Comparison of whole-genome bisulfite sequencing library preparation strategies identifies sources of biases affecting DNA methylation data

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.

Insights to aging prediction with AI based epigenetic clocks

Over the past century, human lifespan has increased remarkably, yet the inevitability of aging persists. The disparity between biological age, which reflects pathological deterioration and disease, and chronological age, indicative of normal aging, has driven prior research focused on identifying mechanisms that could inform interventions to reverse excessive age-related deterioration and reduce morbidity and mortality. DNA methylation has emerged as an important predictor of age, leading to the development of epigenetic clocks that quantify the extent of pathological deterioration beyond what is typically expected for a given age. Machine learning technologies offer promising avenues to enhance our understanding of the biological mechanisms governing aging by further elucidating the gap between biological and chronological ages. This perspective article examines current algorithmic approaches to epigenetic clocks, explores the use of machine learning for age estimation from DNA methylation, and discusses how refining the interpretation of ML methods and tailoring their inferences for specific patient populations and cell types can amplify the utility of these technologies in age prediction. By harnessing insights from machine learning, we are well-positioned to effectively adapt, customize and personalize interventions aimed at aging.

Mitochondrial epigenetics brings new perspectives on doubly uniparental inheritance in bivalves

Mitochondrial epigenetics, particularly mtDNA methylation, is a flourishing field of research. MtDNA methylation appears to play multiple roles, including regulating mitochondrial transcription, cell metabolism and mitochondrial inheritance. In animals, bivalves with doubly uniparental inheritance (DUI) of mitochondria are the exception to the rule of maternal mitochondrial inheritance since DUI also involve a paternal mtDNA transmitted from the father to sons. The mechanisms underlying DUI are still unknown, but mtDNA methylation could play a role in its regulation. Here, we investigated mtDNA methylation levels and machinery in gonads of the mussel Mytilus edulis using methods based on antibodies, enzymatic cleavage and methylome sequencing. Our results confirm the presence in mitochondria of methylated cytosines and adenines and methyltransferases and unveil a more variable cytosine methylation state among males than females. Also, spermatid mtDNA is always methylated, while only few spermatozoa present methylated mtDNA suggesting a relation between cytosine methylation and development stage of male gametes. We propose that mtDNA methylation could play a role in the different fates of the parental mtDNAs in male and female embryos in M. edulis. Our study provides novel insights into the epigenetic landscape of bivalve mtDNA and highlights the multiple roles of mtDNA methylation in animals.

Validation and Performance of Quantitative BRCA1 and RAD51C Promoter Hypermethylation Testing in Breast and Ovarian Cancers

Poly (adenosine diphosphate-ribose) polymerase (PARP) inhibitors represent a significant advancement in the treatment of epithelial ovarian cancer, triple-negative breast cancer, pancreatic cancer, and castrate-resistant prostate cancer, and they are poised to improve treatment in an increasing number of other cancer types. PARP inhibitor efficacy as monotherapy has been primarily observed in tumors with deleterious genetic variants in genes involved in the homologous recombination repair pathway. Tumors without these variants have also been shown to respond; notably, those with hypermethylation at all alleles of the BRCA1 or RAD51C promoter can respond to PARP inhibitors. These epigenetic biomarkers therefore represent a patient population that may also benefit from this targeted therapy. However, no robust test has been conducted to identify these biomarkers in routine clinical specimens that is amenable to implementation for decentralized testing. This study describes the analytical and clinical validation of a BRCA1 and RAD51C promoter methylation test that can be run with a single-day library preparation workflow for sequencing on any next-generation sequencing platform. The results show that this test can accurately quantitate the level of promoter methylation at the BRCA1 and RAD51C genes using formalin-fixed, paraffin-embedded samples, even when the extracted DNA is extremely degraded or the input amount is limited. This test increases the precision of diagnostic tests aimed at identifying patients who are likely and unlikely to respond to PARP inhibitor therapy.

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.

Considering Biomarkers of Neurodegeneration in Alzheimer's Disease: The Potential of Circulating Cell-Free DNA in Precision Neurology

Neurodegenerative diseases, such as Alzheimer's disease (AD), are a growing public health crisis, exacerbated by an aging global population and the lack of effective early disease-modifying therapies. Early detection of neurodegenerative disorders is critical to delaying symptom onset and mitigating disease progression, but current diagnostic tools often rely on detecting pathology once clinical symptoms have emerged and significant neuronal damage has already occurred. While disease-specific biomarkers, such as amyloid-beta and tau in AD, offer precise insights, they are too limited in scope for broader neurodegeneration screening for these conditions. Conversely, general biomarkers like neurofilament light chain (NfL) provide valuable staging information but lack targeted insights. Circulating cell-free DNA (cfDNA), released during cell death, is emerging as a promising biomarker for early detection. Derived from dying cells, cfDNA can capture both general neurodegenerative signals and disease-specific insights, offering multi-layered genomic and epigenomic information. Though its clinical potential remains under investigation, advances in cfDNA detection sensitivity, standardized protocols, and reference ranges could establish cfDNA as a valuable tool for early screening. cfDNA methylation signatures, in particular, show great promise for identifying tissue-of-origin and disease-specific changes, offering a minimally invasive biomarker that could transform precision neurology. However, further research is required to address technological challenges and validate cfDNA's utility in clinical settings. Here, we review recent work assessing cfDNA as a potential early biomarker in AD. With continued advances, cfDNA could play a pivotal role in shifting care from reactive to proactive, improving diagnostic timelines and patient outcomes.

Benchmarking nanopore sequencing and rapid genomics feasibility: validation at a quaternary hospital in New Zealand

Approximately 200 critically ill infants and children in New Zealand are in high-dependency care, many suspected of having genetic conditions, requiring scalable genomic testing. We adopted an acute care genomics protocol from an accredited laboratory and established a clinical pipeline using Oxford Nanopore Technologies PromethION 2 solo system and Fabric GEM™ software. Benchmarking of the pipeline was performed using Global Alliance for Genomics and Health benchmarking tools and Genome in a Bottle samples (HG002-HG007). Evaluation of single nucleotide variants resulted in a precision and recall of 0.997 and 0.992, respectively. Small indel identification approached a precision of 0.922 and recall of 0.838. Large genomic variations from Coriell Copy Number Variation Reference Panel 1 were reliably detected with ~2 M long reads. Finally, we present results obtained from fourteen trio samples, ten of which were processed in parallel with a clinically accredited short-read rapid genomic testing pipeline (Newborn Genomics Programme; NCT06081075; 2023-10-12).

Epigenetic dynamics of partially methylated domains in human placenta and trophoblast stem cells

BACKGROUND

The placenta is essential for nutrient exchange and hormone production between the mother and the developing fetus and serves as an invaluable model for epigenetic research. Most epigenetic studies of the human placenta have used whole placentas from term pregnancies and have identified the presence of partially methylated domains (PMDs). However, the origin of these domains, which are typically absent in most somatic cells, remains unclear in the placental context.

RESULTS

Using whole-genome bisulfite sequencing and analysis of histone H3 modifications, we generated epigenetic profiles of human cytotrophoblasts during the first trimester and at term, as well as human trophoblast stem cells. Our study focused specifically on PMDs. We found that genomic regions likely to form PMDs are resistant to global DNA demethylation during trophectoderm reprogramming, and that PMDs arise through a slow methylation process within condensed chromatin near the nuclear lamina. In addition, we found significant differences in histone H3 modifications between PMDs in cytotrophoblasts and trophoblast stem cells.

CONCLUSIONS

Our findings suggest that spatiotemporal genomic features shape megabase-scale DNA methylation patterns, including PMDs, in the human placenta and highlight distinct differences in PMDs between human cytotrophoblasts and trophoblast stem cells. These findings advance our understanding of placental biology and provide a basis for further research into human development and related diseases.

Improved detection of methylation in ancient DNA

Reconstructing premortem DNA methylation levels in ancient DNA has led to breakthrough studies such as the prediction of anatomical features of the Denisovan. These studies rely on computationally inferring methylation levels from damage signals in naturally deaminated cytosines, which requires expensive high-coverage genomes. Here, we test two methods for direct methylation measurement developed for modern DNA based on either bisulfite or enzymatic methylation treatments. Bisulfite treatment shows the least reduction in DNA yields as well as the least biases during methylation conversion, demonstrating that this method can be successfully applied to ancient DNA.

Mammalian D-Cysteine controls insulin secretion in the pancreas

BACKGROUND

D-amino acids are being recognized as important molecules in mammals with function. This is a first identification of endogenous D-cysteine in mammalian pancreas.

METHODS

Using a novel stereospecific bioluminescent assay, chiral chromatography, enzyme kinetics and a transgenic mouse model we identify endogenous D-cysteine. We elucidate its function in two mice models of type 1 diabetes (STZ and NOD), and in tests of Glucose Stimulated Insulin Secretion in isolated mouse and human islets and INS-1 832/13 cell line.

RESULTS AND DISCUSSION

D-cysteine is synthesized by serine racemase (SR) and SR-/- mice produce 6-10 fold higher levels of insulin in the pancreas and plasma including higher glycogen and ketone bodies in the liver. The excess insulin is stored as amyloid in secretory vesicles and exosomes. In glucose stimulated insulin secretion in mouse and human islets, equimolar amount of D-cysteine showed higher inhibition of insulin secretion compared to D-serine, another closely related stereoisomer synthesized by SR. In mouse models of diabetes (Streptozotocin (STZ) and Non Obese Diabetes (NOD) and human pancreas, the diabetic state showed increased expression of D-cysteine compared to D-serine followed by increased expression of SR. SR-/- mice show decreased cAMP in the pancreas, lower DNA methyltransferase enzymatic and promoter activities followed by reduced phosphorylation of CREB (S133), resulting in decreased methylation of the Ins1 promoter. D-cysteine is efficiently metabolized by D-amino acid oxidase and transported by ASCT2 and Asc1. Dietary supplementation with methyl donors restored the high insulin levels and low DNMT enzymatic activity in SR-/- mice.

CONCLUSIONS

Our data show that endogenous D-cysteine in the mammalian pancreas is a regulator of insulin secretion.

Ultrafast bisulfite sequencing detection of 5-methylcytosine in DNA and RNA

Bisulfite sequencing (BS-seq) to detect 5-methylcytosine (5mC) is limited by lengthy reaction times, severe DNA damage, overestimation of 5mC level and incomplete C-to-U conversion of certain DNA sequences. We present ultrafast BS-seq (UBS-seq), which uses highly concentrated bisulfite reagents and high reaction temperatures to accelerate the bisulfite reaction by ~13-fold, resulting in reduced DNA damage and lower background noise. UBS-seq allows library construction from small amounts of purified genomic DNA, such as from cell-free DNA or directly from 1 to 100 mouse embryonic stem cells, with less overestimation of 5mC level and higher genome coverage than conventional BS-seq. Additionally, UBS-seq quantitatively maps RNA 5-methylcytosine (m5C) from low inputs of mRNA and allows the detection of m5C stoichiometry in highly structured RNA sequences. Our UBS-seq results identify NSUN2 as the major 'writer' protein responsible for the deposition of ~90% of m5C sites in HeLa mRNA and reveal enriched m5C sites in 5'-regions of mammalian mRNA, which may have functional roles in mRNA translation regulation.

A varying-coefficient model for the analysis of methylation sequencing data

DNA methylation is an important epigenetic modification involved in gene regulation. Advances in the next generation sequencing technology have enabled the retrieval of DNA methylation information at single-base-resolution. However, due to the sequencing process and the limited amount of isolated DNA, DNA-methylation-data are often noisy and sparse, which complicates the identification of differentially methylated regions (DMRs), especially when few replicates are available. We present a varying-coefficient model for detecting DMRs by using single-base-resolved methylation information. The model simultaneously smooths the methylation profiles and allows detection of DMRs, while accounting for additional covariates. The proposed model takes into account possible overdispersion by using a beta-binomial distribution. The overdispersion itself can be modeled as a function of the genomic region and explanatory variables. We illustrate the properties of the proposed model by applying it to two real-life case studies.

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.

Beyond the base pairs: comparative genome-wide DNA methylation profiling across sequencing technologies

Deoxyribonucleic acid (DNA) methylation plays a key role in gene regulation and is critical for development and human disease. Techniques such as whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) allow DNA methylation analysis at the genome scale, with Illumina NovaSeq 6000 and MGI Tech DNBSEQ-T7 being popular due to their efficiency and affordability. However, detailed comparative studies of their performance are not available. In this study, we constructed 60 WGBS and RRBS libraries for two platforms using different types of clinical samples and generated approximately 2.8 terabases of sequencing data. We systematically compared quality control metrics, genomic coverage, CpG methylation levels, intra- and interplatform correlations, and performance in detecting differentially methylated positions. Our results revealed that the DNBSEQ platform exhibited better raw read quality, although base quality recalibration indicated potential overestimation of base quality. The DNBSEQ platform also showed lower sequencing depth and less coverage uniformity in GC-rich regions than did the NovaSeq platform and tended to enrich methylated regions. Overall, both platforms demonstrated robust intra- and interplatform reproducibility for RRBS and WGBS, with NovaSeq performing better for WGBS, highlighting the importance of considering these factors when selecting a platform for bisulfite sequencing.

Simultaneous assessment of human genome and methylome data in a single experiment using limited deamination of methylated cytosine

Multiomics require concerted recording of independent information, ideally from a single experiment. In this study, we introduce RIMS-seq2, a high-throughput technique to simultaneously sequence genomes and overlay methylation information while requiring only a small modification of the experimental protocol for high-throughput DNA sequencing to include a controlled deamination step. Importantly, the rate of deamination of 5-methylcytosine is negligible and thus does not interfere with standard DNA sequencing and data processing. Thus, RIMS-seq2 libraries from whole- or targeted-genome sequencing show the same germline variation calling accuracy and sensitivity compared with standard DNA-seq. Additionally, regional methylation levels provide an accurate map of the human methylome.

MethPhaser: methylation-based long-read haplotype phasing of human genomes

The assignment of variants across haplotypes, phasing, is crucial for predicting the consequences, interaction, and inheritance of mutations and is a key step in improving our understanding of phenotype and disease. However, phasing is limited by read length and stretches of homozygosity along the genome. To overcome this limitation, we designed MethPhaser, a method that utilizes methylation signals from Oxford Nanopore Technologies to extend Single Nucleotide Variation (SNV)-based phasing. We demonstrate that haplotype-specific methylations extensively exist in Human genomes and the advent of long-read technologies enabled direct report of methylation signals. For ONT R9 and R10 cell line data, we increase the phase length N50 by 78%-151% at a phasing accuracy of 83.4-98.7% To assess the impact of tissue purity and random methylation signals due to inactivation, we also applied MethPhaser on blood samples from 4 patients, still showing improvements over SNV-only phasing. MethPhaser further improves phasing across HLA and multiple other medically relevant genes, improving our understanding of how mutations interact across multiple phenotypes. The concept of MethPhaser can also be extended to non-human diploid genomes. MethPhaser is available at https://github.com/treangenlab/methphaser .

LABS: linear amplification-based bisulfite sequencing for ultrasensitive cancer detection from cell-free DNA

Methylation-based liquid biopsies show promises in detecting cancer using circulating cell-free DNA; however, current limitations impede clinical application. Most assays necessitate substantial DNA inputs, posing challenges. Additionally, underrepresented tumor DNA fragments may go undetected during exponential amplification steps of traditional sequencing methods. Here, we report linear amplification-based bisulfite sequencing (LABS), enabling linear amplification of bisulfite-treated DNA fragments in a genome-wide, unbiased fashion, detecting cancer abnormalities with sub-nanogram inputs. Applying LABS to 100 patient samples revealed cancer-specific patterns, copy number alterations, and enhanced cancer detection accuracy by identifying tissue-of-origin and immune cell composition.

Real-time MBDi-RPA using methyl-CpG binding protein 2: A real-time detection method for simple and rapid estimation of CpG methylation status

BACKGROUND

Analysis of CpG methylation is informative for cancer diagnosis. Previously, we developed a novel method to discriminate CpG methylation status in target DNA by blocking recombinase polymerase amplification (RPA), an isothermal DNA amplification technique, using methyl-CpG binding domain (MBD) protein 2 (MBD2). The method was named MBD protein interference-RPA (MBDi-RPA). In this study, MBDi-RPA was performed using methyl-CpG binding protein 2 (MeCP2), another MBD family protein, as the blocking agent.

RESULTS

MBDi-RPA using MeCP2 detected low levels of CpG methylation, showing that it had higher sensitivity than MBDi-RPA using MBD2. We also developed real-time RPA, which enabled rapid analysis of DNA amplification without the need for laborious agarose gel electrophoresis and used it in combination with MBDi-RPA. We termed this method real-time MBDi-RPA. The method using MeCP2 could determine the abundance ratio of CpG-methylated target DNA simply and rapidly, although highly sensitive detection was challenging.

SIGNIFICANCE AND NOVELTY

Real-time MBDi-RPA using MeCP2 could be potentially useful for estimating CpG methylation status in target DNA prior to more detailed analyses.

A preliminary study on identification of the blood donor in a body fluid mixture using a novel compound genetic marker blood-specific methylation-microhaplotype

Blood-containing mixtures are frequently encountered at crime scenes involving violence and murder. However, the presence of blood, and the association of blood with a specific donor within these mixtures present significant challenges in forensic analysis. In light of these challenges, this study sought to address these issues by leveraging blood-specific methylation sites and closely linked microhaplotype sites, proposing a novel composite genetic marker known as "blood-specific methylation-microhaplotype". This marker was designed to the detection of blood and the determination of blood donor within blood-containing mixtures. According to the selection criteria mentioned in the Materials and Methods section, we selected 10 blood-specific methylation-microhaplotype loci for inclusion in this study. Among these loci, eight exhibited blood-specific hypomethylation, while the remaining two displayed blood-specific hypermethylation. Based on data obtained from 124 individual samples in our study, the combined discrimination power (CPD) of these 10 successfully sequenced loci was 0.999999298. The sample allele methylation rate (Ram) was obtained from massive parallel sequencing (MPS), which was defined as the proportion of methylated reads to the total clustered reads that were genotyped to a specific allele. To develop an allele type classification model capable of identifying the presence of blood and the blood donor, we used the Random Forest algorithm. This model was trained and evaluated using the Ram distribution of individual samples and the Ram distribution of simulated shared alleles. Subsequently, we applied the developed allele type classification model to predict alleles within actual mixtures, trying to exclude non-blood-specific alleles, ultimately allowing us to identify the presence of blood and the blood donor in the blood-containing mixtures. Our findings demonstrate that these blood-specific methylation-microhaplotype loci have the capability to not only detect the presence of blood but also accurately associate blood with the true donor in blood-containing mixtures with the mixing ratios of 1:29, 1:19, 1:9, 1:4, 1:2, 2:1, 7:1, 8:1, 31:1 and 36:1 (blood:non-blood) by DNA mixture interpretation methods. In addition, the presence of blood and the true blood donor could be identified in a mixture containing four body fluids (blood:vaginal fluid:semen:saliva = 1:1:1:1). It is important to note that while these loci exhibit great potential, the impact of allele dropouts and alleles misidentification must be considered when interpreting the results. This is a preliminary study utilising blood-specific methylation-microhaplotype as a complementary tool to other well-established genetic markers (STR, SNP, microhaplotype, etc.) for the analysis in blood-containing mixtures.

Ultrasensitive amplification-free quantification of a methyl CpG-rich cancer biomarker by single-molecule kinetic fingerprinting

The most well-studied epigenetic marker in humans is the 5-methyl modification of cytosine in DNA, which has great potential as a disease biomarker in liquid biopsies of cell-free DNA. Currently, quantification of DNA methylation relies heavily on bisulfite conversion followed by PCR amplification and NGS or microarray analysis. PCR is subject to potential bias in differential amplification of bisulfite-converted methylated versus unmethylated sequences. Here, we combine bisulfite conversion with single-molecule kinetic fingerprinting to develop an amplification-free assay for DNA methylation at the branched-chain amino acid transaminase 1 (BCAT1) promoter. Our assay selectively responds to methylated sequences with a limit of detection below 1 fM and a specificity of 99.9999%. Evaluating complex genomic DNA matrices, we reliably distinguish 2-5% DNA methylation at the BCAT1 promoter in whole blood DNA from completely unmethylated whole-genome amplified DNA. Taken together, these results demonstrate the feasibility and sensitivity of our amplification-free, single-molecule quantification approach to improve the early detection of methylated cancer DNA biomarkers.

The omics era: a nexus of untapped potential for Mendelian chromatinopathies

The OMICs cascade describes the hierarchical flow of information through biological systems. The epigenome sits at the apex of the cascade, thereby regulating the RNA and protein expression of the human genome and governs cellular identity and function. Genes that regulate the epigenome, termed epigenes, orchestrate complex biological signaling programs that drive human development. The broad expression patterns of epigenes during human development mean that pathogenic germline mutations in epigenes can lead to clinically significant multi-system malformations, developmental delay, intellectual disabilities, and stem cell dysfunction. In this review, we refer to germline developmental disorders caused by epigene mutation as "chromatinopathies". We curated the largest number of human chromatinopathies to date and our expanded approach more than doubled the number of established chromatinopathies to 179 disorders caused by 148 epigenes. Our study revealed that 20.6% (148/720) of epigenes cause at least one chromatinopathy. In this review, we highlight key examples in which OMICs approaches have been applied to chromatinopathy patient biospecimens to identify underlying disease pathogenesis. The rapidly evolving OMICs technologies that couple molecular biology with high-throughput sequencing or proteomics allow us to dissect out the causal mechanisms driving temporal-, cellular-, and tissue-specific expression. Using the full repertoire of data generated by the OMICs cascade to study chromatinopathies will provide invaluable insight into the developmental impact of these epigenes and point toward future precision targets for these rare disorders.

Spatiotemporal DNA methylation dynamics shape megabase-scale methylome landscapes

DNA methylation is an essential epigenetic mechanism that regulates cellular reprogramming and development. Studies using whole-genome bisulfite sequencing have revealed distinct DNA methylome landscapes in human and mouse cells and tissues. However, the factors responsible for the differences in megabase-scale methylome patterns between cell types remain poorly understood. By analyzing publicly available 258 human and 301 mouse whole-genome bisulfite sequencing datasets, we reveal that genomic regions rich in guanine and cytosine, when located near the nuclear center, are highly susceptible to both global DNA demethylation and methylation events during embryonic and germline reprogramming. Furthermore, we found that regions that generate partially methylated domains during global DNA methylation are more likely to resist global DNA demethylation, contain high levels of adenine and thymine, and are adjacent to the nuclear lamina. The spatial properties of genomic regions, influenced by their guanine-cytosine content, are likely to affect the accessibility of molecules involved in DNA (de)methylation. These properties shape megabase-scale DNA methylation patterns and change as cells differentiate, leading to the emergence of different megabase-scale methylome patterns across cell types.

FinaleMe: Predicting DNA methylation by the fragmentation patterns of plasma cell-free DNA

Analysis of DNA methylation in cell-free DNA reveals clinically relevant biomarkers but requires specialized protocols such as whole-genome bisulfite sequencing. Meanwhile, millions of cell-free DNA samples are being profiled by whole-genome sequencing. Here, we develop FinaleMe, a non-homogeneous Hidden Markov Model, to predict DNA methylation of cell-free DNA and, therefore, tissues-of-origin, directly from plasma whole-genome sequencing. We validate the performance with 80 pairs of deep and shallow-coverage whole-genome sequencing and whole-genome bisulfite sequencing data.

Population epigenetics: DNA methylation in the plant omics era

DNA methylation plays an important role in many biological processes. The mechanisms underlying the establishment and maintenance of DNA methylation are well understood thanks to decades of research using DNA methylation mutants, primarily in Arabidopsis (Arabidopsis thaliana) accession Col-0. Recent genome-wide association studies (GWASs) using the methylomes of natural accessions have uncovered a complex and distinct genetic basis of variation in DNA methylation at the population level. Sequencing following bisulfite treatment has served as an excellent method for quantifying DNA methylation. Unlike studies focusing on specific accessions with reference genomes, population-scale methylome research often requires an additional round of sequencing beyond obtaining genome assemblies or genetic variations from whole-genome sequencing data, which can be cost prohibitive. Here, we provide an overview of recently developed bisulfite-free methods for quantifying methylation and cost-effective approaches for the simultaneous detection of genetic and epigenetic information. We also discuss the plasticity of DNA methylation in a specific Arabidopsis accession, the contribution of DNA methylation to plant adaptation, and the genetic determinants of variation in DNA methylation in natural populations. The recently developed technology and knowledge will greatly benefit future studies in population epigenomes.

Dissemination of Circulating Tumor Cells in Breast and Prostate Cancer: Implications for Early Detection

Burgeoning evidence suggests that circulating tumor cells (CTCs) may disseminate into blood vessels at an early stage, seeding metastases in various cancers such as breast and prostate cancer. Simultaneously, the early-stage CTCs that settle in metastatic sites [termed disseminated tumor cells (DTCs)] can enter dormancy, marking a potential source of late recurrence and therapy resistance. Thus, the presence of these early CTCs poses risks to patients but also holds potential benefits for early detection and treatment and opportunities for possibly curative interventions. This review delves into the role of early DTCs in driving latent metastasis within breast and prostate cancer, emphasizing the importance of early CTC detection in these diseases. We further explore the correlation between early CTC detection and poor prognoses, which contribute significantly to increased cancer mortality. Consequently, the detection of CTCs at an early stage emerges as a critical imperative for enhancing clinical diagnostics and allowing for early interventions.

Circulating Nucleic Acids in Colorectal Cancer: Diagnostic and Prognostic Value

Colorectal cancer (CRC) is the third most prevalent cancer in the world and the fourth leading cause of cancer-related mortality. DNA (cfDNA/ctDNA) and RNA (cfRNA/ctRNA) in the blood are promising noninvasive biomarkers for molecular profiling, screening, diagnosis, treatment management, and prognosis of CRC. Technological advancements that enable precise detection of both genetic and epigenetic abnormalities, even in minute quantities in circulation, can overcome some of these challenges. This review focuses on testing for circulating nucleic acids in the circulation as a noninvasive method for CRC detection, monitoring, detection of minimal residual disease, and patient management. In addition, the benefits and drawbacks of various diagnostic techniques and associated bioinformatics tools have been detailed.

Chemical Methods to Identify Epigenetic Modifications in Cytosine Bases

Chemical modifications to Cytosine bases are among the most studied epigenetic markers and their detection in the human genome plays a crucial role in gaining more insights about gene regulation, prognosis of genetic disorders and unraveling genetic inheritance patterns. The Cytosine methylated at the 5th position and oxidized derivatives thereof generated in the demethylation pathways, perform separate and unique epigenetic functions in an organism. As the presence of various Cytosine modifications is associated with diverse diseases, including cancer, there has been a strong focus on developing methods, both chemical and alternative approaches, capable of detecting these modifications at a single-base resolution across the entire genome. In this comprehensive review, we aim to consolidate the various chemical methods and understanding their chemistry that have been established to date for the detection of various Cytosine modifications.

Routine molecular applications and recent advances in breast cancer diagnostics

Cancer stands as one of the most common and lethal diseases, imposing a substantial burden on global mortality rates. Breast cancer is distinct from other forms of cancer in which it is the primary cause of death for women. Early detection of breast cancer can significantly lower the risk of mortality, improving the prognosis for those who are affected. The death rate of breast cancer has been steadily rising, according to epidemiological data, especially since the COVID-19 pandemic. This emphasizes the necessity of sensitive and precise technologies that can be utilized in early breast cancer diagnosis. In this process, biomarkers play a pivotal role by facilitating the early detection and diagnosis of breast cancer. Currently, a wide variety of cancer biomarkers have been identified, improving the accuracy of cancer diagnosis. These biomarkers can be applied in liquid biopsies as well as on solid tissues. In the context of breast cancer, biomarkers are particularly valuable for determining who is predisposed to the disease, predicting prognosis at the time of diagnosis, and selecting the best course of therapy. This review comprehensively explores the recently developed gene-based biomarkers from biofluids that are used in the context of breast cancer, as well as the conventional and cutting-edge techniques that have been employed for breast cancer diagnosis.

Detection of DNA methylation signatures through the lens of genomic imprinting

Genomic imprinting represents an original model of epigenetic regulation resulting in a parent-of-origin expression. Despite the critical role of imprinted genes in mammalian growth, metabolism and neuronal function, there is no molecular tool specifically targeting them for a systematic evaluation. We show here that enzymatic methyl-seq consistently outperforms the bisulfite-based standard in capturing 165 candidate regions for genomic imprinting in the pig. This highlights the potential for a turnkey, fully customizable and reliable capture tool of genomic regions regulated by cytosine methylation in any population of interest. For the field of genomic imprinting, it opens up the possibility of detecting multilocus imprinting variations across the genome, with implications for basic research, agrigenomics and clinical practice.

Current Technologies Unraveling the Significance of Post-Translational Modifications (PTMs) as Crucial Players in Neurodegeneration

Neurodegenerative disorders, such as Parkinson's disease, Alzheimer's disease, and Huntington's disease, are identified and characterized by the progressive loss of neurons and neuronal dysfunction, resulting in cognitive and motor impairment. Recent research has shown the importance of PTMs, such as phosphorylation, acetylation, methylation, ubiquitination, sumoylation, nitration, truncation, O-GlcNAcylation, and hydroxylation, in the progression of neurodegenerative disorders. PTMs can alter protein structure and function, affecting protein stability, localization, interactions, and enzymatic activity. Aberrant PTMs can lead to protein misfolding and aggregation, impaired degradation, and clearance, and ultimately, to neuronal dysfunction and death. The main objective of this review is to provide an overview of the PTMs involved in neurodegeneration, their underlying mechanisms, methods to isolate PTMs, and the potential therapeutic targets for these disorders. The PTMs discussed in this article include tau phosphorylation, α-synuclein and Huntingtin ubiquitination, histone acetylation and methylation, and RNA modifications. Understanding the role of PTMs in neurodegenerative diseases may provide new therapeutic strategies for these devastating disorders.

FinaleMe: Predicting DNA methylation by the fragmentation patterns of plasma cell-free DNA

Analysis of DNA methylation in cell-free DNA (cfDNA) reveals clinically relevant biomarkers but requires specialized protocols and sufficient input material that limits its applicability. Millions of cfDNA samples have been profiled by genomic sequencing. To maximize the gene regulation information from the existing dataset, we developed FinaleMe, a non-homogeneous Hidden Markov Model (HMM), to predict DNA methylation of cfDNA and, therefore, tissues-of-origin directly from plasma whole-genome sequencing (WGS). We validated the performance with 80 pairs of deep and shallow-coverage WGS and whole-genome bisulfite sequencing (WGBS) data.

An Overview of Global, Local, and Base-Resolution Methods for the Detection of 5-Hydroxymethylcytosine in Genomic DNA

The discovery of 5-hydroxymethylcytosine (5hmC) as a common DNA modification in mammalian genomes has ushered in new areas of inquiry regarding the dynamic epigenome. The balance between 5hmC and its precursor, 5-methylcytosine (5mC), has emerged as a determinant of key processes including cell fate specification, and alterations involving these bases have been implicated in the pathogenesis of various diseases. The identification of 5hmC separately from 5mC initially posed a challenge given that legacy epigenetic sequencing technologies could not discriminate between these two most abundant modifications, a significant blind spot considering their potentially functionally opposing roles. The growing interest in 5hmC, as well as in the Ten-Eleven Translocation (TET) family enzymes that catalyze its generation and further oxidation to 5-formylcytosine (5fC) and 5-carboxycytosine (5caC), has spurred the development of versatile methods for 5hmC detection. These methods enable the quantification and localization of 5hmC in diverse biological samples and, in some cases, at the resolution of individual nucleotides. However, navigating this growing toolbox of methods for 5hmC detection can be challenging. Here, we detail existing and emerging methods for the detection, quantification, and localization of 5hmC at global, locus-specific, and base resolution levels. These methods are discussed in the context of their advantages and limitations, with the goal of providing a framework to help guide researchers in choosing the level of resolution and the associated method that could be most suitable for specific needs.

A targeted long-read sequencing approach questions the association of OXTR methylation with high-functioning autism

BACKGROUND

DNA sequence variation and altered epigenetic regulation of the oxytocin receptor gene (OXTR) have been implicated in autism and autistic-like behaviors. While previous studies have examined subsegments of OXTR, nanopore Cas9-targeted sequencing (nCATS) allows deep characterization of entire genes with simultaneous assessment of epigenetic 5-methylcytosine (5mC) modification and without the need for prior DNA amplification or bisulfite conversion. This pilot study uses an nCATS approach to sequence the entire OXTR gene and its regulatory construct and screen for 5mC modification to compare results between individuals with high-functioning autism (HFA) and neurotypical controls (NC).

METHODS

Using DNA extracted from peripheral blood, OXTR (Hg38, chr3: 8750381-8770434, 20,054 base pairs) was analyzed by nCATS. 5mC modification probabilities were calculated and visualized across the gene and differential methylation analysis was performed.

RESULTS

Twenty adults with HFA (10 males, 10 females) and 20 age- and sex-matched NC (± 5 years) were included. There were no apparent group differences in the entire OXTR gene sequence, except for the intron variant rs918316, which was clustered in the HFA group. However, differential methylation analysis did not reveal a single significant group-dependent differentially methylated site among the 412 CpG sites captured.

LIMITATIONS

Limitations of this study include the small number of samples due to the pilot nature of the study, which particularly limits the relevance of the sequence variants found. It should also be noted that the use of peripheral blood material limits the ability to draw conclusions about central processes.

CONCLUSIONS

Previous findings of autism-associated OXTR epigenetic alterations were not reproducible with our method. In our opinion, this may lead to a reconsideration of the relevance of altered methylation at individual OXTR CpG positions in autism research. However, given the pilot nature of the study, these results need to be replicated in independent cohorts and with larger sample sizes.

Search for differentially methylated regions in ancient and modern genomes

Currently, active research is focused on investigating the mechanisms that regulate the development of various pathologies and their evolutionary dynamics. Epigenetic mechanisms, such as DNA methylation, play a significant role in evolutionary processes, as their changes have a faster impact on the phenotype compared to mutagenesis. In this study, we attempted to develop an algorithm for identifying differentially methylated regions associated with metabolic syndrome, which have undergone methylation changes in humans during the transition from a hunter-gatherer to a sedentary lifestyle. The application of existing whole-genome bisulfite sequencing methods is limited for ancient samples due to their low quality and fragmentation, and the approach to obtaining DNA methylation profiles differs significantly between ancient hunter-gatherer samples and modern tissues. In this study, we validated DamMet, an algorithm for reconstructing ancient methylomes. Application of DamMet to Neanderthal and Denisovan genomes showed a moderate level of correlation with previously published methylation profiles and demonstrated an underestimation of methylation levels in the reconstructed profiles by an average of 15-20 %. Additionally, we developed a new Python-based algorithm that allows for the comparison of methylomes in ancient and modern samples, despite the absence of methylation profiles in modern bone tissue within the context of obesity. This analysis involves a two-step data processing approach, where the first step involves the identification and filtration of tissue-specific methylation regions, and the second step focuses on the direct search for differentially methylated regions in specific areas associated with the researcher's target condition. By applying this algorithm to test data, we identified 38 differentially methylated regions associated with obesity, the majority of which were located in promoter regions. The pipeline demonstrated sufficient efficiency in detecting these regions. These results confirm the feasibility of reconstructing DNA methylation profiles in ancient samples and comparing them with modern methylomes. Furthermore, possibilities for further methodological development and the implementation of a new step for studying differentially methylated positions associated with evolutionary processes are discussed.

Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity

Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.

A noninvasive method for whole-genome skin methylome profiling

BACKGROUND

Ageing, disease and malignant transformation of the skin are associated with changes in DNA methylation. So far, mostly invasive methodologies such as biopsies have been applied in collecting DNA methylation signatures. Tape stripping offers a noninvasive option for skin diagnostics. It enables the easy but robust capture of biologic material in large numbers of participants without the need for specialized medical personnel.

OBJECTIVES

To design and validate a methodology for noninvasive skin sample collection using tape stripping for subsequent DNA -methylation analysis.

METHODS

A total of 175 participants were recruited and provided tape-stripping samples from a sun-exposed area; 92 provided matched tape-stripping samples from a sun-protected area, and an additional 5 provided matched skin-shave biopsies from the same area. Using -enzymatic conversion and whole-genome Illumina sequencing, we generated genome-wide DNA methylation profiles that were used to evaluate the feasibility of noninvasive data acquisition, to compare with established sampling approaches and to investigate biomarker identification for age and ultraviolet (UV) exposure.

RESULTS

We found that tape-stripping samples showed strong concordance in their global DNA methylation landscapes to those of conventional invasive biopsies. Moreover, we showed sample reproducibility and consistent global methylation profiles in skin tape-stripping samples collected from different areas of the body. Using matched samples from sun-protected and sun-exposed areas of the body we were able to validate the capacity of our method to capture the effects of environmental changes and ageing in a cohort covering various ages, ethnicities and skin types. We found DNA methylation changes on the skin resulting from UV exposure and identified significant age-related hypermethylation of CpG islands, with a pronounced peak effect at 50-55 years of age, including methylation changes in well-described markers of ageing.

CONCLUSIONS

These data demonstrate the feasibility of using tape stripping combined with whole-genome sequencing as a noninvasive approach to measuring DNA methylation changes in the skin. In addition, they outline a viable experimental framework for the use of skin tape stripping, particularly when it is performed in large cohorts of patients to identify biomarkers of skin ageing, UV damage and, possibly, to track treatment response to therapeutic interventions.

Early detection of hepatocellular carcinoma via no end-repair enzymatic methylation sequencing of cell-free DNA and pre-trained neural network

BACKGROUND

Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC.

METHODS

We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth.

RESULTS

NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%).

CONCLUSIONS

By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace.

PSTVd infection in Nicotiana benthamiana plants has a minor yet detectable effect on CG methylation

Viroids are small circular RNAs infecting a wide range of plants. They do not code for any protein or peptide and therefore rely on their structure for their biological cycle. Observed phenotypes of viroid infected plants are thought to occur through changes at the transcriptional/translational level of the host. A mechanism involved in such changes is RNA-directed DNA methylation (RdDM). Till today, there are contradictory works about viroids interference of RdDM. In this study, we investigated the epigenetic effect of viroid infection in Nicotiana benthamiana plants. Using potato spindle tuber viroid (PSTVd) as the triggering pathogen and via bioinformatic analyses, we identified endogenous gene promoters and transposable elements targeted by 24 nt host siRNAs that differentially accumulated in PSTVd-infected and healthy plants. The methylation status of these targets was evaluated following digestion with methylation-sensitive restriction enzymes coupled with PCR amplification, and bisulfite sequencing. In addition, we used Methylation Sensitive Amplification Polymorphism (MSAP) followed by sequencing (MSAP-seq) to study genomic DNA methylation of 5-methylcytosine (5mC) in CG sites upon viroid infection. In this study we identified a limited number of target loci differentially methylated upon PSTVd infection. These results enhance our understanding of the epigenetic host changes as a result of pospiviroid infection.

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.

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

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

Simultaneous sequencing of genetic and epigenetic bases in DNA

DNA comprises molecular information stored in genetic and epigenetic bases, both of which are vital to our understanding of biology. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases fail to capture common C-to-T mutations or distinguish 5-methylcytosine from 5-hydroxymethylcytosine. We present a single base-resolution sequencing methodology that sequences complete genetics and the two most common cytosine modifications in a single workflow. DNA is copied and bases are enzymatically converted. Coupled decoding of bases across the original and copy strand provides a phased digital readout. Methods are demonstrated on human genomic DNA and cell-free DNA from a blood sample of a patient with cancer. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. Simultaneous, phased reading of genetic and epigenetic bases provides a more complete picture of the information stored in genomes and has applications throughout biomedicine.

Optimized bisulfite sequencing analysis reveals the lack of 5-methylcytosine in mammalian mitochondrial DNA

BACKGROUND

DNA methylation is one of the best characterized epigenetic modifications in the mammalian nuclear genome and is known to play a significant role in various biological processes. Nonetheless, the presence of 5-methylcytosine (5mC) in mitochondrial DNA remains controversial, as data ranging from the lack of 5mC to very extensive 5mC have been reported.

RESULTS

By conducting comprehensive bioinformatic analyses of both published and our own data, we reveal that previous observations of extensive and strand-biased mtDNA-5mC are likely artifacts due to a combination of factors including inefficient bisulfite conversion, extremely low sequencing reads in the L strand, and interference from nuclear mitochondrial DNA sequences (NUMTs). To reduce false positive mtDNA-5mC signals, we establish an optimized procedure for library preparation and data analysis of bisulfite sequencing. Leveraging our modified workflow, we demonstrate an even distribution of 5mC signals across the mtDNA and an average methylation level ranging from 0.19% to 0.67% in both cell lines and primary cells, which is indistinguishable from the background noise.

CONCLUSIONS

We have developed a framework for analyzing mtDNA-5mC through bisulfite sequencing, which enables us to present multiple lines of evidence for the lack of extensive 5mC in mammalian mtDNA. We assert that the data available to date do not support the reported presence of mtDNA-5mC.

ctDNA as a novel and promising approach for cancer diagnosis: a focus on hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent forms of cancer worldwide. Therefore, it is essential to diagnose and treat HCC patients promptly. As a novel discovery, circulating tumor DNA (ctDNA) can be used to analyze the tumor type and the cancer location. Additionally, ctDNA assists the cancer stage determination, which enables medical professionals to provide patients with the most appropriate treatment. This review will discuss the HCC-related mutated genes diagnosed by ctDNA. In addition, we will introduce the different and the most appropriate ctDNA diagnosis approaches based on the facilities.

Region-based epigenetic clock design improves RRBS-based age prediction

Recent studies suggest that epigenetic rejuvenation can be achieved using drugs that mimic calorie restriction and techniques such as reprogramming-induced rejuvenation. To effectively test rejuvenation in vivo, mouse models are the safest alternative. However, we have found that the recent epigenetic clocks developed for mouse reduced-representation bisulphite sequencing (RRBS) data have significantly poor performance when applied to external datasets. We show that the sites captured and the coverage of key CpGs required for age prediction vary greatly between datasets, which likely contributes to the lack of transferability in RRBS clocks. To mitigate these coverage issues in RRBS-based age prediction, we present two novel design strategies that use average methylation over large regions rather than individual CpGs, whereby regions are defined by sliding windows (e.g. 5 kb), or density-based clustering of CpGs. We observe improved correlation and error in our regional blood clocks (RegBCs) compared to published individual-CpG-based techniques when applied to external datasets. The RegBCs are also more robust when applied to low coverage data and detect a negative age acceleration in mice undergoing calorie restriction. Our RegBCs offer a proof of principle that age prediction of RRBS datasets can be improved by accounting for multiple CpGs over a region, which negates the lack of read depth currently hindering individual-CpG-based approaches.

Investigation of Different Library Preparation and Tissue of Origin Deconvolution Methods for Urine and Plasma cfDNA Methylome Analysis

Methylation sequencing is a promising approach to infer the tissue of origin of cell-free DNA (cfDNA). In this study, a single- and a double-stranded library preparation approach were evaluated with respect to their technical biases when applied on cfDNA from plasma and urine. Additionally, tissue of origin (TOO) proportions were evaluated using two deconvolution methods. Sequencing cfDNA from urine using the double-stranded method resulted in a substantial within-read methylation bias and a lower global methylation (56.0% vs. 75.8%, p ≤ 0.0001) compared to plasma cfDNA, both of which were not observed with the single-stranded approach. Individual CpG site-based TOO deconvolution resulted in a significantly increased proportion of undetermined TOO with the double-stranded method (urine: 32.3% vs. 1.9%; plasma: 5.9% vs. 0.04%; p ≤ 0.0001), but no major differences in proportions of individual cell types. In contrast, fragment-level deconvolution led to multiple cell types, with significantly different TOO proportions between the two methods. This study thus outlines potential limitations of double-stranded library preparation for methylation analysis of cfDNA especially for urinary cfDNA. While the double-stranded method allows jagged end analysis in addition to TOO analysis, it leads to significant methylation bias in urinary cfDNA, which single-stranded methods can overcome.

Single-cell methylation sequencing data reveal succinct metastatic migration histories and tumor progression models

Recent studies exploring the impact of methylation in tumor evolution suggest that although the methylation status of many of the CpG sites are preserved across distinct lineages, others are altered as the cancer progresses. Because changes in methylation status of a CpG site may be retained in mitosis, they could be used to infer the progression history of a tumor via single-cell lineage tree reconstruction. In this work, we introduce the first principled distance-based computational method, Sgootr, for inferring a tumor's single-cell methylation lineage tree and for jointly identifying lineage-informative CpG sites that harbor changes in methylation status that are retained along the lineage. We apply Sgootr on single-cell bisulfite-treated whole-genome sequencing data of multiregionally sampled tumor cells from nine metastatic colorectal cancer patients, as well as multiregionally sampled single-cell reduced-representation bisulfite sequencing data from a glioblastoma patient. We show that the tumor lineages constructed reveal a simple model underlying tumor progression and metastatic seeding. A comparison of Sgootr against alternative approaches shows that Sgootr can construct lineage trees with fewer migration events and with more in concordance with the sequential-progression model of tumor evolution, with a running time a fraction of that used in prior studies. Lineage-informative CpG sites identified by Sgootr are in inter-CpG island (CGI) regions, as opposed to intra-CGIs, which have been the main regions of interest in genomic methylation-related analyses.

Circulating cell-free DNA sequencing for early detection of lung cancer

INTRODUCTION

Lung cancer is a leading cause of death in patients with cancer. Early diagnosis is crucial to improve the prognosis of patients with lung cancer. Plasma circulating cell-free DNA (cfDNA) contains comprehensive genetic and epigenetic information from tissues throughout the body, suggesting that early detection of lung cancer can be done non-invasively, conveniently, and cost-effectively using high-sensitivity techniques such as sequencing.

AREAS COVERED

In this review, we summarize the latest technological innovations, coupled with next-generation sequencing (NGS), regarding genomic alterations, methylation, and fragmentomic features of cfDNA for the early detection of lung cancer, as well as their clinical advances. Additionally, we discuss the suitability of study designs for diagnostic accuracy evaluation for different target populations and clinical questions.

EXPERT OPINION

Currently, cfDNA-based early screening and diagnosis of lung cancer faces many challenges, such as unsatisfactory performance, lack of quality control standards, and poor repeatability. However, the progress of several large prospective studies employing epigenetic features has shown promising predictive performance, which has inspired cfDNA sequencing for future clinical applications. Furthermore, the development of multi-omics markers for lung cancer, including genome-wide methylation and fragmentomics, is expected to play an increasingly important role in the future.

A pipeline for sample tagging of whole genome bisulfite sequencing data using genotypes of whole genome sequencing

BACKGROUND

In large-scale high-throughput sequencing projects and biobank construction, sample tagging is essential to prevent sample mix-ups. Despite the availability of fingerprint panels for DNA data, little research has been conducted on sample tagging of whole genome bisulfite sequencing (WGBS) data. This study aims to construct a pipeline and identify applicable fingerprint panels to address this problem.

RESULTS

Using autosome-wide A/T polymorphic single nucleotide variants (SNVs) obtained from whole genome sequencing (WGS) and WGBS of individuals from the Third China National Stroke Registry, we designed a fingerprint panel and constructed an optimized pipeline for tagging WGBS data. This pipeline used Bis-SNP to call genotypes from the WGBS data, and optimized genotype comparison by eliminating wildtype homozygous and missing genotypes, and retaining variants with identical genomic coordinates and reference/alternative alleles. WGS-based and WGBS-based genotypes called from identical or different samples were extensively compared using hap.py. In the first batch of 94 samples, the genotype consistency rates were between 71.01%-84.23% and 51.43%-60.50% for the matched and mismatched WGS and WGBS data using the autosome-wide A/T polymorphic SNV panel. This capability to tag WGBS data was validated among the second batch of 240 samples, with genotype consistency rates ranging from 70.61%-84.65% to 49.58%-61.42% for the matched and mismatched data, respectively. We also determined that the number of genetic variants required to correctly tag WGBS data was on the order of thousands through testing six fingerprint panels with different orders for the number of variants. Additionally, we affirmed this result with two self-designed panels of 1351 and 1278 SNVs, respectively. Furthermore, this study confirmed that using the number of genetic variants with identical coordinates and ref/alt alleles, or identical genotypes could not correctly tag WGBS data.

CONCLUSION

This study proposed an optimized pipeline, applicable fingerprint panels, and a lower boundary for the number of fingerprint genetic variants needed for correct sample tagging of WGBS data, which are valuable for tagging WGBS data and integrating multi-omics data for biobanks.

Transgenerational sperm DMRs escape DNA methylation erasure during embryonic development and epigenetic inheritance

Germline transmission of epigenetic information is a critical component of epigenetic inheritance. Previous studies have suggested that an erasure of DNA methylation is required to develop stem cells in the morula embryo. An exception involves imprinted genes that escape this DNA methylation erasure. Transgenerational differential DNA methylation regions (DMRs) have been speculated to be imprinted-like and escape this erasure. The current study was designed to assess if morula embryos escape the erasure of dichlorodiphenyltrichloroethane-induced transgenerational sperm DMR methylation. Observations demonstrate that the majority (98%) of transgenerational sperm DMR sites retain DNA methylation and are not erased, so appearing similar to imprinted-like sites. Interestingly, observations also demonstrate that the majority of low-density CpG genomic sites had a significant increase in DNA methylation in the morula embryo compared to sperm. This is in contrast to the previously observed DNA methylation erasure of higher-density CpG sites. The general erasure of DNA methylation during embryogenesis appears applicable to high-density DNA methylation sites (e.g. CpG islands) but neither to transgenerational DMR methylation sites nor to low-density CpG deserts, which constitute the vast majority of the genome's DNA methylation sites. The role of epigenetics during embryogenesis appears more dynamic than the simple erasure of DNA methylation.