Harnessing landrace diversity empowers wheat breeding.

Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A.E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, through whole-genome re-sequencing (827 Watkins landraces and 208 modern cultivars) and in-depth field evaluation spanning a decade. We discovered that modern cultivars are derived from just two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium (LD) based haplotypes and association genetics analyses link Watkins genomes to the thousands of high-resolution quantitative trait loci (QTL), and significant marker-trait associations identified. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritised QTL in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilising genetic diversity in crop improvement to achieve sustainable food security.

The genotype of barley cultivars influences multiple aspects of their associated microbiota via differential root exudate secretion.

Plant-associated microbes play vital roles in promoting plant growth and health, with plants secreting root exudates into the rhizosphere to attract beneficial microbes. Exudate composition defines the nature of microbial recruitment, with different plant species attracting distinct microbiota to enable optimal adaptation to the soil environment. To more closely examine the relationship between plant genotype and microbial recruitment, we analysed the rhizosphere microbiomes of landrace (Chevallier) and modern (NFC Tipple) barley (Hordeum vulgare) cultivars. Distinct differences were observed between the plant-associated microbiomes of the 2 cultivars, with the plant-growth promoting rhizobacterial genus Pseudomonas substantially more abundant in the Tipple rhizosphere. Striking differences were also observed between the phenotypes of recruited Pseudomonas populations, alongside distinct genotypic clustering by cultivar. Cultivar-driven Pseudomonas selection was driven by root exudate composition, with the greater abundance of hexose sugars secreted from Tipple roots attracting microbes better adapted to growth on these metabolites and vice versa. Cultivar-driven selection also operates at the molecular level, with both gene expression and the abundance of ecologically relevant loci differing between Tipple and Chevallier Pseudomonas isolates. Finally, cultivar-driven selection is important for plant health, with both cultivars showing a distinct preference for microbes selected by their genetic siblings in rhizosphere transplantation assays.

Lung Cancer Screening Among U.S. Military Veterans by Health Status and Race and Ethnicity, 2017-2020: A Cross-Sectional Population-Based Study.

Introduction: Veterans are at high risk for lung cancer and are an important group for lung cancer screening. Previous research suggests that lung cancer screening may not be reaching healthier and/or non-White individuals, who stand to benefit most from lung cancer screening. We sought to test whether lung cancer screening is associated with poor health and/or race and ethnicity among veterans. Methods: This cross-sectional, population-based study included veterans eligible for lung cancer screening (aged 55-79 years, ≥30 pack-year smoking history, current smokers or quit within 15 years, no previous lung cancer) in the 2017-2020 Behavioral Risk Factor Surveillance System surveys. Exposures were (1) poor health, defined as fair/poor health status and difficulty walking or climbing stairs, aligning with eligibility criteria for a pivotal lung cancer screening trial, and (2) race/ethnicity. The outcome was a receipt of lung cancer screening. All variables were self-reported. Results: Of 3,376 lung cancer screening-eligible veterans representing an underlying population of 866,000 individuals, 20.3% (95% CI=17.3, 23.6) had poor health, and 13.7% (95% CI=10.6, 17.5) identified as non-White. Poor health was strongly associated with lung cancer screening (adjusted RR=1.64, 95% CI=1.06, 2.27); one third of veterans screened for lung cancer would not qualify for a pivotal lung cancer screening trial in terms of health. Marked racial disparities were observed among veterans: after adjustment, non-White veterans were 67% less likely to report lung cancer screening than White veterans (adjusted RR=0.33, 95% CI=0.11, 0.66). Conclusions: Lung cancer screening is correlated with poorer health and White race/ethnicity among veterans, which may undermine its population-level effectiveness. These results highlight the need to promote lung cancer screening, especially for healthier and/or non-White veterans, an important group of Americans for lung cancer screening.

National Survey of Lung Cancer Screening Practices in Veterans Health Administration Facilities.

INTRODUCTION: Lung cancer screening can save lives through the early detection of lung cancer, and professional societies recommend key lung cancer screening program components to ensure high-quality screening. Yet, little is known about the key components that comprise the various screening program models in routine clinical settings. The objective was to compare the utilization of these key components across centralized, hybrid, and decentralized lung cancer screening programs. METHODS: The survey was designed to identify current structures and processes of lung cancer screening programs. It was administered electronically to Veterans Health Administration facilities nationally (N=122) between August and December 2021. Results were analyzed between March and August 2022 and stratified by self-identified lung cancer screening program type, and we tested the hypothesis that centralized screening programs would be more likely to have implemented practices that support lung cancer screening, followed by hybrid and decentralized programs, using the Cochran-Armitage trend test. RESULTS: Overall, 69 (56.6%) facilities completed the survey, and respondents were lung cancer screening coordinators (39.1%), pulmonologists (33.3%), and oncologists (10.1%). Facilities most frequently self-identified as having a centralized (37.7%) program model, followed by identifying as having hybrid (30.4%) and decentralized (20.3%) programs. There was varying implementation of practices to support lung cancer screening, with hybrid and decentralized programs less likely to have lung cancer screening registries, lung cancer screening steering committees, or dedicated lung cancer screening coordinators. CONCLUSIONS: Although there is overlap between the components of various lung cancer screening program types, centralized programs more frequently implemented practices before the initial screening to support lung cancer screening. This work provides a path for future investigations to identify which lung cancer screening practices are effective to improve lung cancer screening outcomes, which could help inform implementation in settings with limited resources.

Development and Validation of a Risk Assessment Model for Pulmonary Nodules Using Plasma Proteins and Clinical Factors.

BACKGROUND: Deficiencies in risk assessment for patients with pulmonary nodules (PNs) contribute to unnecessary invasive testing and delays in diagnosis. RESEARCH QUESTION: What is the accuracy of a novel PN risk model that includes plasma proteins and clinical factors? How does the accuracy compare with that of an established risk model? STUDY DESIGN AND METHODS: Based on technology using magnetic nanosensors, assays were developed with seven plasma proteins. In a training cohort (n = 429), machine learning approaches were used to identify an optimal algorithm that subsequently was evaluated in a validation cohort (n = 489), and its performance was compared with the Mayo Clinic model. RESULTS: In the training set, we identified a support vector machine algorithm that included the seven plasma proteins and six clinical factors that demonstrated an area under the receiver operating characteristic curve of 0.87 and met other selection criteria. The resulting risk reclassification model (RRM) was used to recategorize patients with a pretest risk of between 10% and 84%, and its performance was assessed across five risk strata (low, ≤ 10%; moderate, 10%-34%; intermediate, 35%-70%; high, 71%-84%; very high, > 85%). Stratification by the RRM decreased the proportion of intermediate-risk patients from 26.7% to 10.8% (P < .001) and increased the low-risk and high-risk strata from 16.8% to 21.9% (P < .001) and from 3.7% to 12.1% (P < .001), respectively. Among patients classified as low risk by the RRM and Mayo Clinic model, the corresponding true-negative to false-negative ratios were 16.8 and 19.5, respectively. Among patients classified as very high risk by the RRM and Mayo Clinic model, the corresponding true-positive to false-positive ratios were 28.5 and 17.0, respectively. Compared with the Mayo Clinic model, the RRM provided higher specificity at the low-risk threshold and higher sensitivity at the very high-risk threshold. INTERPRETATION: The RRM accurately reclassified some patients into low-risk and very high-risk categories, suggesting the potential to improve PN risk assessment.

Classification of wheat diseases using deep learning networks with field and glasshouse images.

Crop diseases can cause major yield losses, so the ability to detect and identify them in their early stages is important for disease control. Deep learning methods have shown promise in classifying multiple diseases; however, many studies do not use datasets that represent real field conditions, necessitating either further image processing or reducing their applicability. In this paper, we present a dataset of wheat images taken in real growth situations, including both field and glasshouse conditions, with five categories: healthy plants and four foliar diseases, yellow rust, brown rust, powdery mildew and Septoria leaf blotch. This dataset was used to train a deep learning model. The resulting model, named CerealConv, reached a 97.05% classification accuracy. When tested against trained pathologists on a subset of images from the larger dataset, the model delivered an accuracy score 2% higher than the best-performing pathologist. Image masks were used to show that the model was using the correct information to drive its classifications. These results show that deep learning networks are a viable tool for disease detection and classification in the field, and disease quantification is a logical next step.

Pathogen-induced biosynthetic pathways encode defense-related molecules in bread wheat.

Wheat is a widely grown food crop that suffers major yield losses due to attack by pests and pathogens. A better understanding of biotic stress responses in wheat is thus of major importance. The recently assembled bread wheat genome coupled with extensive transcriptomic resources provides unprecedented new opportunities to investigate responses to pathogen challenge. Here, we analyze gene coexpression networks to identify modules showing consistent induction in response to pathogen exposure. Within the top pathogen-induced modules, we identify multiple clusters of physically adjacent genes that correspond to six pathogen-induced biosynthetic pathways that share a common regulatory network. Functional analysis reveals that these pathways, all of which are encoded by biosynthetic gene clusters, produce various different classes of compounds­namely, flavonoids, diterpenes, and triterpenes, including the defense-related compound ellarinacin. Through comparative genomics, we also identify associations with the known rice phytoalexins momilactones, as well as with a defense-related gene cluster in the grass model plant Brachypodium distachyon. Our results significantly advance the understanding of chemical defenses in wheat and open up avenues for enhancing disease resistance in this agriculturally important crop. They also exemplify the power of transcriptional networks to discover the biosynthesis of chemical defenses in plants with large, complex genomes.

Diversifying the menu for crop powdery mildew resistance.

Powdery mildew, a potentially severe crop disease, can be controlled by mlo mutations, which suppress fungal proliferation but typically also reduce yield. Li et al. (2022) demonstrate that productivity can be restored by overexpressing a host sugar transporter, thus offering a new option for economically and environmentally benign disease control.

Trehalose and α-glucan mediate distinct abiotic stress responses in Pseudomonas aeruginosa.

An important prelude to bacterial infection is the ability of a pathogen to survive independently of the host and to withstand environmental stress. The compatible solute trehalose has previously been connected with diverse abiotic stress tolerances, particularly osmotic shock. In this study, we combine molecular biology and biochemistry to dissect the trehalose metabolic network in the opportunistic human pathogen Pseudomonas aeruginosa PAO1 and define its role in abiotic stress protection. We show that trehalose metabolism in PAO1 is integrated with the biosynthesis of branched α-glucan (glycogen), with mutants in either biosynthetic pathway significantly compromised for survival on abiotic surfaces. While both trehalose and α-glucan are important for abiotic stress tolerance, we show they counter distinct stresses. Trehalose is important for the PAO1 osmotic stress response, with trehalose synthesis mutants displaying severely compromised growth in elevated salt conditions. However, trehalose does not contribute directly to the PAO1 desiccation response. Rather, desiccation tolerance is mediated directly by GlgE-derived α-glucan, with deletion of the glgE synthase gene compromising PAO1 survival in low humidity but having little effect on osmotic sensitivity. Desiccation tolerance is independent of trehalose concentration, marking a clear distinction between the roles of these two molecules in mediating responses to abiotic stress.

Succession of the fungal endophytic microbiome of wheat is dependent on tissue-specific interactions between host genotype and environment.

Fungi living inside plants affect many aspects of plant health, but little is known about how plant genotype influences the fungal endophytic microbiome. However, a deeper understanding of interactions between plant genotype and biotic and abiotic environment in shaping the plant microbiome is of significance for modern agriculture, with implications for disease management, breeding and the development of biocontrol agents. For this purpose, we analysed the fungal wheat microbiome from seed to plant to seeds and studied how different potential sources of inoculum contributed to shaping of the microbiome. We conducted a large-scale pot experiment with related wheat cultivars over one growth-season in two environments (indoors and outdoors) to disentangle the effects of host genotype, abiotic environment (temperature, humidity, precipitation) and fungi present in the seed stock, air and soil on the succession of the endophytic fungal communities in roots, flag leaves and seeds at harvest. The communities were studied with ITS1 metabarcoding and environmental climate factors were monitored during the experimental period. Host genotype, tissue type and abiotic factors influenced fungal communities significantly. The effect of host genotype was mostly limited to leaves and roots, and was location-independent. While there was a clear effect of plant genotype, the relatedness between cultivars was not reflected in the microbiome. For the phyllosphere microbiome, location-dependent weather conditions factors largely explained differences in abundance, diversity, and presence of genera containing pathogens, whereas the root communities were less affected by abiotic factors. Our findings suggest that airborne fungi are the primary inoculum source for fungal communities in aerial plant parts whereas vertical transmission is likely to be insignificant. In summary, our study demonstrates that host genotype, environment and presence of fungi in the environment shape the endophytic fungal community in wheat over a growing season.

Naturally occurring circadian rhythm variation associated with clock gene loci in Swedish Arabidopsis accessions.

Circadian clocks have evolved to resonate with external day and night cycles. However, these entrainment signals are not consistent everywhere and vary with latitude, climate and seasonality. This leads to divergent selection for clocks which are locally adapted. To investigate the genetic basis for this circadian variation, we used a delayed fluorescence imaging assay to screen 191 naturally occurring Swedish Arabidopsis accessions for their circadian phenotypes. We demonstrate that the period length co-varies with both geography and population sub-structure. Several candidate loci linked to period, phase and relative amplitude error (RAE) were revealed by genome-wide association mapping and candidate genes were investigated using TDNA mutants. We show that natural variation in a single non-synonymous substitution within COR28 is associated with a long-period and late-flowering phenotype similar to that seen in TDNA knock-out mutants. COR28 is a known coordinator of flowering time, freezing tolerance and the circadian clock; all of which may form selective pressure gradients across Sweden. We demonstrate the effect of the COR28-58S SNP in increasing period length through a co-segregation analysis. Finally, we show that period phenotypic tails remain diverged under lower temperatures and follow a distinctive "arrow-shaped" trend indicative of selection for a cold-biased temperature compensation response.

The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire.

Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research.

Role of Effector-Sensitivity Gene Interactions and Durability of Quantitative Resistance to Septoria Nodorum Blotch in Eastern U.S. Wheat.

Important advances have been made in understanding the relationship of necrotrophic effectors (NE) and host sensitivity (Snn) genes in the Parastagonospora nodorum-wheat pathosystem. Yet much remains to be learned about the role of these interactions in determining wheat resistance levels in the field, and there is mixed evidence on whether breeding programs have selected against Snn genes due to their role in conferring susceptibility. SNB occurs ubiquitously in the U.S. Atlantic seaboard, and the environment is especially well suited to field studies of resistance to natural P. nodorum populations, as there are no other important wheat leaf blights. Insights into the nature of SNB resistance have been gleaned from multi-year data on phenotypes and markers in cultivars representative of the region's germplasm. In this perspective article, we review the evidence that in this eastern region of the U.S., wheat cultivars have durable quantitative SNB resistance and Snn-NE interactions are of limited importance. This conclusion is discussed in light of the relevant available information from other parts of the world.

Improving plant transient expression through the rational design of synthetic 5' and 3' untranslated regions.

BACKGROUND: The growing field of plant molecular farming relies on expression vectors that allow high yields of recombinant proteins to be produced through transient gene expression. While numerous expression vectors currently exist for this purpose, there are very few examples of systematic efforts to improve upon these. Moreover, the current generation of expression systems makes use of naturally-occurring regulatory elements, typically selected from plant viruses, to maximise yields. This study aims to use rational design to generate synthetic sequences that can rival existing ones. RESULTS: In this work, we present the rational design of novel synthetic 5' and 3' untranslated regions (UTRs) which can be used in various combinations to modulate accumulation levels of transiently-expressed recombinant proteins. Using the pEAQ-HT expression vector as a point of comparison, we show that pre-existing expression systems can be improved by the deployment of rationally designed synthetic UTRs. Notably, we show that a suite of short, synthetic 5'UTRs behave as expression enhancers that outperform the HT 5'UTR present in the CPMV-HT expression system. Furthermore, we confirm the critical role played by the 3'UTR of cowpea mosaic virus RNA-2 in the performance of the CPMV-HT system. Finally, we use the knowledge obtained from these results to develop novel expression vectors (named pHRE and pHREAC) that equal or outperform pEAQ-HT in terms of recombinant protein yield. These new vectors are also domesticated for the use of certain Type IIS restriction enzymes, which allows for quicker cloning and straightforward assessment of different combinations of UTRs. CONCLUSIONS: We have shown that it is possible to rationally design a suite of expression modulators in the form of synthetic UTRs. We have created novel expression vectors that allow very high levels of recombinant protein expression in a transient expression context. This will have important consequences for future efforts to develop ever-better plant transient overexpression vectors for research or industrial applications.

Durability of Quantitative Resistance in Crops: Greater Than We Know?

Quantitative resistance (QR) to crop diseases has usually been much more durable than major-gene, effector-triggered resistance. It has been observed that the effectiveness of some QR has eroded as pathogens adapt to it, especially when deployment is extensive and epidemics occur regularly, but it generally declines more slowly than effector-triggered resistance. Changes in aggressiveness and specificity of diverse pathogens on cultivars with QR have been recorded, along with experimental data on fitness costs of pathogen adaptation to QR, but there is little information about molecular mechanisms of adaptation. Some QR has correlated or antagonistic effects on multiple diseases. Longitudinal data on cultivars' disease ratings in trials over several years can be used to assess the significance of QR for durable resistance in crops. It is argued that published data likely underreport the durability of QR, owing to publication bias. The implications of research on QR for plant breeding are discussed.

Yield instability of winter oilseed rape modulated by early winter temperature.

Yield stability is a major problem in oilseed rape with inter-annual variation accounting for between 30-50% of the crop value among the major global rapeseed producers. The United Kingdom has persistent problems with yield instability, but the underlying causes remain unclear. We tested whether temperature plays a role in UK winter oilseed rape (WOSR) yield variation through analysis of aggregated country-wide on-farm yield data and in annual Recommended List variety trial data run by the UK Agriculture and Horticulture Development Board (AHDB). Our analyses of the two independent datasets both show that mean temperature in early winter is strongly and uniquely linked to variation in WOSR yield, with a rise in mean temperature of 1 °C associated with an average reduction of 113 (+-21) kg ha-1 in yield. We propose that understanding the mechanism by which early winter chilling affects WOSR yield will enable the breeding of varieties with a more stable and resilient yield in Western Europe as climatic variation increases.

A versatile method for assessing pathogenicity of Hymenoscyphus fraxineus to ash foliage.

We describe a method for inoculating rachises of Fraxinus excelsior (European or common ash) with Hymenoscyphus fraxineus, which is faster than previous methods and allows associated foliar symptoms to be assessed on replicate leaves. A total of ten ash seedlings were inoculated with five isolates of H. fraxineus and lesion development assessed over four weeks. A five-point disease progress scale of symptom development was developed from no lesion (0), lesion on rachis (1), "pre-top dead," with curling of distal leaflets and bending of the rachis (2), top dead, with wilting and death of distal leaflets (3) to leaf abscission (4). The method revealed variation in aggressiveness of H. fraxinus isolates and may be suitable for assessing the resistance of F. excelsior and other Fraxinus species to dieback. The in vitro growth rate of H. fraxineus isolates was highly correlated with both disease progress and the length of rachis lesions on susceptible plants, indicating that it can be used as a preliminary step in selecting isolates with high aggressiveness for use in resistance screening.

Age, comorbidity, life expectancy, and pulmonary nodule follow-up in older veterans.

BACKGROUND: Pulmonary nodule guidelines do not indicate how to individualize follow-up according to comorbidity or life expectancy. OBJECTIVES: To characterize comorbidity and life expectancy in older veterans with incidental, symptom-detected, or screen-detected nodules in 2008-09 compared to 2013-14. To determine the impact of these patient factors on four-year nodule follow-up among the 2008-09 subgroup. DESIGN: Retrospective cohort study. SETTING: Urban Veterans Affairs Medical Center. PARTICIPANTS: 243 veterans age ≥65 with newly diagnosed pulmonary nodules in 2008-09 (followed for four years through 2012 or 2013) and 446 older veterans diagnosed in 2013-14. MEASUREMENTS: The primary outcome was receipt of any follow-up nodule imaging and/or biopsy within four years after nodule diagnosis. Primary predictor variables included age, Charlson-Deyo Comorbidity Index (CCI), and life expectancy. Favorable life expectancy was defined as age 65-74 with CCI 0 while limited life expectancy was defined as age ≥85 with CCI ≥1 or age ≥65 with CCI ≥4. Interaction by nodule size was also examined. RESULTS: From 2008-09 to 2013-14, the number of older veterans diagnosed with new pulmonary nodules almost doubled, including among those with severe comorbidity and limited life expectancy. Overall among the 2008-09 subgroup, receipt of nodule follow-up decreased with increasing comorbidity (CCI ≥4 versus 0: adjusted RR 0.61, 95% CI 0.39-0.95) with a trend towards decreased follow-up among those with limited life expectancy (adjusted RR 0.69, 95% CI 0.48-1.01). However, we detected an interaction effect with nodule size such that comorbidity and life expectancy were associated with decreased follow-up only among those with nodules ≤6 mm. CONCLUSIONS: We found some individualization of pulmonary nodule follow-up according to comorbidity and life expectancy in older veterans with smaller nodules only. As increased imaging detects nodules in sicker patients, guidelines need to be more explicit about how to best incorporate comorbidity and life expectancy to maximize benefits and minimize harms for patients with nodules of all sizes.

The ash dieback invasion of Europe was founded by two genetically divergent individuals.

Accelerating international trade and climate change make pathogen spread an increasing concern. Hymenoscyphus fraxineus, the causal agent of ash dieback, is a fungal pathogen that has been moving across continents and hosts from Asian to European ash. Most European common ash trees (Fraxinus excelsior) are highly susceptible to H. fraxineus, although a minority (~5%) have partial resistance to dieback. Here, we assemble and annotate a H. fraxineus draft genome, which approaches chromosome scale. Pathogen genetic diversity across Europe and in Japan, reveals a strong bottleneck in Europe, though a signal of adaptive diversity remains in key host interaction genes. We find that the European population was founded by two divergent haploid individuals. Divergence between these haplotypes represents the ancestral polymorphism within a large source population. Subsequent introduction from this source would greatly increase adaptive potential of the pathogen. Thus, further introgression of H. fraxineus into Europe represents a potential threat and Europe-wide biological security measures are needed to manage this disease.

The role of reactive oxygen in the development of Ramularia leaf spot disease in barley seedlings.

Background and Aims: Ramularia collo-cygni is an ascomycete fungus that colonizes barley primarily as a benign endophyte, although this interaction can become pathogenic, causing the disease Ramularia leaf spot (RLS). Factors, particularly reactive oxygen species, that resulted in the transition of the fungus from endophyte to necrotrophic parasite and the development of disease symptoms were investigated. Methods: Disease development in artificially inoculated seedlings of barley varieties varying in partial resistance to RLS was related to exposure to abiotic stress prior to inoculation. Histochemical and molecular analysis determined the effect of R. collo-cygni colonization on accumulation of reactive oxygen species and antioxidant gene expression. Development of RLS on barley lines defective in antioxidant enzymes and with altered redox status or non-functional chloroplasts was compared with the accumulation of fungal biomass to determine how these factors affect disease symptom expression. Key Results: Exposure to abiotic stress increased symptom development in all susceptible and most partially resistant barley varieties, in association with greater hydrogen peroxide (H2O2) levels in leaves. Decreased activity of the antioxidant enzymes superoxide dismutase and catalase in transgenic and mutant plants had no effect on the disease transition, whereas manipulation of H2O2 levels during asymptomatic growth of the fungus increased disease symptoms in most susceptible varieties but not in partially resistant plants. Barley mutants that undergo rapid loss of green leaf area when infected by R. collo-cygni or albino mutants with non-functional chloroplasts showed reduced development of RLS symptoms. Conclusions: These results imply that in seedlings the pathogenic transition of the normally endophytic fungus R. collo-cygni does not result from senescence as such, but rather is promoted by factors that result in changes to host reactive oxygen species. Barley varieties vary in the extent to which these factors promote RLS disease.