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At least 19 recordsLinked to original sources
PubMed2026

From complexity to clarity: Building dashboards for hit selection in high throughput screens.

High throughput screening produces large, complex datasets that are difficult to interrogate without programming expertise, making hit selection time-consuming and inflexible. While instrument software and commercial tools offer partial solutions, they often lack adaptability or require costly infrastructure. Interactive dashboards provide an effective alternative by enabling dynamic filtering and integrated visualization within a single interface. Here, we present simple R Markdown-based templates for creating customizable, modular dashboards for screen data analysis. Built using the flexdashboard and crosstalk R packages, and HTML widgets, these lightweight, easy-to-build HTML dashboards require no complex installation process or installation of licensed software. They support linked visualizations, threshold-based filtering (e.g., Z-score, p-value, fold change), and interactive data exploration and are shared as a standalone HTML file. This framework enables rapid, flexible hit selection across diverse high throughput screening applications and is designed for users with basic R experience.

High-Throughput Screening Assays↗
PubMed2024

High-Throughput and High-Sensitivity Biomarker Monitoring in Body Fluid by Fast LC SureQuant IS-Targeted Quantitation.

Targeted proteomics methods have been greatly improved and refined over the last decade and are becoming increasingly the method of choice in protein and peptide quantitative assays. Despite the tremendous progress, targeted proteomics assays still suffer from inadequate sensitivity for lower abundant proteins and throughput, especially in complex biological samples. These attributes are essential for establishing targeted proteomics methods at the forefront of clinical use. Here, we report an assay utilizing the SureQuant internal standard-triggered targeted method on a latest generation mass spectrometer coupled with an EvoSep One liquid chromatography platform, which displays high sensitivity and a high throughput of 100 samples per day. We demonstrate the robustness of this method by quantifying proteins spanning six orders of magnitude in human wound fluid exudates, a biological fluid that exhibits sample complexity and composition similar to plasma. Among the targets quantified were low-abundance proteins such at tumor necrosis factor A and interleukin 1-β, highlighting the value of this method in the quantification of trace amounts of invaluable biomarkers that were until recently hardly accessible by targeted proteomics methods. Taken together, this method extends the toolkit of targeted proteomics assays and will help to drive forward mass spectrometry-based proteomics biomarker quantification.

Humans↗
PubMed2025

SetBERT: the deep learning platform for contextualized embeddings and explainable predictions from high-throughput sequencing.

MOTIVATION: High-throughput sequencing (HTS) is a modern sequencing technology used to profile microbiomes by sequencing thousands of short genomic fragments from the microorganisms within a given sample. This technology presents a unique opportunity for artificial intelligence to comprehend the underlying functional relationships of microbial communities. However, due to the unstructured nature of HTS data, nearly all computational models are limited to processing DNA sequences individually. This limitation causes them to miss out on key interactions between microorganisms, significantly hindering our understanding of how these interactions influence the microbial communities as a whole. Furthermore, most computational methods rely on post-processing of samples which could inadvertently introduce unintentional protocol-specific bias. RESULTS: Addressing these concerns, we present SetBERT, a robust pre-training methodology for creating generalized deep learning models for processing HTS data to produce contextualized embeddings and be fine-tuned for downstream tasks with explainable predictions. By leveraging sequence interactions, we show that SetBERT significantly outperforms other models in taxonomic classification with genus-level classification accuracy of 95%. Furthermore, we demonstrate that SetBERT is able to accurately explain its predictions autonomously by confirming the biological-relevance of taxa identified by the model. AVAILABILITY AND IMPLEMENTATION: All source code is available at https://github.com/DLii-Research/setbert. SetBERT may be used through the q2-deepdna QIIME 2 plugin whose source code is available at https://github.com/DLii-Research/q2-deepdna.

Deep Learning↗
PubMed2025

Order among chaos: High throughput MYCroplanters can distinguish interacting drivers of host infection in a highly stochastic system.

The likelihood that a host will be susceptible to infection is influenced by the interaction of diverse biotic and abiotic factors. As a result, substantial experimental replication and scalability are required to identify the contributions of and interactions between the host, the environment, and biotic factors such as the microbiome. For example, pathogen infection success is known to vary by host genotype, bacterial strain identity and dose, and pathogen dose. Elucidating the interactions between these factors in vivo has been challenging because testing combinations of these variables quickly becomes experimentally intractable. Here, we describe a novel high throughput plant growth system (MYCroplanters) to test how multiple host, non-pathogenic bacteria, and pathogen variables predict host health. Using an Arabidopsis-Pseudomonas host-microbe model, we found that host genotype and bacterial strain order of arrival predict host susceptibility to infection, but pathogen and non-pathogenic bacterial dose can overwhelm these effects. Host susceptibility to infection is therefore driven by complex interactions between multiple factors that can both mask and compensate for each other. However, regardless of host or inoculation conditions, the ratio of pathogen to non-pathogen emerged as a consistent correlate of disease. Our results demonstrate that high-throughput tools like MYCroplanters can isolate interacting drivers of host susceptibility to disease. Increasing the scale at which we can screen drivers of disease, such as microbiome community structure, will facilitate both disease predictions and treatments for medicine and agricultural applications.

Arabidopsis↗
PubMed2026

Barcoded mutant library enables high-throughput functional genomics in a filamentous fungus.

Advances in sequencing technology enabling rapid and inexpensive whole-genome sequencing highlight how few genes are functionally characterized. This problem is particularly acute in filamentous fungi, where even in the best studied organisms upward of half of genes are poorly characterized or unannotated. High-throughput tools to identify gene function exist for single-celled organisms, like yeast and bacteria. However, filamentous fungi present challenges to high-throughput gene characterization, including low transformation efficiency and multinucleate cells. Filamentous fungi are critical components of nutrient cycling in ecosystems, form symbioses with plants that improve nutrient uptake, and are devastating human, plant, and animal pathogens causing millions of deaths and substantial crop loss each year. Thus, it is critical to overcome challenges to rapid gene characterization in filamentous fungi. We generated a library of hundreds of millions of uniquely barcoded plasmids containing a broad host-range drug resistance marker for ectopic insertion into filamentous fungal genomes by Agrobacterium tumefaciens. We then optimized A. tumefaciens mediated transformation of the biocontrol agent Trichoderma atroviride and made an insertional mutagenesis library containing 83,311 barcoded insertions, disrupting 5,331 of 11,863 predicted genes. This library enables high-throughput screens to rapidly connect genotype to phenotype. Quantifying relative barcode abundance in the pooled library before and after exposure to experimental conditions identified candidate genes and recovered known pathway components in amino acid biosynthetic, fructose utilization, and xylose utilization pathways. This resource establishes a scalable platform for high-throughput functional genomics in filamentous fungi, enabling investigations of fungal biology to improve medical outcomes, biotechnology, and sustainable agriculture.

Genomics↗
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↗
PubMed2025

Enzymes in high-throughput RNA sequencing: Applications and challenges.

High-throughput RNA sequencing provides genome-wide information on the dynamics of RNA in each cell and how the dynamics responds to environmental changes. Next-generation sequencing by the Illumina platform currently provides the highest information output as compared to other platforms. A key component of next generation sequencing of each RNA is the successful end-to-end reverse-transcription into a cDNA strand. This can be highly challenging given the propensity of each RNA to adopt ordered structures and to contain post-transcriptional modifications. While many reverse transcriptase (RT) enzymes have been developed over the years to maximize read-through of an RNA, their processivity and efficiency varies, raising the question of how to select the RT for the experiment at hand. Here, we use tRNA as a model for genome-wide sequencing, as tRNA has a stable secondary and tertiary structure and has a high density and wide variety of post-transcriptional modifications, presenting one of the most challenging problems of sequencing RNA. We compare the efficiency of end-to-end cDNA synthesis of tRNA among several recent RT enzymes and provide a general sequencing workflow that is applicable to most of these enzymes.

High-Throughput Nucleotide Sequencing↗
PubMed2026

CoSAG-nf: A Scalable Nextflow Pipeline for Co-assembly, Optimization, and Interactive Visualization of High-Throughput Single-Cell Genomes.

MOTIVATION: Single-cell amplified genomes (SAGs) are crucial for resolving intra-population microbial heterogeneity and accurately understanding the metabolic potential of microbial dark matter populations. However, SAGs generated through multiple displacement amplification (MDA) of genomic DNA from single cells with single-copy chromosomes are highly fragmented and prone to contamination, severely hindering high-quality genome reconstruction and functional analysis, which greatly limits their scientific utility. Co-assembly of related SAGs can substantially improve genome quality, but to our knowledge no automated pipeline exists for high-throughput processing, forcing manual implementation of complex workflows that scale poorly to modern dataset sizes. RESULTS: We present CoSAG-nf, an automated high-throughput co-assembly and optimization pipeline for SAGs, implemented following the nf-core framework standards. The pipeline performs alignment-free clustering using sourmash MinHash signatures, then employs iterative tetranucleotide frequency profiling to identify and exclude outlier SAGs from co-assembly groups. CheckM2 quality assessment guides dynamic selection of optimal SAG combinations to optimize genome completeness and minimize contamination. Fully containerized, CoSAG-nf ensures reproducibility and scalability for the high-throughput processing of large-scale SAG datasets across diverse computing environments, including HPC and cloud platforms. The pipeline generates comprehensive HTML reports with quality metrics and taxonomic annotations, providing an end-to-end solution for automated high-throughput single-cell genome reconstruction. AVAILABILITY: CoSAG-nf is freely available under the MIT License at: https://github.com/linfengxu/CoSAG-nf. Archival code repository snapshots are published at zenodo with doi: https://doi.org/10.5281/zenodo.21525244. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Journal Article↗
PubMedDate not supplied

High-throughput DNA preparation system.

A system demonstrating the feasibility of high-throughput, centrifugation-based DNA separations and purifications has been constructed and tested. Samples are currently processed at a rate of 96 in approximately 2-3 h. The device implements an automation-optimized alkaline lysis protocol for the rapid extraction of plasmid or cosmid DNA from 1-ml bacteria cultures. The conditions for optimal culturing in deep-well (96 x 1 ml) microwell plates have been developed, and all sample manipulations are done within these plates. The use of microwell plates was essential to obtain high throughput and make manipulations following the DNA preparation (prep) easier because they can then be manipulated using a variety of commercially available robots. The entire prep system is constructed above a Beckman GPR centrifuge and operated under Macintosh IIcx control. This device has systems for fluid handling, microwell-plate manipulations, and centrifuge rotor alignment.

Automation↗
PubMed1990

Cyclic AMP response to recombinant human relaxin by cultured human endometrial cells--a specific and high throughput in vitro bioassay.

A specific and high throughput 96-well format bioassay for recombinant human relaxin (rhRLX) has been developed using human endometrial cells (NHE cells). rhRLX caused a time- and dose-dependent stimulation of cyclic AMP (cAMP) with 1/2 maximal activity of 3.56 +/- 0.65 ng/ml (n = 30). The range of the standard curve was 0.39 to 25 ng/ml with interplate precision of 17 and 22% CV for high and low controls respectively. The cAMP response requires forskolin and 3-isobutyl-1-methylxanthine, and is enhanced by prostaglandin E2 and F2 alpha. The NHE cells do not respond to A or B chains of rhRLX, or a whole array of hormones. Preincubation of rhRLX with specific monoclonal antibody completely abolished the cAMP response. This bioassay has been used to determine the biological activity of several manufactured lots of recombinant human relaxin.

1-Methyl-3-isobutylxanthine↗
PubMed2026

Herd-level heterogeneity of antimicrobial resistance in commensal Escherichia coli: A nationwide high-throughput survey of Australian pig herds.

Antimicrobial resistance in commensal Escherichia coli provides a useful indicator for overall antimicrobial resistance burden. We applied this approach to assess antimicrobial resistance within and between commercial pig herds across Australia. A high-throughput robotic workflow was used to isolate 2730 E. coli colonies from rectal contents collected in 2022 from healthy slaughter pigs (n = 300) representing 30 herds (∼70% of national production). Up to 94 isolates per herd underwent antimicrobial susceptibility testing using the Robotic Antimicrobial Susceptibility Platform. Isolate- and herd-level antimicrobial resistance indices were calculated, weighting antimicrobials by their human health importance. Resistance to first-line agents was widespread: ampicillin 77% and tetracycline 79%. By contrast, resistance to critically important antimicrobials was rare (ciprofloxacin 0.11%; extended-spectrum cephalosporins 0.04%), and no clinical resistance to carbapenems or colistin was detected. Overall, 56.9% of isolates were multi-class resistant. Herd-level antimicrobial resistance within indices ranged from 1.51 to 5.76, revealing substantial between-herd heterogeneity. Three herds carried critically important antimicrobials-resistant isolates that would likely have been missed using conventional, lower-density sampling approaches. Whole-genome sequencing identified fluoroquinolone-resistant isolates belonging to ST10 and ST69 (both qnrS1), and ST744 (Quinolone Resistance Determining Region mutations plus blaCTX-M-27). By testing approximately tenfold more isolates than conventional surveys, we uncovered considerable antimicrobial resistance with heterogeneity within and between animals and herds, including farm-specific variability. This expanded sampling also enabled detection of critically important antimicrobial resistance at very low prevalence. In conclusion, high-throughput, high-density testing offers a practical early-warning system and herd-level benchmark to inform surveillance and targeted interventions.

Animals↗
PubMed2026

Microdroplet-based high-throughput screening for antagonistic bacteria targeting penaeid shrimp pathogenic Vibrio harveyi.

Antagonistic bacteria that suppress the growth of specific bacteria have attracted attention as an antibiotics-independent strategy for infectious disease control in aquaculture. Microfluidics-based water-in-oil droplets (microdroplets) enable high-throughput screening of antagonistic bacteria in the field of medicine or agriculture. However, the use of this screening system in aquaculture has not yet been reported. In particular, penaeid shrimp aquaculture, one of the largest sectors of global aquaculture, has a strong demand for alternative disease control strategies because vaccination is ineffective. Here, we demonstrated a proof-of-concept study of microdroplet-based high-throughput screening system for antagonistic bacteria targeting penaeid shrimp pathogenic Vibrio harveyi. Using this screening system, we successfully isolated 18 bacterial candidates with potential growth-inhibitory activity, representing three genera (Pseudoalteromonas, Shewanella, and Tenacibaculum), from the bacterial community of kuruma shrimp Penaeus japonicus rearing water. 16S rRNA gene-based bacterial community analysis revealed that these isolates included several low-abundance, rare taxa. Although these isolates showed no inhibitory activity on agar plates, one out of four tested strains showed a trend toward improved survival during co-infection tests using kuruma shrimp. Overall, our study highlights both the potential and limitation of microdroplet-based antagonistic bacterial screening to accelerate the development of biological control strategies in shrimp aquaculture.

Animals↗
PubMed2026

A Rapid Poly(ethylene glycol)-Assisted Magnetic Isolation Approach for High-Throughput Extracellular Vesicle Isolation and Subsequent Biomarker Analysis.

Extracellular vesicles (EVs) are crucial mediators of intercellular communication and have the potential to serve as biomarkers for disease diagnosis and therapeutic monitoring. However, most EV isolation methods often require large sample volumes and specialized instruments or involve trade-offs between purity, yield, cost, and scalability. We developed MagPEG, a workflow that combines poly(ethylene glycol) (PEG)-mediated EV aggregation with magnetic beads to provide a simple, reproducible alternative to ultracentrifugation, size-exclusion chromatography, and commercial precipitation kits. Our optimization experiments clarified the PEG concentration, ionic strength, and bead surface chemistry that collectively influence EV aggregation, capture efficiency, and contaminant coprecipitation, allowing us to define conditions that improve purity while maintaining high recovery. Compared with commonly used methods, MagPEG produced EVs with comparable size distribution, EV markers, and proteomic profiles while relying only on standard laboratory supplies. A key feature of the platform is that EVs and EV-associated DNA, RNA, and proteins can be sequentially extracted from the same bead-bound material, reducing sample loss and hands-on time and enabling multiomic analysis for limited clinical or small animal samples. MagPEG is compatible with downstream applications including proteomics, bead-based assays, and miRNA quantification. When applied to human serum, the method supported high-throughput EV proteomic profiling and enabled the identification of Alzheimer's disease-associated protein signatures, illustrating its utility for biomarker discovery. Overall, our results establish MagPEG as a powerful, rapid, scalable, and high-throughput solution for translational applications in biomarker discovery.

Polyethylene Glycols↗
PubMed2026

ClearDepthIAS enables automated high-throughput quantification of roots in soil-grown taproot crops.

Understanding root system architecture is critical for improving crop productivity and resilience, yet phenotyping root traits such as root growth angle and rooting depth remains technically challenging, especially at high throughput. Here, we present ClearDepthIAS, a high-throughput imaging and analysis platform that enables nondestructive, automated quantification of root architecture traits in taproot system crops. By capturing and stitching 360° images of roots growing along the transparent walls of pots and applying deep learning-based segmentation (ClearDepth-WRT), we measured wall root shallowness (WRS)-a proxy for root growth angle-with high precision. We demonstrated for the tap root systems of soybean and canola that the system accurately detects root tips, quantifies their vertical distribution, and extracts biologically meaningful traits such as root area, distribution indices, and growth angles. Validation experiments in canola and soybean demonstrated that WRS can correlate with root crown architecture in mature plants, both in greenhouse and field settings. Furthermore, WRS and root distribution indices derived from ClearDepthIAS are predictors of early root architecture and can be correlated with root biomass distribution across soil depths under field conditions; however, environmental interactions may influence these relationships and weaken or even negate such correlations, as observed when comparing field to field variation in root system architecture. Our system enables efficient phenotyping of genetically diverse populations, with medium to high trait heritability, supporting its utility for genome-wide association studies and breeding. ClearDepthIAS accelerates the development of root ideotypes for improved resource acquisition and carbon sequestration, offering a scalable tool for supporting climate-resilient agriculture.

Plant Roots↗
PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗
PubMed2024

High-throughput DNA extraction and cost-effective miniaturized metagenome and amplicon library preparation of soil samples for DNA sequencing.

Reductions in sequencing costs have enabled widespread use of shotgun metagenomics and amplicon sequencing, which have drastically improved our understanding of the microbial world. However, large sequencing projects are now hampered by the cost of library preparation and low sample throughput, comparatively to the actual sequencing costs. Here, we benchmarked three high-throughput DNA extraction methods: ZymoBIOMICS™ 96 MagBead DNA Kit, MP BiomedicalsTM FastDNATM-96 Soil Microbe DNA Kit, and DNeasy® 96 PowerSoil® Pro QIAcube® HT Kit. The DNA extractions were evaluated based on length, quality, quantity, and the observed microbial community across five diverse soil types. DNA extraction of all soil types was successful for all kits, however DNeasy® 96 PowerSoil® Pro QIAcube® HT Kit excelled across all performance parameters. We further used the nanoliter dispensing system I.DOT One to miniaturize Illumina amplicon and metagenomic library preparation volumes by a factor of 5 and 10, respectively, with no significant impact on the observed microbial communities. With these protocols, DNA extraction, metagenomic, or amplicon library preparation for one 96-well plate are approx. 3, 5, and 6 hours, respectively. Furthermore, the miniaturization of amplicon and metagenome library preparation reduces the chemical and plastic costs from 5.0 to 3.6 and 59 to 7.3 USD pr. sample. This enhanced efficiency and cost-effectiveness will enable researchers to undertake studies with greater sample sizes and diversity, thereby providing a richer, more detailed view of microbial communities and their dynamics.

Metagenome↗
PubMed2025

High throughput screening of eukaryotic release factor 1 variants to enhance noncanonical amino acid incorporation.

Noncanonical amino acids (ncAAs) enable diversification of protein functions, but the efficiency of genetic code expansion (GCE) in eukaryotes is hindered by competition between suppressor tRNAs and release factors. Prior work has identified eukaryotic release factor 1 (eRF1) mutants that improve ncAA incorporation, suggesting that screens for improved variants may lead to further enhancements. Here, we developed a high-throughput system to screen eRF1 mutants in Saccharomyces cerevisiae where eRF1 mutants are coexpressed on a plasmid alongside genomically encoded, wild-type eRF1. This strategy enabled recovery of live cells expressing eRF1 variants that enhance ncAA incorporation, even with mutants known to severely affect cell viability in the absence of WT eRF1 expression. We prepared and screened a million-member library of randomly mutated eRF1 variants for clones exhibiting improved ncAA integration phenotypes. Deep sequencing revealed a diverse set of enriched mutations across all three major domains of eRF1. Interestingly, several enriched mutations identified here are also found in naturally occurring eRF1 homologs from species that recode canonical stop codons. When eRF1 variants were combined with yeast knockout strains also known to enhance ncAA incorporation, this resulted in further improvements to efficiency, highlighting the complementarity of release factor engineering to other GCE enhancement strategies. This work demonstrates that high-throughput engineering of the eukaryotic translational apparatus is a powerful approach to identify previously unknown solutions for enhancing ncAA incorporation, with implications for elucidating and precisely manipulating the molecular functions of essential translational machinery.

Noncanonical amino acids↗
PubMed2025

Characterization of Novel Luteoviruses in Canadian Highbush Blueberries Using High-Throughput Sequencing.

The Fraser Valley of British Columbia, Canada is among the top ten blueberry producing regions globally. Viral diseases are established in the region and significantly reduce average yields. While testing for two viruses is routine, characterization of all the viruses present in the region is incomplete. We used high-throughput sequencing to obtain an unbiased overview of RNA viruses present in 97 plants collected across the region. In addition to known viruses, we identified four luteoviruses previously unidentified in the region. Two of them matched the blueberry virus L (BlVL) and blueberry virus M (BlVM). recently found in the USA, while the third constitutes a new major variant of BlVM (BlVM-2), and the fourth a new luteovirus, which we named blueberry virus N (BlVN). The genome sequences were ~5 kbp long and contained four open-reading frames similar to other luteoviruses. PCR screening revealed that these luteoviruses are widespread in the region, and that plants typically harbour more than one of these luteoviruses. While luteoviruses are typically vectored by aphids, they were also present in nursery stock, indicating that spread also occurs via vegetative propagation.

High-Throughput Nucleotide Sequencing↗