Inner Workings: Portable DNA sequencer helps farmers stymie devastating viruses

Hybrid RNA sequencing of broad bean wilt virus 2 from faba beans

IMPORTANCE

Globally, viral diseases impair the growth and vigor of cultivated crops such as grains, leading to a significant reduction in quality, marketability, and competitiveness. As an island nation, Australia has a distinct advantage in using its border to prevent the introduction of damaging viruses, which threaten the continental agricultural sector. However, breeding programs in Australia rely on imported seeds as new sources of genetic diversity. As such, it is critical to remain vigilant in identifying new and emerging viral pathogens, by ensuring the availability of accurate genomic diagnostic tools at the grain biosecurity border. High-throughput sequencing offers game-changing opportunities in biosecurity routine testing. Genomic results are more accurate and informative compared to traditional molecular methods or biological indexing. The present work contributes to strengthening accurate phytosanitary screening, to safeguard the Australian grains industry, and expedite germplasm release to the end users.

Applications of long-read sequencing to Mendelian genetics

Advances in clinical genetic testing, including the introduction of exome sequencing, have uncovered the molecular etiology for many rare and previously unsolved genetic disorders, yet more than half of individuals with a suspected genetic disorder remain unsolved after complete clinical evaluation. A precise genetic diagnosis may guide clinical treatment plans, allow families to make informed care decisions, and permit individuals to participate in N-of-1 trials; thus, there is high interest in developing new tools and techniques to increase the solve rate. Long-read sequencing (LRS) is a promising technology for both increasing the solve rate and decreasing the amount of time required to make a precise genetic diagnosis. Here, we summarize current LRS technologies, give examples of how they have been used to evaluate complex genetic variation and identify missing variants, and discuss future clinical applications of LRS. As costs continue to decrease, LRS will find additional utility in the clinical space fundamentally changing how pathological variants are discovered and eventually acting as a single-data source that can be interrogated multiple times for clinical service.

New insights from short and long reads sequencing to explore cytochrome b variants in Plasmopara viticola populations collected from vineyards and related to resistance to complex III inhibitors

Downy mildew is caused by Plasmopara viticola, an obligate oomycete plant pathogen, a devasting disease of grapevine. To protect plants from the disease, complex III inhibitors are among the fungicides widely used. They specifically target the mitochondrial cytochrome b (cytb) of the pathogen to block cellular respiration mechanisms. In the French vineyard, P. viticola has developed resistance against a first group of these fungicides, the Quinone outside Inhibitors (QoI), with a single amino acid substitution G143A in its cytb mitochondrial sequence. The use of QoI was limited and another type of fungicide, the Quinone inside Inhibitors, targeting the same gene and highly effective against oomycetes, was used instead. Recently however, less sensitive P. viticola populations were detected after treatments with some inhibitors, in particular ametoctradin and cyazofamid. By isolating single-sporangia P. viticola strains resistant to these fungicides, we characterized new variants in the cytb sequences associated with cyazofamid resistance: a point mutation (L201S) and more strikingly, two insertions (E203-DE-V204, E203-VE-V204). In parallel with the classical tools, pyrosequencing and qPCR, we then benchmarked short and long-reads NGS technologies (Ion Torrent, Illumina, Oxford Nanopore Technologies) to sequence the complete cytb with a view to detecting and assessing the proportion of resistant variants of P. viticola at the scale of a field population. Eighteen populations collected from French vineyard fields in 2020 were analysed: 12 showed a variable proportion of G143A, 11 of E203-DE-V204 and 7 populations of the S34L variant that confers resistance to ametoctradin. Interestingly, the long reads were able to identify variants, including SNPs, with confidence and to detect a small proportion of P. viticola with multiple variants along the same cytb sequence. Overall, NGS appears to be a promising method for assessing fungicide resistance of pathogens linked to cytb modifications at the field population level. This approach could rapidly become a robust decision support tool for resistance management in the future.

Identification of an emerging cucumber virus in Taiwan using Oxford nanopore sequencing technology

BACKGROUND

In June 2020, severe symptoms of leaf mosaic and fruit malformation were observed on greenhouse-grown cucumber plants in Xizhou Township of Changhua County, Taiwan. An unknown virus, designated CX-2, was isolated from a diseased cucumber sample by single lesion isolation on Chenopodium quinoa leaves. Identification of CX-2 was performed. Moreover, the incidence of cucumber viruses in Taiwan was also investigated.

METHODS

Transmission electron microscopy was performed to examine virion morphology. The portable MinION sequencer released by Oxford Nanopore Technologies was used to detect viral sequences in dsRNA of CX-2-infected leaf tissue. The whole genome sequence of CX-2 was completed by Sanger sequencing and analyzed. Reverse transcription-polymerase chain reaction (RT-PCR) with species-specific primers and indirect enzyme-linked immunosorbent assay (ELISA) with anti-coat protein antisera were developed for virus detection in the field [see Additional file 1].

RESULTS

Icosahedral particles about 30 nm in diameter were observed in the crud leaf sap of CX-2-infected C. quinoa plant. The complete genome sequence of CX-2 was determined as 4577 nt long and shared 97.0-97.2% of nucleotide identity with that of two cucumber Bulgarian latent virus (CBLV) isolates in Iran and Bulgaria. Therefore, CX-2 was renamed CBLV-TW. In 2020-2022 field surveys, melon yellow spot virus (MYSV) had the highest detection rate of 74.7%, followed by cucurbit chlorotic yellows virus (CCYV) (32.0%), papaya ringspot virus virus watermelon type (PRSV-W) (10.7%), squash leaf curl Philippines virus (SLCuPV) (9.3%), CBLV (8.0%) and watermelon silver mottle virus (WSMoV) (4.0%). Co-infection of CBLV and MYSV could be detected in field cucumbers.

CONCLUSION

The emerging CBLV-TW was identified by nanopore sequencing. Whole genome sequence analysis revealed that CBLV-TW is closely related, but phylogenetically distinct, to two known CBLV isolates in Bulgaria and Iran. Detection methods including RT-PCR and indirect ELISA have been developed to detect CBLV and to investigate cucumber viruses in central Taiwan. The 2020-2022 field survey results showed that MYSV and CCYV were the main threats to cucumbers, with CBLV, SLCuPV and WSMoV were occasionally occurring.

Whole blood gene expression within days after total-body irradiation predicts long term survival in Gottingen minipigs

Gottingen minipigs mirror the physiological radiation response observed in humans and hence make an ideal candidate model for studying radiation biodosimetry for both limited-sized and mass casualty incidents. We examined the whole blood gene expression profiles starting one day after total-body irradiation with increasing doses of gamma-rays. The minipigs were monitored for up to 45 days or time to euthanasia necessitated by radiation effects. We successfully identified dose- and time-agnostic (over a 1-7 day period after radiation), survival-predictive gene expression signatures derived using machine-learning algorithms with high sensitivity and specificity. These survival-predictive signatures fare better than an optimally performing dose-differentiating signature or blood cellular profiles. These findings suggest that prediction of survival is a much more useful parameter for making triage, resource-utilization and treatment decisions in a resource-constrained environment compared to predictions of total dose received. It should hopefully be possible to build such classifiers for humans in the future.

Isoform Age - Splice Isoform Profiling Using Long-Read Technologies

Alternative splicing (AS) of RNA is a key mechanism that results in the expression of multiple transcript isoforms from single genes and leads to an increase in the complexity of both the transcriptome and proteome. Regulation of AS is critical for the correct functioning of many biological pathways, while disruption of AS can be directly pathogenic in diseases such as cancer or cause risk for complex disorders. Current short-read sequencing technologies achieve high read depth but are limited in their ability to resolve complex isoforms. In this review we examine how long-read sequencing (LRS) technologies can address this challenge by covering the entire RNA sequence in a single read and thereby distinguish isoform changes that could impact RNA regulation or protein function. Coupling LRS with technologies such as single cell sequencing, targeted sequencing and spatial transcriptomics is producing a rapidly expanding suite of technological approaches to profile alternative splicing at the isoform level with unprecedented detail. In addition, integrating LRS with genotype now allows the impact of genetic variation on isoform expression to be determined. Recent results demonstrate the potential of these techniques to elucidate the landscape of splicing, including in tissues such as the brain where AS is particularly prevalent. Finally, we also discuss how AS can impact protein function, potentially leading to novel therapeutic targets for a range of diseases.

The Future of Livestock Management: A Review of Real-Time Portable Sequencing Applied to Livestock

Oxford Nanopore Technologies' MinION has proven to be a valuable tool within human and microbial genetics. Its capacity to produce long reads in real time has opened up unique applications for portable sequencing. Examples include tracking the recent African swine fever outbreak in China and providing a diagnostic tool for disease in the cassava plant in Eastern Africa. Here we review the current applications of Oxford Nanopore sequencing in livestock, then focus on proposed applications in livestock agriculture for rapid diagnostics, base modification detection, reference genome assembly and genomic prediction. In particular, we propose a future application: 'crush-side genotyping' for real-time on-farm genotyping for extensive industries such as northern Australian beef production. An initial in silico experiment to assess the feasibility of crush-side genotyping demonstrated promising results. SNPs were called from simulated Nanopore data, that included the relatively high base call error rate that is characteristic of the data, and calling parameters were varied to understand the feasibility of SNP calling at low coverages in a heterozygous population. With optimised genotype calling parameters, over 85% of the 10,000 simulated SNPs were able to be correctly called with coverages as low as 6×. These results provide preliminary evidence that Oxford Nanopore sequencing has potential to be used for real-time SNP genotyping in extensive livestock operations.

Integrating independent microbial studies to build predictive models of anaerobic digestion inhibition by ammonia and phenol

Anaerobic digestion (AD) is a process that can efficiently degrade organic waste into renewable energies. AD failure is however common as the underpinning microbial mechanisms are highly vulnerable to a wide range of inhibitory compounds. Sequencing technologies enable the identification of microbial indicators of digesters inhibition, but existing studies are limited. They used different inocula, substrates, sites and types of reactors and reported different or contradictory indicators. Our aim was to identify a robust signature of microbial indicators of phenol and ammonia inhibitions across four independent AD microbial studies. To identify such signature, we applied an original multivariate integrative method on two in-house studies, then validated our approach by predicting the inhibitory status of samples from two other studies with more than 90% accuracy. Our approach shows how we can efficiently leverage on existing studies to extract reproducible microbial community patterns and predict AD inhibition to improve AD microbial management.

Characterization of Potato Virus Y Isolates and Assessment of Nanopore Sequencing to Detect and Genotype Potato Viruses

Potato virus Y (PVY) is the most economically important virus infecting cultivated potato (Solanum tuberosum L.). Accurate diagnosis is crucial to regulate the trade of tubers and for the sanitary selection of plant material for propagation. However, high genetic diversity of PVY represents a challenge for the detection and classification of isolates. Here, the diversity of Irish PVY isolates from a germplasm collection and commercial sites was investigated using conventional molecular and serological techniques. Recombinant PVY isolates were prevalent, with PVYNTNa being the predominant genotype. In addition, we evaluated Nanopore sequencing to detect and reconstruct the whole genome sequence of four viruses (PVY, PVX, PVS, PLRV) and five PVY genotypes in a subset of eight potato plants. De novo assembly of Nanopore sequencing reads produced single contigs covering greater than 90% of the viral genome and sharing greater than 99.5% identity to the consensus sequences obtained with Illumina sequencing. Interestingly, single near full genome contigs were obtained for different isolates of PVY co-infecting the same plant. Mapping reads to available reference viral genomes enabled us to generate near complete genome sequences sharing greater than 99.90% identity to the Illumina-derived consensus. This is the first report describing the use of Oxford Nanopore's MinION to detect and genotype potato viruses. We reconstructed the genome of PVY and other RNA viruses; indicating the technologies potential for virus detection in potato production systems, and for the study of genetic diversity of highly heterogeneous viruses such as PVY.

Molecular Approaches for Low-Cost Point-of-Care Pathogen Detection in Agriculture and Forestry

Early detection of plant diseases is a crucial factor to prevent or limit the spread of a rising infection that could cause significant economic loss. Detection test on plant diseases in the laboratory can be laborious, time consuming, expensive, and normally requires specific technical expertise. Moreover, in the developing countries, it is often difficult to find laboratories equipped for this kind of analysis. Therefore, in the past years, a high effort has been made for the development of fast, specific, sensitive, and cost-effective tests that can be successfully used in plant pathology directly in the field by low-specialized personnel using minimal equipment. Nucleic acid-based methods have proven to be a good choice for the development of detection tools in several fields, such as human/animal health, food safety, and water analysis, and their application in plant pathogen detection is becoming more and more common. In the present review, the more recent nucleic acid-based protocols for point-of-care (POC) plant pathogen detection and identification are described and analyzed. All these methods have a high potential for early detection of destructive diseases in agriculture and forestry, they should help make molecular detection for plant pathogens accessible to anyone, anywhere, and at any time. We do not suggest that on-site methods should replace lab testing completely, which remains crucial for more complex researches, such as identification and classification of new pathogens or the study of plant defense mechanisms. Instead, POC analysis can provide a useful, fast, and efficient preliminary on-site screening that is crucial in the struggle against plant pathogens.

Detection of Plant Viruses and Disease Management: Relevance of Genetic Diversity and Evolution

Plant viruses cause considerable economic losses and are a threat for sustainable agriculture. The frequent emergence of new viral diseases is mainly due to international trade, climate change, and the ability of viruses for rapid evolution. Disease control is based on two strategies: i) immunization (genetic resistance obtained by plant breeding, plant transformation, cross-protection, or others), and ii) prophylaxis to restrain virus dispersion (using quarantine, certification, removal of infected plants, control of natural vectors, or other procedures). Disease management relies strongly on a fast and accurate identification of the causal agent. For known viruses, diagnosis consists in assigning a virus infecting a plant sample to a group of viruses sharing common characteristics, which is usually referred to as species. However, the specificity of diagnosis can also reach higher taxonomic levels, as genus or family, or lower levels, as strain or variant. Diagnostic procedures must be optimized for accuracy by detecting the maximum number of members within the group (sensitivity as the true positive rate) and distinguishing them from outgroup viruses (specificity as the true negative rate). This requires information on the genetic relationships within-group and with members of other groups. The influence of the genetic diversity of virus populations in diagnosis and disease management is well documented, but information on how to integrate the genetic diversity in the detection methods is still scarce. Here we review the techniques used for plant virus diagnosis and disease control, including characteristics such as accuracy, detection level, multiplexing, quantification, portability, and designability. The effect of genetic diversity and evolution of plant viruses in the design and performance of some detection and disease control techniques are also discussed. High-throughput or next-generation sequencing provides broad-spectrum and accurate identification of viruses enabling multiplex detection, quantification, and the discovery of new viruses. Likely, this technique will be the future standard in diagnostics as its cost will be dropping and becoming more affordable.

Genomic biosurveillance of forest invasive alien enemies: A story written in code

The world's forests face unprecedented threats from invasive insects and pathogens that can cause large irreversible damage to the ecosystems. This threatens the world's capacity to provide long-term fiber supply and ecosystem services that range from carbon storage, nutrient cycling, and water and air purification, to soil preservation and maintenance of wildlife habitat. Reducing the threat of forest invasive alien species requires vigilant biosurveillance, the process of gathering, integrating, interpreting, and communicating essential information about pest and pathogen threats to achieve early detection and warning and to enable better decision-making. This process is challenging due to the diversity of invasive pests and pathogens that need to be identified, the diverse pathways of introduction, and the difficulty in assessing the risk of establishment. Genomics can provide powerful new solutions to biosurveillance. The process of invasion is a story written in four chapters: transport, introduction, establishment, and spread. The series of processes that lead to a successful invasion can leave behind a DNA signature that tells the story of an invasion. This signature can help us understand the dynamic, multistep process of invasion and inform management of current and future introductions. This review describes current and future application of genomic tools and pipelines that will provide accurate identification of pests and pathogens, assign outbreak or survey samples to putative sources to identify pathways of spread, and assess risk based on traits that impact the outbreak outcome.