DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation

Applications of Nanopore sequencing in precision cancer medicine

Oxford Nanopore Technologies sequencing, also referred to as Nanopore sequencing, stands at the forefront of a revolution in clinical genetics, offering the potential for rapid, long read, and real-time DNA and RNA sequencing. This technology is currently making sequencing more accessible and affordable. In this comprehensive review, we explore its potential regarding precision cancer diagnostics and treatment. We encompass a critical analysis of clinical cases where Nanopore sequencing was successfully applied to identify point mutations, splice variants, gene fusions, epigenetic modifications, non-coding RNAs, and other pivotal biomarkers that defined subsequent treatment strategies. Additionally, we address the challenges of clinical applications of Nanopore sequencing and discuss the current efforts to overcome them.

Comparative analysis of methodologies for detecting extrachromosomal circular DNA

Extrachromosomal circular DNA (eccDNA) is crucial in oncogene amplification, gene transcription regulation, and intratumor heterogeneity. While various analysis pipelines and experimental methods have been developed for eccDNA identification, their detection efficiencies have not been systematically assessed. To address this, we evaluate the performance of 7 analysis pipelines using seven simulated datasets, in terms of accuracy, identity, duplication rate, and computational resource consumption. We also compare the eccDNA detection efficiency of 7 experimental methods through twenty-one real sequencing datasets. Here, we show that Circle-Map and Circle_finder (bwa-mem-samblaster) outperform the other short-read pipelines. However, Circle_finder (bwa-mem-samblaster) exhibits notable redundancy in its outcomes. CReSIL is the most effective pipeline for eccDNA detection in long-read sequencing data at depths higher than 10X. Moreover, long-read sequencing-based Circle-Seq shows superior efficiency in detecting copy number-amplified eccDNA over 10 kb in length. These results offer valuable insights for researchers in choosing the suitable methods for eccDNA research.

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.

EBV infection alters DNA methylation in primary human colon cells: A path to inflammation and carcinogenesis?

Epstein-Barr Virus (EBV) is associated with several types of human cancers, and changes in DNA methylation are reported to contribute to viral-driven carcinogenesis, particularly in cancers of epithelial origin. In a previous study, we demonstrated that EBV infects human primary colonic cells (HCoEpC) and replicates within these cells, leading to pro-inflammatory and pro-tumorigenic effects. Notably, these effects were mostly prevented by inhibiting viral replication with PAA. Interestingly, the EBV-induced effects correlated with the upregulation of DNMT1 and were counteracted by pretreating cells with 5-AZA, suggesting a role for DNA hypermethylation. Building on this background, the current study investigates the methylation changes induced by EBV infection in HCoEpC, both in the presence and absence of PAA, or ERK1/2 and STAT3 inhibitors, pathways known to be activated by EBV and involved in the dysregulation of methylation in tumor cells. The genome-wide methylation analysis conducted in this study allowed us to identify several biological processes and genes affected by these epigenetic changes, providing insights into the possible underlying mechanisms leading to the pathological effects induced by EBV. Specifically, we found that the virus induced significant methylation changes, with hypermethylation being more prevalent than hypomethylation. Several genes involved in embryogenesis, carcinogenesis, and inflammation were affected.

cGAS deficient mice display premature aging associated with de-repression of LINE1 elements and inflammation

Aging-associated inflammation, or 'inflammaging" is a driver of multiple age-associated diseases. Cyclic GMP-AMP Synthase (cGAS) is a cytosolic DNA sensor that functions to activate interferon response upon detecting viral DNA in the cytoplasm. cGAS contributes to inflammaging by responding to endogenous signals such as damaged DNA or LINE1 (L1) cDNA which forms in aged cells. While cGAS knockout mice are viable their aging has not been examined. Unexpectedly, we found that cGAS knockout mice exhibit accelerated aging phenotype associated with induction of inflammation. Transcription of L1 elements was increased in both cGAS knockout mice and in cGAS siRNA knockdown cells associated with high levels of cytoplasmic L1 DNA and expression of ORF1 protein. Cells from cGAS knockout mice showed increased chromatin accessibility and decreased DNA methylation on L1 transposons. Stimulated emission depletion microscopy (STED) showed that cGAS forms nuclear condensates that co-localize with H3K9me3 heterochromatin marks, and H3K9me3 pattern is disrupted in cGAS knockout cells. Taken together these results suggest a previously undescribed role for cGAS in maintaining heterochromatin on transposable elements. We propose that loss of cGAS leads to loss of chromatin organization, de-repression of transposable elements and induction of inflammation resulting in accelerated aging.

Advances in forensic genetics: Exploring the potential of long read sequencing

DNA-based technologies have been used in forensic practice since the mid-1980s. While PCR-based STR genotyping using Capillary Electrophoresis remains the gold standard for generating DNA profiles in routine casework worldwide, the research community is continually seeking alternative methods capable of providing additional information to enhance discrimination power or contribute with new investigative leads. Oxford Nanopore Technologies (ONT) and PacBio third-generation sequencing have revolutionized the field, offering real-time capabilities, single-molecule resolution, and long-read sequencing (LRS). ONT, the pioneer of nanopore sequencing, uses biological nanopores to analyze nucleic acids in real-time. Its devices have revolutionized sequencing and may represent an interesting alternative for forensic research and routine casework, given that it offers unparalleled flexibility in a portable size: it enables sequencing approaches that range widely from PCR-amplified short target regions (e.g., CODIS STRs) to PCR-free whole transcriptome or even ultra-long whole genome sequencing. Despite its higher error rate compared to Illumina sequencing, it can significantly improve accuracy in read alignment against a reference genome or de novo genome assembly. This is achieved by generating long contiguous sequences that correctly assemble repetitive sections and regions with structural variation. Moreover, it allows real-time determination of DNA methylation status from native DNA without the need for bisulfite conversion. LRS enables the analysis of thousands of markers at once, providing phasing information and eliminating the need for multiple assays. This maximizes the information retrieved from a single invaluable sample. In this review, we explore the potential use of LRS in different forensic genetics approaches.

Comprehensive identification of pathogenic variants in retinoblastoma by long- and short-read sequencing

Retinoblastoma (RB) is the most common intraocular malignancy in childhood. The causal variants in RB are mostly characterized by previously used short-read sequencing (SRS) analysis, which has technical limitations in identifying structural variants (SVs) and phasing information. Long-read sequencing (LRS) technology has advantages over SRS in detecting SVs, phased genetic variants, and methylation. In this study, we comprehensively characterized the genetic landscape of RB using combinatorial LRS and SRS of 16 RB tumors and 16 matched blood samples. We detected a total of 232 somatic SVs, with an average of 14.5 SVs per sample across the whole genome in our cohort. We identified 20 distinct pathogenic variants disrupting RB1 gene, including three novel small variants and five somatic SVs. We found more somatic SVs were detected from LRS than SRS (140 vs. 122) in RB samples with WGS data, particularly the insertions (18 vs. 1). Furthermore, our analysis shows that, with the exception of one sample who lacked the methylation data, all samples presented biallelic inactivation of RB1 in various forms, including two cases with the biallelic hypermethylated promoter and four cases with compound heterozygous mutations which were missing in SRS analysis. By inferring relative timing of somatic events, we reveal the genetic progression that RB1 disruption early and followed by copy number changes, including amplifications of Chr2p and deletions of Chr16q, during RB tumorigenesis. Altogether, we characterize the comprehensive genetic landscape of RB, providing novel insights into the genetic alterations and mechanisms contributing to RB initiation and development. Our work also establishes a framework to analyze genomic landscape of cancers based on LRS data.

Comparing methylation levels assayed in GC-rich regions with current and emerging methods

DNA methylation is an epigenetic mechanism that regulates gene expression, and for mammals typically occurs on cytosines within CpG dinucleotides. A significant challenge for methylation detection methods is accurately measuring methylation levels within GC-rich regions such as gene promoters, as inaccuracies compromise downstream biological interpretation of the data. To address this challenge, we compared methylation levels assayed using four different Methods Enzymatic Methyl-seq (EM-seq), whole genome bisulphite sequencing (WGBS), Infinium arrays (Illumina MethylationEPIC, "EPIC"), and Oxford Nanopore Technologies nanopore sequencing (ONT) applied to human DNA. Overall, all methods produced comparable and consistent methylation readouts across the human genome. The flexibility offered by current gold standard WGBS in interrogating genome-wide cytosines is surpassed technically by both EM-seq and ONT, as their coverages and methylation readouts are less prone to GC bias. These advantages are tempered by increased laboratory time (EM-seq) and higher complexity (ONT). We further assess the strengths and weaknesses of each method, and provide recommendations in choosing the most appropriate methylation method for specific scientific questions or translational needs.

DeepBAM: a high-accuracy single-molecule CpG methylation detection tool for Oxford nanopore sequencing

Recent nanopore sequencing system (R10.4) has enhanced base calling accuracy and is being increasingly utilized for detecting CpG methylation state. However, the robustness and universality of the methylation calling model in officially supplied Dorado remains poorly tested. In this study, we obtained heterogeneous datasets from human and plant sources to carry out comprehensive evaluations, which showed that Dorado performed significantly different across datasets. We therefore developed deep neural networks and implemented several optimizations in training a new model called DeepBAM. DeepBAM achieved superior and more stable performances compared with Dorado, including higher area under the ROC curves (98.47% on average and up to 7.36% improvement) and F1 scores (94.97% on average and up to 16.24% improvement) across the datasets. DeepBAM-based whole genome methylation frequencies have achieved >0.95 correlations with BS-seq on four of five datasets, outperforming Dorado in all instances. It enables unraveling allele-specific methylation patterns, including regions of transposable elements. The enhanced performance of DeepBAM paves the way for broader applications of nanopore sequencing in CpG methylation studies.

Exposure to elevated glucocorticoid during development primes altered transcriptional responses to acute stress in adulthood

Early life stress (ELS) is a major risk factor for developing psychiatric disorders, with glucocorticoids (GCs) implicated in mediating its effects in shaping adult phenotypes. In this process, exposure to high levels of developmental GC (hdGC) is thought to induce molecular changes that prime differential adult responses. However, identities of molecules targeted by hdGC exposure are not completely known. Here, we describe lifelong molecular consequences of hdGC exposure using a newly developed zebrafish double-hit stress model, which shows altered behaviors and stress hypersensitivity in adulthood. We identify a set of primed genes displaying altered expression only upon acute stress in hdGC-exposed adult fish brains. Interestingly, this gene set is enriched in risk factors for psychiatric disorders in humans. Lastly, we identify altered epigenetic regulatory elements following hdGC exposure. Thus, our study provides comprehensive datasets delineating potential molecular targets mediating the impact of hdGC exposure on adult responses.

Local read haplotagging enables accurate long-read small variant calling

Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation simplifies long-read variant calling with DeepVariant.

Decoding the Epigenetic Landscape: Insights into 5mC and 5hmC Patterns in Mouse Cortical Cell Types

The DNA modifications, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), represent powerful epigenetic regulators of temporal and spatial gene expression. Yet, how the cooperation of these genome-wide, epigenetic marks determine unique transcriptional signatures across different brain cell populations is unclear. Here we applied Nanopore sequencing of native DNA to obtain a complete, genome-wide, single-base resolution atlas of 5mC and 5hmC modifications in neurons, astrocytes and microglia in the mouse cortex (99% genome coverage, 40 million CpG sites). In tandem with RNA sequencing, analysis of 5mC and 5hmC patterns across cell types reveals astrocytes drive uniquely high brain 5hmC levels and support two decades of research regarding methylation patterns, gene expression and alternative splicing, benchmarking this resource. As such, we provide the most comprehensive DNA methylation data in mouse brain as an interactive, online tool (NAM-Me, https://olsenlab.shinyapps.io/NAMME/) to serve as a resource dataset for those interested in the methylome landscape.

Rockfish: A transformer-based model for accurate 5-methylcytosine prediction from nanopore sequencing

DNA methylation plays an important role in various biological processes, including cell differentiation, ageing, and cancer development. The most important methylation in mammals is 5-methylcytosine mostly occurring in the context of CpG dinucleotides. Sequencing methods such as whole-genome bisulfite sequencing successfully detect 5-methylcytosine DNA modifications. However, they suffer from the serious drawbacks of short read lengths and might introduce an amplification bias. Here we present Rockfish, a deep learning algorithm that significantly improves read-level 5-methylcytosine detection by using Nanopore sequencing. Rockfish is compared with other methods based on Nanopore sequencing on R9.4.1 and R10.4.1 datasets. There is an increase in the single-base accuracy and the F1 measure of up to 5 percentage points on R.9.4.1 datasets, and up to 0.82 percentage points on R10.4.1 datasets. Moreover, Rockfish shows a high correlation with whole-genome bisulfite sequencing, requires lower read depth, and achieves higher confidence in biologically important regions such as CpG-rich promoters while being computationally efficient. Its superior performance in human and mouse samples highlights its versatility for studying 5-methylcytosine methylation across varied organisms and diseases. Finally, its adaptable architecture ensures compatibility with new versions of pores and chemistry as well as modification types.

Technology to the rescue: how to uncover the role of transposable elements in preimplantation development

Transposable elements (TEs) are highly expressed in preimplantation development. Preimplantation development is the phase when the cells of the early embryo undergo the first cell fate choice and change from being totipotent to pluripotent. A range of studies have advanced our understanding of TEs in preimplantation, as well as their epigenetic regulation and functional roles. However, many questions remain about the implications of TE expression during early development. Challenges originate first due to the abundance of TEs in the genome, and second because of the limited cell numbers in preimplantation. Here we review the most recent technological advancements promising to shed light onto the role of TEs in preimplantation development. We explore novel avenues to identify genomic TE insertions and improve our understanding of the regulatory mechanisms and roles of TEs and their RNA and protein products during early development.

Transfer learning enables identification of multiple types of RNA modifications using nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample.

Profiling genome-wide methylation in two maples: Fine-scale approaches to detection with nanopore technology

DNA methylation is critical to the regulation of transposable elements and gene expression and can play an important role in the adaptation of stress response mechanisms in plants. Traditional methods of methylation quantification rely on bisulfite conversion that can compromise accuracy. Recent advances in long-read sequencing technologies allow for methylation detection in real time. The associated algorithms that interpret these modifications have evolved from strictly statistical approaches to Hidden Markov Models and, recently, deep learning approaches. Much of the existing software focuses on methylation in the CG context, but methylation in other contexts is important to quantify, as it is extensively leveraged in plants. Here, we present methylation profiles for two maple species across the full range of 5mC sequence contexts using Oxford Nanopore Technologies (ONT) long-reads. Hybrid and reference-guided assemblies were generated for two new Acer accessions: Acer negundo (box elder; 65x ONT and 111X Illumina) and Acer saccharum (sugar maple; 93x ONT and 148X Illumina). The ONT reads generated for these assemblies were re-basecalled, and methylation detection was conducted in a custom pipeline with the published Acer references (PacBio assemblies) and hybrid assemblies reported herein to generate four epigenomes. Examination of the transposable element landscape revealed the dominance of LTR Copia elements and patterns of methylation associated with different classes of TEs. Methylation distributions were examined at high resolution across gene and repeat density and described within the broader angiosperm context, and more narrowly in the context of gene family dynamics and candidate nutrient stress genes.

Computational deconvolution of DNA methylation data from mixed DNA samples

In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.

The Application of Long-Read Sequencing to Cancer

Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment.

Functional characteristics of DNA N6-methyladenine modification based on long-read sequencing in pancreatic cancer

Abnormalities of DNA modifications are closely related to the pathogenesis and prognosis of pancreatic cancer. The development of third-generation sequencing technology has brought opportunities for the study of new epigenetic modification in cancer. Here, we screened the N6-methyladenine (6mA) and 5-methylcytosine (5mC) modification in pancreatic cancer based on Oxford Nanopore Technologies sequencing. The 6mA levels were lower compared with 5mC and upregulated in pancreatic cancer. We developed a novel method to define differentially methylated deficient region (DMDR), which overlapped 1319 protein-coding genes in pancreatic cancer. Genes screened by DMDRs were more significantly enriched in the cancer genes compared with the traditional differential methylation method (P < 0.001 versus P = 0.21, hypergeometric test). We then identified a survival-related signature based on DMDRs (DMDRSig) that stratified patients into high- and low-risk groups. Functional enrichment analysis indicated that 891 genes were closely related to alternative splicing. Multi-omics data from the cancer genome atlas showed that these genes were frequently altered in cancer samples. Survival analysis indicated that seven genes with high expression (ADAM9, ADAM10, EPS8, FAM83A, FAM111B, LAMA3 and TES) were significantly associated with poor prognosis. In addition, the distinction for pancreatic cancer subtypes was determined using 46 subtype-specific genes and unsupervised clustering. Overall, our study is the first to explore the molecular characteristics of 6mA modifications in pancreatic cancer, indicating that 6mA has the potential to be a target for future clinical treatment.

A comparison of methods for detecting DNA methylation from long-read sequencing of human genomes

BACKGROUND

Long-read sequencing can enable the detection of base modifications, such as CpG methylation, in single molecules of DNA. The most commonly used methods for long-read sequencing are nanopore developed by Oxford Nanopore Technologies (ONT) and single molecule real-time (SMRT) sequencing developed by Pacific Bioscience (PacBio). In this study, we systematically compare the performance of CpG methylation detection from long-read sequencing.

RESULTS

We demonstrate that CpG methylation detection from 7179 nanopore-sequenced DNA samples is highly accurate and consistent with 132 oxidative bisulfite-sequenced (oxBS) samples, isolated from the same blood draws. We introduce quality filters for CpGs that further enhance the accuracy of CpG methylation detection from nanopore-sequenced DNA, while removing at most 30% of CpGs. We evaluate the per-site performance of CpG methylation detection across different genomic features and CpG methylation rates and demonstrate how the latest R10.4 flowcell chemistry and base-calling algorithms improve methylation detection from nanopore sequencing. Additionally, we show how the methylation detection of 50 SMRT-sequenced genomes compares to nanopore sequencing and oxBS.

CONCLUSIONS

This study provides the first systematic comparison of CpG methylation detection tools for long-read sequencing methods. We compare two commonly used computational methods for the detection of CpG methylation in a large number of nanopore genomes, including samples sequenced using the latest R10.4 nanopore flowcell chemistry and 50 SMRT sequenced samples. We provide insights into the strengths and limitations of each sequencing method as well as recommendations for standardization and evaluation of tools designed for genome-scale modified base detection using long-read sequencing.

Uncalled4 improves nanopore DNA and RNA modification detection via fast and accurate signal alignment

Nanopore signal analysis enables detection of nucleotide modifications from native DNA and RNA sequencing, providing both accurate genetic/transcriptomic and epigenetic information without additional library preparation. Presently, only a limited set of modifications can be directly basecalled (e.g. 5-methylcytosine), while most others require exploratory methods that often begin with alignment of nanopore signal to a nucleotide reference. We present Uncalled4, a toolkit for nanopore signal alignment, analysis, and visualization. Uncalled4 features an efficient banded signal alignment algorithm, BAM signal alignment file format, statistics for comparing signal alignment methods, and a reproducible de novo training method for k-mer-based pore models, revealing potential errors in ONT's state-of-the-art DNA model. We apply Uncalled4 to RNA 6-methyladenine (m6A) detection in seven human cell lines, identifying 26% more modifications than Nanopolish using m6Anet, including in several genes where m6A has known implications in cancer. Uncalled4 is available open-source at github.com/skovaka/uncalled4.

Characterisation and reproducibility of the HumanMethylationEPIC v2.0 BeadChip for DNA methylation profiling

BACKGROUND

The Illumina family of Infinium Methylation BeadChip microarrays has been widely used over the last 15 years for genome-wide DNA methylation profiling, including large-scale and population-based studies, due to their ease of use and cost effectiveness. Succeeding the popular HumanMethylationEPIC BeadChip (EPICv1), the recently released Infinium MethylationEPIC v2.0 BeadChip (EPICv2) claims to extend genomic coverage to more than 935,000 CpG sites. Here, we comprehensively characterise the reproducibility, reliability and annotation of the EPICv2 array, based on bioinformatic analysis of both manifest data and new EPICv2 data from diverse biological samples.

RESULTS

We find a high degree of reproducibility with EPICv1, evidenced by comparable sensitivity and precision from empirical cross-platform comparison incorporating whole genome bisulphite sequencing (WGBS), and high correlation between technical sample replicates, including between samples with DNA input levels below the manufacturer's recommendation. We provide a full assessment of probe content, evaluating genomic distribution and changes from previous array versions. We characterise EPICv2's new feature of replicated probes and provide recommendations as to the superior probes. In silico analysis of probe sequences demonstrates that probe cross-hybridisation remains a significant problem in EPICv2. By mapping the off-target sites at single nucleotide resolution and comparing with WGBS we show empirical evidence for preferential off-target binding.

CONCLUSIONS

Overall, we find EPICv2 a worthy successor to the previous Infinium methylation microarrays, however some technical issues remain. To support optimal EPICv2 data analysis we provide an expanded version of the EPICv2 manifest to aid researchers in understanding probe design, data processing, choosing appropriate probes for analysis and for integration with methylation datasets from previous versions of the Infinium Methylation BeadChip.

Long read sequencing on its way to the routine diagnostics of genetic diseases

The clinical application of technological progress in the identification of DNA alterations has always led to improvements of diagnostic yields in genetic medicine. At chromosome side, from cytogenetic techniques evaluating number and gross structural defects to genomic microarrays detecting cryptic copy number variants, and at molecular level, from Sanger method studying the nucleotide sequence of single genes to the high-throughput next-generation sequencing (NGS) technologies, resolution and sensitivity progressively increased expanding considerably the range of detectable DNA anomalies and alongside of Mendelian disorders with known genetic causes. However, particular genomic regions (i.e., repetitive and GC-rich sequences) are inefficiently analyzed by standard genetic tests, still relying on laborious, time-consuming and low-sensitive approaches (i.e., southern-blot for repeat expansion or long-PCR for genes with highly homologous pseudogenes), accounting for at least part of the patients with undiagnosed genetic disorders. Third generation sequencing, generating long reads with improved mappability, is more suitable for the detection of structural alterations and defects in hardly accessible genomic regions. Although recently implemented and not yet clinically available, long read sequencing (LRS) technologies have already shown their potential in genetic medicine research that might greatly impact on diagnostic yield and reporting times, through their translation to clinical settings. The main investigated LRS application concerns the identification of structural variants and repeat expansions, probably because techniques for their detection have not evolved as rapidly as those dedicated to single nucleotide variants (SNV) identification: gold standard analyses are karyotyping and microarrays for balanced and unbalanced chromosome rearrangements, respectively, and southern blot and repeat-primed PCR for the amplification and sizing of expanded alleles, impaired by limited resolution and sensitivity that have not been significantly improved by the advent of NGS. Nevertheless, more recently, with the increased accuracy provided by the latest product releases, LRS has been tested also for SNV detection, especially in genes with highly homologous pseudogenes and for haplotype reconstruction to assess the parental origin of alleles with de novo pathogenic variants. We provide a review of relevant recent scientific papers exploring LRS potential in the diagnosis of genetic diseases and its potential future applications in routine genetic testing.

Novel genotype-phenotype correlations, differential cerebellar allele-specific methylation, and a common origin of the (ATTTC)n insertion in spinocerebellar ataxia type 37

Spinocerebellar ataxia subtype 37 (SCA37) is a rare disease originally identified in ataxia patients from the Iberian Peninsula with a pure cerebellar syndrome. SCA37 patients carry a pathogenic intronic (ATTTC)n repeat insertion flanked by two polymorphic (ATTTT)n repeats in the Disabled-1 (DAB1) gene leading to cerebellar dysregulation. Herein, we determine the precise configuration of the pathogenic 5'(ATTTT)n-(ATTTC)n-3'(ATTTT)n SCA37 alleles by CRISPR-Cas9 and long-read nanopore sequencing, reveal their epigenomic signatures in SCA37 lymphocytes, fibroblasts, and cerebellar samples, and establish new molecular and clinical correlations. The 5'(ATTTT)n-(ATTTC)n-3'(ATTTT)n pathogenic allele configurations revealed repeat instability and differential methylation signatures. Disease age of onset negatively correlated with the (ATTTC)n, and positively correlated with the 3'(ATTTT)n. Geographic origin and gender significantly correlated with age of onset. Furthermore, significant predictive regression models were obtained by machine learning for age of onset and disease evolution by considering gender, the (ATTTC)n, the 3'(ATTTT)n, and seven CpG positions differentially methylated in SCA37 cerebellum. A common 964-kb genomic region spanning the (ATTTC)n insertion was identified in all SCA37 patients analysed from Portugal and Spain, evidencing a common origin of the SCA37 mutation in the Iberian Peninsula originating 859 years ago (95% CI 647-1378). In conclusion, we demonstrate an accurate determination of the size and configuration of the regulatory 5'(ATTTT)n-(ATTTC)n-3'(ATTTT)n repeat tract, avoiding PCR bias amplification using CRISPR/Cas9-enrichment and nanopore long-read sequencing, resulting relevant for accurate genetic diagnosis of SCA37. Moreover, we determine novel significant genotype-phenotype correlations in SCA37 and identify differential cerebellar allele-specific methylation signatures that may underlie DAB1 pathogenic dysregulation.

High estrogen during ovarian stimulation induced loss of maternal imprinted methylation that is essential for placental development via overexpression of TET2 in mouse oocytes

BACKGROUND

Ovarian stimulation (OS) during assisted reproductive technology (ART) appears to be an independent factor influencing the risk of low birth weight (LBW). Previous studies identified the association between LBW and placenta deterioration, potentially resulting from disturbed genomic DNA methylation in oocytes caused by OS. However, the mechanisms by which OS leads to aberrant DNA methylation patterns in oocytes remains unclear.

METHODS

Mouse oocytes and mouse parthenogenetic embryonic stem cells (pESCs) were used to investigate the roles of OS in oocyte DNA methylation. Global 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) levels were evaluated using immunofluorescence or colorimetry. Genome-wide DNA methylation was quantified using an Agilent SureSelectXT mouse Methyl-Seq. The DNA methylation status of mesoderm-specific transcript homologue (Mest) promoter region was analyzed using bisulfite sequencing polymerase chain reaction (BSP). The regulatory network between estrogen receptor alpha (ERα, ESR1) and DNA methylation status of Mest promoter region was further detected following the knockdown of ERα or ten-eleven translocation 2 (Tet2).

RESULTS

OS resulted in a significant decrease in global 5mC levels and an increase in global 5hmC levels in oocytes. Further investigation revealed that supraphysiological β-estradiol (E2) during OS induced a notable decrease in DNA 5mC and an increase in 5hmC in both oocytes and pESCs of mice, whereas inhibition of estrogen signaling abolished such induction. Moreover, Tet2 may be a direct transcriptional target gene of ERα, and through the ERα-TET2 axis, supraphysiological E2 resulted in the reduced global levels of DNA 5mC. Furthermore, we identified that MEST, a maternal imprinted gene essential for placental development, lost its imprinted methylation in parthenogenetic placentas originating from OS, and ERα and TET2 combined together to form a protein complex that may promote Mest demethylation.

CONCLUSIONS

In this study, a possible mechanism of loss of DNA methylation in oocyte caused by OS was revealed, which may help increase safety and reduce epigenetic abnormalities in ART procedures.

A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing

Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequencing, allows reduced representation methylation sequencing that can be applied to CpG islands or imprinted regions. Here we present DeepMod2, a comprehensive deep-learning framework for methylation detection using ionic current signal from Nanopore sequencing. DeepMod2 implements both a bidirectional long short-term memory (BiLSTM) model and a Transformer model and can analyze POD5 and FAST5 signal files generated on R9 and R10 flowcells. Additionally, DeepMod2 can run efficiently on central processing unit (CPU) through model pruning and can infer epihaplotypes or haplotype-specific methylation calls from phased reads. We use multiple publicly available and newly generated datasets to evaluate the performance of DeepMod2 under varying scenarios. DeepMod2 has comparable performance to Guppy and Dorado, which are the current state-of-the-art methods from Oxford Nanopore Technologies that remain closed-source. Moreover, we show a high correlation (r = 0.96) between reduced representation and whole-genome Nanopore sequencing. In summary, DeepMod2 is an open-source tool that enables fast and accurate DNA methylation detection from whole-genome or adaptive sequencing data on a diverse range of flowcell types.

NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection

MOTIVATION

5-Methylcytosine (5mC), a fundamental element of DNA methylation in eukaryotes, plays a vital role in gene expression regulation, embryonic development, and other biological processes. Although several computational methods have been proposed for detecting the base modifications in DNA like 5mC sites from Nanopore sequencing data, they face challenges including sensitivity to noise, and ignoring the imbalanced distribution of methylation sites in real-world scenarios.

RESULTS

Here, we develop NanoCon, a deep hybrid network coupled with contrastive learning strategy to detect 5mC methylation sites from Nanopore reads. In particular, we adopted a contrastive learning module to alleviate the issues caused by imbalanced data distribution in nanopore sequencing, offering a more accurate and robust detection of 5mC sites. Evaluation results demonstrate that NanoCon outperforms existing methods, highlighting its potential as a valuable tool in genomic sequencing and methylation prediction. In addition, we also verified the effectiveness of our representation learning ability on two datasets by visualizing the dimension reduction of the features of methylation and nonmethylation sites from our NanoCon. Furthermore, cross-species and cross-5mC methylation motifs experiments indicated the robustness and the ability to perform transfer learning of our model. We hope this work can contribute to the community by providing a powerful and reliable solution for 5mC site detection in genomic studies.

AVAILABILITY AND IMPLEMENTATION

The project code is available at https://github.com/Challis-yin/NanoCon.

Circulating cell-free DNA-based methylation pattern in plasma for early diagnosis of esophagus cancer

With the increased awareness of early tumor detection, the importance of detecting and diagnosing esophageal cancer in its early stages has been underscored. Studies have consistently demonstrated the crucial role of methylation levels in circulating cell-free DNA (cfDNA) in identifying and diagnosing early-stage cancer. cfDNA methylation pertains to the methylation state within the genomic scope of cfDNA and is strongly associated with cancer development and progression. Several research teams have delved into the potential application of cfDNA methylation in identifying early-stage esophageal cancer and have achieved promising outcomes. Recent research supports the high sensitivity and specificity of cfDNA methylation in early esophageal cancer diagnosis, providing a more accurate and efficient approach for early detection and improved clinical management. Accordingly, this review aims to present an overview of methylation-based cfDNA research with a focus on the latest developments in the early detection of esophageal cancer. Additionally, this review summarizes advanced analytical technologies for cfDNA methylation that have significantly benefited from recent advancements in separation and detection techniques, such as methylated DNA immunoprecipitation sequencing (MeDIP-seq). Recent findings suggest that biomarkers based on cfDNA methylation may soon find successful applications in the early detection of esophageal cancer. However, large-scale prospective clinical trials are required to identify the potential of these biomarkers.

Wakefield M. The role of aberrant DNA methylation in cancer initiation and clinical impacts

Epigenetic alterations, including aberrant DNA methylation, are now recognized as bone fide hallmarks of cancer, which can contribute to cancer initiation, progression, therapy responses and therapy resistance. Methylation of gene promoters can have a range of impacts on cancer risk, clinical stratification and therapeutic outcomes. We provide several important examples of genes, which can be silenced or activated by promoter methylation and highlight their clinical implications. These include the mismatch DNA repair genes MLH1 and MSH2, homologous recombination DNA repair genes BRCA1 and RAD51C, the TERT oncogene and genes within the P15/P16/RB1/E2F tumour suppressor axis. We also discuss how these methylation changes might occur in the first place - whether in the context of the CpG island methylator phenotype or constitutional DNA methylation. The choice of assay used to measure methylation can have a significant impact on interpretation of methylation states, and some examples where this can influence clinical decision-making are presented. Aberrant DNA methylation patterns in circulating tumour DNA (ctDNA) are also showing great promise in the context of non-invasive cancer detection and monitoring using liquid biopsies; however, caution must be taken in interpreting these results in cases where constitutional methylation may be present. Thus, this review aims to provide researchers and clinicians with a comprehensive summary of this broad, but important subject, illustrating the potentials and pitfalls of assessing aberrant DNA methylation in cancer.

Spatial chromatin accessibility sequencing resolves high-order spatial interactions of epigenomic markers

As the genome is organized into a three-dimensional structure in intracellular space, epigenomic information also has a complex spatial arrangement. However, most epigenetic studies describe locations of methylation marks, chromatin accessibility regions, and histone modifications in the horizontal dimension. Proper spatial epigenomic information has rarely been obtained. In this study, we designed spatial chromatin accessibility sequencing (SCA-seq) to resolve the genome conformation by capturing the epigenetic information in single-molecular resolution while simultaneously resolving the genome conformation. Using SCA-seq, we are able to examine the spatial interaction of chromatin accessibility (e.g. enhancer-promoter contacts), CpG island methylation, and spatial insulating functions of the CCCTC-binding factor. We demonstrate that SCA-seq paves the way to explore the mechanism of epigenetic interactions and extends our knowledge in 3D packaging of DNA in the nucleus.

Preimplantation genetic testing: A remarkable history of pioneering, technical challenges, innovations, and ethical considerations

Preimplantation genetic testing (PGT) has emerged as a powerful companion to assisted reproduction technologies. The origins and history of PGT are reviewed here, along with descriptions of advances in molecular assays and sampling methods, their capabilities, and their applications in preventing genetic diseases and enhancing pregnancy outcomes. Additionally, the potential for increasing accuracy and genome coverage is considered, as well as some of the emerging ethical and legislative considerations related to the expanding capabilities of PGT.

Challenges facing repeat expansion identification, characterisation, and the pathway to discovery

Tandem repeat DNA sequences constitute a significant proportion of the human genome. While previously considered to be functionally inert, these sequences are now broadly accepted as important contributors to genetic diversity. However, the polymorphic nature of these sequences can lead to expansion beyond a gene-specific threshold, causing disease. More than 50 pathogenic repeat expansions have been identified to date, many of which have been discovered in the last decade as a result of advances in sequencing technologies and associated bioinformatic tools. Commonly utilised diagnostic platforms including Sanger sequencing, capillary array electrophoresis, and Southern blot are generally low throughput and are often unable to accurately determine repeat size, composition, and epigenetic signature, which are important when characterising repeat expansions. The rapid advances in bioinformatic tools designed specifically to interrogate short-read sequencing and the development of long-read single molecule sequencing is enabling a new generation of high throughput testing for repeat expansion disorders. In this review, we discuss some of the challenges surrounding the identification and characterisation of disease-causing repeat expansions and the technological advances that are poised to translate the promise of genomic medicine to individuals and families affected by these disorders.

Single molecule MATAC-seq reveals key determinants of DNA replication origin efficiency

Stochastic origin activation gives rise to significant cell-to-cell variability in the pattern of genome replication. The molecular basis for heterogeneity in efficiency and timing of individual origins is a long-standing question. Here, we developed Methylation Accessibility of TArgeted Chromatin domain Sequencing (MATAC-Seq) to determine single-molecule chromatin accessibility of four specific genomic loci. MATAC-Seq relies on preferential modification of accessible DNA by methyltransferases combined with Nanopore-Sequencing for direct readout of methylated DNA-bases. Applying MATAC-Seq to selected early-efficient and late-inefficient yeast replication origins revealed large heterogeneity of chromatin states. Disruption of INO80 or ISW2 chromatin remodeling complexes leads to changes at individual nucleosomal positions that correlate with changes in their replication efficiency. We found a chromatin state with an accessible nucleosome-free region in combination with well-positioned +1 and +2 nucleosomes as a strong predictor for efficient origin activation. Thus, MATAC-Seq identifies the large spectrum of alternative chromatin states that co-exist on a given locus previously masked in population-based experiments and provides a mechanistic basis for origin activation heterogeneity during eukaryotic DNA replication. Consequently, our single-molecule chromatin accessibility assay will be ideal to define single-molecule heterogeneity across many fundamental biological processes such as transcription, replication, or DNA repair in vitro and ex vivo.

Nanopore sequencing reveals methylation changes associated with obesity in circulating cell-free DNA from Göttingen Minipigs

Profiling of circulating cell-free DNA (cfDNA) by tissue-specific base modifications, such as 5-methylcytosines (5mC), may enable the monitoring of ongoing pathophysiological processes. Nanopore sequencing allows genome-wide 5mC detection in cfDNA without bisulphite conversion. The aims of this study were: i) to find differentially methylated regions (DMRs) of cfDNA associated with obesity in Göttingen minipigs using Nanopore sequencing, ii) to validate a subset of the DMRs using methylation-specific PCR (MSP-PCR), and iii) to compare the cfDNA DMRs with those from whole blood genomic DNA (gDNA). Serum cfDNA and gDNA were obtained from 10 lean and 7 obese Göttingen Minipigs both with experimentally induced myocardial infarction and sequenced using Oxford Nanopore MinION. A total of 1,236 cfDNA DMRs (FDR<0.01) were associated with obesity. In silico analysis showed enrichment of the adipocytokine signalling, glucagon signalling, and cellular glucose homoeostasis pathways. A strong cfDNA DMR was discovered in PPARGC1B, a gene linked to obesity and type 2 diabetes. The DMR was validated using MSP-PCR and correlated significantly with body weight (P < 0.05). No DMRs intersected between cfDNA and gDNA, suggesting that cfDNA originates from body-wide shedding of DNA. In conclusion, nanopore sequencing detected differential methylation in minute quantities (0.1-1 ng/µl) of cfDNA. Future work should focus on translation into human and comparing 5mC from somatic tissues to pinpoint the exact location of pathology.

Snapper: high-sensitive detection of methylation motifs based on Oxford Nanopore reads

MOTIVATION

The Oxford Nanopore technology has a great potential for the analysis of methylated motifs in genomes, including whole-genome methylome profiling. However, we found that there are no methylation motifs detection algorithms, which would be sensitive enough and return deterministic results. Thus, the MEME suit does not extract all Helicobacter pylori methylation sites de novo even using the iterative approach implemented in the most up-to-date methylation analysis tool Nanodisco.

RESULTS

We present Snapper, a new highly sensitive approach, to extract methylation motif sequences based on a greedy motif selection algorithm. Snapper does not require manual control during the enrichment process and has enrichment sensitivity higher than MEME coupled with Tombo or Nanodisco instruments that was demonstrated on H.pylori strain J99 studied earlier by the PacBio technology and on four external datasets representing different bacterial species. We used Snapper to characterize the total methylome of a new H.pylori strain A45. At least four methylation sites that have not been described for H.pylori earlier were revealed. We experimentally confirmed the presence of a new CCAG-specific methyltransferase and inferred a gene encoding a new CCAAK-specific methyltransferase.

AVAILABILITY AND IMPLEMENTATION

Snapper is implemented using Python and is freely available as a pip package named "snapper-ont." Also, Snapper and the demo dataset are available in Zenodo (10.5281/zenodo.10117651).

Detection of neuron-derived cfDNA in blood plasma: a new diagnostic approach for neurodegenerative conditions

Neurodegenerative diseases, such as Alzheimer's disease (AD), pose significant challenges in early diagnosis, leading to irreversible brain damage and cognitive decline. In this study, we present a novel diagnostic approach that utilizes whole molecule analysis of neuron-derived cell-free DNA (cfDNA) as a biomarker for early detection of neurodegenerative diseases. By analyzing Differential Methylation Regions (DMRs) between purified cortical neurons and blood plasma samples, we identified robust biomarkers that accurately distinguish between neuronal and non-neuronal cfDNA. The use of cfDNA offers the advantage of convenient and minimally invasive sample collection compared to traditional cerebrospinal fluid or tissue biopsies, making this approach more accessible and patient friendly. Targeted sequencing at the identified DMR locus demonstrated that a conservative cutoff of 5% of neuron-derived cfDNA in blood plasma accurately identifies 100% of patients diagnosed with AD, showing promising potential for early disease detection. Additionally, this method effectively differentiated between patients with mild cognitive impairment (MCI) who later progressed to AD and those who did not, highlighting its prognostic capabilities. Importantly, the differentiation between patients with neurodegenerative diseases and healthy controls demonstrated the specificity of our approach. Furthermore, this cfDNA-based diagnostic strategy outperforms recently developed protein-based assays, which often lack accuracy and convenience. While our current approach focused on a limited set of loci, future research should explore the development of a more comprehensive model incorporating multiple loci to increase diagnostic accuracy further. Although certain limitations, such as technical variance associated with PCR amplification and bisulfite conversion, need to be addressed, this study emphasizes the potential of cfDNA analysis as a valuable tool for pre-symptomatic detection and monitoring of neurodegenerative diseases. With further development and validation, this innovative diagnostic strategy has the potential to significantly impact the field of neurodegenerative disease research and patient care, offering a promising avenue for early intervention and personalized therapeutic approaches.

Comparison of methylation estimates obtained via MinION nanopore sequencing and sanger bisulfite sequencing in the TRPA1 promoter region

BACKGROUND

Bisulfite sequencing has long been considered the gold standard for measuring DNA methylation at single CpG resolution. However, in recent years several new approaches like nanopore sequencing have been developed due to hints for a partial error-proneness of bisulfite sequencing. Since these errors were shown to be sequence-specific, we aimed to verify the methylation data of a particular region of the TRPA1 promoter from our previous studies obtained by bisulfite sequencing.

METHODS

We compared methylation rates determined by direct bisulfite sequencing and nanopore sequencing following Cas9-mediated PCR-free enrichment.

RESULTS

We could show that CpG methylation levels above 20% corroborate well with our previous data. Within the range between 0 and 20% methylation, however, Sanger sequencing data have to be interpreted cautiously, at least in the investigated region of interest (TRPA1 promotor region).

CONCLUSION

Based on the investigation of the TRPA1- region as an example, the present work can help in choosing the right method out of the two current main approaches for methylation analysis for different individual settings regarding many factors like cohort size, costs and prerequisites that should be fulfilled for each method. All in all, both methods have their raison d'être. Furthermore, the present paper contains and illustrates some important basic information and explanation of how guide RNAs should be located for an optimal outcome in Cas9 mediated PCR free target enrichment.

Unlocking the secrets: the power of methylation-based cfDNA detection of tissue damage in organ systems

BACKGROUND

Detecting organ and tissue damage is essential for early diagnosis, treatment decisions, and monitoring disease progression. Methylation-based assays offer a promising approach, as DNA methylation patterns can change in response to tissue damage. These assays have potential applications in early detection, monitoring disease progression, evaluating treatment efficacy, and assessing organ viability for transplantation. cfDNA released into the bloodstream upon tissue or organ injury can serve as a biomarker for damage. The epigenetic state of cfDNA, including DNA methylation patterns, can provide insights into the extent of tissue and organ damage.

CONTENT

Firstly, this review highlights DNA methylation as an extensively studied epigenetic modification that plays a pivotal role in processes such as cell growth, differentiation, and disease development. It then presents a variety of highly precise 5-mC methylation detection techniques that serve as powerful tools for gaining profound insights into epigenetic alterations linked with tissue damage. Subsequently, the review delves into the mechanisms underlying DNA methylation changes in organ and tissue damage, encompassing inflammation, oxidative stress, and DNA damage repair mechanisms. Next, it addresses the current research status of cfDNA methylation in the detection of specific organ tissues and organ damage. Finally, it provides an overview of the multiple steps involved in identifying specific methylation markers associated with tissue and organ damage for clinical trials. This review will explore the mechanisms and current state of research on cfDNA methylation-based assay detecting organ and tissue damage, the underlying mechanisms, and potential applications in clinical practice.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

DARESOME enables concurrent profiling of multiple DNA modifications with restriction enzymes in single cells and cell-free DNA

5-Methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are the most abundant DNA modifications that have important roles in gene regulation. Detailed studies of these different epigenetic marks aimed at understanding their combined effects and dynamic interconversion are, however, hampered by the inability of current methods to simultaneously measure both modifications, particularly in samples with limited quantities. We present DNA analysis by restriction enzyme for simultaneous detection of multiple epigenomic states (DARESOME), an assay based on modification-sensitive restriction digest and sequential tag ligation that can concurrently perform quantitative profiling of unmodified cytosine, 5mC, and 5hmC in CCGG sites genome-wide. DARESOME reveals the opposing roles of 5mC and 5hmC in gene expression regulation as well as their interconversion during aging in mouse brain. Implementation of DARESOME in single cells demonstrates pronounced 5hmC strand bias that reflects the semiconservative replication of DNA. Last, we showed that DARESOME enables integrative genomic, 5mC, and 5hmC profiling of cell-free DNA that uncovered multiomics cancer signatures in liquid biopsy.

Genome-Enabled Insights into Downy Mildew Biology and Evolution

Oomycetes that cause downy mildew diseases are highly specialized, obligately biotrophic phytopathogens that can have major impacts on agriculture and natural ecosystems. Deciphering the genome sequence of these organisms provides foundational tools to study and deploy control strategies against downy mildew pathogens (DMPs). The recent telomere-to-telomere genome assembly of the DMP Peronospora effusa revealed high levels of synteny with distantly related DMPs, higher than expected repeat content, and previously undescribed architectures. This provides a road map for generating similar high-quality genome assemblies for other oomycetes. This review discusses biological insights made using this and other assemblies, including ancestral chromosome architecture, modes of sexual and asexual variation, the occurrence of heterokaryosis, candidate gene identification, functional validation, and population dynamics. We also discuss future avenues of research likely to be fruitful in studies of DMPs and highlight resources necessary for advancing our understanding and ability to forecast and control disease outbreaks.

Long-read sequencing reveals the complex structure of extra dic(21;21) chromosome and its biological effects

Complex congenital chromosome abnormalities are rare but often cause severe symptoms. However, the structures and biological impacts of such abnormalities have seldomly been analyzed at the molecular level. Previously, we reported a Japanese female patient with severe developmental defects. The patient had an extra dicentric chromosome 21 (chr21) consisting of two partial chr21 copies fused together within their long arms along with two centromeres and many copy number changes. In this study, we performed whole-genome, transcriptional, and DNA methylation analyses, coupled with novel bioinformatic approaches, to reveal the complex structure of the extra chromosome and its transcriptional and epigenetic changes. Long-read sequencing accurately identified the structures of junctions related to the copy number changes in extra chr21 and suggested the mechanism of the structural changes. Our transcriptome analysis showed the overexpression of genes in extra chr21. Additionally, an allele-specific DNA methylation analysis of the long-read sequencing data suggested that the centromeric region of extra chr21 was hypermethylated, a property associated with the inactivation of one centromere in the extra chromosome. Our comprehensive analysis provides insights into the molecular mechanism underlying the generation of the extra chromosome and its pathogenic roles.

A tool for rapid, automated characterization of population epigenomics in plants

Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given sample of DNA, tools to profile and compare the methylomes of multiple individual plants or groups of plants at high resolution and low cost are lacking. Here, we describe a computational approach and R package (sounDMR) that leverages the benefits of long read nanopore sequencing to enable robust identification of differential methylation from complex experimental designs, as well as assess the variability within treatment groups and identify individual plants of interest. We demonstrate the utility of this approach by profiling a population of Arabidopsis thaliana exposed to a demethylating agent and identify genomic regions of high epigenetic variability between individuals. Given the low cost of nanopore sequencing devices and the ease of sample preparation, these results show that high resolution epigenetic profiling of plant populations can be made more broadly accessible in plant breeding and biotechnology.

Third-Generation Sequencing Reveals the Adaptive Role of the Epigenome in Three Deep-Sea Polychaetes

The roles of DNA methylation in invertebrates are poorly characterized, and critical data are missing for the phylum Annelida. We fill this knowledge gap by conducting the first genome-wide survey of DNA methylation in the deep-sea polychaetes dominant in deep-sea vents and seeps: Paraescarpia echinospica, Ridgeia piscesae, and Paralvinella palmiformis. DNA methylation calls were inferred from Oxford Nanopore sequencing after assembling high-quality genomes of these animals. The genomes of these worms encode all the key enzymes of the DNA methylation metabolism and possess a mosaic methylome similar to that of other invertebrates. Transcriptomic data of these polychaetes support the hypotheses that gene body methylation strengthens the expression of housekeeping genes and that promoter methylation acts as a silencing mechanism but not the hypothesis that DNA methylation suppresses the activity of transposable elements. The conserved epigenetic profiles of genes responsible for maintaining homeostasis under extreme hydrostatic pressure suggest DNA methylation plays an important adaptive role in these worms.

Host DNA Demethylation Induced by DNMT1 Inhibition Up-Regulates Antiviral OASL Protein during Influenza a Virus Infection

Influenza A virus (IAV) is a leading cause of human respiratory infections and poses a major public health concern. IAV replication can affect the expression of DNA methyltransferases (DNMTs), and the subsequent changes in DNA methylation regulate gene expression and may lead to abnormal gene transcription and translation, yet the underlying mechanisms of virus-induced epigenetic changes from DNA methylation and its role in virus-host interactions remain elusive. Here in this paper, we showed that DNMT1 expression could be suppressed following the inhibition of miR-142-5p or the PI3K/AKT signaling pathway during IAV infection, resulting in demethylation of the promotor region of the 2'-5'-oligoadenylate synthetase-like (OASL) protein and promotion of its expression in A549 cells. OASL expression enhanced RIG-I-mediated interferon induction and then suppressed replication of IAV. Our study elucidated an innate immunity mechanism by which up-regulation of OASL contributes to host antiviral responses via epigenetic modifications in IAV infection, which could provide important insights into the understanding of viral pathogenesis and host antiviral defense.

Taming transposable elements in livestock and poultry: a review of their roles and applications

Livestock and poultry play a significant role in human nutrition by converting agricultural by-products into high-quality proteins. To meet the growing demand for safe animal protein, genetic improvement of livestock must be done sustainably while minimizing negative environmental impacts. Transposable elements (TE) are important components of livestock and poultry genomes, contributing to their genetic diversity, chromatin states, gene regulatory networks, and complex traits of economic value. However, compared to other species, research on TE in livestock and poultry is still in its early stages. In this review, we analyze 72 studies published in the past 20 years, summarize the TE composition in livestock and poultry genomes, and focus on their potential roles in functional genomics. We also discuss bioinformatic tools and strategies for integrating multi-omics data with TE, and explore future directions, feasibility, and challenges of TE research in livestock and poultry. In addition, we suggest strategies to apply TE in basic biological research and animal breeding. Our goal is to provide a new perspective on the importance of TE in livestock and poultry genomes.

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.

Detection of Biological Molecules Using Nanopore Sensing Techniques

Modern biomedical sensing techniques have significantly increased in precision and accuracy due to new technologies that enable speed and that can be tailored to be highly specific for markers of a particular disease. Diagnosing early-stage conditions is paramount to treating serious diseases. Usually, in the early stages of the disease, the number of specific biomarkers is very low and sometimes difficult to detect using classical diagnostic methods. Among detection methods, biosensors are currently attracting significant interest in medicine, for advantages such as easy operation, speed, and portability, with additional benefits of low costs and repeated reliable results. Single-molecule sensors such as nanopores that can detect biomolecules at low concentrations have the potential to become clinically relevant. As such, several applications have been introduced in this field for the detection of blood markers, nucleic acids, or proteins. The use of nanopores has yet to reach maturity for standardization as diagnostic techniques, however, they promise enormous potential, as progress is made into stabilizing nanopore structures, enhancing chemistries, and improving data collection and bioinformatic analysis. This review offers a new perspective on current biomolecule sensing techniques, based on various types of nanopores, challenges, and approaches toward implementation in clinical settings.

Navigating the pitfalls of mapping DNA and RNA modifications

Chemical modifications to nucleic acids occur across the kingdoms of life and carry important regulatory information. Reliable high-resolution mapping of these modifications is the foundation of functional and mechanistic studies, and recent methodological advances based on next-generation sequencing and long-read sequencing platforms are critical to achieving this aim. However, mapping technologies may have limitations that sometimes lead to inconsistent results. Some of these limitations are technical in nature and specific to certain types of technology. Here, however, we focus on common (yet not always widely recognized) pitfalls that are shared among frequently used mapping technologies and discuss strategies to help technology developers and users mitigate their effects. Although the emphasis is primarily on DNA modifications, RNA modifications are also discussed.

Exploring the crop epigenome: a comparison of DNA methylation profiling techniques

Epigenetic modifications play a vital role in the preservation of genome integrity and in the regulation of gene expression. DNA methylation, one of the key mechanisms of epigenetic control, impacts growth, development, stress response and adaptability of all organisms, including plants. The detection of DNA methylation marks is crucial for understanding the mechanisms underlying these processes and for developing strategies to improve productivity and stress resistance of crop plants. There are different methods for detecting plant DNA methylation, such as bisulfite sequencing, methylation-sensitive amplified polymorphism, genome-wide DNA methylation analysis, methylated DNA immunoprecipitation sequencing, reduced representation bisulfite sequencing, MS and immuno-based techniques. These profiling approaches vary in many aspects, including DNA input, resolution, genomic region coverage, and bioinformatics analysis. Selecting an appropriate methylation screening approach requires an understanding of all these techniques. This review provides an overview of DNA methylation profiling methods in crop plants, along with comparisons of the efficacy of these techniques between model and crop plants. The strengths and limitations of each methodological approach are outlined, and the importance of considering both technical and biological factors are highlighted. Additionally, methods for modulating DNA methylation in model and crop species are presented. Overall, this review will assist scientists in making informed decisions when selecting an appropriate DNA methylation profiling method.