Phytopathology®

Australia is the largest producer of Pyrethrum (Tanacetum cinerariifolium) globally. Amongst the constraints on production are the fungal pathogens Didymella tanaceti and Stagonosporopsis tanaceti, which pose a significant threat to the industry, causing substantial yield losses. While the infection biology of S. tanaceti is well characterised, knowledge of D. tanaceti and its potential interaction with S. tanaceti on plants remains limited, hindering disease management. We developed fluorescently labelled strains of both pathogens via Agrobacterium tumefaciens-mediated transformation (ATMT). Binary vectors carrying the mNeonGreen or tdTomato fluorescent protein genes were introduced into D. tanaceti and S. tanaceti, respectively, and expression of the fluorescent proteins was confirmed by microscopy. Genome sequencing revealed single-copy T-DNA insertions in all transformants, with minor genomic rearrangements at insertion sites. Detached leaf assays demonstrated that transformed strains retained pathogenicity, producing disease symptoms indistinguishable from those of the wild type. These fluorescently labelled variants enabled detailed visualisation of D. tanaceti infection biology and its interactions with S. tanaceti, including co-infection dynamics. Co-infection assays using fluorescent strains further facilitated simultaneous visualisation and differentiation of both pathogens within host tissues. Importantly, these tools also allowed the first description of the early stages of infection by D. tanaceti in pyrethrum leaves. This study represents the first successful transformation of D. tanaceti and S. tanaceti, providing valuable resources to investigate their infection processes.

Beyond the significant impact of Cassava witches broom disease (CWBD), caused by the fungus Rhizoctonia (syn. Ceratobasidium) theobromae on cassava cultivation in French Guiana and Brazil, this disease also poses a potential threat to cacao trees in the region, since the fungus is responsible for Vascular Streak Dieback (VSD) of cacao in South East Asia. Cross-pathogenicity trials were conducted in several cassava fields in French Guiana by planting young cacao plants adjacent to diseased cassava plants. Vascular necrosis was observed in some cacao plants, and the presence of R. theobromae in the cacao tissues was confirmed through PCR diagnostics using primers specific to the fungus. Sequence analysis indicated 100% similarity between samples from both hosts and 97.53 to 99.74% identity with R. theobromae isolates previously reported from cassava in the Americas and Southeast Asia. Additionally, symptomatic cacao in a mixed cacao-cassava farm yielded R. theobromae-positive PCR results, suggesting a natural infection. Ongoing work includes artificial inoculations and controlled cross-pathogenicity trials under screenhouse conditions to attempt reproduction of the symptoms. While current data do not yet establish definitive causality, the findings indicate potential host jump and warrant rapid communication to researchers, policy makers, and farmers to safeguard cacao production and Theobroma biodiversity in the Amazon region.

Phytophthora species are globally significant soilborne oomycetes responsible for widespread ecosystem decline. Standard soil sampling protocols, originally developed for qualitative baiting assays, typically require collecting substantial soil volumes in order to capture viable propagules. While effective for culture-based detection, these protocols are labour-intensive and can damage the shallow root systems of sensitive host species such as New Zealand kauri (Agathis australis). Phytophthora agathidicida (PA), the pathogen associated with kauri dieback disease, is routinely surveyed using these methods. However, quantitative data describing the vertical distribution of PA in natural forest soils are lacking. Consequently, it remains unclear whether extensive depth sampling is necessary to ensure consistent molecular detection. In this study, we applied a quantitative oospore DNA (oDNA) qPCR assay to characterise the fine-scale vertical distribution of PA across four soil depth increments (0-5, 5-10, 10-15, 15-20 cm) from 12 kauri trees representing a range of disease stages. Results revealed distinct vertical stratification, with PA DNA concentrations peaking within the upper 0-10 cm of soil in non-symptomatic and possibly symptomatic trees. In symptomatic trees, the absolute peak occasionally reached 10-15 cm, while pathogen signals remained consistently detectable within the top 10 cm. Field validation from an additional eight trees confirmed that targeted 0-10 cm "shallow" sampling yielded higher PA concentrations than deeper sampling protocols. These findings provide a data-driven basis for refining soil sampling strategies, enabling more sensitive molecular detection while minimising disturbance and logistical effort in fragile ecosystems. IMPORTANCEPhytophthora species are among the most destructive soilborne pathogens globally, requiring robust diagnostic protocols for both agricultural and conservation settings. Traditional sampling frameworks were established to meet the biological requirements of baiting assays, which often necessitate collecting large soil volumes from broad depth profiles to ensure the capture of viable, infectious propagules. However, these extensive requirements are labour-intensive and can cause significant soil disturbance in sensitive forest ecosystems. Using P. agathidicida as a model, this study provides a high-resolution quantitative assessment of how pathogen DNA is distributed vertically across different disease stages. We demonstrate that while absolute peak abundance can shift within the 0-15 cm range as infection progresses, the pathogen signal remains consistently detectable within the top 10 cm. This evidence-based approach suggests that targeted, shallow sampling enhances sensitivity by reducing signal dilution, offering a lower-impact path for monitoring soilborne oomycetes worldwide.

Leaf diseases pose a serious threat to faba bean production. Leaf blotch of faba bean, caused by Alternaria spp., has become increasingly widespread and destructive in several countries. Leaf diseases pose a serious threat to faba bean production. The infection of plant by pathogens can be influenced by various factors associated with the host plant, environmental conditions and presence of other microorganisms. The phyllosphere and endosphere play a critical role in plant health and disease development. This study aimed to evaluate the factors shaping the structure and diversity of fungal communities associated with faba beans. Plant samples were collected in 2004 from two intensively managed faba bean production fields in the central region of Latvia. Fungal assemblages were characterized using an ITS region metabarcoding approach based on Illumina MiSeq sequencing. Among the assigned amplicon sequence variant (AVS), 65% belonged to the phylum Ascomycota, while approximately 4% were classified as Basidiomycota. Alternaria and Cladosporium were the dominant genera across samples. The alfa and beta diversities of fungal communities was higher during flowering of faba beans to compare with ripening. The higher abundance of Basidiomycota yeasts were observed during flowering, in contrast, Cladosporium genus was significantly more abundant during ripening. Alternaria DNA was found on leaves that showed no symptoms of the disease. The diversity and composition of fungal communities were significantly influenced by sampling time and presence of leaf blotch, caused by Alternaria spp.

Potato common scab (Streptomyces sp.) is an economically important disease that reduces the quality and market value of tubers. A key aspect in developing management strategies involves accurately quantifying the disease. Due to the three-dimensional nature of the tuber and the heterogeneous distribution of lesions across its surface, visual estimates of severity can be challenging. Therefore, the objectives of this study were to develop and validate a standard area diagram (SAD) for estimating common scab severity on potato tubers and to compare validation outcomes obtained using real tubers and digital images. A SAD comprising six severity levels (from 1.3 to 66.8%) was developed based on image analysis of naturally infected tubers. Validation was conducted using two complementary approaches in which inexperienced raters evaluated either real potato tubers or digital images of the same tubers under unaided and aided conditions. Accuracy, bias components, and inter-rater reliability were quantified using absolute error metrics, Lins concordance correlation coefficient, intraclass correlation coefficients, and overall concordance correlation coefficients. Use of the SAD significantly improved accuracy, reduced systematic bias, and increased inter-rater reliability across both validation approaches. No significant differences were detected between assessments conducted on real tubers and images, although image-based evaluations showed a slight, non-significant tendency toward reduced scale and location bias under aided conditions. These results demonstrate that a dimension-aware SAD integrating information across the full tuber surface enhances the reliability and reproducibility of visual severity assessments and supports the use of image-based evaluations for training, large-scale surveys, and remote or collaborative applications involving three-dimensional plant organs.

Potato (Solanum tuberosum L.) is a staple crop crucial to global food security, yet its production is severely threatened by late blight (LB), caused by Phytophthora infestans, one of the most destructive plant diseases worldwide. Breeding programs for LB resistance have traditionally relied on labor-intensive and subjective visual assessments, which limit scalability and consistency, particularly in early-generation trials. Unmanned aerial vehicle (UAV)-based remote sensing combined with machine learning (ML) offers a promising alternative for objective, high-throughput disease phenotyping. This study evaluated the potential of UAV-derived multispectral imagery and ML techniques to estimate LB severity across large and genetically diverse potato breeding populations, comprising 2,745 clones in one trial and 492 accessions in another, conducted in Oxapampa, Pasco, Peru. We compared vegetation index-based approaches with a machine learning framework that integrates K-means clustering and Kernel Ridge Regression (KRR) and assessed their ability to capture genotypic variation and support selection decisions. NDVI consistently showed a strong correlation with visually assessed LB severity, particularly at advanced stages of disease development, enabling objective discrimination between healthy and diseased canopy tissues. However, the KRR-based approach outperformed linear NDVI-based models by capturing nonlinear relationships between spectral responses and disease progression. Estimates of LB severity derived from NDVI and KRR models, expressed as best linear unbiased estimates (BLUEs), showed strong and biologically consistent relationships with the area under the disease progress curve (AUDPC), particularly during later UAV acquisitions. Selection coincidence between UAV-derived estimates and AUDPC-based rankings was substantially higher at intermediate to advanced stages of disease progression, suggesting that UAV assessments at these stages may capture sufficient phenotypic variation to distinguish genotypes. These findings indicate that UAV-based multispectral phenotyping, especially when integrated with ML, provides a practical and scalable approach for assessing LB severity in potato breeding programs while reducing the need for time-consuming field evaluations.

BackgroundThe cotton bollworm Helicoverpa armigera is a major global pest controlled by genetically engineered crops expressing Bacillus thuringiensis (Bt) toxins, including Vip3Aa. While Vip3Aa is widely deployed, the genetic basis of resistance remains poorly understood. Previous work identified disruption of a thyroglobulin-like gene (HaVipR1) as one mechanism of resistance, suggesting additional loci may be involved. ResultsUsing linkage analysis, transcriptomics, long-read sequencing, and CRISPR-Cas9 gene editing, we identify a second thyroglobulin-like gene, HaVipR2, as a novel mediator of Vip3Aa resistance. Resistance in a field-derived H. armigera line was shown to be monogenic, recessive, and autosomal, mapping to chromosome 29. Long-read sequencing revealed a [~]16 kb transposable element insertion disrupting HaVipR2, which was undetectable using standard short-read approaches. CRISPR-Cas9 knockout of HaVipR2 conferred >900-fold resistance, confirming its causal role. Comparative analyses show that HaVipR1 and HaVipR2 share conserved domain architecture, indicating that thyroglobulin-domain proteins represent a recurrent target of resistance evolution. ConclusionsOur findings establish thyroglobulin-domain proteins as a new class of Bt resistance genes in Lepidoptera and demonstrate that transposable element insertions can drive adaptive resistance while evading detection by conventional methods. These results highlight the importance of long-read sequencing and accurate genome annotation for resistance monitoring and provide new insights into the molecular basis and evolution of Vip3Aa resistance.

Grapevine Trunk diseases (GTDs) represent a major threat for the wine industry. Despite several break-through, their etiology remains unclear and no curative treatment is currently available. Wood anatomy and water transport contribute to the symptoms of young plant decline. This study investigates wood anatomical alterations in two Alsatian grapevine cultivars presenting different susceptibility to GTDs, focusing on wood structure over six months of vegetative growth and in response to infection. Using a validated FasGa staining protocol, wood sections from transverse, tangential, and radial directions were stained to differentiate lignified and cellulosic tissues. Microscopic analysis was performed at x4, x10, and x40 magnifications, yielding a dataset of 4771 images. To support this high-throughput quantitative analysis of microscopy images, a computational model was developed, enabling reliable and efficient assessment of anatomical traits. Pre-established woody tissues presented higher xylem vessels diameter in Gewurztraminer than Riesling, with a dorsoventral arrangement whereas the number of vessels remained the same all over the cross section. No significant anatomical changes were observed in established woody tissues, whereas newly formed xylem anatomy showed a possible rearrangement during infection, especially in Gewurztraminer cultivar. Furthermore, colorimetric analysis quantified the lignification of woody tissues in response to wounding damage compared to un-treated plants. While definitive conclusions remain limited due to the experimental timeframe and sample variability, the findings highlight the need for longer-term studies and broader cultivar evaluation. Code and microscopy images have been made publicly available, providing a scalable digital tool for future research in plant vascular systems.

RNA viruses are common in tephritid fruit flies including the Queensland fruit fly, Australias most significant horticultural pest. For many their transmission, tissue tropism and load across host development remain unexplored. Yet these factors are important for host biology, ecology and pest management. We investigated Bactrocera tryoni orbivirus (OV), Bactrocera tryoni xinmovirus (XV), Bactrocera tryoni toti-like virus (TLV) and Bactrocera tryoni iflavirus species 2 (IVsp.2) that commonly coinfect B. tryoni laboratory populations. OV and XV transmission was vertical within and on eggs, while TLV transmission was vertical within eggs. IVsp.2 was not detected in eggs but was present in adults; however, IVsp.2 was horizontally transmitted, with viral load increasing with cohabitation time with infected flies. Horizontal transmission was not observed for the other viruses. OV had a similar load across all tissues, while XV was consistently more abundant in ovaries. TLV had a high viral load in the brain whereas IVsp.2 was abundant in the thorax, foregut and midgut. Besides differences in eggs, the viruses were detected in all other developmental stages, but viral load patterns differed: viral load remained constant for TLV, fluctuated for OV and XV, and was low in pre-adult stages and high in adults for IVsp.2. Our findings demonstrate distinct transmission strategies and tissue tropism among the viruses, providing new insights into their epidemiology and role in host biology. Furthermore, contrary to prevailing views that viruses are generally horizontally transmitted, most known RNA viruses of B. tryoni are vertically transmitted affecting the evolution of host-virus interactions.

Botrytis cinerea is a necrotrophic fungal pathogen that infects thousands of plant species. During infection, these diverse plant hosts produce different specialized metabolites that can inhibit pathogen growth and shape pathogen fitness. However, the genetic architecture of pathogen resistance toward individual host defense metabolites remains poorly understood. To address this question, we exposed 83 B. cinerea isolates to the metabolite linalool and quantified metabolic and structural responses. Exposure revealed extensive phenotypic diversity across isolates. Genome-wide association identified 101 genes of interest associated with membrane transport and stress response regulation. Genetic associations were stronger for morphological traits than for metabolic traits, suggesting that hyphal architecture may have a complex genetic architecture contributing to linalool resistance. Together, these results establish natural variation in linalool response and provide candidate loci for understanding how generalist pathogens respond to host-derived chemical defenses. Article SummaryTo understand how a generalist pathogen responds to host defenses, we asked how Botrytis cinerea responds to linalool, a widespread monoterpene involved in plant defense. We exposed 83 B. cinerea isolates to 1000 {micro}M of linalool for 72 hours and quantified metabolic traits (growth curves and growth dynamics over time) and morphological traits (hyphal network features). Using GWA, we linked phenotypic variation to genetic variants. Results indicate substantial natural variation in linalool resistance and distinct genetic architectures across trait classes: metabolic responses are driven by a relatively small number of loci with larger effects, whereas structural/morphological responses appear more polygenic.

Lodging in sorghum presents a significant challenge for plant breeders due to the trade-off between lodging resistance and grain yield. Manually measuring lodging across thousands of plots is time-consuming, expensive, and error-prone, making selection for lodging resistance challenging in breeding programs. Unmanned Aerial Vehicle (UAV) derived metrics offer a potential high-throughput, cost-effective alternative for lodging phenotyping. This study developed a framework for predicting plot-level lodging from UAV imagery across 2,675 sorghum breeding plots. Multi-temporal canopy height data were collected at two critical time points: maximum crop height and at manual lodging assessment. Height percentiles were extracted from UAV derived point clouds generated using photogrammetric algorithms. These data were used to develop parametric, non-parametric, and ensemble prediction models, which were evaluated using three statistical metrics. The ensemble model, averaging predictions from all models, achieved the highest accuracy with Pearson correlations of r = 0.80-0.84 and lowest residual mean square error (RMSE=16-18), explaining 64-70% of variation in manual lodging counts. Model diagnostics and iterative refinement, including inspection of UAV imagery and dataset curation, had minimal impact on model performance, demonstrating the robustness of the approach. Model performance was consistent across sites, with minimal effects of stratified sampling on accuracy, confirming the ensemble approach as optimal for plot-level lodging assessment. This study demonstrates that integrated multi-temporal UAV imagery offers a practical alternative to labor-intensive manual evaluation methods by enabling high-throughput lodging assessment suitable for implementation in sorghum breeding programs.

Grain mold severely constrains sorghum [Sorghum bicolor (L.) Moench] productivity and grain quality in subhumid environments. Photoperiod-sensitive flowering plays a key role in mold avoidance and yield stability along north-south rainfall gradients. In response to the high susceptibility of elite cultivars in subhumid zones of Senegal, we developed and characterized a recombinant inbred line (RIL) population derived from Nganda (grain mold-susceptible) and Grinkan (photoperiod-sensitive) varieties. The population was evaluated across three distinct agro-ecological zones over two years. Environmental indices derived from genotype-environmental interactions, together with defined growth windows, strongly influenced flag leaf appearance (FLA), a photoperiodic flowering trait. Plasticity parameters (intercept and slope) for environmental indices, FLA, grain mold severity, and yield enabled identification of loci contributing to flowering response, mold resistance, and yield stability. The maturity gene Ma1 and two QTLs for FLA, qFLA6.2 and qFLA6.3, were identified, stable across environments, and colocalized with grain mold and yield QTLs. The wild-type Ma1 allele from Grinkan delayed FLA and reduced grain mold damage but was not associated with increased yield. The Ma1 effect was confirmed using the developed breeder-friendly KASP marker, Sbv3.1_06_40312464K, in 174 F3 three-way cross families. Photoperiod-sensitive lines with intermediate-to-late FLA alleles showed strong negative associations with mold damage. Overall, the identified stable loci and candidate lines provide foundations for effective molecular breeding of climate-resilient varieties. PLAIN LANGUAGE SUMMARYGrain mold is a fungal disease that reduces sorghum grain yield and quality, particularly in subhumid climates. With the limited number of resistant elite varieties, photoperiod-sensitive flowering to day length variation can contribute to grain mold escape at the end of rainy seasons. We characterized 286 sorghum recombinant inbred lines across three contrasting environments over two years along rainfall gradients in Senegal. Using flag leaf appearance (FLA), which is a photoperiodic flowering trait, strong genotype-environment interactions for FLA and genotypic plasticity were revealed. We identified and validated the common genomic locus associated with FLA variation and its plasticity across environments, the canonical maturity gene Ma1, which was influenced by temperature variation across environments. The presence of Ma1 in the background of photoperiod-sensitive lines enhances grain mold avoidance and yield stability along rainfall gradients in Senegal. CORE IDEASO_LIWe investigated photoperiodic flowering plasticity in sorghum as a contributor to grain mold resistance and yield stability along rainfall gradients. C_LIO_LIThe Maturity locus Ma1 (qFLA6.1) is the major contributor of photoperiodic flowering and its plasticity across semi-arid and subhumid environments. C_LIO_LIHybrid genotypes carrying two stable loci qFLA6.1 and qFLA6.2 sustain high grain mold avoidance in diverse environments. C_LIO_LIPhotoperiod-sensitive lines with medium to late flowering times are effective in avoiding grain mold, while maintaining yield stability in subhumid regions. C_LI

We present a genome assembly from a specimen of Quercus canariensis (Fagaceae; Fagales; Magnoliopsida). The assembly was generated using PacBio HiFi long reads with an approximate sequencing depth of 39X and scaffolded using a reference-guided approach. The genome sequence has a total length of 816.0 megabases for haplotype 1 and 804.8 megabases for haplotype 2. The two haplotypes are each resolved into 12 chromosomal pseudomolecules, with only 3.48% and 1.36% of sequences remaining unplaced in haplotypes 1 and 2, respectively. Assembly completeness is supported by BUSCO scores of 98.3% and 98.2% complete genes for haplotypes 1 and 2, respectively. Structural annotation identified 51,882 and 46,482 protein-coding genes in haplotypes 1 and 2, respectively. This genome assembly provides the first chromosome-scale reference genome for Q. canariensis, laying the base for future genomic and evolutionary studies in this understudied species of the hybridizing white oak species complex. TaxonomyLineage cellular organisms; Eukaryota; Viridiplantae; Streptophyta; Embryophyta; Tracheophyta; Spermatophyta; Magnoliopsida; eudicotyledons; Gunneridae; Pentapetalae; rosids; fabids; Fagales; Fagaceae; Quercus EBI:txid568684 Quercus canariensis Willd. 1809 (Willdenow)

The plant-beneficial bacterium Pseudomonas protegens CHA0 (CHA0) is widely studied for the biological control of soil-borne plant diseases. Beyond its root-colonising capabilities, CHA0 can also infect and kill insect larvae and thus exhibits a multi-host lifestyle shared with other plant- and insect-colonising bacteria. To better understand the robustness of this multi-host lifestyle, we subjected CHA0 to ten consecutive passages through larvae of the pest insect Plutella xylostella via repeated cycles of insect colonisation and killing forcing it into an insect-only lifestyle. Overall, serial passaging did not result in consistent changes in insect killing speed, larval or root colonisation, plant protection efficiency, microbial antagonism or in vitro growth. This suggests that its multi-host lifestyle was conserved following serial passage. Nonetheless, a few independently passaged lines showed an increase in larval killing speed, which in one case might be linked to choline uptake. To disentangle changes specific to the insect host from those arising due to the experimental system itself, we conducted parallel serial passages through the same system while omitting the insect host. In some of these lines, exposure to the background of the system led to changes in microbial antagonism and in in vitro growth, which likely are associated with mutations in regions encoding for regulatory systems. Our findings indicate that P. protegens CHA0 remains phenotypically stable in complex environments such as an insect host, suggesting that the multi-host lifestyle might also be conserved when applied in the field and supporting CHA0s potential for reliable biocontrol performance against both plant diseases and insect pests. Author summaryControlling insect pests with living organisms, known as biological control, offers an environmentally friendly alternative to chemical pesticides. The plant-beneficial bacterium Pseudomonas protegens CHA0 is a promising biocontrol candidate that not only colonizes plant roots but also infects and kills certain insect larvae. This ability to colonize different hosts appears to be a conserved trait also observed in other bacteria. To better understand the robustness of this multi-host lifestyle, we repeatedly exposed CHA0 to larvae of the insect pest Plutella xylostella and assessed the resulting physiological and genetic changes. Surprisingly, after ten cycles, CHA0 largely retained its insect-killing and plant-protective traits. Although a few populations showed minor changes, including slightly faster insect killing and traits associated with aspects of the experimental system, these changes were limited in scope. Overall, our findings suggest that P. protegens CHA0 does not change rapidly in complex environments such as an insect host, supporting its potential for reliable biocontrol performance in the field.

Improving photosynthesis is a promising approach to enhance sugar beet productivity. However, genetic variation in leaf photosynthesis and its relationship with disease resistance remain underexplored. We evaluated 98 sugar beet genotypes representing different breeding categories, including commercial F1 hybrids, seed-parent lines, and pollinator lines, in Hokkaido, northern Japan. Leaf gas exchange was measured during early growth under field conditions around the infection period of Cercospora leaf spot (CLS). To account for fluctuating irradiance during large-scale phenotyping, we applied a multilevel mixed-effects light-response model to estimate genotype-specific photosynthetic characteristics. Substantial genotypic variations in photosynthetic characteristics were detected. F1 hybrids exhibited higher photosynthetic capacity than breeding lines, whereas differences among breeding categories were unclear due to large within-category variation. Some breeding lines exhibited photosynthetic rates higher than those of hybrids, indicating exploitable genetic resources within the present genetic panel. We did not detect statistically significant trade-off between leaf photosynthesis and CLS resistance among 98 genotypes; in a subset of 19 genotypes analysed in detail, the relationship was even synergistic. Our results highlight the genetic diversity of leaf photosynthesis and its category-dependent structure, and suggest that selection for enhanced photosynthesis can proceed without substantial trade-off with CLS resistance. HighlightLeaf photosynthesis of 98 sugar beet genotypes showed significant genetic variation and dependence on breeding category. Active photosynthesis incurred minimal trade-off with Cercospora leaf spot resistance.

Spinach (Spinacia oleraceae) is a principal vegetable crop commercially grown in Controlled Environment Agriculture (CEA). Recent research suggests that root morphological and architectural differences among crop species influence yield, resource use efficiency, and environmental stress tolerance. These root traits may be exploited to increase yield, promote efficient nutrient use, and mitigate environmental stressors. This study measured differences between various spinach cultivars in CEA systems to reveal morphological and anatomical variation. We grew three spinach cultivars with different reported growing rates ( Income, Darkside, and El-Majestic) under NFT hydroponic and substrate-based systems in a controlled greenhouse environment over 45 days with destructive harvests at days 15, 30, and 45. Supplemental light (250 {micro}mol/m2/s) with 12-hour photoperiod and periodic fertigation was used. Harvests included the collection of leaf and root biomass, and scanning of root systems in WinRhizo software, measuring ten variables. On day 45, root cross-sections from orders 1-5 were embedded in JB-4 resin, sectioned, stained, and analyzed for diameter, vasculature, and rhizodermis characteristics. Results indicate that in spinach, differences in root system morphology are linked to cultivation systems over cultivar identity. Vascular and root anatomical alterations are minor compared to morphological differences in response to the cultivation system. Hydroponic-style growth systems are associated with the proliferation of fine-root ideotypes compared with substrate-based conditions. Such findings affirm previous studies, which suggest plastic root morphology in response to growth systems, and may be used to help create more resilient, resource-efficient cultivars. HighlightsO_LIIn spinach, root system morphology differences are linked to cultivation systems. C_LIO_LIRoot vascular and anatomical alterations are minor in response to cultivation system. C_LIO_LIHydroponic growth systems are linked to fine-root ideotype proliferation in spinach. C_LIO_LIFine-root ideotype proliferation may be a breeding target for CEA spinach. C_LI

The yerba mate psyllid (Gyropsylla spegazziniana) poses a significant threat to yerba mate crops, causing extensive economic losses. While some ecological aspects as well as control strategies have been studied, its associated viral diversity remains unexplored. Here, by generating the first RNA high-throughput analysis (HTS) of this pest, we explored the G. spegazziniana virome, revealing novel and diverse RNA viruses. We characterized five new viral members belonging to distinct families, with evolutionary cues of beny-like viruses (Benyviridae), picorna-like viruses (Picornaviridae), and sobemo-like viruses (Solemoviridae); which were tentatively named Gyropsylla spegazziniana beny-like virus 1 (GSBlV1), Gyropsylla spegazziniana picorna-like virus 1 (GSPlV1), and Gyropsylla spegazziniana sobemo-like virus 1-3 (GSSlV1-3), respectively. Phylogenetic analysis of the bi-segmented and highly divergent sobemo-like viruses showed a distinctive evolutionary trajectory of its encoding proteins at the periphery of recently reported invertebrate Sobelivirales. The beny-like virus belonged to a cluster of insect-associated beny-like viruse; while the picorna-like virus clustered together with psyllid-associated picorna-like viruses. These results highlight the existence of a complex virome within G. spegazziniana and establish the basis for future studies investigating the ecological roles, evolutionary dynamics, and potential biocontrol applications of these viruses in the G. spegazziniana -yerba mate eco-systems.

Field-based monitoring of tree species in forests is often sparse due to logistical constraints. Remote sensing enables repeated, spatially contiguous collection of reflectance data across large areas. Tree species classification accuracy using such data is variable, likely because most studies use observational datasets where species occurrence correlates with environmental variation. We used two sites of a tree biodiversity experiment in Germany (BIOTREE: Kaltenborn and Bechstedt), where different species have been planted with high replication under controlled diversity levels, to assess how well tree species could be classified using reflectance data from airborne imaging spectroscopy and different classification methods (linear discriminant analysis, LDA, and a non-linear support vector machine, SVM). Reflectance data for 589 wavelengths between 400-2400 nm were acquired at 1 m spatial resolution during peak growing season. Reflectance spectra showed large and significant variation between taxonomic classes, orders, and species, and weak, but still significant, interactions between classes or orders and diversity levels. Classification accuracy reached 100% in training datasets, 77%-83% for the four species in Kaltenborn prediction datasets, and 31%-49% for the 16 species in Bechstedt prediction datasets. LDA provided more accurate predictions than SVM; and using similarly-spaced original wavelengths with LDA was as efficient as using principal components derived from the original data. While airborne imaging spectroscopy effectively distinguished up to four tree species in our datasets, classification accuracy was lower in more species-rich plots. In these cases, the methodology may be more useful for functional diversity monitoring than for tree species classification.

Nakaseomyces glabratus is a globally distributed opportunistic fungal pathogen. An ongoing discussion in studies of N. glabratus population structure has been whether genetic clusters are best defined using multilocus sequence typing (MLST) or short-read whole-genome sequencing (WGS). To assess the concordance between MLST- and WGS-based phylogenies, we analyzed a dataset of 548 N. glabratus WGS sequences from 12 countries. Clusters identified from WGS largely recapitulated the MLST-defined sequence type (ST) groups: fourteen WGS clusters were composed of a single MLST ST, and the remaining contained STs with very closely related MLST profiles. We thus propose a pragmatic naming convention, consistent with the system used in other microbial species, which specifies WGS cluster labels based on the primary ST. From the large WGS isolate dataset, we determined the prevalence of admixture and genomic variants. Interestingly, seven of the nine singleton isolates were admixed, in addition to 58 isolates from six different clusters. Aneuploidy was detected in 4% of isolates, most commonly in chrE, which contains ERG11, the gene encoding the enzyme targeted by azole antifungals. Aneuploid chromosomes did not exhibit elevated heterozygosity relative to the sequencing error rate, consistent with instability of extra chromosome copies. Copy number variants were found in 3% of the isolates; some of the CNVs co-occurred with aneuploidies, and were primarily identified on chrD, chrE, chrI, and chrM. Our findings demonstrate that deep splits between clusters preserve the utility of MLST ST designations for clade-level designation, yet underscore the utility of WGS for high-resolution genomic analyses. Article SummaryThere is an ongoing debate in studies on Nakaseomyces glabratus about whether traditional MLST analysis is sufficient to determine population structure, or whether the precision of whole genome sequencing (WGS) is necessary. We analyzed WGS data from 548 isolates from around the world. We found a very strong agreement between the two methods. We propose a hybrid naming system, where cluster names are based on the dominant MLST group. We used the WGS data to show that admixed isolates, and those with extra chromosomes or CNVs are rare (<7% of isolates in each class) and are distributed throughout the phylogeny.

Black spruce (Picea mariana [Mill.] B.S.P.) is an emblematic and ubiquitous species of the North Americas boreal forest. While conifer breeding programs have traditionally focused on growth and wood property traits, the study of climate adaptation traits is becoming increasingly prevalent, given the predicted impact of climate change on North Americas boreal zone. Through this study, we aimed to identify genes associated with climate adaptation in black spruce across Canada. A total of 254 black spruce trees from 30 populations, covering most of the species distribution range, were sampled and genotyped for SNPs located in [~]5000 gene loci. Uni- and multivariate Genotype-Environment Association (GEA) approaches, namely LFMM and RDA, as well as an outlier method based on population differentiation (FST) were used to identify genes significantly associated with climatic factors. As such, a total of 77 genes carrying significant candidate SNPs were identified, among which 14 candidates were corroborated by at least two methods. Many of these gene SNPs were also confirmed at a smaller geographic scale, across west - east partitions corresponding to the two main black spruce historical lineages. Notably, significant gene SNPs were more frequently associated to moisture/aridity factors in the western part of the range, and more to temperature factors in the eastern part. The genes carrying these SNPs were also frequently associated to abiotic and biotic stress response. In the context of rapid climate change in the Canadian boreal forest, the results obtained within the framework of this study should support implementing gene conservation efforts while assisting prediction in black spruce breeding programs, which are instrumental to producing adapted planting stock for the large-scale reforestation efforts conducted annually across the Canadian boreal forest.