Comparison of current methods for genome-wide DNA methylation profiling

Zebrafish is a widely used model organism for investigating human diseases, including hematopoietic disorders. However, a comprehensive methylation baseline for zebrafish primary hematopoietic organ, the kidney marrow (KM), is still lacking. We employed Oxford Nanopore Technologies (ONT) sequencing to profile DNA methylation in zebrafish KM by generating four KM datasets, with two groups based on the presence or absence of red blood cells. Our findings revealed that blood contamination in the KM samples reduced read quality and altered methylation patterns. Compared with whole-genome bisulfite sequencing (WGBS), the ONT-based methylation profiling can cover more CpG sites (92.4% vs 70%–80%), and exhibit less GC bias with more even genomic coverage. And the ONT methylation calling results showed a high correlation with WGBS results when using shared sites. This study establishes a comprehensive methylation profile for zebrafish KM, paving the way for further investigations into epigenetic regulation and the development of targeted therapies for hematopoietic disorders.

DNA methylation plays an important role in the regulation of the expression of transposons and genes. Various methods have been developed to assay DNA methylation levels. Bisulfite sequencing is considered to be the "gold standard" for single-base resolution measurement of DNA methylation levels. Coupled with next-generation sequencing, whole-genome bisulfite sequencing (WGBS) allows DNA methylation to be evaluated at a genome-wide scale. Here, we described a protocol for WGBS in plant species with large genomes. This protocol has been successfully applied to assay genome-wide DNA methylation levels in maize and barley. This protocol has also been successfully coupled with sequence capture technology to assay DNA methylation levels in a targeted set of genomic regions.

DNA methylation, a key epigenetic modification, regulates gene expression and diverse cellular functions. Bisulfite sequencing (BS) remains the gold standard for methylation detection, while PacBio HiFi sequencing enables direct detection without chemical conversion. Although both technologies are increasingly used, few studies have directly compared their concordance, particularly in clinically relevant settings such as Down syndrome (DS). We performed a comparative analysis of DNA methylation profiles using whole-genome bisulfite sequencing (WGBS) and PacBio high-fidelity (HiFi) whole-genome sequencing (WGS) in a pair of monozygotic twins with DS. WGBS data were processed with two pipelines, wg-blimp and Bismark, while HiFi WGS data were analyzed using pb-CpG-tools. Our analysis focused on four key aspects: CpG site detection, genomic distribution of methylated CpGs (mCs), average methylation levels, and inter-platform concordance. HiFi WGS detected a greater number of mCs—particularly in repetitive elements and regions with low WGBS coverage—while WGBS reported higher average methylation levels than HiFi WGS. Both platforms exhibited methylation patterns consistent with known biological principles, such as low methylation in CpG islands, and the relative methylation patterns across genomic features were largely concordant. Pearson correlation coefficients indicated strong agreement between platforms (r ≈ 0.8), with higher concordance in GC-rich regions and at increased sequencing depths. Depth-matched comparisons and site-level down-sampling revealed that methylation concordance improves with increasing coverage, with stronger agreement observed beyond 20 × . Our findings support the reliability of HiFi WGS for methylation detection and highlight its advantages in regions that are challenging for bisulfite-based methods. This study demonstrates that HiFi WGS can serve as a robust alternative for genome-wide methylation profiling.

DNA methylation, a key epigenetic modification, regulates gene expression and diverse cellular functions. Bisulfite sequencing (BS) remains the gold standard for methylation detection, while PacBio HiFi sequencing enables direct detection without chemical conversion. Although both technologies are increasingly used, few studies have directly compared their concordance, particularly in clinically relevant settings such as Down syndrome (DS). We performed a comparative analysis of DNA methylation profiles using whole-genome bisulfite sequencing (WGBS) and PacBio high-fidelity (HiFi) whole-genome sequencing (WGS) in a pair of monozygotic twins with DS. WGBS data were processed with two pipelines, wg-blimp and Bismark, while HiFi WGS data were analyzed using pb-CpG-tools. Our analysis focused on four key aspects: CpG site detection, genomic distribution of methylated CpGs (mCs), average methylation levels, and inter-platform concordance. HiFi WGS detected a greater number of mCs-particularly in repetitive elements and regions with low WGBS coverage-while WGBS reported higher average methylation levels than HiFi WGS. Both platforms exhibited methylation patterns consistent with known biological principles, such as low methylation in CpG islands, and the relative methylation patterns across genomic features were largely concordant. Pearson correlation coefficients indicated strong agreement between platforms (r ≈ 0.8), with higher concordance in GC-rich regions and at increased sequencing depths. Depth-matched comparisons and site-level down-sampling revealed that methylation concordance improves with increasing coverage, with stronger agreement observed beyond 20 × . Our findings support the reliability of HiFi WGS for methylation detection and highlight its advantages in regions that are challenging for bisulfite-based methods. This study demonstrates that HiFi WGS can serve as a robust alternative for genome-wide methylation profiling.

DNA methylation is the most important epigenetic change affecting gene expression in plants grown under normal as well as under stress conditions. Therefore, researchers study differential DNA methylation under distinct environmental conditions and their relationship with transcriptome abundance. Up to date, more than 25 methods and techniques are available to detect DNA methylation based on different principles. Bisulfite sequencing method is considered as a gold standard since it is able to distinguish 5-methylcytosine from cytosine using the bisulfite treatment. Therefore, it is useful for qualitative and semiquantitative measurement of DNA methylation. However, the reliability of data obtaining from this technique is mainly depending on the efficiency of bisulfite conversion and number of sequencing clones representing the target-converted sequence. Therefore, it is labor intensive and time-consuming. Revolution of next generation DNA sequencing (NGS) has allowed researches to combine conventional bisulfite sequencing methods with high-throughput Illumina sequencing in a technique called whole genome bisulfite sequencing (WGBS). This technique allows a single nucleotide resolution of 5-methylcytosine on a genome scale. WGBS technique workflow involves DNA fragmentation, processing through end blunting, terminal A(s) addition at 3' end and adaptor ligation, bisulfite treatment, PCR amplification, sequencing libraries and assembling, and finally alignment with the reference genome and data analysis. Despite the fact that WGBS is more reliable than the conventional clone-based bisulfite sequencing, it is costly, requires large amount of DNA and its output data is not easily handled.

Nanopore long-read sequencing has expanded the capacity of long-range, single-base, and single-molecule DNA-methylation (DNAme) detection and haplotype-aware allele-specific epigenetic phasing. Previously, we benchmarked and ranked the robustness of seven computational tools for DNAme detection using nanopore sequencing. The top performers were Megalodon, Nanopolish, DeepSignal and Guppy. However, these algorithms exhibit lower performance at regions with discordant non-singleton DNAme patterns compared to genome-wide regions. Furthermore, long-read sequencing analysis of mammalian genomes requires higher computational resources than next-generation sequencing. To address these issues, we developed a NANOpore Methylation (NANOME) a consensus DNAme predictive model using XGBoost, which integrates the output of Megalodon, Nanopolish, and Deepsignal for analyzing data obtained using Oxford Nanopore Technologies (ONT). NANOME enhanced DNAme detection precision (mean square error) at single-base resolution by 11% and improved accuracy (F1-score) at single-molecule resolution by 2.4% for human B-lymphocyte European cell lines (NA12878). The consensus model also detected ~200,000 more CpGs than all three tools. Combing variant calling and long-read phasing, NANOME can detect haplotype-aware allele-specific DNAme in known imprinting controls in resolved and previously unresolved regions. We conducted haplotype-aware methylation detection on the T2T genome for dataset NA12878, revealing significant variations in differentially methylated region (DMR) density between gap and non-gap regions. Overall, NANOME represents a significant step forward in DNAme detection and long-range epigenetic phasing, offering a robust and accessible tool for researchers studying the epigenome.

Nanopore long-read sequencing has expanded the capacity of long-range, single-base, and single-molecule DNA-methylation (DNAme) detection and haplotype-aware allele-specific epigenetic phasing. Previously, we benchmarked and ranked the robustness of seven computational tools for DNAme detection using nanopore sequencing. Overall, the top performers were Megalodon, Nanopolish, DeepSignal and Guppy. However, these algorithms exhibit lower performance at regions with discordant non-singleton DNAme patterns, intergenic regions, low CG density regions, and repetitive regions compared to genome-wide region. Furthermore, long-read sequencing analysis of mammalian genomes requires higher computational resources than next-generation sequencing. To address these issues, we developed NANOME, the first cloud-compatible, Nextflow-based container environment for consensus DNAme detection. We designed a consensus DNAme predictive model using XGBoost, which integrates the output of Megalodon, Nanopolish, and Deepsignal for analyzing data obtained using Oxford Nanopore Technologies (ONT). The consensus model enhanced DNAme detection at single-base resolution by 12% (mean square error) and improved accuracy at single-molecule resolution by 3% (F1-score accuracy) for human B-lymphocyte cell lines (NA12878 and NA19240). The consensus model also detected ∼200,000 more CpGs than Nanopolish. Combing variant calling and long-read phasing, NANOME can detect haplotype-aware allele-specific DNAme in known imprinting controls. We conducted haplotype-aware methylation detection on the T2T genome for dataset NA12878, revealing significant variations in DMR density between gap and non-gap regions, with notable higher densities in gap regions of chromosomes 2, 10, and 20. Overall, NANOME represents a significant step forward in DNAme detection and long-range epigenetic phasing, offering a robust and accessible tool for researchers studying the epigenome. Citation Format: Yang Liu, Ziwei Pan, Christina Chatzipantsiou, Emma Wade, Thatcher Slocum, Lasya Karuturi, Yue Zhao, Shilpita Karmakar, Sheng Li. NANOME: A Nextflow pipeline for haplotype-aware allele-specific consensus DNA methylation detection by nanopore long-read sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB345.

Do embryos with different developmental competence exhibit different DNA methylation profiles at the blastocyst stage? We established genome-wide DNA methylome analysis for embryo trophectoderm (TE) biopsy samples and our findings demonstrated correlation of methylation profile of trophectoderm with euploidy status and with maternal age, indicating that genome-wide methylation level might be negatively correlated with embryo quality. DNA methylation is a fundamental epigenetic regulatory mechanism that affects differentiation of cells into their future lineages during pre-implantation embryo development. Currently there is no established approach available to assess the epigenetic status of the human preimplantation embryo during routine IVF treatment. In total, we collected trophectoderm biopsy samples from 30 randomly selected human blastocysts and conducted whole-genome bisulfite sequencing (WGBS) to evaluate their DNA methylation profile. Nested linear models were used to assess association between DNA methylation level and ploidy status (aneuploidy [n = 20] vs. euploidy [n = 10]), maternal age (29.4-42.5 years old), and time of blastulation (day 5 [n = 16] vs. day 6 [n = 14]), using embryo identity as a covariate. TE biopsy samples were obtained and submitted to bisulfite conversion. For WGBS, whole-genome sequencing libraries were then generated from the converted genome. An average of 75 million reads were obtained for each sample, and about 63% of the reads aligned to human reference. An average of 40 million reads used for the final analysis after the unconverted reads were filtered out. We revealed an increase of genome-wide DNA methylation level in aneuploid embryo TE biopsies compared to euploid embryos (25.4% ± 3.2% vs. 24.7% ± 3.2%, P < 0.005). We also found genome-wide DNA methylation level to be increased with the maternal age (P < 0.005). On a chromosomal scale, we found monosomic embryos have lower methylation levels on the involved chromosome while no drastic change was observed for the involved chromosome in trisomies. Additionally, we revealed that WGBS data precisely revealed the chromosome copy number variance. Though our results demonstrated a negative correlation of genome-wide methylation level and embryo quality, further WGBS analysis on a greater number of embryos and specific investigation of its correlation with implantation and live birth are needed before any practical use of this approach for evaluation of embryo competence. This study revealed a change in genome-wide DNA methylation profile among embryos with different developmental potentials, reinforcing the critical role of DNA methylation in early development. No external funding was received for this study. Intramural funding was provided by the Foundation for Embryonic Competence (FEC). E.S. is a consultant for and receives research funding from the Foundation for Embryonic Competence; he is also co-founder and a shareholder of ACIS LLC and coholds patent US2019/055906 issued for utilizing electrical resistance measurement for assessing cell viability and cell membrane piercing. N/A.

Integrative analysis of whole genome bisulfite and transcriptome sequencing reveals the effect of sodium butyrate on DNA methylation in the differentiation of bovine skeletal muscle satellite cells

DNA methylations are well known for their regulatory functions and involved in various biological processes. Due to its great importance, the exploration of DNA methylation for different phenotypic characters is gaining much attention among the research community. DNA methylations are mainly reported on cytosine (C) residues particularly CG, CHH, and CHG contexts. DNA methylations can be identified using methylation-sensitive restriction enzymes or through bisulfite treatment of DNA. Later converts the nonmethylated C to uracil (U) and subsequently reads as thymine (T) after PCR; however, methylated C remains unchanged. Advanced sequencing technologies add to the exploration of DNA methylation to the whole-genome level with single-base resolution. In the present chapter, we provide a complete protocol for whole genome bisulfite sequencing (WGBS) which can be used for whole genome methylation profiling of crop plants.Key wordsEpigeneticsCytosine methylationsBisulfite conversionMethylated DNA immune precipitationDifferentially methylated regions

Methylation of cytosines in DNA is the most stable type of epigenetic modification that is established and maintained by different enzymes. In plants, DNA methylation is inherited from one generation to another leaving an epigenetic mark as a memory of previous state, which may include encounter with stress or pathogen. Advancement in the next generation sequencing technologies has enabled the profiling of methylation marks. Whole-genome bisulfite sequencing (WGBS) has the potential to unravel the patterns of DNA methylation at single-base resolution. Though the sequencing technologies have evolved drastically, analysis of WGBS data still remains challenging. Here, we provide a methodology for performing WGBS data analysis along with critical steps for identification of methylation marks in plant genomes including legumes.

SRSF10 regulates isoform expression of transcripts associated with proliferative diabetes retinopathy in ARPE-19 cells based on long-read RNA and immunoprecipitation sequencing.

ABSTRACTSequencing of the 16S ribosomal RNA (rRNA) gene is an important tool in addition to conventional methods for the identification of bacterial pathogens in human infections. In polymicrobial samples, Sanger sequencing can produce uninterpretable chromatograms. This limitation can be overcome by Next Generation Sequencing (NGS) of the 16S rRNA gene. We investigated the applicability of Oxford Nanopore Technologies (ONT) sequencing of the partial 16S rRNA gene as a diagnostic routine method for pathogen detection in clinical samples. From June 2021 to August 2022, 101 clinical samples positive in PCR for partial 16S rRNA gene analysis were subjected to both Sanger and ONT sequencing. Sanger sequences were edited and compared with deposited sequences in the NCBI database using BLAST, while ONT data were processed using EPI2ME Fastq 16S. The positivity rate (clinically relevant pathogen) was higher for ONT vs. Sanger sequencing: 72% and 59%, respectively. Concordance between Sanger and ONT sequencing was 80%. Furthermore, ONT detected more samples with polymicrobial presence compared to Sanger (13 vs. 5) sequencing. Interestingly, in one joint fluid sample, Borrelia bissettiiae was identified by ONT but not by Sanger. The results show that the detection of both monobacterial and multiple bacterial species is improved using ONT.

Evaluation of real-time nanopore sequencing for Salmonella serotype prediction

Locked Nucleic Acids Can Enhance the Analytical Performance of Quantitative Methylation-Specific Polymerase Chain Reaction