BackgroundIn February 2016, a new fungal disease was spotted in wheat fields across eight districts in Bangladesh. The epidemic spread to an estimated 15,000 hectares, about 16 % of the cultivated wheat area in Bangladesh, with yield losses reaching up to 100 %. Within weeks of the onset of the epidemic, we performed transcriptome sequencing of symptomatic leaf samples collected directly from Bangladeshi fields.ResultsReinoculation of seedlings with strains isolated from infected wheat grains showed wheat blast symptoms on leaves of wheat but not rice. Our phylogenomic and population genomic analyses revealed that the wheat blast outbreak in Bangladesh was most likely caused by a wheat-infecting South American lineage of the blast fungus Magnaporthe oryzae.ConclusionOur findings suggest that genomic surveillance can be rapidly applied to monitor plant disease outbreaks and provide valuable information regarding the identity and origin of the infectious agent.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-016-0309-7) contains supplementary material, which is available to authorized users.

Background: In February 2016, a new fungal disease was spotted in wheat fields across eight districts in Bangladesh. The epidemic spread to an estimated 15,000 hectares, about 16 % of the cultivated wheat area in Bangladesh, with yield losses reaching up to 100 %. Within weeks of the onset of the epidemic, we performed transcriptome sequencing of symptomatic leaf samples collected directly from Bangladeshi fields. Results: Reinoculation of seedlings with strains isolated from infected wheat grains showed wheat blast symptoms on leaves of wheat but not rice. Our phylogenomic and population genomic analyses revealed that the wheat blast outbreak in Bangladesh was most likely caused by a wheat-infecting South American lineage of the blast fungus Magnaporthe oryzae.

Wheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late twentieth century. However, isolated outbreaks have occurred in recent years. Here we investigate whether a lack of resistance in modern European varieties, increased presence of its alternate host barberry and changes in climatic conditions could be facilitating its resurgence. We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years, with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25 years also suggest increasingly conducive conditions for infection. Furthermore, we document the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that wheat stem rust does occur in the UK and, when climatic conditions are conducive, could severely harm wheat and barley production.

Host-parasite systems provide convincing examples of Red Queen co-evolutionary dynamics. Yet, a key process underscored in Van Valen's theory - that arms race dynamics can result in extinction - has never been documented. One reason for this may be that most sampling designs lack the breadth needed to illuminate the rapid pace of adaptation by pathogen populations. In this study, we used a 25-year temporal sampling to decipher the demographic history of a plant pathogen: the poplar rust fungus, Melampsora larici-populina. A major adaptive event occurred in 1994 with the breakdown of R7 resistance carried by several poplar cultivars widely planted in Western Europe since 1982. The corresponding virulence rapidly spread in M. larici-populina populations and nearly reached fixation in northern France, even on susceptible hosts. Using both temporal records of virulence profiles and temporal population genetic data, our analyses revealed that (i) R7 resistance breakdown resulted in the emergence of a unique and homogeneous genetic group, the so-called cultivated population, which predominated in northern France for about 20 years, (ii) selection for Vir7 individuals brought with it multiple other virulence types via hitchhiking, resulting in an overall increase in the population-wide number of virulence types and (iii) - above all - the emergence of the cultivated population superseded the initial population which predominated at the same place before R7 resistance breakdown. Our temporal analysis illustrates how antagonistic co-evolution can lead to population extinction and replacement, hence providing direct evidence for the escalation process which is at the core of Red Queen dynamics.

Pathogen populations are expected to evolve virulence traits in response to resistance deployed in agricultural settings. However, few temporal datasets have been available to characterize this process at the population level. Here, we examined two temporally separated populations of Puccinia coronata f. sp. avenae (Pca), which causes crown rust disease in oat (Avena sativa) sampled from 1990 to 2015. We show that a substantial increase in virulence occurred from 1990 to 2015 and this was associated with a genetic differentiation between populations detected by genome-wide sequencing. We found strong evidence for genetic recombination in these populations, showing the importance of the alternate host in generating genotypic variation through sexual reproduction. However, asexual expansion of some clonal lineages was also observed within years. Genome-wide association analysis identified seven Avr loci associated with virulence towards fifteen Pc resistance genes in oat and suggests that some groups of Pc genes recognize the same pathogen effectors. The temporal shift in virulence patterns in the Pca populations between 1990 and 2015 is associated with changes in allele frequency in these genomic regions. Nucleotide diversity patterns at a single Avr locus corresponding to Pc38, Pc39, Pc55, Pc63, Pc70, and Pc71 showed evidence of a selective sweep associated with the shift to virulence towards these resistance genes in all 2015 collected isolates.

Recent disease outbreaks caused by (re-)emerging plant pathogens have been associated with expansions in pathogen geographic distribution and increased virulence. For example, in the past two decades’ wheat yellow (stripe) rust, Puccinia striiformis f. sp. tritici, has seen the emergence of new races that are adapted to warmer temperatures, have expanded virulence profiles, and are more aggressive than previous races, leading to wide-scale epidemics. Here, we used field-based genotyping to generate high-resolution data on P. striiformis genetics and carried out global population analysis. We also undertook comparative analysis of the 2014 and 2013 UK populations and assessed the temporal dynamics and host specificity of distinct pathogen genotypes. Our analysis revealed that P. striiformis lineages recently detected in Europe are extremely diverse and in fact similar to globally dispersed populations. In addition, we identified a considerable shift in the UK P. striiformis population structure including the first identification of one infamous race known as Kranich. Next, by establishing the genotype of both the pathogen and host within a single infected field sample, we uncovered evidence for varietal specificity for genetic groups of P. striiformis. Finally, we found potential seasonal specificity for certain genotypes of the pathogen with several lineages identified only in samples collected in late spring and into the summer, whereas one lineage was identified throughout the wheat growing season. Our discovery of which wheat varieties are susceptible to which specific P. striiformis isolates, and when those isolates are prevalent throughout the year, represents a powerful tool for disease management.

Background Effective disease management depends on timely and accurate diagnosis to guide control measures. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. The genomics revolution has led to technologies that can rapidly produce high-resolution genotypic information to define individual variants of a pathogen species. However, their application to complex fungal pathogens has remained limited due to the frequent inability to culture these pathogens in the absence of their host and their large genome sizes. Results Here, we describe the development of Mobile And Real-time PLant disEase (MARPLE) diagnostics, a portable, genomics-based, point-of-care approach specifically tailored to identify individual strains of complex fungal plant pathogens. We used targeted sequencing to overcome limitations associated with the size of fungal genomes and their often obligately biotrophic nature. Focusing on the wheat yellow rust pathogen, Puccinia striiformis f.sp. tritici ( Pst ), we demonstrate that our approach can be used to rapidly define individual strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles and monitor genes of importance. Conclusions MARPLE diagnostics enables rapid identification of individual pathogen strains and has the potential to monitor those with specific properties such as fungicide resistance directly from field-collected infected plant tissue in situ. Generating results within 48 h of field sampling, this new strategy has far-reaching implications for tracking plant health threats. Electronic supplementary material The online version of this article (10.1186/s12915-019-0684-y) contains supplementary material, which is available to authorized users.

Melampsora larici-populina is a fungal pathogen responsible for foliar rust disease on poplar trees, which causes damage to forest plantations worldwide, particularly in Northern Europe. The reference genome of the isolate 98AG31 was previously sequenced using a whole genome shotgun strategy, revealing a large genome of 101 megabases containing 16,399 predicted genes, which included secreted protein genes representing poplar rust candidate effectors. In the present study, the genomes of 15 isolates collected over the past 20 years throughout the French territory, representing distinct virulence profiles, were characterized by massively parallel sequencing to assess genetic variation in the poplar rust fungus. Comparison to the reference genome revealed striking structural variations. Analysis of coverage and sequencing depth identified large missing regions between isolates related to the mating type loci. More than 611,824 single-nucleotide polymorphism (SNP) positions were uncovered overall, indicating a remarkable level of polymorphism. Based on the accumulation of non-synonymous substitutions in coding sequences and the relative frequencies of synonymous and non-synonymous polymorphisms (i.e., PN/PS), we identify candidate genes that may be involved in fungal pathogenesis. Correlation between non-synonymous SNPs in genes encoding secreted proteins (SPs) and pathotypes of the studied isolates revealed candidate genes potentially related to virulences 1, 6, and 8 of the poplar rust fungus.