Effects of cultivar resistance and fungicide application on stem canker of oilseed rape (Brassica napus) and potential interseasonal transmission of Leptosphaeria spp. inoculum

© 2021 The Authors. Plant Pathology published by John Wiley & Sons Ltd on behalf of British Society for Plant Pathology. This is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/Phoma stem canker is a damaging disease of oilseed rape (Brassica napus) that causesannual yield losses to UK oilseed rape growers worth approximately £100 million,despite the use of fungicides. In the UK, oilseed rape is sown in August/Septemberand harvested in the following July. The disease epidemics are initiated by ascosporesreleased from Leptosphaeria spp. pseudothecia (ascocarps) on stem stubble in theautumn/winter. Control of this disease is reliant on the use of cultivars with “fieldresistance” and azole fungicides. This study investigated the effects of cultivar resistanceand application of the fungicide prothioconazole on the severity of stem cankerbefore harvest and the subsequent production of pseudothecia on the infected stubbleunder natural conditions in the 2017/2018, 2018/2019, and 2019/2020 croppingseasons. The application of prothioconazole and cultivar resistance decreased theseverity of phoma stem canker before harvest, and the subsequent production ofLeptosphaeria spp. pseudothecia on stubble in terms of pseudothecial density. Resultsshowed that stems with less severe stem cankers produced fewer mature pseudotheciaof Leptosphaeria spp. on the infected stubble. This investigation suggests that themost sustainable and effective integrated control strategy for phoma stem canker inseasons with low quantities of inoculum is to use cultivars with medium or good fieldresistance and apply only one spray of prothioconazole when required.Peer reviewe

Insight into Genotype-Phenotype Associations through eQTL Mapping in Multiple Cell Types in Health and Immune-Mediated Disease

Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases.This research was funded by a Wellcome Trust Clinical PhD Programme Fellowship (JEP), the NIH-Oxford-Cambridge Scholars Program (ACR), Wellcome Trust Grant 083650/Z/07/Z and MRC Grant MR/L19027/1 (KGCS), and the National Institute for Health Research Cambridge Biomedical Research Centre. KGCS is a National Institute for Health Research Senior Investigator. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

A method for identifying genetic heterogeneity within phenotypically defined disease subgroups.

Many common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic architectures, in which disease-associated variants have different effect sizes in two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximizing power in comparison to standard variant-by-variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post hoc identification of the contributing genetic variants. We demonstrate the method on a range of simulated and test data sets, for which expected results are already known. We investigate subgroups of individuals with type 1 diabetes (T1D) defined by autoantibody positivity, establishing evidence for differential genetic architecture with positivity for thyroid-peroxidase-specific antibody, driven generally by variants in known T1D-associated genomic regions.We acknowledge the help of the Diabetes and Inflammation Laboratory Data Service for access and quality control procedures on the data sets used in this study. The JDRF/Wellcome Trust Diabetes and Inflammation Laboratory is in receipt of a Wellcome Trust Strategic Award (107212; J.A.T.) and receives funding from the NIHR Cambridge Biomedical Research Centre. J.L. is funded by the NIHR Cambridge Biomedical Research Centre and is on the Wellcome Trust PhD program in Mathematical Genomics and Medicine at the University of Cambridge. C.W. is funded by the MRC (grant MC_UP_1302/5). We thank M. Simmonds, S. Gough, J. Franklyn, and O. Brand for sharing their AITD genetic association data set and all patients with AITD and control subjects for participating in this study. The AITD UK national collection was funded by the Wellcome Trust. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Coulomb and nuclear excitations of narrow resonances in Ne-17

New experimental data for dissociation of relativistic 17Ne projectiles incident on targets of lead, carbon, and polyethylene targets at GSI are presented. Special attention is paid to the excitation and decay of narrow resonant states in 17Ne. Distributions of internal energy in the O15+p+p three-body system have been determined together with angular and partial-energy correlations between the decay products in different energy regions. The analysis was done using existing experimental data on 17Ne and its mirror nucleus 17N. The isobaric multiplet mass equation is used for assignment of observed resonances and their spins and parities. A combination of data from the heavy and light targets yielded cross sections and transition probabilities for the Coulomb excitations of the narrow resonant states. The resulting transition probabilities provide information relevant for a better understanding of the 17Ne structure

A novel approach to investigate tissue-specific trinucleotide repeat instability

Abstract Background In Huntington's disease (HD), an expanded CAG repeat produces characteristic striatal neurodegeneration. Interestingly, the HD CAG repeat, whose length determines age at onset, undergoes tissue-specific somatic instability, predominant in the striatum, suggesting that tissue-specific CAG length changes could modify the disease process. Therefore, understanding the mechanisms underlying the tissue specificity of somatic instability may provide novel routes to therapies. However progress in this area has been hampered by the lack of sensitive high-throughput instability quantification methods and global approaches to identify the underlying factors. Results Here we describe a novel approach to gain insight into the factors responsible for the tissue specificity of somatic instability. Using accurate genetic knock-in mouse models of HD, we developed a reliable, high-throughput method to quantify tissue HD CAG repeat instability and integrated this with genome-wide bioinformatic approaches. Using tissue instability quantified in 16 tissues as a phenotype and tissue microarray gene expression as a predictor, we built a mathematical model and identified a gene expression signature that accurately predicted tissue instability. Using the predictive ability of this signature we found that somatic instability was not a consequence of pathogenesis. In support of this, genetic crosses with models of accelerated neuropathology failed to induce somatic instability. In addition, we searched for genes and pathways that correlated with tissue instability. We found that expression levels of DNA repair genes did not explain the tissue specificity of somatic instability. Instead, our data implicate other pathways, particularly cell cycle, metabolism and neurotransmitter pathways, acting in combination to generate tissue-specific patterns of instability. Conclusion Our study clearly demonstrates that multiple tissue factors reflect the level of somatic instability in different tissues. In addition, our quantitative, genome-wide approach is readily applicable to high-throughput assays and opens the door to widespread applications with the potential to accelerate the discovery of drugs that alter tissue instability

Validation of the Body Concealment Scale for Scleroderma (BCSS): Replication in the Scleroderma Patient-centered Intervention Network (SPIN) Cohort

© 2016 Elsevier Ltd Body concealment is an important component of appearance distress for individuals with disfiguring conditions, including scleroderma. The objective was to replicate the validation study of the Body Concealment Scale for Scleroderma (BCSS) among 897 scleroderma patients. The factor structure of the BCSS was evaluated using confirmatory factor analysis and the Multiple-Indicator Multiple-Cause model examined differential item functioning of SWAP items for sex and age. Internal consistency reliability was assessed via Cronbach's alpha. Construct validity was assessed by comparing the BCSS with a measure of body image distress and measures of mental health and pain intensity. Results replicated the original validation study, where a bifactor model provided the best fit. The BCSS demonstrated strong internal consistency reliability and construct validity. Findings further support the BCSS as a valid measure of body concealment in scleroderma and provide new evidence that scores can be compared and combined across sexes and ages

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)