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PubMed2000

RIKEN integrated sequence analysis (RISA) system--384-format sequencing pipeline with 384 multicapillary sequencer.

The RIKEN high-throughput 384-format sequencing pipeline (RISA system) including a 384-multicapillary sequencer (the so-called RISA sequencer) was developed for the RIKEN mouse encyclopedia project. The RISA system consists of colony picking, template preparation, sequencing reaction, and the sequencing process. A novel high-throughput 384-format capillary sequencer system (RISA sequencer system) was developed for the sequencing process. This system consists of a 384-multicapillary auto sequencer (RISA sequencer), a 384-multicapillary array assembler (CAS), and a 384-multicapillary casting device. The RISA sequencer can simultaneously analyze 384 independent sequencing products. The optical system is a scanning system chosen after careful comparison with an image detection system for the simultaneous detection of the 384-capillary array. This scanning system can be used with any fluorescent-labeled sequencing reaction (chain termination reaction), including transcriptional sequencing based on RNA polymerase, which was originally developed by us, and cycle sequencing based on thermostable DNA polymerase. For long-read sequencing, 380 out of 384 sequences (99.2%) were successfully analyzed and the average read length, with more than 99% accuracy, was 654.4 bp. A single RISA sequencer can analyze 216 kb with >99% accuracy in 2.7 h (90 kb/h). For short-read sequencing to cluster the 3' end and 5' end sequencing by reading 350 bp, 384 samples can be analyzed in 1.5 h. We have also developed a RISA inoculator, RISA filtrator and densitometer, RISA plasmid preparator which can handle throughput of 40,000 samples in 17.5 h, and a high-throughput RISA thermal cycler which has four 384-well sites. The combination of these technologies allowed us to construct the RISA system consisting of 16 RISA sequencers, which can process 50,000 DNA samples per day. One haploid genome shotgun sequence of a higher organism, such as human, mouse, rat, domestic animals, and plants, can be revealed by seven RISA systems within one month.

Animals↗
PubMed2024

Diversity of ribosomes at the level of rRNA variation associated with human health and disease.

Ribosomal DNA and RNA (rDNA and rRNA) sequences are usually discarded from sequencing analyses. But with hundreds of copies of rDNA genes it is unknown whether they possess sequence variations that form different types of ribosomes that affect human physiology and disease. Here, we developed an algorithm for variant-calling between paralog genes (termed RGA) and compared rDNA variations found in short- and long-read sequencing data from the 1,000 Genomes Project (1KGP) and Genome In A Bottle (GIAB). We additionally developed a novel protocol for long-read sequencing full-length rRNA (RIBO-RT) from actively translating ribosomes. Our analyses identified hundreds of rDNA variants, most of which, surprisingly, are short insertion-deletions (indels) and dozens of highly abundant rRNA variants that are incorporated into translationally active ribosomes. To visualize variant ribosomes at the single cell level, we developed an in-situ rRNA sequencing method (SWITCH-seq) which revealed that variants are co-expressed within individual cells. Strikingly, by analyzing rDNA, we found that variants assemble into distinct ribosome subtypes. We discovered that these subtypes acquire different rRNA structures by successfully employing dimethyl sulfate (DMS) probing of full length rRNA. With this atlas we investigated rRNA variation changes across human tissues and cancer types. This revealed tissue-specific rRNA subtype expression in endoderm/ectoderm-derived tissues. In cancer, low abundant rRNA variants can become highly expressed, which suggests the presence of cancer-specific ribosomes. Together, this study identifies and comprehensively characterizes the diversity of ribosomes at the level of rRNA variants which is dominated by indel variants, their chromosomal location and unique structure as well as the association of ribosome variation with tissue-specific biology and cancer.

Journal Article↗
PubMed2026

Long-read transcriptomics corrects Trichomonas vaginalis intron annotations and refines transcript-end features.

BACKGROUND: Trichomonas vaginalis causes the most prevalent non-viral sexually transmitted infection worldwide. Despite its large genome (181.5 Mb; 36,310 predicted protein-coding genes in NYU_TvagG3_2), intron annotations remain limited and inconsistently validated. A recent short-read RNA-seq study reported 63 putative active introns, but short reads can misassign splice boundaries and cannot resolve complete transcript structures. METHODS: We integrated Oxford Nanopore direct RNA sequencing (DRS), ONT cDNA long-read sequencing, and Illumina RNA-seq to refine intron annotations, transcript-end features, and UTR boundaries in T. vaginalis. Candidate introns were validated by targeted PCR and Sanger sequencing, and representative splicing events were further assessed using public SRA datasets. RESULTS: Starting from 31 historically annotated introns, motif-guided long-read screening and orthogonal validation identified 17 additional validated introns, increasing the curated set to 48 confirmed introns. Among these 17 events, three were previously unrecognized in the current NYU_TvagG3_2 reference annotation. We also corrected five reported loci, including two false-positive introns, two splice-coordinate misannotations, and one gene-sequence error. DRS further supported transcript termination site mapping, UAAA polyadenylation-signal profiling relative to poly(A) addition sites, and single-molecule poly(A)-tail estimation. StringTie mixed-mode assemblies provided updated UTR boundaries for intron-bearing transcripts and transcripts without curated introns. CONCLUSIONS: This study provides a rigorously validated, long-read-refined resource of intron annotations, UTR boundaries, and UAAA-guided transcript-end features for T. vaginalis, together with a reproducible workflow for non-model protists. These refinements improve the current reference annotation and support future studies of functional genomics, parasite biology, pathogenesis, and diagnostic development.

Trichomonas vaginalis↗
PubMed2026

An enhanced multisegment RT-PCR method for influenza A virus sequencing: Improved performance and reduced preparation time over traditional methods.

Influenza A viruses (IAVs) remain a major global health threat, affecting both human and animal populations. Whole-genome sequencing is essential for monitoring viral evolution, zoonotic transmission, and emerging variants. However, conventional RT-PCR methods often result in incomplete gene coverage, amplification biases, and reduced sequencing accuracy, particularly in clinical samples. We developed a robust In-house method for IAV full-genome sequencing using the Oxford Nanopore Technologies (ONT) long-read sequencing platform. This method integrates an in-house multisegment Reverse Transcription PCR (RT-PCR) method with a streamlined 2-pool primer design targeting all eight IAV gene segments. RNA extracted from clinical and stock virus samples was reverse-transcribed and amplified using Superscript IV-based chemistry, followed by magnetic bead purification to ensure high-quality amplicons. Sequencing libraries were prepared with the Native Barcoding Kit 24 (SQK-NBD114.24) and sequenced on R10.4.1 flow cells on the MinION MK1C device. Data analysis using the Iterative Refinement Meta-Assembler (IRMA) confirmed improved read depth, uniform coverage, and complete genome recovery. Compared to conventional methods, our In-House Multisegment 2-Pool (IH-MS2P) RT-PCR method generated higher numbers of matched read counts, minimized chimeric artifacts, and delivered superior genome coverage across human, swine, and avian isolates. This optimized RT-PCR method provides a high-performance, time-efficient, and portable solution for influenza genomics, demonstrating robust applicability even with clinical samples of low RNA yield.

Influenza A virus↗
PubMed2026

Optimizing GRIDSS for clinical use: A targeted NGS filtering strategy for germline structural variant detection.

Detecting intermediate-sized structural variants (SVs) remains challenging in diagnostics, as tools for single-nucleotide and copy-number variants, particularly read-depth-based methods, are often insufficient. GRIDSS addresses this gap by integrating paired-end mapping, split-read analysis, and assembly-based approaches. However, its use in targeted sequencing and diagnostic workflows remains complex. NGS panel data from 9726 patients with suspected hereditary cancer were analyzed using GRIDSS. A filtering strategy was developed to prioritize clinically relevant germline SVs. Multiple parameter settings were tested to optimize performance. The initial dataset of 1,307,592 variants was reduced to 89 candidates after applying the selected filtering strategy. Of these, 24 had been previously detected by routine callers and were not further analyzed. Among the remaining 65, 13 were considered likely true positives after visual inspection using IGV. Experimental validation was performed by Sanger/Nanopore long-read sequencing for these variants, all of which were confirmed. Eight were classified as (likely) pathogenic, including two frameshift duplications in MSH6, one splicing variant in BARD1, and five mobile element insertions in APC, BRCA2, and PALB2. Altogether, GRIDSS implementation increased diagnostic yield while maintaining feasibility for diagnostic workflows. Comprehensive workflow scheme for germline structural variant detection and results in our diagnostic setting.

Humans↗
PubMed2025

A personalized multi-platform assessment of somatic mosaicism in the human frontal cortex.

Somatic mutations in individual cells create genomic mosaicism, influencing genetic disorders and cancers. While clonal mutations in cancers are well-studied, rarer somatic variants in normal tissues remain poorly characterized. This study systematically evaluates detection methods using a personalized donor-specific assembly (DSA) from a neurotypical individual's dorsolateral prefrontal cortex assessed with Oxford Nanopore, NovaSeq, linked-read sequencing, Cas9-targeted long-read sequencing (TEnCATS), and single-neuron MALBAC amplification. The haplotype-resolved DSA improved cross-platform analysis, dramatically increasing phasing rates. Germline SNVs, structural variations (SVs), and transposable elements (TEs) were recalled with 99.4%-99.7% accuracy in bulk tissue, and phased haplotype analysis reduced false positives by 15.4%-75.1% for putative somatic candidates. Long-read single-neuron sequencing detected nine somatic SV candidates, demonstrating enhanced sensitivity for rare variants, while TEnCATS identified eight low-frequency somatic TE candidates. These findings highlight advanced methodologies for precise somatic variant detection, critical for understanding mosaicism's role in health and disease.

Multi-platform Sequencing↗
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↗
PubMed2025

Detection and characterization of neonatal cytomegalovirus through nanopore sequencing using flongle flow cells: Pilot study in Philadelphia, Pennsylvania.

BACKGROUND: Cytomegalovirus (CMV) remains a significant infection in neonates and its early detection can aid with further treatment (antiviral, audiology). However, current diagnostics do not provide genetic information. OBJECTIVE: We explored the use of the portable and comprehensive sequencing method from Oxford Nanopore Technologies, utilizing low-cost Flongle flow cells to detect and perform sequence-level characterization of neonatal urine samples that tested positive for CMV by PCR. STUDY DESIGN: We performed a pilot study based on a retrospective cohort study of neonates who were positive for CMV by PCR, who were admitted at two birth hospitals in Philadelphia, PA. We leveraged deep and long-read sequencing results to analyze the reads in two forms: by comparing them against a reference-based strain and by reconstructing the genome through de novo assembly with phylogenetic tree analysis. RESULTS: We assayed seven clinical samples, including a positive and negative control sample, from newborns ranging from 23 weeks' gestation to term, with testing performed for microcephaly, hearing test results, small gestational age, and thrombocytopenia. Each sample showed multiple differences compared to the reference strain, and the phylogenetic tree analysis of the de novo assembly depicted the genetic diversity of the samples. CONCLUSION: This pilot study shows that nanopore sequencing with low-cost Flongle flow cells can detect and characterize CMV strains from clinical neonatal urine samples. This, coupled with current screening and diagnostic criteria, could further our genomic understanding of neonatal CMV, such as viral genome diversity, genotype-phenotype associations, and spread of strains.

Humans↗
PubMed2026

Characterisation of Trichuris incognita n sp in Côte d'Ivoire: a morphological, genomic, and genome-wide association with drug sensitivity study.

BACKGROUND: Trichuriasis is a neglected tropical disease that affects up to 500 million individuals and can cause considerable morbidity. For decades, trichuriasis was thought to be caused by one species of whipworm, Trichuris trichiura. The aim of this study was to investigate the origin of differences in response rates to the best available anthelmintic treatment for trichuriasis-a combination of albendazole and ivermectin-in Côte d'Ivoire by analysing the parasite population. METHODS: In this morphological, genomic, and genome-wide association study (GWAS) with drug sensitivity we used long-read and short-read sequencing approaches and assembled a high-quality reference genome of Trichuris incognita n sp isolated in a primary interventional study conducted in the Lagunes district of Côte d'Ivoire. Children aged 6-12 years were screened between July 14, 2022, and July 31, 2022; children positive for T trichiura on duplicate Kato-Katz smears and with infection intensity of 200 eggs per gram or more were eligible and treated first with albendazole (400 mg) and ivermectin (200 μg/kg) then with oxantel pamoate (20 mg/kg). We constructed a species tree of the Trichuris genus using 12 434 orthologous groups. We sequenced individual worms, which were used to confirm the phylogenetic placement and investigate patterns of adaptation through comparative genomic analyses. Finally, we conducted a GWAS to compare albendazole-ivermectin sensitive worms to drug non-sensitive worms. FINDINGS: 670 children were screened, of whom 243 were enrolled and from whom 271 worms were isolated after the first treatment and 827 worms after the second treatment. Sufficient DNA was recovered from 747 worms of which 721 were suitable for further bioinformatic analysis; of these, 179 were albendazole-ivermectin sensitive worms and 542 were drug non-sensitive worms. We present and characterise a new, human-infecting Trichuris species named T incognita n sp, which is morphologically indistinguishable from T trichiura, but forms a distinct phylogenetic clade, closer to Trichuris suis than to the canonical human-infective T trichiura. Comparative genomic analysis of genes suspected to confer resistance to either albendazole or ivermectin in helminths revealed a high number of β-tubulin orthologs, present in the whole population of T incognita n sp, compared with the canonical T trichiura species, but these genes were not associated with a resistant phenotype. The GWAS did not provide conclusive evidence of adaptation to drug pressure within the same species. INTERPRETATION: Our results demonstrate that trichuriasis can be caused by multiple whipworm species, and that differences in response rates might result from species responding differently to drug treatment, rather than from the intraspecies establishment of resistance. This discovery, coupled with the high tolerability of T incognita n sp to albendazole-ivermectin, marks a substantial shift in how we understand and approach whipworm infections. FUNDING: European Research Council.

Trichuris↗
PubMed2025

Evaluation of sequencing reads at scale using rdeval.

MOTIVATION: Large sequencing datasets are being produced and deposited into public archives at unprecedented rates. The availability of tools that can reliably and efficiently generate and store sequencing read summary statistics has become critical. RESULTS: As part of the effort by the Vertebrate Genomes Project (VGP) to generate high-quality reference genomes at scale, we sought to address the community's need for efficient sequence data evaluation by developing rdeval, a standalone tool to quickly compute and interactively display sequencing read metrics. Rdeval can either run on the fly or store key sequence data metrics in tiny read 'snapshot' files. Statistics can then be efficiently recalled from snapshots for additional processing. Rdeval can convert fa*[.gz] files to and from other popular formats including BAM and CRAM for better compression. Overall, while CRAM achieves the best compression, the gain compared to BAM is marginal, and BAM achieves the best compromise between data compression and access speed. Rdeval also generates a detailed visual report with multiple data analytics that can be exported in various formats. We showcase rdeval's functionalities using long-read data from different sequencing platforms and species, including human. For PacBio long-read sequencing, our analysis shows dramatic improvements in both read length and quality over time, as well as the benefit of increased coverage for genome assembly, though the magnitude varies by taxa. AVAILABILITY AND IMPLEMENTATION: Rdeval is implemented in C++ for data processing and in R for data visualization. Precompiled releases (Linux, MacOS, Windows) and commented source code for rdeval are available under MIT license at https://github.com/vgl-hub/rdeval. Documentation is available on ReadTheDocs (https://rdeval-documentation.readthedocs.io). Rdeval is also available in Bioconda and in Galaxy (https://usegalaxy.org). An automated test workflow ensures the consistency of software updates.

Software↗
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

TaxTriage: an open-source metagenomic sequencing data analysis pipeline enabling putative pathogen detection.

MOTIVATION: TaxTriage is a comprehensive pathogen identification workflow designed for both short- and long-read untargeted DNA and RNA sequencing data. Combining read classification, mapping, and de novo assembly approaches, putative pathogens are identified through comparisons to curated pathogens and abundance expectations from healthy cohort data. Flexible installation options are enabled using Nextflow™ (NF), including cloud deployment via NF Tower (Seqera Platform) and local installation on a variety of systems, including standalone installations without external internet access. Final analysis summaries are compiled into an Organism Discovery Report, which lists likely pathogens and supporting data, including a custom confidence score. RESULTS: Evaluation of published in silico, clinical, and outbreak datasets identified performance comparable to alternative cloud-based processing pipelines for expected pathogen and co-infection detection with similar sensitivity and increased specificity. To support both public health and veterinary diagnostics communities, customization options have been incorporated to enable improved performance for host species of interest. AVAILABILITY AND IMPLEMENTATION: Source code for TaxTriage is freely available at https://github.com/jhuapl-bio/taxtriage. TaxTriage v2.1.1 has been archived on Zenodo at https://zenodo.org/records/17081354 to permit reproducible analysis as described in this manuscript.

Software↗
PubMed2026

Long-read, high-coverage reference genome of the nymphalid butterfly Catonephele acontius (Nymphalidae: Biblidinae).

Catonephele acontius (Nymphalidae:Biblidinae:Epicalinii) is a butterfly species with a wide distribution across the Neotropics including the Amazon. Here, we present a long-read high-coverage reference genome for this species to serve as a genomic resource for future studies on Biblidinae butterflies, a group that is the subject of ongoing studies of seasonal adaptation under climate change. We used PacBio HiFi and IsoSeq reads to generate a highly contiguous and well-annotated reference genome. Five libraries were constructed, 4 using RNA from different tissues and 1 using high molecular weight (HMW) DNA from a wild-caught female. The DNA was sequenced using PacBio HiFi technology, and the RNA was sequenced using long read PacBio IsoSeq technology. About 20 Gb of raw HiFi data were generated and assembled to an initial size of 520.7 Mb (39 × homozygous coverage) in 90 contigs. The assembly was then polished and decontaminated into 40 contigs with an N50 of 19.927 Mb (BUSCO completeness: 99.0%; duplication: 0.5%; fragmentation: 0.7%; and missing: 0.3%). Final assembly size was 519.2 Mb. Repeats were annotated, showing that the genome consisted of 40.4% transposable elements. IsoSeq transcriptome data from antennae, leg, ovary, and digestive tissue was then used to structurally and functionally annotate gene models for the softmasked genome, uncovering ∼18,500 genes, with 70% of them given functional annotation. This reference assembly joins many published genomes in the Nymphalidae family but represents one of the first high-quality genomes from the Biblidinae subfamily. It provides a valuable resource to study the evolution of plastic and seasonal traits and will help investigate the genetic processes that may influence these species' responses to rapid climate change.

Animals↗
PubMed2025

Comprehensive benchmarking of somatic structural variant detection at ultra-low allele fractions.

Postzygotic mosaicism gives rise to somatic structural variants (SVs) at ultra-low variant allele fractions (VAFs), which pose challenges for detection due to the high-coverage sequencing required and noise introduced by sequencing artifacts. Although somatic SV detection has been extensively studied in cancer, these studies are not directly applicable to the study of tissue mosaicism, as they rely on matched normals, target higher VAF ranges, and are enriched for different types of SVs. We present comprehensive benchmark data and best practices for non-cancer somatic SV detection. We created a synthetic mosaic sample by combining six HapMap individuals at varying proportions, generating allele fractions as low as 0.25%. This sample was sequenced to ~2,300x total coverage using Illumina, PacBio, and Nanopore technologies across multiple sequencing centers. A high-confidence benchmark SV set containing over 21,000 pseudo-somatic insertions and deletions ≥50bp was derived from haplotype-resolved assemblies. We evaluated 12 SV discovery pipelines and identified caller-specific strengths and sequencing platform-specific shortcomings. We find that short read-based approaches show reduced recall for insertions and repeat-associated SVs, whereas long-read sequencing achieves high accuracy throughout the genome, increasing linearly with coverage. The best algorithm's sensitivity exceeded 80% for VAFs ≥4% and 15% for VAFs of 0.5-1% with 60x coverage. The publicly available benchmarking data and comparative analysis of current methods provide a foundation for robust discovery of SV mosaicism in non-cancer tissues..

Journal Article↗
PubMed2025

Assembling genomes of non-model plants: A case study with evolutionary insights from Ranunculus (Ranunculaceae).

Whereas genome sequencing and assembly technologies are improving, cost can still be prohibitive for plant species with large, complex genomes. As a consequence, genomics work on some taxa in evolutionarily pivotal positions in the vascular plant tree of life has been hampered. The species-rich genus Ranunculus (Ranunculaceae) is an important angiosperm group for the study of polyploidy, apomixis, and reticulate evolution. However, neither mitochondrial nor high-quality nuclear genome sequences are available. This limits phylogenomic, functional, and taxonomic analyses thus far. Here, we tested Illumina short-read, Oxford Nanopore Technology (ONT) and PacBio (HiFi) long-read, and hybrid-read assembly strategies. We sequenced the diploid progenitor species R. cassubicifolius (R. auricomus species complex) and selected the best assemblies in terms of completeness, contiguity, and quality scores. We first assembled the plastome (156 kbp, 85 genes) and mitogenome (1.18 Mbp, 40 genes) sequences using Illumina and Illumina-PacBio-hybrid strategies, respectively. We also present an updated plastome and the first mitogenome phylogeny of Ranunculaceae, including studies of gene loss (e.g., infA, ycf15, or rps) with evolutionary implications. For the nuclear genome sequence, we favored a PacBio-based assembly polished three times with filtered short reads and subsequently scaffolded into eight pseudochromosomes by chromatin conformation data (Hi-C). We obtained a haploid genome sequence of 2.69 Gbp, with 94.1% complete BUSCO genes found and 35 482 annotated genes, and inferred ancient gene duplications compared to existing Ranunculales genomes. The genomic information presented here will enable advanced evolutionary-functional analyses for the species complex, but also for the genus and beyond Ranunculaceae.

Ranunculus↗
PubMed2026

Lineage-associated small inversions disrupt dosT, dnaE2, and a promoter-adjacent region in some Mycobacterium tuberculosis isolates.

UNLABELLED: Large molecular inversions in the genome of Mycobacterium tuberculosis (Mtb) due to factors like the presence of insertion sequences and transposases are widely known. However, smaller inversions within coding sequences and non-coding control elements are rarely reported. The present study aims to identify inversions and their potential impact on Mtb biology in a lineage-specific manner. Structural variants (SVs) could only be detected by long reads. For this, we simulated long reads by de novo assembling the short-read sequencing data sets and subsequently aligned representative strains from each lineage using the Progressive Mauve algorithm. Independently, long-read sequencing from the Pacific Biosciences platform was acquired and analyzed using the structural variant identification method. Variants were merged, and Fisher's exact test was carried out to identify the inversion association with lineages. To visualize deoxyribonucleic acid (DNA) features, the DNA-features-viewer tool was used. Simulated reads from short-read sequencing gave indications of lineage (L)-specific inversions. The long-read sequencing approach led to the identification of seven unique inversions: two positively associated with L1, one positively associated with L3, two negatively associated with L4, and two positively associated with L3 but negatively associated with L4 (P < 0.05). The inversions encompassed primarily non-essential genes like sdaA, dosT, Rv2026c, dnaE2, Rv1341, Rv1342, and lprD. An interesting inversion was observed in the upstream control element of purB and Rv0776c. The study sheds light on small inversions that may be causing alterations in expression, formation of fusion genes, and nonsense mutations that may have a role in lineage-specific phenotypic changes. IMPORTANCE: The role of mutations like SNPs and INDELs and their association with drug resistance is well known in Mycobacterium tuberculosis (Mtb). However, structural variations, especially inversions, are largely overlooked and unreported. In this paper, publicly available whole-genome sequencing datasets from Illumina and Pacific Biosciences-Oxford Nanopore Technologies platform have been used to detect inversions and report seven unreported Mtb lineage-specific small inversions.

Mycobacterium tuberculosis↗
PubMed2026

Haplotype-aware long-read error correction.

Error correction of long reads is an important initial step in genome assembly workflows. For organisms with ploidy greater than one, it is important to preserve haplotype-specific variation during read correction. This challenge has driven the development of several haplotype-aware correction methods. However, existing methods are based on either ad-hoc heuristics or deep learning approaches. In this paper, we introduce a rigorous formulation for this problem. Our approach builds on the minimum error correction framework used in reference-based haplotype phasing. We prove that the proposed formulation for error correction of reads in de novo context, i.e., without using a reference genome, is NP-hard. To make our exact algorithm scale to large datasets, we introduce practical heuristics. Experiments using PacBio HiFi sequencing datasets from human and plant genomes show that our approach achieves accuracy comparable to state-of-the-art methods. Implementation: https://github.com/at-cg/HALE .

Clustering↗