Whole-genome sequences of Bipolaris bicolor, Curvularia hawaiiensis, Curvularia spicifera, and Exserohilum rostratum isolated from rice in Burkina Faso, France, Mali, and Pakistan.

Different fungal species of the Pleosporaceae family infect rice, causing similar symptoms. Reference genomic sequences are useful tools to study the evolution of these species and to develop accurate molecular diagnostic tools. Here, we report the complete genome sequences of Bipolaris bicolor, Curvularia hawaiiensis, Curvularia spicifera, and Exserohilum rostratum.

Adaptive evolution in virulence effectors of the rice blast fungus Pyricularia oryzae.

Plant pathogens secrete proteins called effectors that target host cellular processes to promote disease. Recently, structural genomics has identified several families of fungal effectors that share a similar three-dimensional structure despite remarkably variable amino-acid sequences and surface properties. To explore the selective forces that underlie the sequence variability of structurally-analogous effectors, we focused on MAX effectors, a structural family of effectors that are major determinants of virulence in the rice blast fungus Pyricularia oryzae. Using structure-informed gene annotation, we identified 58 to 78 MAX effector genes per genome in a set of 120 isolates representing seven host-associated lineages. The expression of MAX effector genes was primarily restricted to the early biotrophic phase of infection and strongly influenced by the host plant. Pangenome analyses of MAX effectors demonstrated extensive presence/absence polymorphism and identified gene loss events possibly involved in host range adaptation. However, gene knock-in experiments did not reveal a strong effect on virulence phenotypes suggesting that other evolutionary mechanisms are the main drivers of MAX effector losses. MAX effectors displayed high levels of standing variation and high rates of non-synonymous substitutions, pointing to widespread positive selection shaping the molecular diversity of MAX effectors. The combination of these analyses with structural data revealed that positive selection acts mostly on residues located in particular structural elements and at specific positions. By providing a comprehensive catalog of amino acid polymorphism, and by identifying the structural determinants of the sequence diversity, our work will inform future studies aimed at elucidating the function and mode of action of MAX effectors.

Evolution of the rice blast pathogen on spatially structured rice landraces maintains multiple generalist fungal lineages.

Traditional agrosystems, where humans, crops and microbes have coevolved over long periods, can serve as models to understand the ecoevolutionary determinants of disease dynamics and help the engineering of durably resistant agrosystems. Here, we investigated the genetic and phenotypic relationship between rice (Oryza sativa) landraces and their rice blast pathogen (Pyricularia oryzae) in the traditional Yuanyang terraces of flooded rice paddies in China, where rice landraces have been grown and bred over centuries without significant disease outbreaks. Analyses of genetic subdivision revealed that indica rice plants clustered according to landrace names. Three new diverse lineages of rice blast specific to the Yuanyang terraces coexisted with lineages previously detected at the worldwide scale. Population subdivision in the pathogen population did not mirror pattern of population subdivision in the host. Measuring the pathogenicity of rice blast isolates on landraces revealed generalist life history traits. Our results suggest that the implementation of disease control strategies based on the emergence or maintenance of a generalist lifestyle in pathogens may sustainably reduce the burden of disease in crops.

Genetic diversity and structure of Bipolaris oryzae and Exserohilum rostratum populations causing brown spot of rice in Burkina Faso based on genotyping-by-sequencing.

In recent years, Brown spot disease of rice (BSR) has been observed on leaves and seeds of rice in all rice-growing areas of Burkina Faso. Bipolaris oryzae and Exserohilum rostratum are the main fungal species isolated from BSR infected tissues and they are frequently observed in the same field. However, we are lacking information on the genetic diversity and population structure of these fungi in Burkina Faso. The mode of reproduction is also unknown. The genetic diversity of isolates of B. oryzae (n=61) and E. rostratum (n=151), collected from major rice-growing areas of Burkina Faso, was estimated using genotyping-by-sequencing (GBS). The mean values for nucleotide diversity (π) were 1.9 x10-4 for B. oryzae and 4.8 x10-4 for E. rostratum. There is no genetic differentiation between the geographical populations of each species. The analysis of molecular variance revealed that 89% and 94% of the genetic variances were within the populations of B. oryzae and E. rostratum, respectively. For each species, four genetic clusters were identified by two clustering methods (DAPC and sNMF). The distribution of these genetic groups was independent of the geographical origin of the isolates. Evidence of recombination was detected in the populations of B. oryzae and E. rostratum. For B. oryzae balanced mating type ratios were supporting sexual reproduction. For E. rostratum overrepresentation of MAT1-2 isolates (79%) suggested a predominant asexual reproduction. This study provides important information on the biology and genetics of the two major fungi causing brown spot disease of rice in Burkina Faso.

Correction: Maintenance of divergent lineages of the Rice Blast Fungus Pyricularia oryzae through niche separation, loss of sex and post-mating genetic incompatibilities.

[This corrects the article DOI: 10.1371/journal.ppat.1010687.].

Gene copy number variations at the within-host population level modulate gene expression in a multipartite virus.

Multipartite viruses have a segmented genome, with each segment encapsidated separately. In all multipartite virus species for which the question has been addressed, the distinct segments reproducibly accumulate at a specific and host-dependent relative frequency, defined as the 'genome formula'. Here, we test the hypothesis that the multipartite genome organization facilitates the regulation of gene expression via changes of the genome formula and thus via gene copy number variations. In a first experiment, the faba bean necrotic stunt virus (FBNSV), whose genome is composed of eight DNA segments each encoding a single gene, was inoculated into faba bean or alfalfa host plants, and the relative concentrations of the DNA segments and their corresponding messenger RNAs (mRNAs) were monitored. In each of the two host species, our analysis consistently showed that the genome formula variations modulate gene expression, the concentration of each genome segment linearly and positively correlating to that of its cognate mRNA but not of the others. In a second experiment, twenty parallel FBNSV lines were transferred from faba bean to alfalfa plants. Upon host switching, the transcription rate of some genome segments changes, but the genome formula is modified in a way that compensates for these changes and maintains a similar ratio between the various viral mRNAs. Interestingly, a deep-sequencing analysis of these twenty FBNSV lineages demonstrated that the host-related genome formula shift operates independently of DNA-segment sequence mutation. Together, our results indicate that nanoviruses are plastic genetic systems, able to transiently adjust gene expression at the population level in changing environments, by modulating the copy number but not the sequence of each of their genes.

Maintenance of divergent lineages of the Rice Blast Fungus Pyricularia oryzae through niche separation, loss of sex and post-mating genetic incompatibilities.

Many species of fungal plant pathogens coexist as multiple lineages on the same host, but the factors underlying the origin and maintenance of population structure remain largely unknown. The rice blast fungus Pyricularia oryzae is a widespread model plant pathogen displaying population subdivision. However, most studies of natural variation in P. oryzae have been limited in genomic or geographic resolution, and host adaptation is the only factor that has been investigated extensively as a contributor to population subdivision. In an effort to complement previous studies, we analyzed genetic and phenotypic diversity in isolates of the rice blast fungus covering a broad geographical range. Using single-nucleotide polymorphism genotyping data for 886 isolates sampled from 152 sites in 51 countries, we showed that population subdivision of P. oryzae in one recombining and three clonal lineages with broad distributions persisted with deeper sampling. We also extended previous findings by showing further population subdivision of the recombining lineage into one international and three Asian clusters, and by providing evidence that the three clonal lineages of P. oryzae were found in areas with different prevailing environmental conditions, indicating niche separation. Pathogenicity tests and bioinformatic analyses using an extended set of isolates and rice varieties indicated that partial specialization to rice subgroups contributed to niche separation between lineages, and differences in repertoires of putative virulence effectors were consistent with differences in host range. Experimental crosses revealed that female sterility and early post-mating genetic incompatibilities acted as strong additional barriers to gene flow between clonal lineages. Our results demonstrate that the spread of a fungal pathogen across heterogeneous habitats and divergent populations of a crop species can lead to niche separation and reproductive isolation between distinct, widely distributed, lineages.

EggLib 3: A python package for population genetics and genomics.

Rapid and repeatable polymorphism analyses have become a necessity with the current amount of genomic data that can be collected in many organisms. Traditionally, such analyses are conducted using a variety of tools in combination, often requiring numerous format translation and manipulation. Here, we present a massively updated version of our previous software package egglib, intended to alleviate such costly and error-prone tinkering with the data. egglib has been streamlined into a python package and thoroughly updated and optimized to accommodate modern-day sized dataset. We show the main characteristics of the package making it a tool of choice to perform population genetics analyses. Once the data are imported (whatever their encoding), they can be filtered, edited, analysed and compared to coalescent simulations very easily and efficiently. Furthermore, the list of diversity and polymorphism statistics that can now be calculated has been greatly expanded. The software and its full documentation are available at https://egglib.org/.

Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen.

Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus Pseudocercospora fijiensis, was recently identified in the northern Caribbean region. Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of P. fijiensis were identified in genomic regions by combining annotation analysis with available biological data.

Convergent Adaptation to Quantitative Host Resistance in a Major Plant Pathogen.

Plant pathogens can adapt to quantitative resistance, eroding its effectiveness. The aim of this work was to reveal the genomic basis of adaptation to such a resistance in populations of the fungus Pseudocercospora fijiensis, a major devastating pathogen of banana, by studying convergent adaptation on different cultivars. Samples from P. fijiensis populations showing a local adaptation pattern on new banana hybrids with quantitative resistance were compared, based on a genome scan approach, with samples from traditional and more susceptible cultivars in Cuba and the Dominican Republic. Whole-genome sequencing of pools of P. fijiensis isolates (pool-seq) sampled from three locations per country was conducted according to a paired population design. The findings of different combined analyses highly supported the existence of convergent adaptation on the study cultivars between locations within but not between countries. Five to six genomic regions involved in this adaptation were detected in each country. An annotation analysis and available biological data supported the hypothesis that some genes within the detected genomic regions may play a role in quantitative pathogenicity, including gene regulation. The results suggested that the genetic basis of fungal adaptation to quantitative plant resistance is at least oligogenic, while highlighting the existence of specific host-pathogen interactions for this kind of resistance.IMPORTANCE Understanding the genetic basis of pathogen adaptation to quantitative resistance in plants has a key role to play in establishing durable strategies for resistance deployment. In this context, a population genomic approach was developed for a major plant pathogen (the fungus Pseudocercospora fijiensis causing black leaf streak disease of banana) whereby samples from new resistant banana hybrids were compared with samples from more susceptible conventional cultivars in two countries. A total of 11 genomic regions for which there was strong evidence of selection by quantitative resistance were detected. An annotation analysis and available biological data supported the hypothesis that some of the genes within these regions may play a role in quantitative pathogenicity. These results suggested a polygenic basis of quantitative pathogenicity in this fungal pathogen and complex molecular plant-pathogen interactions in quantitative disease development involving several genes on both sides.

Structure of African Populations of Pyricularia oryzae from Rice.

Rice blast, caused by the filamentous ascomycete Pyricularia oryzae, is one of the most devastating diseases of rice. Four genetic clusters were previously identified, and three have a large geographic distribution. Asia is the center of diversity and the origin of most migrations to other continents, and sexual reproduction persisted only in the South China-Laos-North Thailand region, which was identified as the putative center of origin of all P. oryzae populations on rice. Despite the importance of rice blast disease, little is known about the diversity and the population structure of the pathogen in Africa (including Madagascar). The present study was intended to describe the structure of African populations of P. oryzae and identify the relationship between African and worldwide genetic clusters. A set of 2,057 strains (937 African and 1,120 Madagascan strains) were genotyped with 12 simple sequence repeat markers to assess the diversity and the population structure of P. oryzae. Four genetic clusters were identified in Africa and Madagascar. All four clusters previously identified are present in Africa. Populations from West Africa, East Africa, and Madagascar are highly differentiated. The geographic structure is consistent with limited dispersion and with some migration events between neighboring countries. The two mating types are present in Africa with a dominance of Mat1.2, but no female-fertile strain was detected, supporting the absence of sexual reproduction on this continent. This study showed an unsuspected high level of genetic diversity of P. oryzae in Africa and suggested several independent introductions.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Tracing the Origin and Evolutionary History of Pyricularia oryzae Infecting Maize and Barnyard Grass.

Blast disease is a notorious fungal disease leading to dramatic yield losses on major food crops such as rice and wheat. The causal agent, Pyricularia oryzae, encompasses different lineages, each having a different host range. Host shifts are suspected to have occurred in this species from Setaria spp. to rice and from Lolium spp. to wheat. The emergence of blast disease on maize in Iran was observed for the first time in the north of the country in 2012. We later identified blast disease in two additional regions of Iran: Gilan in 2013 and Golestan in 2016. Epidemics on the weed barnyard grass (Echinochloa spp.) were also observed in the same maize fields. Here, we showed that P. oryzae is the causal agent of this disease on both hosts. Pathogenicity assays in the greenhouse revealed that strains from maize can infect barnyard grass and conversely. However, genotyping with simple sequence repeat markers and comparative genomics showed that strains causing field epidemics on maize and on barnyard grass are different, although they belong to the same previously undescribed clade of P. oryzae. Phylogenetic analyses including these strains and a maize strain collected in Gabon in 1985 revealed two independent host-range expansion events from barnyard grass to maize. Comparative genomics between maize and barnyard grass strains revealed the presence or absence of five candidate genes associated with host specificity on maize, with the deletion of a small genomic region possibly responsible for adaptation to maize. This recent emergence of P. oryzae on maize provides a case study to understand host range expansion. Epidemics on maize raise concerns about potential yield losses on this crop in Iran and potential geographic expansion of the disease.

Coexistence of Multiple Endemic and Pandemic Lineages of the Rice Blast Pathogen.

The rice blast fungus Magnaporthe oryzae (syn., Pyricularia oryzae) is both a threat to global food security and a model for plant pathology. Molecular pathologists need an accurate understanding of the origins and line of descent of M. oryzae populations in order to identify the genetic and functional bases of pathogen adaptation and to guide the development of more effective control strategies. We used a whole-genome sequence analysis of samples from different times and places to infer details about the genetic makeup of M. oryzae from a global collection of isolates. Analyses of population structure identified six lineages within M. oryzae, including two pandemic on japonica and indica rice, respectively, and four lineages with more restricted distributions. Tip-dating calibration indicated that M. oryzae lineages separated about a millennium ago, long after the initial domestication of rice. The major lineage endemic to continental Southeast Asia displayed signatures of sexual recombination and evidence of DNA acquisition from multiple lineages. Tests for weak natural selection revealed that the pandemic spread of clonal lineages entailed an evolutionary "cost," in terms of the accumulation of deleterious mutations. Our findings reveal the coexistence of multiple endemic and pandemic lineages with contrasting population and genetic characteristics within a widely distributed pathogen.IMPORTANCE The rice blast fungus Magnaporthe oryzae (syn., Pyricularia oryzae) is a textbook example of a rapidly adapting pathogen, and it is responsible for one of the most damaging diseases of rice. Improvements in our understanding of Magnaporthe oryzae's diversity and evolution are required to guide the development of more effective control strategies. We used genome sequencing data for samples from around the world to infer the evolutionary history of M. oryzae We found that M. oryzae diversified about 1,000 years ago, separating into six main lineages: two pandemic on japonica and indica rice, respectively, and four with more restricted distributions. We also found that a lineage endemic to continental Southeast Asia displayed signatures of sexual recombination and the acquisition of genetic material from multiple lineages. This work provides a population-level genomic framework for defining molecular markers for the control of rice blast and investigations of the molecular basis of differences in pathogenicity between M. oryzae lineages.

Gene Flow between Divergent Cereal- and Grass-Specific Lineages of the Rice Blast Fungus Magnaporthe oryzae.

Delineating species and epidemic lineages in fungal plant pathogens is critical to our understanding of disease emergence and the structure of fungal biodiversity and also informs international regulatory decisions. Pyricularia oryzae (syn. Magnaporthe oryzae) is a multihost pathogen that infects multiple grasses and cereals, is responsible for the most damaging rice disease (rice blast), and is of growing concern due to the recent introduction of wheat blast to Bangladesh from South America. However, the genetic structure and evolutionary history of M. oryzae, including the possible existence of cryptic phylogenetic species, remain poorly defined. Here, we use whole-genome sequence information for 76 M. oryzae isolates sampled from 12 grass and cereal genera to infer the population structure of M. oryzae and to reassess the species status of wheat-infecting populations of the fungus. Species recognition based on genealogical concordance, using published data or extracting previously used loci from genome assemblies, failed to confirm a prior assignment of wheat blast isolates to a new species (Pyricularia graminis-tritici). Inference of population subdivisions revealed multiple divergent lineages within M. oryzae, each preferentially associated with one host genus, suggesting incipient speciation following host shift or host range expansion. Analyses of gene flow, taking into account the possibility of incomplete lineage sorting, revealed that genetic exchanges have contributed to the makeup of multiple lineages within M. oryzae These findings provide greater understanding of the ecoevolutionary factors that underlie the diversification of M. oryzae and highlight the practicality of genomic data for epidemiological surveillance in this important multihost pathogen.IMPORTANCE Infection of novel hosts is a major route for disease emergence by pathogenic microorganisms. Understanding the evolutionary history of multihost pathogens is therefore important to better predict the likely spread and emergence of new diseases. Magnaporthe oryzae is a multihost fungus that causes serious cereal diseases, including the devastating rice blast disease and wheat blast, a cause of growing concern due to its recent spread from South America to Asia. Using whole-genome analysis of 76 fungal strains from different hosts, we have documented the divergence of M. oryzae into numerous lineages, each infecting a limited number of host species. Our analyses provide evidence that interlineage gene flow has contributed to the genetic makeup of multiple M. oryzae lineages within the same species. Plant health surveillance is therefore warranted to safeguard against disease emergence in regions where multiple lineages of the fungus are in contact with one another.

Emergence of wheat blast in Bangladesh was caused by a South American lineage of Magnaporthe oryzae.

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. CONCLUSION: Our 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.

TOGGLE: toolbox for generic NGS analyses.

BACKGROUND: The explosion of NGS (Next Generation Sequencing) sequence data requires a huge effort in Bioinformatics methods and analyses. The creation of dedicated, robust and reliable pipelines able to handle dozens of samples from raw FASTQ data to relevant biological data is a time-consuming task in all projects relying on NGS. To address this, we created a generic and modular toolbox for developing such pipelines. RESULTS: TOGGLE (TOolbox for Generic nGs anaLysEs) is a suite of tools able to design pipelines that manage large sets of NGS softwares and utilities. Moreover, TOGGLE offers an easy way to manipulate the various options of the different softwares through the pipelines in using a single basic configuration file, which can be changed for each assay without having to change the code itself. We also describe one implementation of TOGGLE in a complete analysis pipeline designed for SNP discovery for large sets of genomic data, ready to use in different environments (from a single machine to HPC clusters). CONCLUSION: TOGGLE speeds up the creation of robust pipelines with reliable log tracking and data flow, for a large range of analyses. Moreover, it enables Biologists to concentrate on the biological relevance of results, and change the experimental conditions easily. The whole code and test data are available at https://github.com/SouthGreenPlatform/TOGGLE .

The coffee genome hub: a resource for coffee genomes.

The whole genome sequence of Coffea canephora, the perennial diploid species known as Robusta, has been recently released. In the context of the C. canephora genome sequencing project and to support post-genomics efforts, we developed the Coffee Genome Hub (http://coffee-genome.org/), an integrative genome information system that allows centralized access to genomics and genetics data and analysis tools to facilitate translational and applied research in coffee. We provide the complete genome sequence of C. canephora along with gene structure, gene product information, metabolism, gene families, transcriptomics, syntenic blocks, genetic markers and genetic maps. The hub relies on generic software (e.g. GMOD tools) for easy querying, visualizing and downloading research data. It includes a Genome Browser enhanced by a Community Annotation System, enabling the improvement of automatic gene annotation through an annotation editor. In addition, the hub aims at developing interoperability among other existing South Green tools managing coffee data (phylogenomics resources, SNPs) and/or supporting data analyses with the Galaxy workflow manager.