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PubMed2026

Development and evaluation of a multiplex PCR-based dual-platform targeted sequencing framework for precise differentiation of lumpy skin disease virus.

BACKGROUND: Lumpy skin disease virus (LSDV) shares over 96% genomic identity with goatpox and sheeppox viruses, presenting severe diagnostic challenges due to cross-reactivity. METHODS: To address this bottleneck, we established a targeted sequencing framework integrating multiplex PCR with short-read and long-read platforms. By sequentially screening target pathogens, identifying low-homology genes, and designing short and gradient long-fragment primer pools, we evaluated these dual-platform panels using highly homologous poxvirus samples. RESULTS: The short-read panel stably detected target viruses at inputs as low as 5.26 ×101 copies/μL. Under strict alignment criteria, LSDV mapping rates reached 42.91%, suppressing non-target signals to 3.05%. The Nanopore-Targeted Sequencing (NTS) long-amplicon strategy successfully eliminated homologous interference. By applying length-dependent diagnostic thresholds (≥ 100 reads for short amplicons; ≥ 50 reads for long amplicons), precise species-level identification was achieved, maintaining near-zero cross-reads (0-5) in ultra-long regions. Crucially, the field-deployable NTS workflow enabled complete detection in approximately 4 h. CONCLUSION: This complementary strategy seamlessly meets both laboratory demands for high-sensitivity enrichment and frontline requirements for rapid typing, providing a reliable tool for LSDV surveillance, mutation tracking, and outbreak control.

Capripoxvirus differentiation↗

PubMed2026

Small Copy Number Neutral Intrachromosomal Translocation of PAX6 and Aniridia.

IMPORTANCE: Approximately 5% to 10% of individuals with classic aniridia do not receive a molecular diagnosis after clinical testing for variants in PAX6 and its downstream regulatory region. OBJECTIVE: To apply optical genome mapping (OGM) and long-read whole-genome sequencing (lrWGS) to diagnose an individual with unexplained classic aniridia. DESIGN, SETTING, AND PARTICIPANTS: High-quality DNA was extracted from the blood of a 16-year-old male patient with classic aniridia and prior negative clinical test results that included sequencing and copy number analysis of PAX6 exons and downstream regulatory region as well as genomic analysis via short-read whole-genome sequencing (srWGS) and analyzed using OGM and lrWGS. All analyses were performed in a research laboratory in Wisconsin from January 2019 to September 2025. INTERVENTIONS: OGM and lrWGS. MAIN OUTCOMES AND MEASURES: Identification of a structural variant disrupting PAX6 expression in an individual with classic aniridia, following negative prior testing including srWGS. RESULTS: OGM identified a 55-kb deletion on 11p13 encompassing all PAX6 exons and exon 12 of ELP4, with insertion of this segment into 11q21. lrWGS delineated the exact breakpoints, confirming that the downstream regulatory region, required for normal PAX6 expression, remained at the 11p13 locus. Consequently, the translocated copy of PAX6 at 11q21 is expected to lack expression due to the loss of its essential regulatory elements. CONCLUSIONS AND RELEVANCE: These findings in an individual with classic aniridia harboring an intrachromosomal rearrangement at the PAX6 locus identified by OGM and lrWGS may represent the smallest reported structural variant to separate the PAX6 coding sequence from its downstream regulatory region. This structural variant may have fallen below the detection threshold of srWGS due to its balanced nature and small size, suggesting OGM and lrWGS would be needed for definitive identification.

Aniridia↗

PubMed2026

Complete genome sequence of the Anaplasma phagocytophilum clinical isolate NCH-1.

Anaplasma phagocytophilum is an obligate intracellular gram-negative bacterium and etiologic agent of human granulocytic anaplasmosis. A. phagocytophilum genomic sequencing has historically been performed via short-read platforms. Our optimized bacterial isolation protocol combined with Nanopore sequencing produced a single, closed 1,481,805 bp circular A. phagocytophilum strain NCH-1 chromosome.

Anaplasma phagocytophilum↗

PubMed2026

Long-read sequencing reveals putatively mobilizable resistance genes and multi-drug resistance plasmids underestimated by short-read metagenomics.

While shotgun metagenomics is often used to profile antibiotic resistome in gut microbial communities, few studies have investigated if the choice of sequencing platform and assembly strategy affect what mobile genetic elements and antimicrobial resistance genes are recovered. In this study, we compared three platforms (Illumina, Oxford Nanopore, and PacBio HiFi) and seven assembly strategies on gut metagenomes from cattle, pig, and human as case studies. Long-read assemblies recovered 5- to 7-fold more plasmid sequence than Illumina in cattle and pig (mean 17.0 Mb vs. 3.1 Mb), while Illumina performed comparably in the less diverse human gut where high per-species coverage enabled effective short-read plasmid assembly. Long reads also detected more resistance genes on plasmid contigs. Hybrid assembly results depended on the algorithm: scaffolding-based OPERA-MS preserved long-read contiguity and recovered more plasmid-borne resistance genes, while the short-read-centric metaSPAdes hybrid mode produced fragmented assemblies. After collapsing haplotype redundancy, PacBio HiFi identified 2 and 49 unique multi-drug resistance plasmid lineages in cattle and pig, respectively. On the other hand, only 2 and 4 were identified from Illumina. Long reads also placed far more ARGs in a putative mobilization context (50-73%) compared to 14-21% for short reads. Platform and assembly strategy are thus key variables in mobilome and resistome characterization and should be accounted for in antimicrobial resistance surveillance.

Animals↗

PubMed2026

Genetic Ancestry and Colorectal Cancer in the All of Us Dataset.

IMPORTANCE: Genetic ancestry may complement biological, behavioral, and clinical factors in understanding colorectal cancer (CRC) disparities; yet, ancestry-informed analyses in CRC remain limited. OBJECTIVE: To characterize associations of genetic ancestry with CRC burden, age at diagnosis, and age-specific risk, and to develop a multiethnic CRC risk-prediction model. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used All of Us data from July 1986 to October 2023, with follow-up through last visit or death (median [IQR], 133.1 [57.1-186.5] months); analyses were conducted from February to June 2026. All of Us is a US research cohort with linked electronic health record (EHR) and short-read whole-genome sequencing (srWGS) data. All of Us Research Program participants with srWGS and linked EHR data were included, except those with hereditary polyposis or Lynch syndrome. EXPOSURES: Genetically inferred ancestry categories and principal components. MAIN OUTCOMES AND MEASURES: Any CRC was the primary outcome. Associations were evaluated using Fisher exact tests, cumulative incidence functions with Gray tests, cause-specific and Fine-Gray subdistribution hazard models, and pooled multivariable logistic regression. Prediction models used penalized least absolute shrinkage and selection operator and extreme gradient boosting (XGBoost). RESULTS: Among 316 624 participants (median [IQR] age, 56.3 [40.2-68.2] years; 172 327 [54.4%] of European ancestry; 191 705 female [61.2%]; 121 585 male [38.8%]), 2914 (0.9%) developed CRC. European ancestry was associated with higher odds of CRC vs all other ancestries combined (odds ratio, 1.50; 95% CI, 1.39-1.62). The median age at CRC diagnosis was older in European (63.4 [53.9-71.2] years) than in American admixed-Latino, African, East Asian, and Other ancestry groups. In cause-specific hazard models on the attained-age scale, American admixed-Latino (hazard ratio, 1.30; 95% CI, 1.14-1.47) and East Asian (hazard ratio, 1.43; 95% CI, 1.06-1.94) ancestry had higher age-specific CRC hazard than European ancestry, with consistent findings on the subdistribution scale accounting for competing death. The multiethnic XGBoost model performed best (receiver operating characteristic area under the curve, 0.898; 95% CI, 0.882-0.912; precision-recall area under the curve, 0.338; 95% CI, 0.296-0.379) and was well calibrated. CONCLUSIONS AND RELEVANCE: In this cohort study, genetic ancestry was associated with meaningful differences in CRC burden and age-specific risk. These findings suggest that a multiethnic XGBoost model may complement CRC screening as a risk-enrichment tool.

Aged↗

PubMed2026

MetaStrainer: accurate reconstruction of bacterial strain genotypes from short-read metagenomic samples.

MOTIVATION: Metagenomics provides broad insights from microbial communities, but more biological relevant phenotypes are attributed to subtle changes at the strain-level rather than species. Despite development of several tools using different algorithms, resolving individual strains from short-read pair-end sequencing data remains challenging. RESULTS: Here we present MetaStrainer, a tool capable of reconstructing strain genotypes from metagenomic data. Compared with existing approaches, MetaStrainer substantially increases genotype accuracy, correctly identifies the number of strains, and accurately estimates their relative abundances. Accuracy of reconstructed genotypes is robust to choice of mapping reference. AVAILABILITY: MetaStrainer is implemented in Python 3. Source code and instructions are available on GitHub at www.github.com/lbobay/MetaStrainer and on Zenodo: 10.5281/zenodo.17872331.

Metagenomics↗

PubMed2026

Bridging the gap between legacy polymerase chain reaction-based microsatellite data with high-throughput sequencing data for conservation genomics.

Microsatellites are powerful markers for tracking genetic variation in wildlife populations due to their high polymorphism and genome-wide abundance. While polymerase chain reaction (PCR)-based fragment size analysis has been the standard for genotyping microsatellites, high-throughput sequencing offers greater resolution and the opportunity to sync historical datasets with modern analyses. We evaluated how genotypes from whole-genome sequencing align with PCR data for 15 microsatellite loci in 11 North American brown bears (Ursus arctos). Brown bear populations in the 48 contiguous United States have declined from approximately 50,000 to fewer than 2,000 over the past decades. Their endangered status has prompted extensive research and genetic monitoring, yielding large, multiyear microsatellite datasets upon which future conservation efforts can build. We achieved an overall microsatellite genotype concordance rate of 94.5% comparing high-throughput sequencing results to PCR based-fragment size results. All discrepancies occurred at complex loci containing multiple insertions and/or deletions (indels). Physically linked indels or single nucleotide polymorphisms (SNPs) occurring within the loci were misinterpreted as independent insertions, underscoring the need for genotyping tools that incorporate phasing when genotyping. To evaluate coverage effects, we downsampled high-throughput sequence data from 30x to 2x. Concordance remained high at 20 to 30x but dropped sharply at 10x, with 5x and 2x having discordant genotypes or insufficient coverage for genotyping. Accurate genotyping required both sufficient depth and number of reads spanning the entire repeat regions. Our results show that short-read whole-genome sequencing can recover microsatellite genotypes with high accuracy when paired with careful variant interpretation. By aligning historical PCR datasets with modern sequencing data, we can preserve decades of genetic insight and strengthen long-term monitoring of at-risk populations.

Animals↗

PubMed2026

Coexistence of carbapenemase and hypervirulence-associated genes among Klebsiella pneumoniae high-risk clones in Hungary.

INTRODUCTION: Strains of Klebsiella pneumoniae carrying hypervirulence and carbapenemase genes represent a rapidly emerging global public health threat. Our study aimed to comprehensively characterise the genomics of hypervirulence-associated and carbapenemase genes carrying K. pneumoniae (hv(a)CpKp) isolates in Hungary. MATERIALS AND METHODS: Between January 2022 and April 2024, 89 aerobactin (iucA-D/iutA)-positive non-duplicate carbapenemase-producing K. pneumoniae isolates from 15 Hungarian healthcare institutes underwent short-read (Illumina, MiSeq, NextSeq) whole-genome sequencing, followed by detailed plasmid analysis using long-read sequencing (Nanopore, MinION) in a representative subset of 32 strains. RESULTS: Most isolates (79/89) belonged to the high-risk clone ST147. Hypervirulence-associated (hva) genes-including rmpA/rmpA2, peg344, shiF, iucA-D, and iutA-were universally present, and 59 isolates possessed chromosomally integrated yersiniabactin loci. Most isolates (87/89) carried the bla NDM-1 carbapenemase gene. Hypervirulence-associated genes were most frequently (29/32) associated with IncHI1B/IncFIB(Mar) plasmids. Notably, we identified plasmids carrying both hva and carbapenemase genes-designated as hybrid plasmids-in 13 of 32 strains. The bla NDM-1 was linked to the IS26 transposase and was present in conserved, identical cassettes on all bla NDM-1-carrying plasmids. DISCUSSION/CONCLUSION: Our study identified hv(a)CpKp strains, particularly the ST147 clone, circulating in Hungary. Our findings highlight the need for routine virulence gene monitoring and continuous genomic and plasmid-based surveillance to mitigate the clinical and epidemiological impact of emerging hv(a)CpKp lineages.

Klebsiella pneumoniae↗

PubMed2026

Genomic Diversity and Extended-Spectrum β-Lactamase Gene Contexts of Community Resident-Carried Escherichia coli in Ecuador.

Community carriage of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli represents an important reservoir of antimicrobial resistance. However, the genomic diversity and population structure of ESBL-producing E. coli circulating in community settings remain poorly characterized. This study aimed to characterize ESBL-producing E. coli isolated from fecal samples of residents in Ecuador, with an emphasis on the diversity and genomic context of ESBL genes. ESBL-producing E. coli was isolated from fecal samples obtained from 55 residents using MacConkey agar supplemented with cefotaxime. Whole-genome sequencing of the isolates was performed using a hybrid approach combining long- and short-read platforms. Plasmids and β-lactamase genes were identified using DFAST and PlasmidFinder. Bacterial identification and antimicrobial susceptibility testing were conducted by MALDI-TOF MS and the broth microdilution method, respectively. ESBL-producing E. coli were isolated from 35 of 55 fecal samples (63.6%). Complete circular genomes were obtained from 31 isolates. All isolates harbored bla CTX-M genes, predominantly belonging to the bla CTX-M-1 group, whereas 65.7% carried bla TEM, mainly bla TEM-1, and related variants. Although β-lactamase genes were predominantly plasmid-borne, chromosomal integration was detected in 40% of the isolates. Notably, 87.5% of the isolates harbored IncF plasmids with multiple replicons. Conserved IS26-flanked transposons carrying bla CTX-M and bla TEM were frequently identified in the plasmids. Phylogenetic analysis revealed substantial genomic diversity across seven phylogroups, together with closely related isolates detected within and between households. These findings provide high-resolution genomic insights into the ESBL determinants circulating in community residents and reveal region-specific patterns of ESBL genomic diversity.

CTX-M β-lactamases↗

PubMed2026

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

PubMed2026

Exploring differences across pangenome-graph representations using Escherichia coli O157:H7 as a model.

Pangenome graphs are increasingly used to represent population-scale bacterial diversity, yet construction methods span fundamentally different representation paradigms whose outputs and sensitivities to assembly quality remain poorly quantified. We systematically reviewed microbial pangenome graph tools and benchmarked seven representative methods spanning gene-cluster, compacted coloured de Bruijn graph, one hybrid approach and one multiple sequence alignment method. Using a repeat-rich Escherichia coli O157:H7 dataset with complete genomes and matched short-read data, we constructed graphs from identical inputs and observed orders-of-magnitude differences in graph size and fragmentation, indicating that global topology is driven by representation strategy. Varying completeness composition revealed that assembly fragmentation is a first-order determinant of graph structure: gene-cluster graphs contracted as draft assemblies replaced complete genomes, whereas compacted coloured de Bruijn graphs expanded, with distinct degree-prevalence fingerprints across tools. In contrast, the multiple sequence alignment method could not be evaluated across fragmented inputs because it did not run reliably on draft-assembly datasets. Computational cost mirrored these shifts and depended strongly on completeness composition, including a pronounced runtime penalty for one compacted coloured de Bruijn graph implementation on all-draft inputs. Finally, analysis of Shiga toxin loci showed that pangenome-level reconciliation by gene-cluster-based tools does not reliably correct assembly artefacts at challenging multi-copy genes and that performance varies by locus. Together, these findings show that pangenome graphs are representation-dependent models of bacterial diversity, and that, in this repeat-rich O157:H7 benchmark dataset, assembly completeness is a primary determinant of their topology, scalability, and locus-level accuracy.

Escherichia coli O157↗

PubMed2026

Likelihood-based optimization enables accurate copy number estimation for paralogous genes using exome data.

MOTIVATION: Exome sequencing is widely used for genetic studies; however, accurate detection of copy number variants (CNV) in paralogous genes is challenging due to short-read mapping ambiguity and extensive copy-number variation. The human genome contains several hundred paralogous genes, many of which are known to harbor disease-associated CNVs. Existing exome CNV callers are primarily designed for rare CNV detection in uniquely mappable regions and are not well-suited for paralogous genes. METHODS: We describe a computational method (EdgeCopy) for copy number profiling of paralogous genes using whole-exome sequence data. EdgeCopy aggregates reads mapped to all copies of paralogous genes and relates observed read depth to copy number for multiple exome samples using an approximate composite likelihood function. The likelihood function is optimized using numerical optimization to obtain gene-level fractional copy number estimates that are discretized and refined using a Hidden Markov Model to obtain exon-level copy number estimates. RESULTS: Benchmarking of Edgecopy using experimental copy number data showed high concordance (mean = 0.973) for six disease-associated paralogous genes. We evaluated performance using whole-exome data from approximately 2400 samples across five continental populations from the 1000 Genomes Project. EdgeCopy shows robust concordance with whole-genome sequencing based estimates (0.974-0.982) across populations and 130 paralogous genes spanning a wide range of copy-number variation. In comparison, copy number analysis using a state-of-the-art exome CNV caller failed to estimate copy number for paralogous genes with very high mapping ambiguity and showed much lower concordance (0.565) for CNV events compared to EdgeCopy (0.908). AVAILABILITY: EdgeCopy is freely available at https://github.com/vibansal-lab/edgecopy.

Humans↗

PubMed2026

nf-core/pacsomatic: a scalable somatic analytic pipeline using PacBio HiFi data.

MOTIVATION: Pacific Biosciences (PacBio) HiFi long-read sequencing enables robust characterization of complex genomic regions, repetitive elements, and structural variants (SVs) that are often inaccessible to short-read technologies. To fully leverage HiFi reads to advance cancer genomics and epigenetics, researchers require an end-to-end, scalable and optimized bioinformatics workflow. The nf-core framework meets this need by providing rigorously tested, community-curated pipelines that ensure reproducibility, transparency, and broad compatibility across computational environments. RESULTS: We present nf-core/pacsomatic, an automated Nextflow DSL2 pipeline designed for comprehensive paired tumor-normal somatic analysis using PacBio HiFi data. The workflow includes steps for read alignments against reference genome, somatic SNV/indel, SV, and CNV calling, CpG methylation profiling and differential methylation region (DMR) detection. Additional downstream modules support functional annotation, mutational signature analysis, tumor purity and ploidy estimation, and homologous recombination deficiency (HRD) assessment. Utilizing nf-core's modular design and containerized execution, nf-core/pacsomatic provides a stable framework for the reproducible discovery of biological insights. AVAILABILITY: nf-core/pacsomatic is available under the MIT License at nf-core (https://nf-co.re/pacsomatic) and github (https://github.com/nf-core/pacsomatic).

Software↗

PubMed2026

Molecular residual disease assessment in colorectal and bladder cancer by somatic structural variant analysis of cell-free DNA whole-genome sequencing data.

BACKGROUND: Whole-genome sequencing (WGS)-based methods for circulating tumor DNA (ctDNA) detection typically rely on tumor-informed identification of somatic single nucleotide variants (SNVs). Somatic structural variants (SVs) are another type of cancer-specific genomic alteration, which owing to their larger genomic footprint and unique breakpoint junctions, are easier to distinguish from sequencing noise than SNVs. They are, however, rarely used for ctDNA detection because of (1) artifacts from WGS procedures that SV callers may falsely interpret as genuine SVs. This makes it difficult to establish high-confidence SV catalogos from short-read tumor WGS and can cause false-positive ctDNA detections. (2) Lack of robust strategies to quantify SV-supporting reads in plasma WGS. To address these barriers and enable integration of SV biomarkers into WGS-based ctDNA detection, we present a bioinformatic framework for algorithmic curation of somatic SV calls from fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tumors, coupled with a novel approach for sensitive, accurate mapping and quantification of SV breakpoint-supporting reads in plasma WGS. METHODS: Tumor, normal and plasma WGS data from 144 patients with stage III colorectal cancer was used to establish the bioinformatic framework. This included ~30x WGS data from 1564 serially collected plasma samples. The framework was validated using tumor/normal/plasma WGS data from 32 patients with muscle-invasive bladder cancer. SV-based ctDNA detection was benchmarked against previously published SNV-based ctDNA results for the same samples. RESULTS: After curation of SV calls and quantification in plasma WGS, our SV-based approach enabled robust ctDNA detection with overall specificity exceeding 99% in plasma samples. Furthermore, we observed strong concordance (Pearson’s r > 0.93, p < 2.2 × 10− 16) between ctDNA-positive samples identified by our SV-based method and previous SNV-based analyses, validating the reliability of our approach. Finally, we demonstrated application of the method in an independent bladder cancer cohort, highlighting its generalizability and potential clinical use. CONCLUSIONS: We provide a bioinformatic framework that establishes somatic SVs as ultra-specific biomarkers for WGS-based, tumor-informed ctDNA detection. The approach delivers specific detection even when the SV catalogos are established from FFPE samples. The SV framework can stand alone or enhance SNV-based analysis pipelines.

Humans↗

PubMed2026

Long-read sequencing reveals widespread novel splicing and neojunction-derived neoantigens in nasopharyngeal carcinoma.

The widespread transcriptomic diversity driven by alternative splicing (AS) contributes to all hallmarks of cancer and represents a critical source of neoantigens for personalized immunotherapy. However, unlike other major malignancies, the full repertoire of AS in nasopharyngeal carcinoma (NPC) remains underexplored. Here, we employ long-read sequencing (LR-seq) to generate a high-resolution, isoform-level transcriptomic atlas from a cohort of 14 NPC tumor samples and four immortalized nasopharyngeal epithelial cell lines. We identify a substantial number of full-length novel transcripts (22,687; ∼44.38%), which reveal diverse splicing patterns and previously unannotated splicing events. By integrating short-read RNA-seq data to quantify isoform expression, we discover a subset of novel transcripts that are differentially expressed between tumor samples and immortalized nasopharyngeal epithelial cell lines. Furthermore, LR-seq enables precise identification of chimeric readthrough fusion transcripts, such as CLDN15-FIS1 and FOXRED2-TXN2 Finally, we develop a computational framework, tumor-specific splicing neoantigen detection (TS-SNAD), to predict neoantigens originating from novel exon-exon junctions (neojunctions) in tumor-specific novel transcripts. Using this framework, we identify neojunction-derived neoantigens and experimentally validate the immunogenicity of selected HLA-B*40:01-restricted neoantigens. These neojunction-derived peptides constitute a new class of noncanonical neoantigens with significant potential for developing personalized cancer vaccines for NPC.

Humans↗

PubMed2026

ORFannotate: reproducible coding sequence annotation of transcriptome assemblies.

SUMMARY: Accurate annotation of coding sequences and translational features within transcript models is essential for interpreting assembled transcriptomes and their functional potential. Existing open reading frame (ORF) prediction tools typically operate on transcript FASTA files and do not reintegrate coding sequence (CDS) information back into transcript models, limiting their utility in long-read sequencing workflows where GTF/GFF annotations are the primary output. We present ORFannotate, a lightweight, GTF-native Python command-line tool that predicts ORFs from transcript annotations and reinserts precise, exon-aware CDS and UTR features into the original GTF/GFF file. In addition, ORFannotate provides biologically informative translational context by annotating Kozak sequence strength, detecting non-overlapping upstream ORFs (uORFs) with coding probabilities, characterising 5' and 3' untranslated regions (UTRs), and predicting nonsense-mediated decay (NMD) susceptibility. All annotations are consolidated in a transcript-level summary to support downstream analysis. By generating GTF files with accurate CDS annotations, ORFannotate facilitates reproducible analysis of both long- and short-read transcriptomes and integrates seamlessly with visualization tools, genome browsers, and comparative transcript analysis workflows. ORFannotate is fast, scalable and provides a practical solution for transcriptome annotation beyond coding potential prediction alone. AVAILABILITY AND IMPLEMENTATION: ORFannotate is implemented in Python and freely available under the GNU General Public License v3 (GPL-3.0) at: https://github.com/egustavsson/ORFannotate (DOI: https://doi.org/10.5281/zenodo.16812866).

Open Reading Frames↗

PubMed2026

StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution.

SUMMARY: Metagenomic workflows involve complex multi-step analyses, from quality control and assembly to binning, annotation, and strain-level profiling. Few existing metagenomic pipelines achieve the combination of flexibility, reproducibility, and hybrid assembly support within a unified workflow. We present StrainMake, a Snakemake-based workflow for de novo metagenomic analysis from short, long, or hybrid sequencing data. StrainMake integrates widely used tools across all major steps-quality control, assembly, binning, dereplication, taxonomic and functional annotation-while also providing non-redundant gene catalogues, community-scale metabolic models, and strain-level microdiversity metrics. The modular design enables the use of alternative tools, scalable execution on HPC systems, and full reproducibility through Snakemake and Conda. RESULTS: Applied to the CAMI II strain-madness dataset, StrainMake produced high-quality assemblies and metagenome-assembled genomes (MAGs), while enabling strain-resolved comparisons across samples. Hybrid assemblies improved contiguity, whereas short-read assemblies offered faster runtimes, illustrating the workflow's benchmarking capacity. AVAILABILITY AND IMPLEMENTATION: StrainMake is open source and available at https://github.com/UMMISCO/strainmake, together with comprehensive documentation. Generated data are deposited in Zenodo (doi: 10.5281/zenodo.16950162).

Metagenomics↗

PubMed2026

Long-read low-pass sequencing enhances variant detection in a peanut MAGIC population.

Accurate genotyping accelerates crop improvement, yet long-read sequencing remains underused in breeding due to cost. We present a scalable long-read low-pass (LRLP) sequencing framework for high-throughput variant discovery and trait mapping. Using PacBio HiFi reads in an allotetraploid peanut (Arachis hypogaea; AABB, 2n = 4x = 40) MAGIC population, we generated both LRLP and short-read low-pass (SRLP) data. At comparable depths, LRLP achieved substantially greater whole-genome and gene-space coverage than SRLP. Data were analyzed using both a single-reference genome and an 18-parent pangenome graph constructed with KhufuPan, a new tool for graph-based genotyping. Across analytical approaches, LRLP consistently identified more SNPs, indels (2-1,000 bp), and structural variants (>1 kb) than SRLP, improving genotype resolution and selection accuracy, particularly for large structural variants. By reducing cost barriers and increasing variant discovery in complex genomes, LRLP provides a practical path for deploying advanced genomics in under-resourced and orphan crops critical to global food security.

Arachis↗