Search Results (450)

The white rhinoceros (Ceratotherium simum) offers a unique model for investigating the genomic consequences of extreme demographic bottlenecks. However, the fragmented southern white rhinoceros genome assembly has limited chromosome-scale structural and evolutionary comparisons with the functionally extinct northern subspecies. Here, we report a chromosome-scale genome assembly for the southern white rhinoceros by integrating Oxford Nanopore Technology long-read sequencing, Illumina short-read polishing and high-throughput chromosome conformation capture (Hi-C) scaffolding. The final assembly spans 2.48 Gb and achieves a contig N50 of 42.06 Mb, representing a 452-fold improvement in contiguity over the previous assembly. In total, 2.46 Gb of sequence was anchored to 40 autosomes plus the X and Y chromosomes. Genome annotation identified 1.13 Gb of repetitive elements (45.7% of the assembly), 22,593 protein-coding genes, and 100.68 Mb of segmental duplications. Inspection of the major histocompatibility complex class II gene region further supported the local assembly and annotation reliability, revealing conserved gene composition and order between the southern and northern white rhinoceroses. Whole-genome comparison with the northern white rhinoceros assembly indicated extensive chromosome-scale synteny, along with localized structural variants between the two subspecies, including 111 inversions spanning 33.48 Mb and 497 translocations spanning 36.48 Mb. Furthermore, coalescent demographic reconstruction indicated asynchronous Pleistocene population dynamics for southern and northern white rhinoceroses, reflecting divergent responses to historical climate oscillations. Both subspecies also exhibit lower recent effective population sizes than estimated Pleistocene ancestral levels, underscoring persistent conservation concern. This assembly provides a useful resource for evaluating the genomic consequences of historical bottlenecks, informing future genomic-rescue plans, and strengthening the comparative framework for rhinoceros conservation and evolutionary genomics. Full article

Rapid and accurate diagnosis of infectious diseases in aquaculture is essential for preventing major economic and ecological losses. Traditional culture-based methods focus on isolation of individual pathogens, and often are burdened with extended processing times, particularly during investigations of polymicrobial infections. Application of Oxford Nanopore Technologies (ONT) sequencing offers a rapid, culture-independent workflow for the identification of bacterial and fungal pathogens directly from fish tissues. Swab and organ samples from four cases (1: Salmo spp.; 2: Cyprinus carpio; 3: Salvelinus fontinalis; 4: Heniochus acuminatus) were analyzed using ONT long-read sequencing for metagenomic screening and bioinformatic classification. The results revealed case-, species-, and tissue-specific microbial profiles, with external tissues showing higher microbial diversity and internal organs enriched in pathogenic taxa. Dominant pathogens included Streptococcus iniae, Aeromonas hydrophila, Pseudomonas spp., and Saprolegnia parasitica, alongside opportunistic zoonotic bacteria such as Escherichia coli and Acinetobacter baumannii. We demonstrate the potential for diagnostic application of ONT sequencing in investigations and detection of multi-pathogen infections, including assessments of microbial community structure changes during disease outbreaks in aquatic species. The presented workflow enables rapid, cost-effective, and comprehensive pathogen profiling, supporting early disease surveillance and improved management in aquatic veterinary practice. Full article

Background: The aim of this study was to compare microbial diversity and compositional changes under digestive stress in yogurts produced using different culture strategies in a dynamic in vitro gastrointestinal system. Methods: Yogurts produced with probiotic starter cultures, standard yogurt cultures, and probiotic sachet supplementation were evaluated using a dynamic in vitro gastrointestinal system including mouth, stomach, and small intestinal phases under controlled pH, temperature, and digestion conditions. Microbial diversity and compositional changes before and after the in vitro gastrointestinal simulation were determined using a 16S rRNA amplicon-based Oxford Nanopore sequencing approach, and the resulting data were analyzed using bioinformatics, alpha-diversity, and beta-diversity metrics. Results: Probiotic sachet addition significantly increased microbial species richness, alpha diversity, and community balance compared to starter culture yogurts (Shannon and Inverse Simpson, p < 0.05). In vitro gastrointestinal system led to a reduction to a Firmicutes-dominant core microbiota in all samples; in contrast, beta diversity and PCoA analyses showed that the post-digestive microbial structure of sachet-supplemented yogurts was significantly different (PERMANOVA, p = 0.001). Conclusions: Consequently, it was demonstrated that adding probiotic sachets to yogurt increases the diversity and resilience of beneficial bacteria throughout the digestive tract, making the product a more robust and functional food for health. Full article

Background/Objectives: Age-related macular degeneration (AMD) is a multifactorial retinal disease involving inflammatory, metabolic, and genetic factors. Increasing evidence suggests that the gut microbiome may contribute to systemic pathways involved in retinal homeostasis. This exploratory pilot study investigated gut microbiome alterations in AMD patients and controls using long-read whole-genome sequencing. Methods: Bacterial DNA was extracted from fecal samples and analyzed using Oxford Nanopore sequencing, followed by taxonomic profiling, alpha and beta diversity analyses, and differential abundance testing. Results: AMD patients showed significantly reduced microbial diversity, reflected by lower richness, Shannon and Simpson indices. Species-level beta diversity analyses revealed significant differences in microbial community composition, particularly with Bray-Curtis metrics, alongside increased inter-individual microbial heterogeneity in AMD samples. Differential abundance analyses identified the depletion of several potentially beneficial commensal taxa, including Faecalibacterium prausnitzii and Parabacteriodes distasonis, whereas Staphylococcus aureus was enriched in AMD patients. Comparisons between wet and dry subtypes showed no significant differences in alpha or beta diversity. Conclusions: Overall, the findings support the presence of gut microbial dysbiosis in AMD characterized by reduced diversity, abundance-driven community shifts, and increased microbiome heterogeneity. Given the small cohort size, cross-sectional design and lack of functional analysis, these results should be considered preliminary and hypothesis-generating. Full article

Long-read sequencing technologies provide portable and flexible service, making them attractive for small-scale sequencing studies. However, many existing RNA-sequencing analysis frameworks are designed for transcriptome-wide analyses and require substantial computational resources. Here we present a lightweight and reproducible computational pipeline for targeted long-read transcriptomic profiling using Oxford Nanopore Technologies (ONT) cDNA sequencing data. The pipeline was evaluated using targeted long-read transcriptomic datasets generated from formalin-fixed paraffin-embedded (FFPE) colorectal carcinoma samples previously classified as microsatellite instability—high (MSI-high) by PCR-based testing. Libraries were sequenced on the Oxford Nanopore MinION platform using R10.4.1 flow cells. Application of the workflow enabled rapid quantification of mismatch repair gene expression and detection of immune-related transcripts including CD8A, PDCD1, and HAVCR2 across multiplexed barcode samples. The pipeline performs targeted alignment of long-read sequencing data to a custom transcript reference panel using minimap2, followed by gene-level read counting and normalization using reads-per-million (RPM). Optional modules enable immune marker profiling, detection of reads aligning to multiple genes, exploratory variant analysis, and visualization of expression patterns. By combining simplicity, reproducibility, and minimal computational overhead, the present pipeline provides an accessible framework for targeted transcriptomic analysis of long-read sequencing data. It may facilitate adoption of ONT-based transcriptomic profiling in settings with restricted computational resources. Full article

Sea buckthorn (Hippophae rhamnoides L.) is a valuable plant whose fruits are rich in biologically active compounds. We sequenced the genome of variety Triumf of H. rhamnoides ssp. mongolica Rousi on the Oxford Nanopore Technologies (ONT) platform. With the Hifiasm algorithm optimized for ONT data, we assembled the 1.17-Gb genome into eleven complete chromosomes and one chromosome consisting of two contigs, which were scaffolded (Chr3). Eleven of twelve chromosomes had pronounced telomeric repeats at both ends and were assembled as telomere-to-telomere (T2T), and one chromosome (Chr12) had telomeric repeats only at one end. We also sequenced transcriptomes of thirteen Triumf organs/tissues and performed genome annotation using these and previously obtained RNA-Seq data for this variety. As a result, we predicted 25,915 genes and 30,527 transcripts. Repetitive elements comprised 66.9% of the genome size. The obtained near-T2T annotated genome assembly of H. rhamnoides ssp. mongolica variety Triumf enabled the identification of correct composition and sequences of important gene families in sea buckthorn. We demonstrated this with the FAT, SAD, and FAD gene families involved in fatty acid synthesis. Expression analysis revealed which FAT, SAD, and FAD genes are essential for specific organs/tissues. Thus, the Triumf genome assembly is a crucial tool for basic and applied studies of H. rhamnoides. Full article

Background: Human hospitals and veterinary centres are hotspots for resistant microbes and plasmids, and metagenomic sequencing offers an agnostic insight into microbiomes, resistomes, and mobilomes, informing strategies for reducing AMR spread. Methods: Environmental samples, including wastewater and surface swabs, were taken from a tertiary human hospital ward (36 samples) and a companion animal veterinary hospital (48 samples) in London. Whole DNA was extracted and metagenomic sequencing undertaken using Oxford Nanopore Technologies’ MinION. Data were analyzed for microbiomes, resistomes and mobilomes and compared. Results: Microbial diversity analyses highlight higher richness across human hospital (HH) environmental samples, but more evenness in veterinary hospital (VH) environmental samples. Diversity showed distinct microbial communities in the HH and VH samples. There were significantly more total antimicrobial resistance gene (ARG) types (p < 0.0001) in the environmental HH samples compared with the environmental VH samples. There was a significantly higher mean number of Enterobacteriales plasmid types (p ≤ 0.0001) in the HH samples. There were significantly more total Gram-Positive plasmid types (p ≤ 0.0001) in the VH samples. Discussion: This research highlights the presence of human and animal pathogens, ARGs and mobile genetic elements in clinical environments, underscoring the importance of multisectoral surveillance. Integrating taxonomic, resistome, and mobilome analyses provides a better understanding of the potential for AMR dissemination at the human–animal–environment interface. This provides insights relevant for the development of targeted surveillance and mitigation strategies within a OH framework. Full article

Rooibos (Aspalathus linearis) is one of the few endemic South African plants that has achieved economic importance and international acclaim, mostly as a herbal tea. Plant production, limited to a small mountainous region in South Africa, is at risk as commercial rooibos longevity is in decline, mostly due to low stress tolerance. Transcriptome data can serve to identify molecular markers for improved stress response, which would speed up selection and facilitate the establishment of breeding programmes. Previously, rooibos leaf transcriptomes have been sequenced using Illumina, which yields short reads, hampering correct reassembly of full-length transcripts. Here, we established Oxford Nanopore-based, long-read transcriptome analysis for leaf and root samples from rooibos. We report on potential pitfalls in data pre-processing (PolyA tail trimming and rRNA removal), and compare two assemblers (RATTLE and RNA-Bloom2) and two clustering algorithms (VSEARCH and CD-HIT). The best assembly comprising 169,122 transcripts was generated using RNA-Bloom2 with short-read polishing, followed by CD-HIT clustering. Of the 95,054 predicted proteins, only 67% were also present in the Illumina dataset. The remainder comprised substantially shorter, mostly full-length sequences from a wide range of primary and secondary biosynthesis pathways. Functional annotation indicated that this transcriptome represents a high-quality, comprehensive resource for data mining. In the leaf fraction, comparative transcriptomics identified overexpressed rooibos transcripts potentially involved in photosynthesis, photorespiration and carbon fixation. In the roots, overexpressed transcripts encoded enzymes potentially involved in regulation of root growth and secondary metabolite biosynthesis. These transcripts may represent first targets for molecular marker development. Full article

This study combines Oxford Nanopore (ONT) third-generation sequencing with targeted amino acid metabolomics to elucidate the mechanisms underlying the structural and metabolic responses of the microbial community in Golden Ear Mushroom (Naematelia sinensis) during Trichoderma infection. By comparing healthy tissue (MOCK), adjacent healthy areas (HAF) and the core lesion area (DiR), the results indicate that pathogen infection significantly reduces bacterial community diversity, with a progressive decline observed across these regions. In the DiR region, the fungal community underwent significant restructuring, with the abundance of the Trichoderma genus (T. lixii and T. afroharzianum) rising to over 45%, whilst that of host symbiotic fungi (Stereum and Tremella) decreased by 50–60%. Metabolomic analysis indicated that levels of various amino acids and antioxidant-related metabolites were significantly reduced in the host tissue of the DiR region, suggesting that amino acid metabolism was inhibited. Concurrently, changes were observed in certain metabolites associated with nitrogen metabolism (e.g., L-glutamine). KEGG analysis further revealed that amino acid biosynthesis and D-amino acid metabolic pathways were inhibited, whilst ABC transporters and arginine/proline metabolic pathways were activated. All metabolic changes originated from the host fungal tissue itself, rather than from commensal microorganisms. In summary, Trichoderma may promote the infection process by disrupting the host microbial community and metabolic networks, providing a theoretical basis for understanding the mechanisms of fungal diseases and their control. Full article

Bovine mastitis remains a major impediment to optimal dairy production. Somatic cell count (SCC) is commonly used as an indicator of mammary gland inflammation, while milk microbiota may also reflect mastitis-related changes. Here, we employed Oxford Nanopore full-length transcript sequencing to delineate the peripheral blood transcriptomic landscape of Xinjiang Brown cattle stratified by high (SCC ≥ 1,000,000 cells mL⁻¹) and low (SCC ≤ 200,000 cells mL⁻¹) SCCs, with the objective of identifying candidate genes underpinning mastitis resistance. We identified 226 differentially expressed genes and 441 differentially expressed transcripts. Genes in the high-SCC group were prominently enriched in immune response pathways and chemokine signalling cascades. Protein–protein interaction network analysis further delineated a core module of ten immune-related genes, including CCL4, IL1B and CXCL2. Integrative analysis with complementary second-generation sequencing data pinpointed CXCL2 as a high-priority candidate. Subsequent RT–qPCR and enzyme-linked immunosorbent assay (ELISA) validation revealed that CXCL2 expression was significantly elevated both in high-SCC individuals and in an LPS-induced bovine mammary epithelial cell inflammation model. Collectively, these findings establish CXCL2 as a putative molecular marker for mastitis resistance breeding and provide a foundational resource for deciphering the molecular mechanisms governing mammary health. Full article

Background: The litchi fruit borer, Conopomorpha sinensis (Lepidoptera: Gracillariidae), is a devastating pest affecting litchi and longan production across Asia. Although a reference mitochondrial genome (mitogenome) has been published, its utility is limited by the lack of precise geographical data and raw sequencing data. Methods: In this study, we sequenced and characterized the complete mitogenome of C. sinensis collected from Taiwan using a hybrid assembly of Illumina and Oxford Nanopore technologies. Results: The assembled mitogenome is 17,301 bp in length with a mean sequencing depth of 19,155-fold, comprising 13 protein-coding genes (PCGs), 22 transfer RNA genes, two ribosomal RNA genes, and an AT-rich control region. Notably, we identified a rare tRNA gene rearrangement (trnR-trnA-trnN-trnS1-trnE-trnF) that deviates from the ancestral lepidopteran ditrysian pattern. Comparative analysis revealed a 94.65% overall sequence identity with the reference mitogenome, though the PCGs remained highly conserved at 99.35%. Variant analysis demonstrated that this divergence is predominantly driven by structural variations (228 indels) rather than nucleotide substitutions (2 SNPs) across the entire mitogenome; furthermore, 94.7% of the indels were identified in the control region and intergenic spacers. Subtle differences in codon usage were also observed in the ND6 start codon (ATT vs. ATA) and COX1 stop codon (TAA vs. T). Phylogenetic and molecular clock analyses robustly clustered the Taiwan specimen within the C. sinensis clade. Molecular dating estimates that the Conopomorpha lineage originated during the Late Cretaceous (~77.23 Ma). Notably, the divergence between the Taiwan specimen and the reference lineage was estimated to be negligible (<0.01 Ma) within the protein-coding regions, demonstrating a high degree of purifying selection that maintains coding-sequence stability across geographically distinct specimens, even as substantial variation accumulates in non-coding genomic regions. Conclusions: These findings provide high-resolution genomic resources and a temporal framework for the evolutionary study of Gracillariidae, offering foundational tools for targeted pest management. Full article

Studying soil microbiomes is challenging because soil contains thousands of microbial species at vastly different abundances. The choice of sequencing method has a strong effect on which of these species are detected and how the community is described. Three approaches now dominate soil microbiome research: short-read 16S rRNA amplicon sequencing on Illumina platforms, full-length 16S sequencing on Oxford Nanopore Technologies (ONT) platforms (particularly the R10.4.1 flow cell), and long-read shotgun metagenomics. Each has distinct biases that shape the recovered community, yet researchers routinely select a method based on cost, understanding, or local expertise rather than on a clear knowledge of what each approach methodically over- or under-represents. Here, we review head-to-head benchmarking studies that have applied two or more of these methods to the same soil or directly comparable samples. We show that while long-read and short-read 16S approaches generally converge on dominant taxa and on between-sample differences, they disagree substantially on alpha diversity estimates, rare taxon detection, and the relative abundances of entire phyla. The R10.4.1 flow cell chemistry has narrowed but not eliminated the accuracy gap with Illumina, and shotgun metagenomics reveals systematic biases in both short and long-read assembly that depend on population diversity within the sample. We synthesise this evidence into an evidence-based decision framework tied to specific research questions and recognise the gaps in soil-specific benchmarking that limit current methods. Rather than asking which platform is “best,” we argue that method choice should be framed as an important part of study design, with the biases of the chosen method acknowledged and, where possible, controlled for. Full article

Methylomics has emerged as a central framework for understanding gene regulation in development and disease, yet the rapid expansion of profiling technologies, computational integration methods, and clinical applications has outpaced comprehensive synthesis. This review addresses that gap by systematically examining current advances across the full methylomics pipeline, from data generation to clinical translation. We draw on evidence from large-scale consortium datasets and benchmarking studies of multi-omics integration methods including MOFA, DIABLO, and deep learning architectures, single-cell and spatial methylomic technologies, long-read sequencing platforms (Oxford Nanopore, PacBio HiFi), and cell-free DNA (cfDNA) liquid biopsy approaches. The review further surveys methylation dysregulation across major disease domains, including cancer, cardiovascular disease, neurological disorders, and autoimmune conditions. Integrating methylomic data with transcriptomic and chromatin accessibility layers, particularly in spatial and single-cell contexts, substantially improves the resolution of disease-associated regulatory mechanisms. cfDNA methylation profiling emerges as a cross-disease, non-invasive monitoring platform with broad diagnostic potential, supported by machine learning-based deconvolution. We conclude that while technological barriers are diminishing, standardization of analytical workflows, population diversity in reference datasets, and regulatory alignment remain the principal challenges for translating methylomics advances into broadly accessible precision medicine. Full article