA are independent, activation domains recruit cofactors that destabilize nucleosomes, driving observed TF binding cooperativity. Average TF occupancy linearly determines promoter activity, and we decompose TF strength into separable binding and activation terms. Finally, we develop thermodynamic and kinetic models that quantitatively predict both the enhancer binding microstates and gene expression dynamics. This work provides a template for the quantitative dissection of distinct contributors to gene expression, including TF activation domains, concentration, binding affinity, binding site configuration and recruitment of chromatin regulators.

MethyLasso: a segmentation approach to analyze DNA methylation patterns and identify differentially methylated regions from whole-genome datasets

DNA methylation is an epigenetic mark involved in the regulation of gene expression, and patterns of DNA methylation anticorrelate with chromatin accessibility and transcription factor binding. DNA methylation can be profiled at the single cytosine resolution in the whole genome and has been performed in many cell types and conditions. Computational approaches are then essential to study DNA methylation patterns in a single condition or capture dynamic changes of DNA methylation levels across conditions. Toward this goal, we developed MethyLasso, a new approach to segment DNA methylation data. We use it as an all-in-one tool to perform the identification of low-methylated regions, unmethylated regions, DNA methylation valleys and partially methylated domains in a single condition as well as differentially methylated regions between two conditions. We performed a rigorous benchmarking comparing existing approaches by evaluating the agreement of the regions across tools, their number, size, level of DNA methylation, boundaries, cytosine-guanine content and coverage using several real datasets as well as the sensitivity and precision of the approaches using simulated data and show that MethyLasso performs best overall. MethyLasso is freely available at https://github.com/bardetlab/methylasso.

A DNA Polymerase Variant Senses the Epigenetic Marker 5-Methylcytosine by Increased Misincorporation

Dysregulation of DNA methylation is associated with human disease, particularly cancer, and the assessment of aberrant methylation patterns holds great promise for clinical diagnostics. However, DNA polymerases do not effectively discriminate between processing 5-methylcytosine (5 mC) and unmethylated cytosine, resulting in the silencing of methylation information during amplification or sequencing. As a result, current detection methods require multi-step DNA conversion treatments or careful analysis of sequencing data to decipher individual 5 mC bases. To overcome these challenges, we propose a novel DNA polymerase-mediated 5 mC detection approach. Here, we describe the engineering of a thermostable DNA polymerase variant derived from Thermus aquaticus with altered fidelity towards 5 mC. Using a screening-based evolutionary approach, we have identified a DNA polymerase that exhibits increased misincorporation towards 5 mC during DNA synthesis. This DNA polymerase generates mutation signatures at methylated CpG sites, allowing direct detection of 5 mC by reading an increased error rate after sequencing without prior treatment of the sample DNA.