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PubMed2026

Genetic Identification of Burned Human Remains: A Systematic Review.

Background/Objectives: DNA-based identification of degraded human remains represents a major challenge in forensic science, particularly in cases involving burned, fragmented, or commingled bodies. Advances in forensic genetics have expanded the analytical capabilities for such samples; however, the effectiveness of different approaches and their integration within Disaster Victim Identification (DVI) workflows remain heterogeneous. This systematic review aims to critically evaluate current evidence on DNA-based identification of degraded remains, focusing on methodological strategies, emerging genomic technologies, and DVI applications, while integrating laboratory evidence and operational forensic practice into a structured analytical framework. Methods: A systematic literature search was conducted in Scopus and Web of Science from database inception to 5 June 2026, following PRISMA 2020 guidelines. Eligible studies included original research addressing DNA analysis of degraded, thermally altered, or highly compromised human remains in forensic or DVI contexts. After a multistep screening process involving title/abstract and full-text evaluation, 37 studies were included. Data were extracted and organized into three thematic categories: (i) core DNA analysis, (ii) advanced molecular technologies, and (iii) DVI case applications. Results: The findings demonstrate that DNA recovery from degraded remains is influenced by thermal exposure, tissue type, and sampling strategy. Teeth and dense cortical bone consistently provide higher DNA yield. While autosomal STR profiling remains the primary analytical approach, its limitations in highly degraded samples are mitigated through the complementary use of mitochondrial DNA (mtDNA), Y-chromosome STRs (Y-STRs), and SNP markers, together with advanced sequencing technologies such as massively parallel sequencing (MPS). Emerging technologies, including rapid DNA systems and predictive models based on macroscopic indicators, significantly enhance efficiency and success rates. DVI studies report identification rates exceeding 90-95% when multidisciplinary and structured workflows are applied. The evidence further supports a flexible triage-based analytical strategy, in which marker selection is guided by tissue preservation and degradation level. Conclusions: DNA-based identification of degraded human remains has evolved into an adaptive, multi-level forensic process. Successful outcomes rely on the integration of optimized sampling, hierarchical genetic analysis, and coordinated DVI strategies. The findings support a triage-based framework that links tissue selection, degradation assessment, and analytical methodology to maximize identification success. Future developments should focus on predictive models, advanced genomic tools, and standardized workflows to further improve identification in challenging forensic scenarios.

Humans↗
PubMed2025

A Comprehensive Bioinformatics Approach to Analysis of Variants: Variant Calling, Annotation, and Prioritization.

Next-Generation Sequencing (NGS), also known as high-throughput sequencing technologies, has enabled rapid and efficient sequencing of large amounts of DNA and RNA. These technologies have revolutionized the field of genomics, transcriptomics, and proteomics and have been widely used in cancer research, leading to advances in clinical diagnosis and treatment. Improvements in the NGS technologies enabled millions of fragments to be sequenced simultaneously in a time- and cost-effective manner and resulted in large amount of genomic data which require efficient analysis methods. Analysis of the genomic data requires both efficient computer resources and bioinformatics approaches. This chapter details a comprehensive computational approach and analysis steps for genomic data analysis.

Computational Biology↗
PubMed2025

Advances in large-scale DNA engineering with the CRISPR system.

In recent years, DNA engineering technology has undergone significant advancements, with clustered regularly interspaced short palindromic repeats (CRISPR)-based target-specific DNA insertion emerging as one of the most rapidly expanding and widely studied approaches. Traditional DNA insertion technologies employing recombinases typically involve introducing foreign DNA into genes in vivo by either pre-engineering recognition sequences specific to the recombinase or through genetic crossing to incorporate the requisite recognition sequence into the target gene. However, CRISPR-based gene insertion technologies have advanced to streamline this engineering process by combining the CRISPR-Cas module with recombinase enzymes. This process enables accurate and efficient one-step insertion of foreign DNA into the target gene in vivo. Here we provide an overview of the latest developments in CRISPR-based gene insertion technologies and discusses their potential future applications.

CRISPR-Cas Systems↗
PubMed1978

The replicative life spans of euploid hybrids derived from short-lived and long-lived human skin fibroblast cultures.

Two recent technical advances facilitate the derivation of proliferating hybrids from human diploid fibroblast strains without recourse to biochemical selection: (1) a new chemically-mediated method of somatic cell fusion (PEG-DMSO) yields hybrids at rates as high as 1 in 160 colonies after dilute plating of treated cell mixtures, and (2) a simple technology for assessment of DNA content (flow microfluorometry) permits rapid and highly sensitive monitoring of ploidy. Employing these techniques, we isolated 43 chromosomally stable hybrid clones from 12 crosses between seven different strains representing a wide range of longevities. Crosses between short-lived strains resulted in short-lived hybrid offspring, whereas hybrids derived from long-lived parents tended to be long-lived. Crosses between strains of contrasting longevities gave clones with intermediate growth potentials relative to the other types of hybrids. The failure to observe complementation (enhanced longevity) of hybrids argues against random recessive single-copy gene mutations as important determinants of clonal senescence.

Cell Fusion↗
PubMed2026

Comparative performance of portable DNA extraction protocols and bioinformatics workflows for rapid detection of gram-negative bacteria and antimicrobial resistance using Oxford Nanopore sequencing.

Oxford Nanopore Technology (ONT) enables rapid, portable pathogen identification and antimicrobial resistance (AMR) detection, but the reliability of downstream genomic analyses is highly dependent on DNA extraction quality, particularly in resource-limited settings. This study comparatively evaluated four portable bacterial DNA extraction protocols derived from three commercial kits to determine their impact on nanopore sequencing performance, bioinformatics workflow completion, and field deployability. Six gram-negative bacterial isolates (Escherichia coli, n = 4; Pseudomonas sp., n = 1; and Salmonella sp., n = 1) were processed using four extraction protocols: SwiftX DNA, SwiftX DNA with proteinase K (ProtK), SwiftX ParaBact, and NucleoSpin Microbial. Twenty-four resulting DNA extracts were sequenced on a single multiplexed MinION R10.4.1 flow cell. Sequencing data were analyzed using validated Galaxy-based generic and species-specific pipelines. Workflow completion was defined as successful progression through quality control, assembly, virulence, plasmid, and AMR detection modules. DNA purity varied substantially by extraction protocol and was strongly associated with successful workflow completion (Kruskal-Wallis, P = 0.0006). Accordingly, NucleoSpin Microbial achieved 100% workflow completion, and SwiftX ParaBact achieved 83%, while both SwiftX DNA-based protocols failed to complete full workflows. Importantly, key AMR genes required to classify isolates as multidrug-resistant were consistently detected using both NucleoSpin Microbial and SwiftX ParaBact extractions. However, NucleoSpin Microbial assemblies showed significantly higher contiguity and enabled a broader, more complete detection of virulence factors, pathogenicity islands, plasmid replicons, and accessory AMR genes, reflecting enhanced genomic resolution.IMPORTANCERapid whole-genome sequencing is increasingly used to detect antimicrobial resistance and guide public health responses, but its reliability depends strongly on how bacterial DNA is extracted. In this study, we have shown that DNA extraction method choice has a major impact on Oxford Nanopore sequencing performance across clinically relevant gram-negative bacteria. While silica column-based extraction maximized genomic completeness and analytical depth, paramagnetic bead-based reverse purification offered superior portability with sufficient resolution for frontline AMR surveillance. These findings highlight a practical trade-off between field deployability and high-resolution genomic characterization in low-resource settings.

DNA extraction↗
PubMed2026

Benchmarking DNA extraction protocols across use cases for culture-independent Nanopore metagenomics.

Oxford Nanopore Technologies (ONT) sequencing offers several advantages for metagenomics, including long reads, rapid turnaround, low upfront cost, scalability and portability. However, for ONT metagenomics, DNA yield, quality and integrity are important considerations when selecting an extraction method. Many metagenomic extraction methods use harsh lysis conditions to extract a wide range of species and provide an accurate community composition, but these conditions can compromise DNA fragment length. Therefore, extraction methods for ONT metagenomics must balance DNA shearing and recovery with representative community lysis. We systematically evaluated DNA extraction methods for ONT metagenomic sequencing using a use case-oriented framework. Among nearly 50 extraction methods screened, 7 were selected for detailed comparison based on suitability for metagenomics, variation in methodology, availability, cost and processing time: Norgen BioTek Corp's Stool DNA Isolation (NG), Zymo Research's ZymoBIOMICS Quick-DNA HMW MagBead (ZMG), Qiagen's DNeasy Blood and Tissue (QBT), Macherey-Nagel's NucleoMag DNA Microbiome (MN), Zymo Research's ZymoBIOMICS DNA Mini Prep (ZMI), Qiagen's DNeasy PowerSoil/QIAamp PowerFecal Pro (PS) and Qiagen's QIAamp Fast DNA Stool Mini (QIA). Methods were tested using Zymo Research's ZymoBIOMICS Microbial Community Standard (MCS), a matrix-free mock community with known composition. DNA extracts were sequenced on an ONT PromethION using the Rapid Barcoding Kit, except QIA due to insufficient DNA yield. Metrics for the method, DNA extracts, sequencing and genomes were evaluated, revealing trade-offs between methods. The two magnetic bead methods, MN and ZMG, produced the highest mean read length N50 values (13.9 and 16.5 kb, respectively) but showed apparent community compositions skewed towards Gram-negative bacteria. In contrast, ZMI and PS maintained a community composition close to expected, with reduced mean read length N50 values (4.5 vs. 7.5 kb). Performance across various metrics is presented in the context of the following use cases: maximizing genome coverage and assembly completeness, preserving composition accuracy, targeting specific species and limiting required resources (equipment, time or budget). The metrics and use case considerations presented offer practical guidance for informed selection of DNA extraction methods for ONT metagenomics. For accurate community composition, ZMI or PS are recommended, while PS and ZMG perform best at maximizing genome coverage and assembly completeness. NG and QBT may be the most economical options, though performance trade-offs were observed. Finally, PS may be the preferred method for time-sensitive diagnostic or field applications.

Metagenomics↗
PubMed2026

OligoSeq: Rapid nanopore-sequencing of single-stranded oligonucleotides.

Nanopore-based DNA sequencing technology has achieved remarkable success in sequencing increasingly long DNA strands (e.g., over a million nucleotides long) for genomics research and biotechnology applications. However, the same level of progress has not been achieved for DNA oligonucleotides (usually ≤ 300 nucleotides long). Oligonucleotides play a crucial role in genome engineering efforts through oligo library generation and in DNA data storage, where they are used to encode computer information, such as binary (digital) data in DNA libraries. To enable these applications, accurate sequencing of oligonucleotides in a way that allows to assess for sequence variability, quality and length is essential. But sequencing solutions for oligonucleotides - particularly DNA primers for PCR, oligo DNA libraries used for mutagenesis or cDNA libraries used in gene expression analysis - remain inadequate. To address this gap, OligoSeq is presented as an innovative approach that integrates two complementary techniques: AmpliSeq (based on PCR) and RevSeq (based on reverse complementation with sequence-specific or random primers) to facilitate sequencing of single-stranded oligonucleotides using reference sequence anchor matches of more than ≥ 90% identity spanning from about 70% to 10% with AmpliSeq or RevSeq with random nonamers, respectively, and resolving the final reference sequence based on the most likely candidate from basecall frequencies, regardless of length and double-stranding method. OligoSeq can be integrated with nanopore sequencing technology pipelines and can be used as a reference for other sequencing platforms requiring double-stranded adapters, offering a practical and scalable alternative for standard quality control in single-stranded oligonucleotide synthesis. The use of nanopore technology, compatible with the double-stranding methods showcased, is shown to be the most cost-effective method for resolving original DNA sequences of different length and quality, and to assess its sequence variability, compared to other methods such as Illumina, PacBio or HPLC/MS.

Sequence Analysis, DNA↗
PubMed2025

CRISPRoff epigenome editing for programmable gene silencing in human cell lines and primary T cells.

The advent of CRISPR-based technologies has enabled the rapid advancement of programmable gene manipulation in cells, tissues, and whole organisms. An emerging platform for targeted gene perturbation is epigenetic editing, the direct editing of chemical modifications on DNA and histones that ultimately results in repression or activation of the targeted gene. In contrast to CRISPR nucleases, epigenetic editors modulate gene expression without inducing DNA breaks or altering the genomic sequence of host cells. Recently, we developed the CRISPRoff epigenetic editing technology that simultaneously establishes DNA methylation and repressive histone modifications at targeted gene promoters. Transient expression of CRISPRoff and the accompanying single guide RNAs in mammalian cells results in transcriptional repression of targeted genes that is memorized heritably by cells through cell division and differentiation. Here, we describe our protocol for the delivery of CRISPRoff through plasmid DNA transfection, as well as the delivery of CRISPRoff mRNA, into transformed human cell lines and primary immune cells. We also provide guidance on evaluating target gene silencing and highlight key considerations when utilizing CRISPRoff for gene perturbations. Our protocols are broadly applicable to other CRISPR-based epigenetic editing technologies, as programmable genome manipulation tools continue to evolve rapidly.

Humans↗
PubMed2026

Comparative evaluation of molecular technologies for the identification of prevalent non-tuberculous mycobacteria in pulmonary infections: a systematic review and meta-analysis.

BACKGROUND: The increasing prevalence of non-tuberculous mycobacteria pulmonary disease (NTM PD) is a burden to public health. Successful management of NTM PD critically depends on accurate species identification and reliable drug susceptibility testing to guide appropriate antibiotic therapy. Emerging molecular technologies offer rapid diagnostic solutions compared to conventional methods, but their performance varies. This study aims to provide a comprehensive evaluation of current molecular techniques for NTM identification and to present a global antibiotic resistance profile. METHODS: A systematic literature search was conducted in PubMed and Web of Science for studies published between 2005 and 2024. Studies applying molecular methods for NTM identification and resistance detection in humans were included. Data on study characteristics, diagnostic methods, sample types, sample sizes, identification sensitivity, and drug susceptibility results were extracted. Meta-analysis was performed using R with the meta4diag package. The quality of included studies was assessed using the QUADAS-2 tool. RESULTS: The analysis included 49 studies on NTM identification and 33 studies on antibiotic resistance. For species identification, all evaluated molecular technologies (MALDI-TOF MS, PCR-based methods, Sequencing, DNA chip, and DNA strip) demonstrated high pooled sensitivities (>0.92). Subgroup analysis revealed that sample type significantly affected performance for MALDI-TOF MS. Preliminary analysis of antibiotic resistance rates revealed varying patterns. For slowly growing mycobacteria, a significantly high Ethambutol resistance rate was observed in M. avium (69.20%). Among rapidly growing mycobacteria, resistance to Imipenem was notable (54.22%), and Clarithromycin resistance varied significantly within the Mycobacterium abscessus complex. CONCLUSION: Emerging molecular technologies have revolutionized the methodology for NTM identification with excellent performance. However, their performance can be influenced by sample type, particularly for MALDI-TOF MS. The alarming and heterogeneous antibiotic resistance patterns also highlight the critical need for rapid and accurate species identification and drug susceptibility testing to inform effective therapeutic strategies. Key messagesMolecular technologies demonstrate high accuracy for NTM identification.Antibiotic resistance is a serious concern with variations among NTM species and subspecies.Rapid and accurate species identification and drug susceptibility testing are crucial for guiding effective clinical management of NTM PD.

Humans↗
PubMed2026

From scissors to editors: how the evolution of precision is redefining therapeutic genome editing.

Since its introduction as a genome-editing tool, CRISPR-based technology has undergone rapid refinement, with precision emerging as a central focus of development. Early CRISPR-Cas9 systems demonstrated unprecedented ease and efficiency in targeting specific DNA sequences, but concerns over off-target effects and variable editing outcomes limited their broader application. This review outlines the progression of CRISPR from its discovery in prokaryotes to its application as a versatile tool in precision medicine, where it supports targeted therapies for genetic disorders in various ways. Although technical challenges, including off-target editing and delivery inefficiencies, persist alongside ethical considerations of accessibility and long-term consequences, CRISPR's ongoing refinements and innovations reflect a clear trajectory toward greater specificity, safety, and predictability, positioning CRISPR as an increasingly precise platform for both fundamental research and therapeutic use.

Gene Editing↗
PubMed1979

Application of flow cytometry and cell sorting to megakaryocytopoiesis.

We have employed flow cytometry (FCM) and cell sorting to quantitate and study megakaryocytes in mouse and rat femoral marrow following their 20- to 30-fold concentration by centrifugal elutriation (CE). This enrichment of megakaryocytes permitted the first determination of their DNA-related fluorescence by FCM analysis following DNA staining. Fluorescence distributions of CE-enriched cell fractions following supravital staining with Hoechst 33342 were similar to those following chromomycin A3 staining of ethanol-fixed cells. Microscopic examination of cells sorted onto glass slides on the basis of their DNA-related fluorescence following supravital staining together with specific acetylcholinesterase staining for megakaryocytes indicated that megakaryocytes generally increased in cell size with increasing DNA content. This technologic application represents a significant advance in the study of megakaryocytopoiesis, since the kinetics of either the normal or perturbed population can now be studied rapidly and quantitatively.

Animals↗
PubMed2025

CountASAP: a lightweight, easy to use python package for processing ASAPseq data.

BACKGROUND: Declining sequencing costs coupled with the increasing availability of easy-to-use kits for the isolation of DNA and RNA transcripts from single cells have driven a rapid proliferation of studies centered around genomic and transcriptomic data. Simultaneously, a wealth of new techniques have been developed that utilize single cell technologies to interrogate a broad range of cell-biological processes. One recently developed technique, transposase-accessible chromatin with sequencing (ATAC) with select antigen profiling by sequencing (ASAPseq), provides a combination of chromatin accessibility assessments with measurements of cell-surface marker expression levels. While software exists for the characterization of these datasets, there currently exists no tool explicitly designed to reformat ASAP surface marker FASTQ data into a count matrix which can then be used for these downstream analyses. RESULTS: To address this lack of a dedicated tool for ASAPseq data processing, we created CountASAP, an easy-to-use Python package purposefully designed to transform FASTQ files from ASAP experiments into count matrices compatible with commonly-used downstream bioinformatic analysis packages. CountASAP takes advantage of the independence of the relevant data structures to perform fully parallelized matches of each sequenced read to user-supplied input ASAP oligos and unique cell-identifier sequences. We directly compare the performance and user-friendliness of CountASAP to existing tools using similarly-structured data from a more common sequencing experiment: cellular indexing of transcriptomes and epitopes by sequencing (CITEseq). Further benchmarking against existing tools helps to identify proper defaults for CountASAP and assess the agreement of outputs from all tested software. A final test using a novel ASAPseq dataset provides evidence that CountASAP can generate biologically meaningful results that correlate well with paired chromatin accessibility data. CONCLUSIONS: CountASAP shows good agreement with existing, well-tested data processing tools in the analysis of similarly-structured benchmarking data. CountASAP runs efficiently on a standard laptop, has user-friendly documentation, a one-step installation, and represents the first and only tool designed specifically for the processing of ASAPseq data.

Software↗
PubMed2025

N6-methyladenine identification using deep learning and discriminative feature integration.

N6-methyladenine (6 mA) is a pivotal DNA modification that plays a crucial role in epigenetic regulation, gene expression, and various biological processes. With advancements in sequencing technologies and computational biology, there is an increasing focus on developing accurate methods for 6 mA site identification to enhance early detection and understand its biological significance. Despite the rapid progress of machine learning in bioinformatics, accurately detecting 6 mA sites remains a challenge due to the limited generalizability and efficiency of existing approaches. In this study, we present Deep-N6mA, a novel Deep Neural Network (DNN) model incorporating optimal hybrid features for precise 6 mA site identification. The proposed framework captures complex patterns from DNA sequences through a comprehensive feature extraction process, leveraging k-mer, Dinucleotide-based Cross Covariance (DCC), Trinucleotide-based Auto Covariance (TAC), Pseudo Single Nucleotide Composition (PseSNC), Pseudo Dinucleotide Composition (PseDNC), and Pseudo Trinucleotide Composition (PseTNC). To optimize computational efficiency and eliminate irrelevant or noisy features, an unsupervised Principal Component Analysis (PCA) algorithm is employed, ensuring the selection of the most informative features. A multilayer DNN serves as the classification algorithm to identify N6-methyladenine sites accurately. The robustness and generalizability of Deep-N6mA were rigorously validated using fivefold cross-validation on two benchmark datasets. Experimental results reveal that Deep-N6mA achieves an average accuracy of 97.70% on the F. vesca dataset and 95.75% on the R. chinensis dataset, outperforming existing methods by 4.12% and 4.55%, respectively. These findings underscore the effectiveness of Deep-N6mA as a reliable tool for early 6 mA site detection, contributing to epigenetic research and advancing the field of computational biology.

Deep Learning↗
PubMed2024

Private detection of relatives in forensic genomics using homomorphic encryption.

BACKGROUND: Forensic analysis heavily relies on DNA analysis techniques, notably autosomal Single Nucleotide Polymorphisms (SNPs), to expedite the identification of unknown suspects through genomic database searches. However, the uniqueness of an individual's genome sequence designates it as Personal Identifiable Information (PII), subjecting it to stringent privacy regulations that can impede data access and analysis, as well as restrict the parties allowed to handle the data. Homomorphic Encryption (HE) emerges as a promising solution, enabling the execution of complex functions on encrypted data without the need for decryption. HE not only permits the processing of PII as soon as it is collected and encrypted, such as at a crime scene, but also expands the potential for data processing by multiple entities and artificial intelligence services. METHODS: This study introduces HE-based privacy-preserving methods for SNP DNA analysis, offering a means to compute kinship scores for a set of genome queries while meticulously preserving data privacy. We present three distinct approaches, including one unsupervised and two supervised methods, all of which demonstrated exceptional performance in the iDASH 2023 Track 1 competition. RESULTS: Our HE-based methods can rapidly predict 400 kinship scores from an encrypted database containing 2000 entries within seconds, capitalizing on advanced technologies like Intel AVX vector extensions, Intel HEXL, and Microsoft SEAL HE libraries. Crucially, all three methods achieve remarkable accuracy levels (ranging from 96% to 100%), as evaluated by the auROC score metric, while maintaining robust 128-bit security. These findings underscore the transformative potential of HE in both safeguarding genomic data privacy and streamlining precise DNA analysis. CONCLUSIONS: Results demonstrate that HE-based solutions can be computationally practical to protect genomic privacy during screening of candidate matches for further genealogy analysis in Forensic Genetic Genealogy (FGG).

Humans↗
PubMed2026

Comparative evaluation of three high-molecular-weight DNA extraction kits for Oxford Nanopore sequencing of Clostridioides difficile and Clostridium perfringens.

UNLABELLED: Clostridioides difficile and Clostridium perfringens are Gram-positive, spore-forming anaerobic pathogens affecting humans and animals, for which genomic data have been mainly generated using short-read or hybrid sequencing approaches. In this study, we evaluated three commercial non-bead-beating DNA extraction kits designed for high-molecular-weight DNA recovery for Oxford Nanopore long-read whole-genome sequencing of two C. difficile and two C. perfringens strains, including one reference strain and one clinical or environmental isolate per species. Based on sequencing performance and kit ease of use, one kit was selected for additional sequencing of plasmid-carrying strains of both species. All three kits allowed correct identification of sequence types, toxin-encoding genes, and antimicrobial resistance determinants, confirming their suitability for clinical and epidemiological applications. However, the BT MasterPure Kit provided the highest DNA concentrations, longest fragment sizes, and superior read lengths and N50 values, particularly for C. difficile, achieving >100× coverage and enabling reliable circularization of chromosomes and plasmids, including a C. difficile metronidazole resistance plasmid and C. perfringens plasmids carrying toxin and antibiotic resistance genes. The other kits produced slightly lower DNA yields, resulting in shorter reads and reduced genome coverage for C. difficile, highlighting the challenge of extracting high-quality DNA from Gram-positive, spore-forming bacteria. Overall, this study provides practical guidance for selecting DNA extraction protocols optimized for Oxford Nanopore sequencing of C. difficile and C. perfringens, supporting high-quality genome assemblies and plasmid characterization and facilitating the routine genomic surveillance of clinically relevant spore-forming pathogens. IMPORTANCE: High-quality genomic data are essential for accurate characterization of Clostridioides difficile and Clostridium perfringens, two clinically and epidemiologically important Gram-positive, spore-forming pathogens. However, long-read sequencing performance can be strongly influenced by the choice of DNA extraction method, particularly for organisms with robust cell walls, where commonly used methods can lead to fragmented DNA. In this work, DNA of four strains was extracted using three commercial high-molecular-weight DNA extraction kits and sequenced using Oxford Nanopore Technologies. The best-performing kit was also evaluated using three additional strains known to harbor plasmids in order to assess its plasmid recovery efficiency. The results demonstrated successful plasmid recovery, circularization, and characterization. DNA extraction protocols optimized for Oxford Nanopore sequencing enable the rapid and cost-effective characterization of C. difficile and C. perfringens for genomic surveillance or outbreak investigations.

Clostridioides difficile↗
PubMed2025

DNA methylation and machine learning: challenges and perspective toward enhanced clinical diagnostics.

DNA methylation is an epigenetic modification that regulates gene expression by adding methyl groups to DNA, affecting cellular function and disease development. Machine learning, a subset of artificial intelligence, analyzes large datasets to identify patterns and make predictions. Over the past two decades, advances in bioinformatics technologies for arrays and sequencing have generated vast amounts of data, leading to the widespread adoption of machine learning methods for analyzing complex biological information for medical problems. This review explores recent advancements in DNA methylation studies that leverage emerging machine learning techniques for more precise, comprehensive, and rapid patient diagnostics based on DNA methylation markers. We present a general workflow for researchers, from clinical research questions to result interpretation and monitoring. Additionally, we showcase successful examples in diagnosing cancer, neurodevelopmental disorders, and multifactorial diseases. Some of these studies have led to the development of diagnostic platforms that have entered the global healthcare market, highlighting the promising future of this field.

Humans↗
PubMed2026

Cross-Platform Concordance in DNA Methylation Based Classification of CNS Tumors.

DNA methylation profiling enables precise classification of pediatric central nervous system (CNS) tumors. Oxford Nanopore Technologies (ONT) offers same-day, single-sample methylation readouts, but its concordance with Illumina EPIC arrays in routine diagnostic tasks remains incompletely defined. We profiled 23 pediatric tumors (18 CNS, 5 non-CNS) by EPIC arrays and ONT. Methylation profiles from both platforms were classified with crossNN (brain model or pan-cancer model); ONT data were additionally classified with Rapid-CNS2 and Sturgeon. We compared (i) classifier agreement with integrated histology (w/o NGS) at family/class levels, (ii) pass-rate above platform-specific score cutoffs, (iii) cross-platform concordance of copy-number variation (CNV), and MGMT promoter methylation status. In CNS cases, ONT and EPIC methylation profiles demonstrated strong correlation, except for a single outlier (P2), which was excluded from further analysis. Comparative assessment of the two platforms showed that: (a) Molecular classification of CNS tumors using the crossNN classifier was consistent with histology (w/o NGS) at the family level in all cases. (b) Copy-number profiles showed high concordance between platforms. (c) MGMT promoter methylation status matched in 94% of cases (16/17). When comparing ONT-specific analysis pipelines using the ONT data, the Rapid-CNS2 pipeline yielded the most reliable class level assignments with 94% (16/17) concordance with the histopathological diagnosis, which marginally exceeded the crossNN and sturgeon classifiers. In non-CNS tumors, the pan-cancer model produced low-confidence outputs with poor agreement with histology (w/o NGS) (only 1/5 concordant), indicating limited readiness for these entities. In conclusion, ONT enables same-day, clinically reliable family-level CNS tumor classification with high concordance to arrays, while EPIC retains a modest class-level edge. A key limitation of ONT is its reliance on fresh-frozen DNA and on classifiers originally built around array-derived CpG sites, rather than on models developed natively from ONT data.

DNA methylation↗