All‐in‐one Xylella detection and identification: A nanopore sequencing‐compatible conventional PCR

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All-in-one Xylella detection and identification: A nanopore sequencing-compatible conventional PCR

A new diagnostic PCR assay assesed with an Interlaboratory Test Performance Study (TPS) by five plant pathology laboratories that can accurately detect and differentiate all species and subspecies in Xylella genus.


Abstract

Xylella fastidiosa is a plant-pathogenic bacterium that poses a serious threat to the production of economically important plant species including grapes, almonds, olives and a broad range of amenity plants, causing significant economic losses worldwide. While multiple molecular detection assays have been developed for X. fastidiosa, there is a lack of molecular tools available for detection and differentiation of the closely related pear pathogen, Xylella taiwanensis. In this study, we present a novel conventional PCR assay with primers that can amplify both Xylella species. The amplified product could be sequenced and used for discrimination between the two species and the subspecies within the fastidiosa species. This PCR assay was designed using a genome-informed approach to target the ComEC/Rec2 gene of both Xylella species, ensuring a higher specificity than other previously developed PCR assays. A test performance study across five national plant diagnostic laboratories in Australia and New Zealand demonstrated this assay's high sensitivity and specificity to all known species and subspecies within the Xylella genus. This PCR assay can be used for Xylella identification at the species and subspecies level and is compatible with Sanger sequencing and nanopore sequencing for rapid turnaround time. The newly developed conventional PCR assay presented here offers rapid detection and accurate identification of both Xylella species from plant, insect vector or bacterial samples, enabling timely implementation of biosecurity measures or disease management responses.

Inheritance and genetic mapping of the first CPMMV tolerance locus in common bean

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Inheritance and genetic mapping of the first CPMMV tolerance locus in common bean

A QTL locus for CPMMV tolerance in common bean cv. BRS Sublime was mapped to the terminal region on chromosome Pv08, linked to the SNP_Ch_8_62396711 marker. Two LRR genes and one protein kinase were located within the confidence interval.


Abstract

Although cowpea mild mottle virus (CPMMV) has been reported in Brazil since 1983, it has only become a significant concern for researchers and farmers in recent years. The objective of this work was to investigate the genetic basis of CPMMV tolerance, mapping and reporting the first loci associated with this trait in common bean (cv. BRS Sublime). Phenotypic assays were carried out on 180 individual plants (F2 generation) and 180 F2:3 progenies comprising 12 plants per family and their parents (BRS Sublime, tolerant parent × CNFCT 16207, susceptible parent). CPMMV was mechanically inoculated and symptoms were evaluated at 35 days after inoculation, using a 1–5 scoring scale. A linkage map was constructed using 1695 single-nucleotide polymorphism (SNP) and SilicoDArT markers that segregated in the F2 and F2:3 generations as expected. Markers were distributed across 11 common bean chromosomes, resulting in a total length of 2864 cM, with an average distance between markers of 1.8 cM. Phenotypic observations revealed that tolerance in cv. BRS Sublime is controlled by a single dominant gene. The main effect quantitative trait locus (QTL; CPMMV.Pv08) associated with CPMMV tolerance was identified in the terminal region on chromosome 8 (Pv08). This QTL explained approximately 77% of phenotypic variation, indicating that the inheritance of tolerance to CPMMV is monogenic, controlled by a major locus. As far as we know, this study represents the first investigation into the inheritance and genetic mapping of CPMMV tolerance in common bean, with potential for the development of elite lines with multiple virus resistance/tolerance.

Landscape‐scale patterns and predictors of potato viruses in Scotland

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Landscape-scale patterns and predictors of potato viruses in Scotland

ArcGIS and machine learning are used to provide a comprehensive overview of potato viruses in Scotland, a deeper understanding of landscape epidemiology, and a model that could serve as the basis of a decision support tool.


Abstract

Virus diseases represent important economic threats to seed potato production worldwide, yet relatively little is known of their epidemiology at the landscape-scale. In this study, data was compiled from the Scottish national seed potato classification scheme on the incidence of 10 different potato viruses for the years 2009–2022. A co-occurrence analysis identified that 12 virus species pairs occurred together more often than expected by chance, and potato blackleg was positively associated with eight potato viruses. ArcGIS was used to investigate spatial and spatiotemporal variation in incidence rates of the three most prevalent viruses (potato virus Y, potato leaf roll virus and potato virus A), and this revealed prominent geographic differences in long-term disease outcomes. Focusing on potato virus Y as the most commonly occurring single infection, interpretable machine-learning techniques were used to investigate the influence of key crop, management and environmental factors on patterns of incidence in space and time. The results showed that health characteristics of seed stocks were among the most important predictors of incidence, along with blackleg infection, several management features, cultivar resistance, distance to the nearest seed and ware crop, temperature variables and several soil features. This approach provides a comprehensive overview of potato viruses in Scotland, a deeper understanding of epidemiological risk factors at the landscape-scale and a forecast model that could serve as the basis of a decision support tool for improved management of potato virus Y.

Genome assembly and multi‐omic analyses reveal the mechanisms underlying flower color formation in Torenia fournieri

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Abstract

Torenia fournieri Lind. is an ornamental plant that is popular for its numerous flowers and variety of colors. However, its genomic evolutionary history and the genetic and metabolic bases of flower color formation remain poorly understood. Here, we report the first T. fournieri reference genome, which was resolved to the chromosome scale and was 164.4 Mb in size. Phylogenetic analyses clarified relationships with other plant species, and a comparative genomic analysis indicated that the shared ancestor of T. fournieri and Antirrhinum majus underwent a whole genome duplication event. Joint transcriptomic and metabolomic analyses identified many metabolites related to pelargonidin, peonidin, and naringenin production in rose (TfR)-colored flowers. Samples with blue (TfB) and deep blue (TfD) colors contained numerous derivatives of petunidin, cyanidin, quercetin, and malvidin; differences in the abundances of these metabolites and expression levels of the associated genes were hypothesized to be responsible for variety-specific differences in flower color. Furthermore, the genes encoding flavonoid 3-hydroxylase, anthocyanin synthase, and anthocyanin reductase were differentially expressed between flowers of different colors. Overall, we successfully identified key genes and metabolites involved in T. fournieri flower color formation. The data provided by the chromosome-scale genome assembly establish a basis for understanding the differentiation of this species and will facilitate future genetic studies and genomic-assisted breeding.

Genome‐wide scanning to identify and validate single nucleotide polymorphism markers associated with drought tolerance in spring wheat seedlings

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Abstract

Unlike other growth stages of wheat, very few studies on drought tolerance have been done at the seedling stage, and this is due to the complexity and sensitivity of this stage to drought stress resulting from climate change. As a result, the drought tolerance of wheat seedlings is poorly understood and very few genes associated with drought tolerance at this stage were identified. To address this challenge, a set of 172 spring wheat genotypes representing 20 different countries was evaluated under drought stress at the seedling stage. Drought stress was applied on all tested genotypes by water withholding for 13 days. Two types of traits, namely morphological and physiological traits were scored on the leaves of all tested genotypes. Genome-wide association study (GWAS) is one of the effective genetic analysis methods that was used to identify target single nucleotide polymorphism (SNP) markers and candidate genes for later use in marker-assisted selection. The tested plant materials were genotyped using 25k Infinium iSelect array (25K) (herein after it will be identified as 25K) (for 172 genotypes) and genotyping-by-sequencing (GBS) (for 103 genotypes), respectively. The results of genotyping revealed 21,093 25K and 11,362 GBS-SNPs, which were used to perform GWAS analysis for all scored traits. The results of GWAS revealed that 131 and 55 significant SNPs were controlling morphological and physiological traits, respectively. Moreover, a total of eight and seven SNP markers were found to be associated with more than one morphological and physiological trait under drought stress, respectively. Remarkably, 10 significant SNPs found in this study were previously reported for their association with drought tolerance in wheat. Out of the 10 validated SNP markers, four SNPs were associated with drought at the seedling stage, while the remaining six SNPs were associated with drought stress at the reproductive stage. Moreover, the results of gene enrichment revealed 18 and six pathways as highly significant biological and molecular pathways, respectively. The selection based on drought-tolerant alleles revealed 15 genotypes with the highest number of different drought-tolerant alleles. These genotypes can be used as candidate parents in future breeding programs to produce highly drought-tolerant genotypes with high genetic diversity. Our findings in this study provide novel markers and useful information on the genetic basis of drought tolerance at early growth stages.

Experimental warming has limited impacts on post‐fire succession across a burn severity gradient

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Experimental warming has limited impacts on post-fire succession across a burn severity gradient

Open-top warming chambers were installed across a burn severity gradient within nine months of a mixed-severity fire in order to assess the combined effects of burn severity, time since fire, and experimental warming on plant community recovery. Composition differed significantly according to burn severity, time since fire, and their interaction, while experimental warming did not significantly influence composition. Species richness significantly increased in burned areas compared to unburned control within two years of fire.


Abstract

Questions

Anthropogenic climate change is causing increases in the severity of wildland fire in many parts of the world. At the same time, post-fire succession is occurring under new, warmer temperatures that are projected to continue increasing. Despite this, the combined effects of uncharacteristically high burn severity and increased ambient temperature on post-fire community composition remain poorly understood. We ask how post-fire forest understorey community composition and species richness are influenced by (1) burn severity, (2) experimental warming, and (3) years since fire.

Location

Museum Fire Scar, Pinus ponderosa forest, Arizona, United States.

Methods

We established 120 1-m2 quadrats in unburned, low- and high-severity locations nine months after a mixed-severity fire. Half of the plots were subject to experimental warming via open-top warming chambers that elevated daytime temperatures by 1.079°C, simulating near-term anthropogenic warming. Plant composition data were collected annually for three years. Relationships between community composition, burn severity, and experimental warming were analyzed using repeated-measures PERMANOVA and linear mixed-effects models.

Results

Composition differed significantly according to burn severity, time since fire, and their interaction, while experimental warming did not significantly influence composition. Species richness significantly increased in burned areas compared to unburned control within two years of fire.

Conclusions

Our results suggest that near-term temperature increases, driven by anthropogenic climate change, will have little effect on community composition relative to fire severity. High-severity fire drove large, rapid changes in plant composition compared to unburned controls, favoring exotic annuals in a historically perennial-dominated plant community.