We examined the genomes of 100 isolates of Magnaporthe oryzae (Pyricularia oryzae), the causal agent of rice blast disease. We grouped current field populations of M. oryzae into three major globally distributed groups. A genetically diverse group, clade 1, which may represent a group of closely related lineages, contains isolates of both mating types. Two well-separated clades, clades 2 and 3, appear to have arisen as clonal lineages distinct from the genetically diverse clade. Examination of genes involved in mating pathways identified clade-specific diversification of several genes with orthologs involved in mating behavior in other fungi. All isolates within each clonal lineage are of the same mating type. Clade 2 is distinguished by a unique deletion allele of a gene encoding a small cysteine-rich protein that we determined to be a virulence factor. Clade 3 isolates have a small deletion within the MFA2 pheromone precursor gene, and this allele is shared with an unusual group of isolates we placed within clade 1 that contain AVR1-CO39 alleles. These markers could be used for rapid screening of isolates and suggest specific events in evolution that shaped these populations. Our findings are consistent with the view that M. oryzae populations in Asia generate diversity through recombination and may have served as the source of the clades 2 and 3 isolates that comprise a large fraction of the global population.

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BackgroundConsent forms have lengthened over time and become harder for participants to understand. We sought to demonstrate the feasibility of creating a simplified consent form for biobanking that comprises the minimum information necessary to meet ethical and regulatory requirements. We then gathered preliminary data concerning its content from hypothetical biobank participants.Methodology/Principal FindingsWe followed basic principles of plain-language writing and incorporated into a 2-page form (not including the signature page) those elements of information required by federal regulations and recommended by best practice guidelines for biobanking. We then recruited diabetes patients from community-based practices and randomized half (n = 56) to read the 2-page form, first on paper and then a second time on a tablet computer. Participants were encouraged to use “More information” buttons on the electronic version whenever they had questions or desired further information. These buttons led to a series of “Frequently Asked Questions” (FAQs) that contained additional detailed information. Participants were asked to identify specific sentences in the FAQs they thought would be important if they were considering taking part in a biorepository. On average, participants identified 7 FAQ sentences as important (mean 6.6, SD 14.7, range: 0–71). No one sentence was highlighted by a majority of participants; further, 34 (60.7%) participants did not highlight any FAQ sentences.ConclusionsOur preliminary findings suggest that our 2-page form contains the information that most prospective participants identify as important. Combining simplified forms with supplemental material for those participants who desire more information could help minimize consent form length and complexity, allowing the most substantively material information to be better highlighted and enabling potential participants to read the form and ask questions more effectively.

Background and objective: Asthma is a global problem and complex disease suited for metabolomic profiling. This study explored the candidate biomarkers specific to paediatric asthma and provided insights into asthmatic pathophysiology. Methods: Children (aged 6-11 years) meeting the criteria for healthy control (n = 29), uncontrolled asthma (n = 37) or controlled asthma (n = 43) were enrolled. Gas chromatography-mass spectrometry was performed on urine samples of the patients to explore the different types of metabolite profile in paediatric asthma. Additionally, we employed a comprehensive strategy to elucidate the relationship between significant metabolites and asthma-related genes. Results: We identified 51 differential metabolites mainly related to dysfunctional amino acid, carbohydrate and purine metabolism. A combination of eight candidate metabolites, including uric acid, stearic acid, threitol, acetylgalactosamine, heptadecanoic acid, aspartic acid, xanthosine and hypoxanthine (adjusted P < 0.05 and fold-change >1.5 or <0.67), showed excellent discriminatory performance for the presence of asthma and the differentiation of poor-controlled or well-controlled asthma, and area under the curve values were >0.97 across groups. Enrichment analysis based on these targets revealed that the Fc receptor, intracellular steroid hormone receptor signalling pathway, DNA damage and fibroblast proliferation were involved in inflammation, immunity and stress-related biological progression of paediatric asthma. Conclusion: Metabolomic analysis of patient urine combined with network-biology approaches allowed discrimination of asthma profiles and subtypes according to the metabolic patterns. The results provided insight into the potential mechanism of paediatric asthma.We investigated metabolic profiles of paediatric asthma patients to identify asthma-specific biomarkers in urine. A combination of eight metabolites showed excellent discrimination across groups. Enrichment analysis identified complex biological processes associated with immunity, inflammation, oxidative stress and DNA damage. These approaches enabled discrimination between asthma stages and elucidate its mechanisms.