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Pathogenic fungal diseases in crops are mediated by the release of effector proteins that facilitate infection. Characterising the structure of these fungal effectors is vital to understanding their virulence mechanisms and interactions with their hosts, which is crucial in the breeding of plant cultivars for disease resistance. Several effectors have been identified and validated experimentally; however, their lack of sequence conservation often impedes the identification and prediction of their structure using sequence similarity approaches. Structural similarity has, nonetheless, been observed within fungal effector protein families, creating interest in validating the use of computational methods to predict their tertiary structure from their sequence. We used Rosetta ab initio modelling to predict the structures of members of the ToxA-like and MAX effector families for which experimental structures are known to validate this method. An optimised approach was then used to predict the structures of phenotypically validated effectors lacking known structures. Rosetta was found to successfully predict the structure of fungal effectors in the ToxA-like and MAX families, as well as phenotypically validated but structurally unconfirmed effector sequences. Interestingly, potential new effector structural families were identified on the basis of comparisons with structural homologues and the identification of associated protein domains.

The discovery of new fungal effector proteins is necessary to enable the screening of cultivars for disease resistance. Sequence-based bioinformatics methods have been used for this purpose, but only a limited number of functional effector proteins have been successfully predicted and subsequently validated experimentally. A significant obstacle is that many fungal effector proteins discovered so far lack sequence similarity or conserved sequence motifs. The availability of experimentally determined three-dimensional (3D) structures of a number of effector proteins has recently highlighted structural similarities amongst groups of sequence-dissimilar fungal effectors, enabling the search for similar structural folds amongst effector sequence candidates. We have applied template-based modelling to predict the 3D structures of candidate effector sequences obtained from bioinformatics predictions and the PHI-BASE database. Structural matches were found not only with ToxA- and MAX-like effector candidates but also with non-fungal effector-like proteins—including plant defensins and animal venoms—suggesting the broad conservation of ancestral structural folds amongst cytotoxic peptides from a diverse range of distant species. Accurate modelling of fungal effectors were achieved using RaptorX. The utility of predicted structures of effector proteins lies in the prediction of their interactions with plant receptors through molecular docking, which will improve the understanding of effector–plant interactions.

Ascochyta rabiei is the causal organism of ascochyta blight of chickpea and is present in chickpea crops worldwide. Here we report the release of a high-quality PacBio genome assembly for the Australian A. rabiei isolate ArME14. We compare the ArME14 genome assembly with an Illumina assembly for Indian A. rabiei isolate, ArD2. The ArME14 assembly has gapless sequences for nine chromosomes with telomere sequences at both ends and 13 large contig sequences that extend to one telomere. The total length of the ArME14 assembly was 40,927,385 bp, which was 6.26 Mb longer than the ArD2 assembly. Division of the genome by OcculterCut into GC-balanced and AT-dominant segments reveals 21% of the genome contains gene-sparse, AT-rich isochores. Transposable elements and repetitive DNA sequences in the ArME14 assembly made up 15% of the genome. A total of 11,257 protein-coding genes were predicted compared with 10,596 for ArD2. Many of the predicted genes missing from the ArD2 assembly were in genomic regions adjacent to AT-rich sequence. We compared the complement of predicted transcription factors and secreted proteins for the two A. rabiei genome assemblies and found that the isolates contain almost the same set of proteins. The small number of differences could represent real differences in the gene complement between isolates or possibly result from the different sequencing methods used. Prediction pipelines were applied for carbohydrate-active enzymes, secondary metabolite clusters and putative protein effectors. We predict that ArME14 contains between 450 and 650 CAZymes, 39 putative protein effectors and 26 secondary metabolite clusters.

Guava wilt disease is caused by the fungus Nalanthamala psidii. The wilt disease results in large-scale destruction of orchards in South Africa, Taiwan, and several Southeast Asian countries. De novo assembly, annotation, and in-depth analysis of the N. psidii genome were carried out to facilitate the identification of characteristics associated with pathogenicity and pathogen evolution. The predicted secretome revealed a range of CAZymes, proteases, lipases and peroxidases associated with plant cell wall degradation, nutrient acquisition, and disease development. Further analysis of the N. psidii carbohydrate-active enzyme profile exposed the broad-spectrum necrotrophic lifestyle of the pathogen, which was corroborated by the identification of putative effectors and secondary metabolites with the potential to induce tissue necrosis and cell surface-dependent immune responses. Putative regulatory proteins including transcription factors and kinases were identified in addition to transporters potentially involved in the secretion of secondary metabolites. Transporters identified included important ABC and MFS transporters involved in the efflux of fungicides. Analysis of the repetitive landscape and the detection of mechanisms linked to reproduction such as het and mating genes rendered insights into the biological complexity and evolutionary potential of N. psidii as guava pathogen. Hence, the assembly and annotation of the N. psidii genome provided a valuable platform to explore the pathogenic potential and necrotrophic lifestyle of the guava wilt pathogen.

Background Narrow-leafed lupin is an emerging crop of significance in agriculture, livestock feed and human health food. However, its susceptibility to various diseases is a major obstacle towards increased adoption. Sclerotinia sclerotiorum and Botrytis cinerea – both necrotrophs with broad host-ranges - are reported among the top 10 lupin pathogens. Whole-genome sequencing and comparative genomics are useful tools to discover genes responsible for interactions between pathogens and their hosts. Results Genomes were assembled for one isolate of B. cinerea and two isolates of S. sclerotiorum, which were isolated from either narrow-leafed or pearl lupin species. Comparative genomics analysis between lupin-derived isolates and others isolated from alternate hosts was used to predict between 94 to 98 effector gene candidates from among their respective non-conserved gene contents. Conclusions Detection of minor differences between relatively recently-diverged isolates, originating from distinct regions and with hosts, may highlight novel or recent gene mutations and losses resulting from host adaptation in broad host-range fungal pathogens. Electronic supplementary material The online version of this article (10.1186/s12864-019-5774-2) contains supplementary material, which is available to authorized users.

Plant diseases caused by fungal pathogens are typically initiated by molecular interactions between ‘effector’ molecules released by a pathogen and receptor molecules on or within the plant host cell. In many cases these effector-receptor interactions directly determine host resistance or susceptibility. The search for fungal effector proteins is a developing area in fungal-plant pathology, with more than 165 distinct confirmed fungal effector proteins in the public domain. For a small number of these, novel effectors can be rapidly discovered across multiple fungal species through the identification of known effector homologues. However, many have no detectable homology by standard sequence-based search methods. This study employs a novel comparison method (RemEff) that is capable of identifying protein families with greater sensitivity than traditional homology-inference methods, leveraging a growing pool of confirmed fungal effector data to enable the prediction of novel fungal effector candidates by protein family association. Resources relating to the RemEff method and data used in this study are available from https://figshare.com/projects/Effector_protein_remote_homology/87965.

The wheat pathogen Parastagonospora nodorum has emerged as a model necrotrophic fungal species with growing genomic resources. Recent population-level pan-genome studies were leveraged to provide novel insights into pathogen evolution and effector-like gene contents relevant to local crop disease outbreaks. In this study, we examined 156 isolates representing a regional population from the Western Australian (WA) wheat-belt region, and 17 internationally sourced isolates. We observed a highly diverse local population, within which were numerous small and highly similar clusters of isolates from hotter and drier regions. Pan-genome assembly and orthologous gene datasets resulted in 3579 predicted effector candidates, 2291 of which exhibited presence-absence variation (PAV) across the population, and 1362 were specific to WA isolates. There was an abundance of mutations (including repeat-induced point mutation (RIP)), distributed in ‘hot-spots’ within the pan-genomic landscape that were rich in effector candidates. Three characterised effector loci (ToxA, Tox1 and Tox3) were located within sub- telomeric regions of lower diversity, but were nestled within larger high-diversity regions. RIP was widespread across the genome, but non-synonymous RIP-like mutations were strongly selected against. These improved bioinformatic resources for P. nodorum, represent progressive advancements in fungal pan-genomics, with a view towards supporting region- specific surveillance of host-pathogen interactions.

Phytophthora cinnamomi is a pathogenic oomycete that causes plant dieback disease across a range of natural ecosystems and in many agriculturally important crops on a global scale. An annotated draft genome sequence and annotation is publicly available (JGI Mycocosm) and suggests 26,131 gene models. In this study, soluble mycelial, extracellular (secretome) and zoospore proteins of P. cinnamomi were exploited to refine the genome by correcting gene annotations and discovering novel genes. By implementing the diverse set of sub-proteomes into a generated proteogenomics pipeline, we were able to improve the P. cinnamomi genome. Liquid chromatography mass spectrometry was used to obtain high confidence peptides with spectral matching to both the annotated genome and a generated 6-frame translation. 2,764 annotations from the draft genome were confirmed by spectral matching. Using a proteogenomic pipeline, mass spectra were used to edit the P. cinnamomi genome and allowed identification of 23 new gene models and 60 edited gene features using high confidence peptides obtained by mass spectrometry, suggesting a rate of incorrect annotations of 3% of the detectable proteome. The novel features were further validated by total peptide support, alongside functional analysis including the use of Gene Ontology and functional domain identification. We demonstrated the use of spectral data in combination with our proteogenomics pipeline can be used to improve the genome of important plant diseases and identify biologically relevant missed genes. This study presents the first use of spectral data to edit and manually annotate an oomycete pathogen.

Background The fungus Parastagonospora nodorum causes septoria nodorum blotch (SNB) of wheat (Triticum aestivum) and is a model species for necrotrophic plant pathogens. The genome assembly of reference isolate Sn15 was first reported in 2007. P. nodorum infection is promoted by its production of proteinaceous necrotrophic effectors, three of which are characterised – ToxA, Tox1 and Tox3. Results A chromosome-scale genome assembly of P. nodorum Australian reference isolate Sn15, which combined long read sequencing, optical mapping and manual curation, produced 23 chromosomes with 21 chromosomes possessing both telomeres. New transcriptome data were combined with fungal-specific gene prediction techniques and manual curation to produce a high-quality predicted gene annotation dataset, which comprises 13,869 high confidence genes, and an additional 2534 lower confidence genes retained to assist pathogenicity effector discovery. Comparison to a panel of 31 internationally-sourced isolates identified multiple hotspots within the Sn15 genome for mutation or presence-absence variation, which was used to enhance subsequent effector prediction. Effector prediction resulted in 257 candidates, of which 98 higher-ranked candidates were selected for in-depth analysis and revealed a wealth of functions related to pathogenicity. Additionally, 11 out of the 98 candidates also exhibited orthology conservation patterns that suggested lateral gene transfer with other cereal-pathogenic fungal species. Analysis of the pan-genome indicated the smallest chromosome of 0.4 Mbp length to be an accessory chromosome (AC23). AC23 was notably absent from an avirulent isolate and is predominated by mutation hotspots with an increase in non-synonymous mutations relative to other chromosomes. Surprisingly, AC23 was deficient in effector candidates, but contained several predicted genes with redundant pathogenicity-related functions. Conclusions We present an updated series of genomic resources for P. nodorum Sn15 – an important reference isolate and model necrotroph – with a comprehensive survey of its predicted pathogenicity content.

‘Effectors’ are a broad class of cytotoxic or virulence-promoting molecules that are released from plant-pathogen cells to cause disease in their host. Fungal effectors are a core research area for improving host disease resistance; however, because they generally lack common distinguishing features or obvious sequence similarity, discovery of effectors remains a major challenge. This study presents a novel tool and pipeline for effector prediction - Predector - which interfaces with multiple software tools and methods, aggregates disparate features that are relevant to fungal effector proteins, and ranks effector candidate proteins using a pairwise learning to rank approach. Predector outperformed alternative effector prediction methods that were applied to a curated set of confirmed effectors derived from multiple species. We present Predector as a useful tool for the prediction and ranking of effector candidates, which aggregates and reports additional supporting information relevant to effector and secretome prediction in a simple, efficient, and reproducible manner. Predector is available from https://github.com/ccdmb/predector and associated data from https://github.com/ccdmb/predector-data.

Fungal plant-pathogens promote infection of their hosts through the release of ‘effectors’—a broad class of cytotoxic or virulence-promoting molecules. Effectors may be recognised by resistance or sensitivity receptors in the host, which can determine disease outcomes. Accurate prediction of effectors remains a major challenge in plant pathology, but if achieved will facilitate rapid improvements to host disease resistance. This study presents a novel tool and pipeline for the ranking of predicted effector candidates—Predector—which interfaces with multiple software tools and methods, aggregates disparate features that are relevant to fungal effector proteins, and applies a pairwise learning to rank approach. Predector outperformed a typical combination of secretion and effector prediction methods in terms of ranking performance when applied to a curated set of confirmed effectors derived from multiple species. We present Predector (https://github.com/ccdmb/predector) as a useful tool for the ranking of predicted effector candidates, which also aggregates and reports additional supporting information relevant to effector and secretome prediction in a simple, efficient, and reproducible manner.

In the absence of a primary crop host, secondary plant hosts may act as a reservoir for fungal plant pathogens of agricultural crops. Secondary hosts may potentially harbor heteroecious biotrophs (e.g., the stripe rust fungus Puccinia striiformis) or other pathogens with broad host ranges. Agricultural grain production tends toward monoculture or a limited number of crop hosts over large regions, and local weeds are a major source of potential secondary hosts. In this study, the fungal phyllospheres of 12 weed species common in the agricultural regions of Western Australia (WA) were compared through high-throughput DNA sequencing. Amplicons of D2 and ITS were sequenced on an Illumina MiSeq system using previously published primers and BLAST outputs analyzed using MEGAN. A heatmap of cumulative presence–absence for fungal taxa was generated, and variance patterns were investigated using principal components analysis (PCA) and canonical correspondence analysis (CCA). We observed the presence of several major international crop pathogens, including basidiomycete rusts of the Puccinia spp., and ascomycete phytopathogens of the Leptosphaeria and Pyrenophora genera. Unrelated to crop production, several endemic pathogen species including those infecting Eucalyptus trees were also observed, which was consistent with local native flora. We also observed that differences in latitude or climate zones appeared to influence the geographic distributions of plant pathogenic species more than the presence of compatible host species, with the exception of Brassicaceae host family. There was an increased proportion of necrotrophic Ascomycete species in warmer and drier regions of central WA, compared to an increased proportion of biotrophic Basidiomycete species in cooler and wetter regions in southern WA.

We report a fungal pan-genome study involving Parastagonospora spp., including 21 isolates of the wheat (Triticum aestivum) pathogen Parastagonospora nodorum, 10 of the grass-infecting Parastagonospora avenae, and 2 of a closely related undefined sister species. We observed substantial variation in the distribution of polymorphisms across the pan-genome, including repeat-induced point mutations, diversifying selection and gene gains and losses. We also discovered chromosome-scale inter and intraspecific presence/absence variation of some sequences, suggesting the occurrence of one or more accessory chromosomes or regions that may play a role in host-pathogen interactions. The presence of known pathogenicity effector loci SnToxA, SnTox1, and SnTox3 varied substantially among isolates. Three P. nodorum isolates lacked functional versions for all three loci, whereas three P. avenae isolates carried one or both of the SnTox1 and SnTox3 genes, indicating previously unrecognized potential for discovering additional effectors in the P. nodorum-wheat pathosystem. We utilized the pan-genomic comparative analysis to improve the prediction of pathogenicity effector candidates, recovering the three confirmed effectors among our top-ranked candidates. We propose applying this pan-genomic approach to identify the effector repertoire involved in other host-microbe interactions involving necrotrophic pathogens in the Pezizomycotina.

Key message This study revealed that the western Mediterranean provided the founder population for domesticated narrow-leafed lupin and that genetic diversity decreased significantly during narrow-leafed lupin domestication. Abstract The evolutionary history of plants during domestication profoundly shaped the genome structure and genetic diversity of today’s crops. Advances in next-generation sequencing technologies allow unprecedented opportunities to understand genome evolution in minor crops, which constitute the majority of plant domestications. A diverse set of 231 wild and domesticated narrow-leafed lupin (Lupinus angustifolius L.) accessions were subjected to genotyping-by-sequencing using diversity arrays technology. Phylogenetic, genome-wide divergence and linkage disequilibrium analyses were applied to identify the founder population of domesticated narrow-leafed lupin and the genome-wide effect of domestication on its genome. We found wild western Mediterranean population as the founder of domesticated narrow-leafed lupin. Domestication was associated with an almost threefold reduction in genome diversity in domesticated accessions compared to their wild relatives. Selective sweep analysis identified no significant footprints of selection around domestication loci. A genome-wide association study identified single nucleotide polymorphism markers associated with pod dehiscence. This new understanding of the genomic consequences of narrow-leafed lupin domestication along with molecular marker tools developed here will assist plant breeders more effectively access wild genetic diversity for crop improvement. Electronic supplementary material The online version of this article (10.1007/s00122-018-3171-x) contains supplementary material, which is available to authorized users.

The traditional classification of fungal and oomycete phytopathogens into three classes – biotrophs, hemibiotrophs, or necrotrophs – is unsustainable. This study highlights multiple phytopathogen species for which these labels have been inappropriately applied. We propose a novel and reproducible classification based solely on genome-derived analysis of carbohydrate-active enzyme (CAZyme) gene content called CAZyme-Assisted Training And Sorting of -trophy (CATAStrophy). CATAStrophy defines four major divisions for species associated with living plants. These are monomertrophs (Mo) (corresponding to biotrophs), polymertrophs (P) (corresponding to necrotrophs), mesotrophs (Me) (corresponding to hemibiotrophs), and vasculartrophs (including species commonly described as wilts, rots, or anthracnoses). The Mo class encompasses symbiont, haustorial, and non-haustorial species. Me are divided into the subclasses intracellular and extracellular Me, and the P into broad and narrow host sub-classes. This gives a total of seven discrete plant-pathogenic classes. The classification provides insight into the properties of these species and offers a facile route to develop control measures for newly recognized diseases. Software for CATAStrophy is available online at https://github.com/ccdmb/catastrophy. We present the CATAStrophy method for the prediction of trophic phenotypes based on CAZyme gene content, as a complementary method to the traditional tripartite “biotroph–hemibiotroph–necrotroph” classifications that may encourage renewed investigation and revision within the fungal biology community.

Summary Lupins are important grain legume crops that form a critical part of sustainable farming systems, reducing fertilizer use and providing disease breaks. It has a basal phylogenetic position relative to other crop and model legumes and a high speciation rate. Narrow‐leafed lupin (NLL; Lupinus angustifolius L.) is gaining popularity as a health food, which is high in protein and dietary fibre but low in starch and gluten‐free. We report the draft genome assembly (609 Mb) of NLL cultivar Tanjil, which has captured >98% of the gene content, sequences of additional lines and a dense genetic map. Lupins are unique among legumes and differ from most other land plants in that they do not form mycorrhizal associations. Remarkably, we find that NLL has lost all mycorrhiza‐specific genes, but has retained genes commonly required for mycorrhization and nodulation. In addition, the genome also provided candidate genes for key disease resistance and domestication traits. We also find evidence of a whole‐genome triplication at around 25 million years ago in the genistoid lineage leading to Lupinus. Our results will support detailed studies of legume evolution and accelerate lupin breeding programmes.

Rhizoctonia solani is an important root infecting pathogen of a range of food staples worldwide including wheat, rice, maize, soybean, potato, legumes and others. Conventional resistance breeding strategies are hindered by the absence of tractable genetic resistance in any crop host. Understanding the biology and pathogenicity mechanisms of this fungus is important for addressing these disease issues, however, little is known about how R. solani causes disease. The data described in this article is derived from applying mass spectrometry based proteomics to identify soluble, membrane-bound and culture filtrate proteins produced under wheat infection and vegetative growth conditions. Comparisons of the data for sample types in this set will be useful to identify metabolic pathway changes as the fungus switches from saprophytic to a pathogenic lifestyle or pathogenicity related proteins contributing to the ability to cause disease on wheat. The data set is deposited in the PRIDE archive under identifier PRIDE: PXD002806. Keywords: Fungal pathogenesis, Wheat, Rhizoctonia solani, Basidiomycete

We present a novel method to measure the local GC-content bias in genomes and a survey of published fungal species. The method, enacted as “OcculterCut” (https://sourceforge.net/projects/occultercut, last accessed April 30, 2016), identified species containing distinct AT-rich regions. In most fungal taxa, AT-rich regions are a signature of repeat-induced point mutation (RIP), which targets repetitive DNA and decreases GC-content though the conversion of cytosine to thymine bases. RIP has in turn been identified as a driver of fungal genome evolution, as RIP mutations can also occur in single-copy genes neighboring repeat-rich regions. Over time RIP perpetuates “two speeds” of gene evolution in the GC-equilibrated and AT-rich regions of fungal genomes. In this study, genomes showing evidence of this process are found to be common, particularly among the Pezizomycotina. Further analysis highlighted differences in amino acid composition and putative functions of genes from these regions, supporting the hypothesis that these regions play an important role in fungal evolution. OcculterCut can also be used to identify genes undergoing RIP-assisted diversifying selection, such as small, secreted effector proteins that mediate host-microbe disease interactions.

Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified

The pathogenic fungus Sclerotinia sclerotiorum infects over 600 species of plant. It is present in numerous environments throughout the world and causes significant damage to many agricultural crops. Fragmentation and lack of gene flow between populations may lead to population sub-structure. Within discrete recombining populations, positive selection may lead to a ‘selective sweep’. This is characterised by an increase in frequency of a favourable allele leading to reduction in genotypic diversity in a localised genomic region due to the phenomenon of genetic hitchhiking. We aimed to assess whether isolates of S. sclerotiorum from around the world formed genotypic clusters associated with geographical origin and to determine whether signatures of population-specific positive selection could be detected. To do this, we sequenced the genomes of 25 isolates of S. sclerotiorum collected from four different continents–Australia, Africa (north and south), Europe and North America (Canada and the northen United States) and conducted SNP based analyses of population structure and selective sweeps. Among the 25 isolates, there was evidence for two major population clusters. One of these consisted of 11 isolates from Canada, the USA and France (population 1), and the other consisted of nine isolates from Australia and one from Morocco (population 2). The rest of the isolates were genotypic outliers. We found that there was evidence of outcrossing in these two populations based on linkage disequilibrium decay. However, only a single candidate selective sweep was observed, and it was present in population 2. This sweep was close to a Major Facilitator Superfamily transporter gene, and we speculate that this gene may have a role in nutrient uptake from the host. The low abundance of selective sweeps in the S. sclerotiorum genome contrasts the numerous examples in the genomes of other fungal pathogens. This may be a result of its slow rate of evolution and low effective recombination rate due to self-fertilisation and vegetative reproduction.

The pathogenic fungus Sclerotinia sclerotiorum infects over 600 species of plant. It is present in numerous environments throughout the world and causes significant damage to many agricultural crops. Fragmentation and lack of gene flow between populations may lead to population sub-structure. Within discrete recombining populations, positive selection may lead to a ‘selective sweep’. This is characterised by an increase in frequency of a favourable allele leading to reduction in genotypic diversity in a localised genomic region due to the phenomenon of genetic hitchhiking.We aimed to assess whether isolates of S. sclerotiorum from around the world formed genotypic clusters associated with geographical origin and to determine whether signatures of population-specific positive selection could be detected. To do this, we sequenced the genomes of 25 isolates of S. sclerotiorum collected from four different continents - Australia, Africa (north and south), Europe and North America (Canada and the northen United States) and conducted SNP based analyses of population structure and selective sweeps.Among the 25 isolates, there was evidence for four population clusters. One of these consisted of 11 isolates from Canada, the USA and France (population 1), another consisted of five isolates from Australia and one from Morocco (population 2). A further cluster was made up of Australian isolates, and the single South African isolate appeared to be from a separate population. We found that there was evidence of distinct selective sweeps between population 1 and population 2. Many of these sweeps overlapped genes involved in transcriptional regulation, such as transcription factors. It is possible that distinct populations of S. sclerotiorum from differing global environments have undergone selective sweeps at different genomic loci. This study lays the foundation for further work into investigation of the differing selective pressures that S. sclerotiorum populations are subjected to on a global scale.

Background Pyrenophora tritici-repentis (Ptr) is a necrotrophic fungal pathogen that causes the major wheat disease, tan spot. We set out to provide essential genomics-based resources in order to better understand the pathogenicity mechanisms of this important pathogen. Results Here, we present eight new Ptr isolate genomes, assembled and annotated; representing races 1, 2 and 5, and a new race. We report a high quality Ptr reference genome, sequenced by PacBio technology with Illumina paired-end data support and optical mapping. An estimated 98% of the genome coverage was mapped to 10 chromosomal groups, using a two-enzyme hybrid approach. The final reference genome was 40.9 Mb and contained a total of 13,797 annotated genes, supported by transcriptomic and proteogenomics data sets. Conclusions Whole genome comparative analysis revealed major chromosomal segmental rearrangements and fusions, highlighting intraspecific genome plasticity in this species. Furthermore, the Ptr race classification was not supported at the whole genome level, as phylogenetic analysis did not cluster the ToxA producing isolates. This expansion of available Ptr genomics resources will directly facilitate research aimed at controlling tan spot disease. Electronic supplementary material The online version of this article (10.1186/s12864-018-4680-3) contains supplementary material, which is available to authorized users.

Fungal pathogen genomes can often be divided into core and accessory regions. Accessory regions ARs) may be comprised of either ARs (within core chromosomes (CCs) or wholly dispensable (accessory) chromosomes (ACs). Fungal ACs and ARs typically accumulate mutations and structural rearrangements more rapidly over time than CCs and many harbor genes relevant to host-pathogen interactions. These regions are of particular interest in plant pathology and include host-specific virulence factors and secondary metabolite synthesis gene clusters. This review outlines known ACs and ARs in fungal genomes, methods used for their detection, their common properties that differentiate them from the core genome, and what is currently known of their various roles in pathogenicity. Reports on the evolutionary processes generating and shaping AC and AR compartments are discussed, including repeat induced point mutation and breakage fusion bridge cycles. Previously ACs have been studied extensively within key genera, including Fusarium, Zymoseptoria, and Alternaria, but are growing in frequency of observation and perceived importance across a wider range of fungal species. Recent advances in sequencing technologies permit affordable genome assembly and resequencing of populations that will facilitate further discovery and routine screening of ACs.

Zymoseptoria tritici (syn. Mycosphaerella graminicola, Septoria tritici) is a haploid fungus belonging to the class Dothideomycetes. It is the causal agent of septoria leaf blotch – one of the world’s most significant diseases of wheat. Here we review the genomic and bioinformatic resources that have been generated for Z. tritici. These include the whole-genome reference assembly for isolate IPO323, genome resequencing of alternate isolates, mitochondrial genome sequences, transcriptome sequences and expression data, and annotations of gene structure and function. We also highlight important advances in our fundamental knowledge of genome evolution and its effects on adaptation and pathogenicity in Z. tritici that have been facilitated by these resources.

Key message This first pan-Mediterranean analysis of genetic diversity in wild narrow-leafed lupin revealed strong East–West genetic differentiation of populations, an historic eastward migration, and signatures of genetic adaptation to climatic variables. Abstract Most grain crops suffer from a narrow genetic base, which limits their potential for adapting to new challenges such as increased stresses associated with climate change. Plant breeders are returning to the wild ancestors of crops and their close relatives to broaden the genetic base of their crops. Understanding the genetic adaptation of these wild relatives will help plant breeders most effectively use available wild diversity. Here, we took narrow-leafed lupin (Lupinus angustifolius L.) as a model to understand adaptation in a wild crop ancestor. A set of 142 wild accessions of narrow-leafed lupin from across the Mediterranean basin were subjected to genotyping-by-sequencing using Diversity Arrays Technology. Phylogenetic, linkage disequilibrium and demographic analyses were employed to explore the history of narrow-leafed lupin within the Mediterranean region. We found strong genetic differentiation between accessions from the western and eastern Mediterranean, evidence of an historic West to East migration, and that eastern Mediterranean narrow-leafed lupin experienced a severe and recent genetic bottleneck. We showed that these two populations differ for flowering time as a result of local adaptation, with the West flowering late while the East flowers early. A genome-wide association study identified single nucleotide polymorphism markers associated with climatic adaptation. Resolving the origin of wild narrow-leafed lupin and how its migration has induced adaptation to specific regions of the Mediterranean serves as a useful resource not only for developing narrow-leafed lupin cultivars with greater resilience to a changing climate, but also as a model which can be applied to other legumes. Electronic supplementary material The online version of this article (10.1007/s00122-017-3045-7) contains supplementary material, which is available to authorized users.

Our agricultural system and hence food security is threatened by combination of events, such as increasing population, the impacts of climate change, and the need to a more sustainable development. Evolutionary adaptation may help some species to overcome environmental changes through new selection pressures driven by climate change. However, success of evolutionary adaptation is dependent on various factors, one of which is the extent of genetic variation available within species. Genomic approaches provide an exceptional opportunity to identify genetic variation that can be employed in crop improvement programs. In this review, we illustrate some of the routinely used genomics‐based methods as well as recent breakthroughs, which facilitate assessment of genetic variation and discovery of adaptive genes in legumes. Although additional information is needed, the current utility of selection tools indicate a robust ability to utilize existing variation among legumes to address the challenges of climate uncertainty., Agriculture is facing a combination of factors that threaten global food security. In this review, we discuss some of the routinely used genomics‐based methods as well as recent breakthroughs that can help adapt legume crops to climate change by facilitating assessment of genetic variation and discovery of adaptive genes.

Effector proteins are important virulence factors of fungal plant pathogens and their prediction largely relies on bioinformatic methods. In this review we outline the current methods for the prediction of fungal plant pathogenicity effector proteins. Some fungal effectors have been characterised and are represented by conserved motifs or in sequence repositories, however most fungal effectors do not generally exhibit high conservation of amino acid sequence. Therefore various predictive methods have been developed around: general properties, structure, position in the genomic landscape, and detection of mutations including repeat-induced point mutations and positive selection. A combinatorial approach incorporating several of these methods is often employed and candidates can be prioritised by either ranked scores or hierarchical clustering.

Rhizoctonia solani is a fungal pathogen causing substantial damage to many of the worlds’ largest food crops including wheat, rice, maize and soybean. Despite impacting global food security, little is known about the pathogenicity mechanisms employed by R. solani. To enable prediction of effectors possessing either broad efficacy or host specificity, a combined secretome was constructed from a monocot specific isolate, a dicot specific isolate and broad host range isolate infecting both monocot and dicot hosts. Secretome analysis suggested R. solani employs largely different virulence mechanisms to well-studied pathogens, despite in many instances infecting the same host plants. Furthermore, the secretome of the broad host range AG8 isolate may be shaped by maintaining functions for saprophytic life stages while minimising opportunities for host plant recognition. Analysis of possible co-evolution with host plants and in-planta up-regulation in particular, aided identification of effectors including xylanase and inhibitor I9 domain containing proteins able to induce cell death in-planta. The inhibitor I9 domain was more abundant in the secretomes of a wide range of necrotising fungi relative to biotrophs. These findings provide novel targets for further dissection of the virulence mechanisms and potential avenues to control this under-characterised but important pathogen.

Narrow-leafed lupin (NLL; Lupinus angustifolius L.) is an important grain legume crop that is valuable for sustainable farming and is becoming recognized as a human health food. NLL breeding is directed at improving grain production, disease resistance, drought tolerance and health benefits. However, genetic and genomic studies have been hindered by a lack of extensive genomic resources for the species. Here, the generation, de novo assembly and annotation of transcriptome datasets derived from five different NLL tissue types of the reference accession cv. Tanjil are described. The Tanjil transcriptome was compared to transcriptomes of an early domesticated cv. Unicrop, a wild accession P27255, as well as accession 83A:476, together being the founding parents of two recombinant inbred line (RIL) populations. In silico predictions for transcriptome-derived gene-based length and SNP polymorphic markers were conducted and corroborated using a survey assembly sequence for NLL cv. Tanjil. This yielded extensive indel and SNP polymorphic markers for the two RIL populations. A total of 335 transcriptome-derived markers and 66 BAC-end sequence-derived markers were evaluated, and 275 polymorphic markers were selected to genotype the reference NLL 83A:476 × P27255 RIL population. This significantly improved the completeness, marker density and quality of the reference NLL genetic map.

Stagonospora nodorum is an important wheat (Triticum aestivum) pathogen in many parts of the world, causing major yield losses. It was the first species in the large fungal Dothideomycete class to be genome sequenced. The reference genome sequence (SN15) has been instrumental in the discovery of genes encoding necrotrophic effectors that induce disease symptoms in specific host genotypes. Here we present the genome sequence of two further S. nodorum strains (Sn4 and Sn79) that differ in their effector repertoire from the reference. Sn79 is avirulent on wheat and produces no apparent effectors when infiltrated onto many cultivars and mapping population parents. Sn4 is pathogenic on wheat and has virulences not found in SN15. The new strains, sequenced with short-read Illumina chemistry, are compared with SN15 by a combination of mapping and de novo assembly approaches. Each of the genomes contains a large number of strain-specific genes, many of which have no meaningful similarity to any known gene. Large contiguous sections of the reference genome are absent in the two newly sequenced strains. We refer to these differences as “sectional gene absences.” The presence of genes in pathogenic strains and absence in Sn79 is added to computationally predicted properties of known proteins to produce a list of likely effector candidates. Transposon insertion was observed in the mitochondrial genomes of virulent strains where the avirulent strain retained the likely ancestral sequence. The study suggests that short-read enabled comparative genomics is an effective way to both identify new S. nodorum effector candidates and to illuminate evolutionary processes in this species.

Pyrenophora tritici-repentis is a necrotrophic fungus causal to the disease tan spot of wheat, whose contribution to crop loss has increased significantly during the last few decades. Pathogenicity by this fungus is attributed to the production of host-selective toxins (HST), which are recognized by their host in a genotype-specific manner. To better understand the mechanisms that have led to the increase in disease incidence related to this pathogen, we sequenced the genomes of three P. tritici-repentis isolates. A pathogenic isolate that produces two known HSTs was used to assemble a reference nuclear genome of approximately 40 Mb composed of 11 chromosomes that encode 12,141 predicted genes. Comparison of the reference genome with those of a pathogenic isolate that produces a third HST, and a nonpathogenic isolate, showed the nonpathogen genome to be more diverged than those of the two pathogens. Examination of gene-coding regions has provided candidate pathogen-specific proteins and revealed gene families that may play a role in a necrotrophic lifestyle. Analysis of transposable elements suggests that their presence in the genome of pathogenic isolates contributes to the creation of novel genes, effector diversification, possible horizontal gene transfer events, identified copy number variation, and the first example of transduplication by DNA transposable elements in fungi. Overall, comparative analysis of these genomes provides evidence that pathogenicity in this species arose through an influx of transposable elements, which created a genetically flexible landscape that can easily respond to environmental changes.

The wheat pathogen Stagonospora nodorum, causal organism of the wheat disease Stagonospora nodorum blotch, has emerged as a model for the Dothideomycetes, a large fungal taxon that includes many important plant pathogens. The initial annotation of the genome assembly included 16 586 nuclear gene models. These gene models were used to design a microarray that has been interrogated with labelled transcripts from six cDNA samples: four from infected wheat plants at time points spanning early infection to sporulation, and two time points taken from growth in artificial media. Positive signals of expression were obtained for 12 281 genes. This represents strong corroborative evidence of the validity of these gene models. Significantly differential expression between the various time points was observed. When infected samples were compared with axenic cultures, 2882 genes were expressed at a higher level in planta and 3630 were expressed more highly in vitro. Similar numbers were differentially expressed between different developmental stages. The earliest time points in planta were particularly enriched in differentially expressed genes. A disproportionate number of the early expressed gene products were predicted to be secreted, but otherwise had no obvious sequence homology to functionally characterized genes. These genes are candidate necrotrophic effectors. We have focused attention on genes for carbohydrate metabolism and the specific biosynthetic pathways active during growth in planta. The analysis points to a very dynamic adjustment of metabolism during infection. Functional analysis of a gene in the coenzyme A biosynthetic pathway showed that the enzyme was dispensable for growth, indicating that a precursor is supplied by the plant.

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Here, we report on the use of quantitative PCR (qPCR) to determine gene copy number in filamentous fungi. Using the sequenced dothideomycete Stagonospora nodorum, qPCR was used to unequivocally confirm the presence of single, two and three copy regions as predicted by in silico PCR. Further validation of the technique was demonstrated by verifying the copy numbers of introduced gene cassettes in previously characterised transformants of S. nodorum. Apart from increased sensitivity, this technique offers a high-throughput alternative to Southern blots for determining gene copy number, a

Parastagonospora nodorum, the causal agent of Septoria nodorum blotch (SNB), is an economically important pathogen of wheat (Triticum spp.), and a model for the study of necrotrophic pathology and genome evolution. The reference P. nodorum strain SN15 was the first Dothideomycete with a published genome sequence, and has been used as the basis for comparison within and between species. Here we present an updated reference genome assembly with corrections of SNP and indel errors in the underlying genome assembly from deep resequencing data as well as extensive manual annotation of gene models using transcriptomic and proteomic sources of evidence (https://github.com/robsyme/Parastagonospora_nodorum_SN15). The updated assembly and annotation includes 8,366 genes with modified protein sequence and 866 new genes. This study shows the benefits of using a wide variety of experimental methods allied to expert curation to generate a reliable set of gene models.

Background Soil-borne fungi of the Fusarium oxysporum species complex cause devastating wilt disease on many crops including legumes that supply human dietary protein needs across many parts of the globe. We present and compare draft genome assemblies for three legume-infecting formae speciales (ff. spp.): F. oxysporum f. sp. ciceris (Foc-38-1) and f. sp. pisi (Fop-37622), significant pathogens of chickpea and pea respectively, the world’s second and third most important grain legumes, and lastly f. sp. medicaginis (Fom-5190a) for which we developed a model legume pathosystem utilising Medicago truncatula. Results Focusing on the identification of pathogenicity gene content, we leveraged the reference genomes of Fusarium pathogens F. oxysporum f. sp. lycopersici (tomato-infecting) and F. solani (pea-infecting) and their well-characterised core and dispensable chromosomes to predict genomic organisation in the newly sequenced legume-infecting isolates. Dispensable chromosomes are not essential for growth and in Fusarium species are known to be enriched in host-specificity and pathogenicity-associated genes. Comparative genomics of the publicly available Fusarium species revealed differential patterns of sequence conservation across F. oxysporum formae speciales, with legume-pathogenic formae speciales not exhibiting greater sequence conservation between them relative to non-legume-infecting formae speciales, possibly indicating the lack of a common ancestral source for legume pathogenicity. Combining predicted dispensable gene content with in planta expression in the model legume-infecting isolate, we identified small conserved regions and candidate effectors, four of which shared greatest similarity to proteins from another legume-infecting ff. spp. Conclusions We demonstrate that distinction of core and potential dispensable genomic regions of novel F. oxysporum genomes is an effective tool to facilitate effector discovery and the identification of gene content possibly linked to host specificity. While the legume-infecting isolates didn’t share large genomic regions of pathogenicity-related content, smaller regions and candidate effector proteins were highly conserved, suggesting that they may play specific roles in inducing disease on legume hosts. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2486-8) contains supplementary material, which is available to authorized users.

The first predominantly gene-based genetic linkage map of lentil (Lens culinaris ssp. culinaris) was constructed using an F5 population developed from a cross between the cultivars Digger (ILL5722) and Northfield (ILL5588) using 79 intron-targeted amplified polymorphic (ITAP) and 18 genomic simple sequence repeat (SSR) markers. Linkage analysis revealed seven linkage groups (LGs) comprised of 5-25 markers that varied in length from 80.2 to 274.6 cM. The genome map spanned a total length of 928.4 cM. Clear evidence of a simple and direct macrosyntenic relationship between lentil and Medicago truncatula was observed. Sixty-six out of the 71 gene-based markers, which were previously assigned to M. truncatula genetic and physical maps, were found in regions syntenic between the Lens c. ssp. culinaris and M. truncatula genomes. However, there was evidence of moderate chromosomal rearrangements which may account for the difference in chromosome numbers between these two legume species. Eighteen common SSR markers were used to connect the current map with the most comprehensive and recent map that exists for lentil, providing the syntenic context of four important domestication traits. The composite map presented, anchored with orthologous markers mapped in M. truncatula, provides a strong foundation for the future use of genomic and genetic information in lentil genetic analysis and breeding.

We report the first gene-based linkage map of Lupinus angustifolius (narrow-leafed lupin) and its comparison to the partially sequenced genome of Medicago truncatula. The map comprises 382 loci in 20 major linkage groups, two triplets, three pairs and 11 unlinked loci and is 1,846 cM in length. The map was generated from the segregation of 163 RFLP markers, 135 gene-based PCR markers, 75 AFLP and 4 AFLP-derived SCAR markers in a mapping population of 93 recombinant inbred lines, derived from a cross between domesticated and wild-type parents. This enabled the mapping of five major genes controlling key domestication traits in L. angustifolius. Using marker sequence data, the L. angustifolius genetic map was compared to the partially completed M. truncatula genome sequence. We found evidence of conserved synteny in some regions of the genome despite the wide evolutionary distance between these legume species. We also found new evidence of widespread duplication within the L. angustifolius genome.

The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available ( https://sourceforge.net/projects/codingquarry/ ), and suitable for incorporation into genome annotation pipelines.

Repeat-induced point mutation (RIP) is a form of genome mutation that is targeted towards repeated DNA sequences and which is observed only in certain fungal taxa; the Pezizomycotina (filamentous Ascomycota) and some species of the Basidiomycota. RIP is widely believed to have evolved to protect fungal genomes against transposon replication.