EffectorP: predicting fungal effector proteins from secretomes using machine learning

Whole-body transcriptome mining for candidate effectors from Diuraphis noxia

Background

Proteins within aphid saliva play a crucial role as the molecular interface between aphids and their host plants. These salivary effectors modulate plant responses to favour aphid feeding and facilitate infestation. The identification of effectors from economically important pest species is central in understanding the molecular events during the aphid-plant interaction. The Russian wheat aphid (Diuraphis noxia, Kurdjumov) is one such pest that causes devastating losses to wheat and barley yields worldwide. Despite the severe threat to food security posed by D. noxia, the non-model nature of this pest and its host has hindered progress towards understanding this interaction. In this study, in the absence of a salivary gland transcriptome, whole-body transcriptomics data was mined to generate a candidate effector catalogue for D. noxia.

Results

Mining the transcriptome identified 725 transcripts encoding putatively secreted proteins amongst which were transcripts specific to D. noxia. Six of the seven examined D. noxia putative effectors, termed DnE’s (Diuraphis noxia effectors) exhibited salivary gland-specific expression. A comparative analysis between whole-body D. noxia transcriptome data versus the head and body transcriptomes from three other aphid species allowed us to define a catalogue of transcripts putatively upregulated in D. noxia head tissue. Five of these were selected for RT-qPCR confirmation, and were found to corroborate the differential expression predictions, with a further three confirmed to be highly expressed in D. noxia salivary gland tissue.

Conclusions

Determining a putative effector catalogue for D. noxia from whole-transcriptome data, particularly the identification of salivary-specific sequences potentially unique to D. noxia, provide the basis for future functional characterisation studies to gain further insight into this aphid-plant interaction. Furthermore, due to a lack of publicly available aphid salivary gland transcriptome data, the capacity to use comparative transcriptomics to compile a list of putative effector candidates from whole-body transcriptomics data will further the study of effectors in various aphid species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08712-4.

Using a Hybrid Mapping Population to Identify Genomic Regions of Pyrenophora teres Associated With Virulence

Net blotches caused by Pyrenophora teres are important foliar fungal diseases of barley and result in significant yield losses of up to 40%. The two types of net blotch, net-form net blotch and spot-form net blotch, are caused by P. teres f. teres (Ptt) and P. teres f. maculata (Ptm), respectively. This study is the first to use a cross between Ptt and Ptm to identify quantitative trait loci (QTL) associated with virulence and leaf symptoms. A genetic map consisting of 1,965 Diversity Arrays Technology (DArT) markers was constructed using 351 progenies of the Ptt/Ptm cross. Eight barley cultivars showing differential reactions to the parental isolates were used to phenotype the hybrid progeny isolates. Five QTL associated with virulence and four QTL associated with leaf symptoms were identified across five linkage groups. Phenotypic variation explained by these QTL ranged from 6 to 16%. Further phenotyping of selected progeny isolates on 12 more barley cultivars revealed that three progeny isolates are moderately to highly virulent across these cultivars. The results of this study suggest that accumulation of QTL in hybrid isolates can result in enhanced virulence.

Identification of Pathogenicity-Related Effector Proteins and the Role of Piwsc1 in the Virulence of Penicillium italicum on Citrus Fruits

Blue mold caused by Penicillium italicum is one of the two major postharvest diseases of citrus fruits. The interactions of pathogens with their hosts are complicated, and virulence factors that mediate pathogenicity have not yet been identified. In present study, a prediction pipeline approach based on bioinformatics and transcriptomic data is designed to determine the effector proteins of P. italicum. Three hundred and seventy-five secreted proteins of P. italicum were identified, many of which (29.07%) were enzymes for carbohydrate utilization. Twenty-nine candidates were further analyzed and the expression patterns of 12 randomly selected candidate effector genes were monitored during the early stages of growth on PDA and infection of Navel oranges for validation. Functional analysis of a cell wall integrity-related gene Piwsc1, a core candidate, was performed by gene knockout. The deletion of Piwsc1 resulted in reduced virulence on citrus fruits, as presented by an approximate 57% reduction in the diameter of lesions. In addition, the mycelial growth rate, spore germination rate, and sporulation of ΔPiwsc1 decreased. The findings provide us with new insights to understand the pathogenesis of P. italicum and develop an effective and sustainable control method for blue mold.

Comparative Genomic Analyses Provide Insight Into the Pathogenicity of Metschnikowia bicuspidata LNES0119

Metschnikowia bicuspidata is a globally distributed pathogenic yeast with a wide range of aquatic hosts. A new strain, M. bicuspidata LNES0119, isolated from the Chinese mitten crab Eriocheir sinensis, has caused a serious reduction in production and marked economic loss for the aquaculture industry in China. Therefore, the whole-genome sequence of M. bicuspidata LNES0119 was sequenced using Illumina and Oxford Nanopore technology; whole-genome annotation and comparative genomic analyses of this pathogen were performed as well. A high-quality genome of M. bicuspidata LNES0119 was 16.13 Mb in size, with six scaffolds and six contigs, and encoded 5,567 putative predicted genes. Of these, 1,467 genes shared substantial homology with genes in the pathogen–host interactions database. Comparative genomic analyses of three M. bicuspidata strains and one non-pathogenic yeast, M. aff. pulcherrima, showed 331 unique genes in M. bicuspidata LNES0119, 30 of which were putatively related to pathogenicity. Overall, we identified several meaningful characteristics related to pathogenicity and virulence that may play essential roles in the infection and pathogenicity of M. bicuspidata LNES0119. Our study will aid in identifying potential targets for further exploration of the molecular basis of the pathogenicity of M. bicuspidata as well as the therapeutic intervention of M. bicuspidata infection.

Infection Strategies and Pathogenicity of Biotrophic Plant Fungal Pathogens

Biotrophic plant pathogenic fungi are widely distributed and are among the most damaging pathogenic organisms of agriculturally important crops responsible for significant losses in quality and yield. However, the pathogenesis of obligate parasitic pathogenic microorganisms is still under investigation because they cannot reproduce and complete their life cycle on an artificial medium. The successful lifestyle of biotrophic fungal pathogens depends on their ability to secrete effector proteins to manipulate or evade plant defense response. By integrating genomics, transcriptomics, and effectoromics, insights into how the adaptation of biotrophic plant fungal pathogens adapt to their host populations can be gained. Efficient tools to decipher the precise molecular mechanisms of rust–plant interactions, and standardized routines in genomics and functional pipelines have been established and will pave the way for comparative studies. Deciphering fungal pathogenesis not only allows us to better understand how fungal pathogens infect host plants but also provides valuable information for plant diseases control, including new strategies to prevent, delay, or inhibit fungal development. Our review provides a comprehensive overview of the efforts that have been made to decipher the effector proteins of biotrophic fungal pathogens and demonstrates how rapidly research in the field of obligate biotrophy has progressed.

Comparative Genomics of Fusarium circinatum Isolates Used to Screen Southern Pines for Pitch Canker Resistance

Pitch canker, caused by the fungal pathogen Fusarium circinatum, is a global disease affecting many Pinus spp. Often fatal, this disease causes significant mortality in both commercially grown and natural pine forests and is an issue of current and growing concern. F. circinatum isolates collected from three locations in the U.S. state of Florida were shown to be virulent on both slash and loblolly pine, with two of the isolates causing equivalent and significantly larger lesions than those caused by the third isolate during pathogenicity trials. In addition, significant genetic variation in lesion length in the pedigreed slash pine population was evident and rankings of parents for lesion length were similar across isolates. Experimental data demonstrate that both host and pathogen genetics contribute to disease severity. High-quality genomic assemblies of all three isolates were created and compared for structural differences and gene content. No major structural differences were observed among the isolates; however, missing or altered genes do contribute to genomic variation in the pathogen population. This work evaluates in planta virulence among three isolates of F. circinatum, provides genomic resources to facilitate study of this organism, and details comparative genomic methods that may be used to explore the pathogen's contribution to disease development.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Effector-GAN: prediction of fungal effector proteins based on pretrained deep representation learning methods and generative adversarial networks

MOTIVATION

Phytopathogenic fungi secrete effector proteins to subvert host defenses and facilitate infection. Systematic analysis and prediction of candidate fungal effector proteins is crucial for experimental validation and biological control of plant disease. However, two problems are still considered intractable to be solved in fungal effector prediction: one is the high-level diversity in effector sequences that increases the difficulty of protein feature learning, and the other is the class imbalance between effector and non-effector samples in the training dataset.

RESULTS

In our study, pretrained deep representation learning methods are presented to represent multiple characteristics of sequences for predicting fungal effectors and generative adversarial networks are adapted to create synthetic feature samples to address the data imbalance problem. Compared with the state-of-the-art fungal effector prediction methods, Effector-GAN shows an overall improvement in accuracy in the independent test set.

AVAILABILITY AND IMPLEMENTATION

Effector-GAN offers a user-friendly interface to inspect potential fungal effector proteins (http://lab.malab.cn/~wys/webserver/Effector-GAN). The Python script can be downloaded from http://lab.malab.cn/~wys/gitlab/effector-gan.

RFPDR: a random forest approach for plant disease resistance protein prediction

Background

Plant innate immunity relies on a broad repertoire of receptor proteins that can detect pathogens and trigger an effective defense response. Bioinformatic tools based on conserved domain and sequence similarity are within the most popular strategies for protein identification and characterization. However, the multi-domain nature, high sequence diversity and complex evolutionary history of disease resistance (DR) proteins make their prediction a real challenge. Here we present RFPDR, which pioneers the application of Random Forest (RF) for Plant DR protein prediction.

Methods

A recently published collection of experimentally validated DR proteins was used as a positive dataset, while 10x10 nested datasets, ranging from 400-4,000 non-DR proteins, were used as negative datasets. A total of 9,631 features were extracted from each protein sequence, and included in a full dimension (FD) RFPDR model. Sequence selection was performed, to generate a reduced-dimension (RD) RFPDR model. Model performances were evaluated using an 80/20 (training/testing) partition, with 10-cross fold validation, and compared to baseline, sequence-based and state-of-the-art strategies. To gain some insights into the underlying biology, the most discriminatory sequence-based features in the RF classifier were identified.

Results and Discussion

RD-RFPDR showed to be sensitive (86.4 ± 4.0%) and specific (96.9 ± 1.5%) for identifying DR proteins, while robust to data imbalance. Its high performance and robustness, added to the fact that RD-RFPDR provides valuable information related to DR proteins underlying properties, make RD-RFPDR an interesting approach for DR protein prediction, complementing the state-of-the-art strategies.

Pangenome Analysis of the Soilborne Fungal Phytopathogen Rhizoctonia solani and Development of a Comprehensive Web Resource: RsolaniDB

Rhizoctonia solani is a collective group of genetically and pathologically diverse basidiomycetous fungi that damage economically important crops. Its isolates are classified into 13 Anastomosis Groups (AGs) and subgroups having distinctive morphology and host ranges. The genetic factors driving the unique features of R. solani pathology are not well characterized due to the limited availability of its annotated genomes. Therefore, we performed genome sequencing, assembly, annotation and functional analysis of 12 R. solani isolates covering 7 AGs and select subgroups (AG1-IA; AG1-IB; AG1-IC; AG2-2IIIB; AG3-PT, isolates Rhs 1AP and the hypovirulent Rhs1A1; AG3-TB; AG4-HG-I, isolates Rs23 and R118-11; AG5; AG6; and AG8), in which six genomes are reported for the first time. Using a pangenome comparative analysis of 12 R. solani isolates and 15 other Basidiomycetes, we defined the unique and shared secretomes, CAZymes, and effectors across the AGs. We have also elucidated the R. solani-derived factors potentially involved in determining AG-specific host preference, and the attributes distinguishing them from other Basidiomycetes. Finally, we present the largest repertoire of R. solani genomes and their annotated components as a comprehensive database, viz. RsolaniDB, with tools for large-scale data mining, functional enrichment and sequence analysis not available with other state-of-the-art platforms.

Root-associated microbiota drive phytoremediation strategies to lead of Sonchus Asper (L.) Hill as revealed by intercropping-induced modifications of the rhizosphere microbiome

Intercropping or assistant endophytes promote phytoremediation capacities of hyperaccumulators and enhance their tolerance to heavy metal (HM) stress. Findings from a previous study showed that intercropping the hyperaccumulator Sonchus asper (L.) Hill grown in HM-contaminated soils with maize improved the remediating properties and indicated an excluder-to-hyperaccumulator switched mode of action towards lead. In the current study, RNA-Seq analysis was conducted on Sonchus roots grown under intercropping or monoculture systems to explore the molecular events underlying this shift in lead sequestering strategy. The findings showed that intercropping only slightly affects S. asper transcriptome but significantly affects expression of root-associated microbial genomes. Further, intercropping triggers significant reshaping of endophytic communities associated with a 'root-to-shoot' transition of lead sequestration and improved phytoremediation capacities of S. asper. These findings indicate that accumulator activities of a weed are partially attributed to the root-associated microbiota, and a complex network of plant-microbe-plant interactions shapes the phytoremediation potential of S. asper. Analysis showed that intercropping may significantly change the structure of root-associated communities resulting in novel remediation properties, thus providing a basis for improving phytoremediation practices to restore contaminated soils.

A chromosome-scale genome assembly of the tomato pathogen Cladosporium fulvum reveals a compartmentalized genome architecture and the presence of a dispensable chromosome

Cladosporium fulvum is a fungal pathogen that causes leaf mould of tomato. The reference genome of this pathogen was released in 2012 but its high repetitive DNA content prevented a contiguous assembly and further prohibited the analysis of its genome architecture. In this study, we combined third generation sequencing technology with the Hi-C chromatin conformation capture technique, to produce a high-quality and near complete genome assembly and gene annotation of a Race 5 isolate of C. fulvum. The resulting genome assembly contained 67.17 Mb organized into 14 chromosomes (Chr1-to-Chr14), all of which were assembled telomere-to-telomere. The smallest of the chromosomes, Chr14, is only 460 kb in size and contains 25 genes that all encode hypothetical proteins. Notably, PCR assays revealed that Chr14 was absent in 19 out of 24 isolates of a world-wide collection of C. fulvum, indicating that Chr14 is dispensable. Thus, C. fulvum is currently the second species of Capnodiales shown to harbour dispensable chromosomes. The genome of C. fulvum Race 5 is 49.7 % repetitive and contains 14 690 predicted genes with an estimated completeness of 98.9%, currently one of the highest among the Capnodiales. Genome structure analysis revealed a compartmentalized architecture composed of gene-dense and repeat-poor regions interspersed with gene-sparse and repeat-rich regions. Nearly 39.2 % of the C. fulvum Race 5 genome is affected by Repeat-Induced Point (RIP) mutations and evidence of RIP leakage toward non-repetitive regions was observed in all chromosomes, indicating the RIP plays an important role in the evolution of this pathogen. Finally, 345 genes encoding candidate effectors were identified in C. fulvum Race 5, with a significant enrichment of their location in gene-sparse regions, in accordance with the 'two-speed genome' model of evolution. Overall, the new reference genome of C. fulvum presents several notable features and is a valuable resource for studies in plant pathogens.

Tracking of Diversity and Evolution in the Brown Rot Fungi Monilinia fructicola, Monilinia fructigena, and Monilinia laxa

Monilinia species are among the most devastating fungi worldwide as they cause brown rot and blossom blight on fruit trees. To understand the molecular bases of their pathogenic lifestyles, we compared the newly assembled genomes of single strains of Monilinia fructicola, M. fructigena and M. laxa, with those of Botrytis cinerea and Sclerotinia sclerotiorum, as the closest species within Sclerotiniaceae. Phylogenomic analysis of orthologous proteins and syntenic investigation suggest that M. laxa is closer to M. fructigena than M. fructicola, and is closest to the other investigated Sclerotiniaceae species. This indicates that M. laxa was the earliest result of the speciation process. Distinct evolutionary profiles were observed for transposable elements (TEs). M. fructicola and M. laxa showed older bursts of TE insertions, which were affected (mainly in M. fructicola) by repeat-induced point (RIP) mutation gene silencing mechanisms. These suggested frequent occurrence of the sexual process in M. fructicola. More recent TE expansion linked with low RIP action was observed in M. fructigena, with very little in S. sclerotiorum and B. cinerea. The detection of active non-syntenic TEs is indicative of horizontal gene transfer and has resulted in alterations in specific gene functions. Analysis of candidate effectors, biosynthetic gene clusters for secondary metabolites and carbohydrate-active enzymes, indicated that Monilinia genus has multiple virulence mechanisms to infect host plants, including toxins, cell-death elicitor, putative virulence factors and cell-wall-degrading enzymes. Some species-specific pathogenic factors might explain differences in terms of host plant and organ preferences between M. fructigena and the other two Monilinia species.

Application of machine learning in understanding plant virus pathogenesis: trends and perspectives on emergence, diagnosis, host-virus interplay and management

Background

Inclusion of high throughput technologies in the field of biology has generated massive amounts of data in the recent years. Now, transforming these huge volumes of data into knowledge is the primary challenge in computational biology. The traditional methods of data analysis have failed to carry out the task. Hence, researchers are turning to machine learning based approaches for the analysis of high-dimensional big data. In machine learning, once a model is trained with a training dataset, it can be applied on a testing dataset which is independent. In current times, deep learning algorithms further promote the application of machine learning in several field of biology including plant virology.

Main body

Plant viruses have emerged as one of the principal global threats to food security due to their devastating impact on crops and vegetables. The emergence of new viral strains and species help viruses to evade the concurrent preventive methods. According to a survey conducted in 2014, plant viruses are anticipated to cause a global yield loss of more than thirty billion USD per year. In order to design effective, durable and broad-spectrum management protocols, it is very important to understand the mechanistic details of viral pathogenesis. The application of machine learning enables precise diagnosis of plant viral diseases at an early stage. Furthermore, the development of several machine learning-guided bioinformatics platforms has primed plant virologists to understand the host-virus interplay better. In addition, machine learning has tremendous potential in deciphering the pattern of plant virus evolution and emergence as well as in developing viable control options.

Conclusions

Considering a significant progress in the application of machine learning in understanding plant virology, this review highlights an introductory note on machine learning and comprehensively discusses the trends and prospects of machine learning in the diagnosis of viral diseases, understanding host-virus interplay and emergence of plant viruses.

Comparative genomics of plant pathogenic Diaporthe species and transcriptomics of Diaporthe caulivora during host infection reveal insights into pathogenic strategies of the genus

Background

Diaporthe caulivora is a fungal pathogen causing stem canker in soybean worldwide. The generation of genomic and transcriptomic information of this ascomycete, together with a comparative genomic approach with other pathogens of this genus, will contribute to get insights into the molecular basis of pathogenicity strategies used by D. caulivora and other Diaporthe species.

Results

In the present work, the nuclear genome of D. caulivora isolate (D57) was resolved, and a comprehensive annotation based on gene expression and genomic analysis is provided. Diaporthe caulivora D57 has an estimated size of 57,86 Mb and contains 18,385 predicted protein-coding genes, from which 1501 encode predicted secreted proteins. A large array of D. caulivora genes encoding secreted pathogenicity-related proteins was identified, including carbohydrate-active enzymes (CAZymes), necrosis-inducing proteins, oxidoreductases, proteases and effector candidates. Comparative genomics with other plant pathogenic Diaporthe species revealed a core secretome present in all Diaporthe species as well as Diaporthe-specific and D. caulivora-specific secreted proteins. Transcriptional profiling during early soybean infection stages showed differential expression of 2659 D. caulivora genes. Expression patterns of upregulated genes and gene ontology enrichment analysis revealed that host infection strategies depends on plant cell wall degradation and modification, detoxification of compounds, transporter activities and toxin production. Increased expression of effectors candidates suggests that D. caulivora pathogenicity also rely on plant defense evasion. A high proportion of the upregulated genes correspond to the core secretome and are represented in the pathogen-host interaction (PHI) database, which is consistent with their potential roles in pathogenic strategies of the genus Diaporthe.

Conclusions

Our findings give novel and relevant insights into the molecular traits involved in pathogenicity of D. caulivora towards soybean plants. Some of these traits are in common with other Diaporthe pathogens with different host specificity, while others are species-specific. Our analyses also highlight the importance to have a deeper understanding of pathogenicity functions among Diaporthe pathogens and their interference with plant defense activation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08413-y.

Genome Analysis of the Broad Host Range Necrotroph Nalanthamala psidii Highlights Genes Associated With Virulence

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.

EffectorP 3.0: Prediction of Apoplastic and Cytoplasmic Effectors in Fungi and Oomycetes

Many fungi and oomycete species are devasting plant pathogens. These eukaryotic filamentous pathogens secrete effector proteins to facilitate plant infection. Fungi and oomycete pathogens have diverse infection strategies and their effectors generally do not share sequence homology. However, they occupy similar host environments, either the plant apoplast or plant cytoplasm, and, therefore, may share some unifying properties based on the requirements of these host compartments. Here, we exploit these biological signals and present the first classifier (EffectorP 3.0) that uses two machine-learning models: one trained on apoplastic effectors and one trained on cytoplasmic effectors. EffectorP 3.0 accurately predicts known apoplastic and cytoplasmic effectors in fungal and oomycete secretomes with low estimated false-positive rates of 3 and 8%, respectively. Cytoplasmic effectors have a higher proportion of positively charged amino acids, whereas apoplastic effectors are enriched for cysteine residues. The combination of fungal and oomycete effectors in training leads to a higher number of predicted cytoplasmic effectors in biotrophic fungi. EffectorP 3.0 expands predicted effector repertoires beyond small, cysteine-rich secreted proteins in fungi and RxLR-motif containing secreted proteins in oomycetes. We show that signal peptide prediction is essential for accurate effector prediction, because EffectorP 3.0 recognizes a cytoplasmic signal also in intracellular, nonsecreted proteins.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Host-Induced Gene Silencing Using BPMV on Soybean to Study Genes in the Soybean Rust Fungus Phakopsora pachyrhizi

To obtain direct evidence for the influence of an effector on the virulence or pathogenicity of a pathogen, it is necessary to knock out, knock down, or silence the respective gene. Since genetic transformation is not yet possible for rust fungi, silencing the gene is the only option. Posttranscriptional gene silencing uses RNAi. RNAi in plant pathogens can be accomplished by introducing dsRNA either by direct application of in vitro synthesized dsRNA or through positive-strand or double-strand RNA plant viruses. For studying effectors in Phakopsora pachyrhizi, we have implemented a host-induced silencing procedure based on virus-induced gene silencing using the bean pod mottle virus system. Here, procedures and interpretations of results are described and limitations of the system are discussed.

The Parastagonospora nodorum necrotrophic effector SnTox5 targets the wheat gene Snn5 and facilitates entry into the leaf mesophyll

Parastagonospora nodorum is an economically important necrotrophic fungal pathogen of wheat. Parastagonospora nodorum secretes necrotrophic effectors that target wheat susceptibility genes to induce programmed cell death (PCD). In this study, we cloned and functionally validated SnTox5 and characterized its role in pathogenesis. We used whole genome sequencing, genome-wide association study (GWAS) mapping, CRISPR-Cas9-based gene disruption, gain-of-function transformation, quantitative trait locus (QTL) analysis, haplotype and isoform analysis, protein modeling, quantitative PCR, and laser confocal microscopy to validate SnTox5 and functionally characterize SnTox5. SnTox5 is a mature 16.26 kDa protein with high structural similarity to SnTox3. Wild-type and mutant P. nodorum strains and wheat genotypes of SnTox5 and Snn5, respectively, were used to show that SnTox5 not only targets Snn5 to induce PCD but also facilitates the colonization of the mesophyll layer even in the absence of Snn5. Here we show that SnTox5 facilitates the efficient colonization of the mesophyll tissue and elicits PCD specific to host lines carrying Snn5. The homology to SnTox3 and the ability of SnTox5 to facilitate the colonizing of the mesophyll also suggest a role in the suppression of host defense before PCD induction.

A triple threat: the Parastagonospora nodorum SnTox267 effector exploits three distinct host genetic factors to cause disease in wheat

Parastagonospora nodorum is a fungal pathogen of wheat. As a necrotrophic specialist, it deploys effector proteins that target dominant host susceptibility genes to elicit programmed cell death (PCD). Here we identify and functionally validate the effector targeting the host susceptibility genes Snn2, Snn6 and Snn7. We utilized whole-genome sequencing, association mapping, gene-disrupted mutants, gain-of-function transformants, virulence assays, bioinformatics and quantitative PCR to characterize these interactions. A single proteinaceous effector, SnTox267, targeted Snn2, Snn6 and Snn7 to trigger PCD. Snn2 and Snn6 functioned cooperatively to trigger PCD in a light-dependent pathway, whereas Snn7-mediated PCD functioned in a light-independent pathway. Isolates harboring 20 SnTox267 protein isoforms quantitatively varied in virulence. The diversity and distribution of isoforms varied between populations, indicating adaptation to local selection pressures. SnTox267 deletion resulted in the upregulation of effector genes SnToxA, SnTox1 and SnTox3. We validated a novel effector operating in an inverse-gene-for-gene manner to target three genetically distinct host susceptibility genes and elicit PCD. The discovery of the complementary gene action of Snn2 and Snn6 indicates their potential function in a guard or decoy model. Additionally, differences in light dependency in the elicited pathways and upregulation of unlinked effectors sheds new light onto a complex fungal necrotroph-host interaction.

Functional Genomics and Comparative Lineage-Specific Region Analyses Reveal Novel Insights into Race Divergence in Verticillium dahliae

Verticillium dahliae is a widespread soilborne fungus that causes Verticillium wilt on numerous economically important plant species. In tomato, until now, three races have been characterized based on the response of differential cultivars to V. dahliae, but the genetic basis of race divergence in V. dahliae remains undetermined. To investigate the genetic basis of race divergence, we sequenced the genomes of two race 2 strains and four race 3 strains for comparative analyses with two known race 1 genomes. The genetic basis of race divergence was described by the pathogenicity-related genes among the three races, orthologue analyses, and genomic structural variations. Global comparative genomics showed that chromosomal rearrangements are not the only source of race divergence and that race 3 should be split into two genotypes based on orthologue clustering. Lineage-specific regions (LSRs), frequently observed between genomes of the three races, encode several predicted secreted proteins that potentially function as suppressors of immunity triggered by known effectors. These likely contribute to the virulence of the three races. Two genes in particular that can act as markers for race 2 and race 3 (VdR2e and VdR3e, respectively) contribute to virulence on tomato, and the latter acts as an avirulence factor of race 3. We elucidated the genetic basis of race divergence through global comparative genomics and identified secreted proteins in LSRs that could potentially play critical roles in the differential virulence among the races in V. dahliae.

IMPORTANCE Deciphering the gene-for-gene relationships during host-pathogen interactions is the basis of modern plant resistance breeding. In the Verticillium dahliae-tomato pathosystem, two races (races 1 and 2) and their corresponding avirulence (Avr) genes have been identified, but strains that lack these two Avr genes exist in nature. In this system, race 3 has been described, but the corresponding Avr gene has not been identified. We de novo-sequenced genomes of six strains and identified secreted proteins within the lineage-specific regions (LSRs) distributed among the genomes of the three races that could potentially function as manipulators of host immunity. One of the LSR genes, VdR3e, was confirmed as the Avr gene for race 3. The results indicate that differences in transcriptional regulation may contribute to race differentiation. This is the first study to describe these differences and elucidate roles of secreted proteins in LSRs that play roles in race differentiation.

Chromosome-level genomes provide insights into genome evolution, organization and size in Epichloe fungi

Epichloe fungi are endophytes of cool season grasses, both wild species and commercial cultivars, where they may exhibit mutualistic or pathogenic lifestyles. The Epichloe-grass symbiosis is of great interest to agricultural research for the fungal bioprotective properties conferred to host grasses but also serves as an ideal system to study the evolution of fungal plant-pathogens in natural environments. Here, we assembled and annotated gapless chromosome-level genomes of two pathogenic Epichloe sibling species. Both genomes have a bipartite genome organization, with blocks of highly syntenic gene-rich regions separated by blocks of AT-rich DNA. The AT-rich regions show an extensive signature of RIP (repeat-induced point mutation) and the expansion of this compartment accounts for the large difference in genome size between the two species. This study reveals how the rapid evolution of repeat structure can drive divergence between closely related taxa and highlights the evolutionary role of dynamic compartments in fungal genomes.

Candidate Effectors of Plasmodiophora brassicae Pathotype 5X During Infection of Two Brassica napus Genotypes

Clubroot, caused by Plasmodiophora brassicae, is one of the most important diseases of canola (Brassica napus) in Canada. Disease management relies heavily on planting clubroot resistant (CR) cultivars, but in recent years, new resistance-breaking pathotypes of P. brassicae have emerged. Current efforts against the disease are concentrated in developing host resistance using traditional genetic breeding, omics and molecular biology. However, because of its obligate biotrophic nature, limited resources have been dedicated to investigating molecular mechanisms of pathogenic infection. We previously performed a transcriptomic study with the cultivar resistance-breaking pathotype 5X on two B. napus hosts presenting contrasting resistance/susceptibility, where we evaluated the mechanisms of host response. Since cultivar-pathotype interactions are very specific, and pathotype 5X is one of the most relevant resistance-breaking pathotypes in Canada, in this study, we analyze the expression of genes encoding putative secreted proteins from this pathotype, predicted using a bioinformatics pipeline, protein modeling and orthologous comparisons with effectors from other pathosystems. While host responses were found to differ markedly in our previous study, many common effectors are found in the pathogen while infecting both hosts, and the gene response among biological pathogen replicates seems more consistent in the effectors associated with the susceptible interaction, especially at 21 days after inoculation. The predicted effectors indicate the predominance of proteins with interacting domains (e.g., ankyrin), and genes bearing kinase and NUDIX domains, but also proteins with protective action against reactive oxygen species from the host. Many of these genes confirm previous predictions from other clubroot studies. A benzoic acid/SA methyltransferase (BSMT), which methylates SA to render it inactive, showed high levels of expression in the interactions with both hosts. Interestingly, our data indicate that E3 ubiquitin proteasome elements are also potentially involved in pathogenesis. Finally, a gene with similarity to indole-3-acetaldehyde dehydrogenase is a promising candidate effector because of its involvement in indole acetic acid synthesis, since auxin is one of the major players in clubroot development.

Bioinformatics and Transcriptome Analysis of CFEM Proteins in Fusarium graminearum

Fusarium blight of wheat is usually caused by Fusarium graminearum, and the pathogenic fungi will secrete effectors into the host plant tissue to affect its normal physiological process, so as to make it pathogenic. The CFEM (Common in Fungal Extracellular Membrane) protein domain is unique to fungi, but it is not found in all fungi. The CFEM protein contained in F. graminearum may be closely related to pathogenicity. In this study, 23 FgCFEM proteins were identified from the F. graminearum genome. Then, features of these proteins, such as signal peptide, subcellular localization, and transmembrane domains, etc., were analyzed and candidate effectors were screened out. Sequence alignment results revealed that each FgCFEM protein contains one CFEM domain. The amino acids of the CFEM domain are highly conserved and contain eight spaced cysteines, with the exception that FgCFEM8, 9, and 15 lack two cysteines and three cysteines were missed in FgCFEM18 and FgCFEM22. A recently identified CFEM_DR motif was detected in 11 FgCFEMs, and importantly we identified two new conserved motifs containing about 29 and 18 amino acids (CFEM_WR and CFEM_KF), respectively, in some of FgCFEM proteins. Transcriptome analysis of the genes encoding CFEM proteins indicated that all the CFEM-containing genes were expressed during wheat infection, with seven and six genes significantly up- and down-regulated, respectively, compared with in planta and in vitro. Based on the above analysis, FgCFEM11 and FgCFEM23 were predicted to be F. graminearum effectors. This study provides the basis for future functional analyses of CFEM proteins in F. graminearum.

The Fusarium graminearum FGSG_03624 Xylanase Enhances Plant Immunity and Increases Resistance against Bacterial and Fungal Pathogens

Fungal enzymes degrading the plant cell wall, such as xylanases, can activate plant immune responses. The Fusarium graminearum FGSG_03624 xylanase, previously shown to elicit necrosis and hydrogen peroxide accumulation in wheat, was investigated for its ability to induce disease resistance. To this aim, we transiently and constitutively expressed an enzymatically inactive form of FGSG_03624 in tobacco and Arabidopsis, respectively. The plants were challenged with Pseudomonas syringae pv. tabaci or pv. maculicola and Botrytis cinerea. Symptom reduction by the bacterium was evident, while no reduction was observed after B. cinerea inoculation. Compared to the control, the presence of the xylanase gene in transgenic Arabidopsis plants did not alter the basal expression of a set of defense-related genes, and, after the P. syringae inoculation, a prolonged PR1 expression was detected. F. graminearum inoculation experiments of durum wheat spikes exogenously treated with the FGSG_03624 xylanase highlighted a reduction of symptoms in the early phases of infection and a lower fungal biomass accumulation than in the control. Besides, callose deposition was detected in infected spikes previously treated with the xylanase and not in infected control plants. In conclusion, our results highlight the ability of FGSG_03624 to enhance plant immunity, thus decreasing disease severity.

An automated and combinative method for the predictive ranking of candidate effector proteins of fungal plant pathogens

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.

The Conserved Colletotrichum spp. Effector Candidate CEC3 Induces Nuclear Expansion and Cell Death in Plants

Plant pathogens secrete proteins, known as effectors, that promote infection by manipulating host cells. Members of the phytopathogenic fungal genus Colletotrichum collectively have a broad host range and generally adopt a hemibiotrophic lifestyle that includes an initial biotrophic phase and a later necrotrophic phase. We hypothesized that Colletotrichum fungi use a set of conserved effectors during infection to support the two phases of their hemibiotrophic lifestyle. This study aimed to examine this hypothesis by identifying and characterizing conserved effectors among Colletotrichum fungi. Comparative genomic analyses using genomes of ascomycete fungi with different lifestyles identified seven effector candidates that are conserved across the genus Colletotrichum. Transient expression assays showed that one of these putative conserved effectors, CEC3, induces nuclear expansion and cell death in Nicotiana benthamiana, suggesting that CEC3 is involved in promoting host cell death during infection. Nuclear expansion and cell death induction were commonly observed in CEC3 homologs from four different Colletotrichum species that vary in host specificity. Thus, CEC3 proteins could represent a novel class of core effectors with functional conservation in the genus Colletotrichum.

Bioinformatic tools support decision-making in plant disease management

Food loss due to pathogens is a major concern in agriculture, requiring the need for advanced disease detection and prevention measures to minimize pathogen damage to plants. Novel bioinformatic tools have opened doors for the low-cost rapid identification of pathogens and prevention of disease. The number of these tools is growing fast and a comprehensive and comparative summary of these resources is currently lacking. Here, we review all current bioinformatic tools used to identify the mechanisms of pathogen pathogenicity, plant resistance protein identification, and the detection and treatment of plant disease. We compare functionality, data volume, data sources, performance, and applicability of all tools to provide a comprehensive toolbox for researchers in plant disease management.

Host Adaptation and Virulence in Heteroecious Rust Fungi

Rust fungi (Pucciniales, Basidiomycota) are obligate biotrophic pathogens that cause rust diseases in plants, inflicting severe damage to agricultural crops. Pucciniales possess the most complex life cycles known in fungi. These include an alternation of generations, the development of up to five different sporulating stages, and, for many species, the requirement of infecting two unrelated host plants during different parts of their life cycle, termed heteroecism. These fungi have been extensively studied in the past century through microscopy and inoculation studies, providing precise descriptions of their infection processes, although the molecular mechanisms underlying their unique biology are poorly understood. In this review, we cover recent genomic and life cycle transcriptomic studies in several heteroecious rust species, which provide insights into the genetic tool kits associated with host adaptation and virulence, opening new avenues for unraveling their unique evolution.

High-Quality Genome Sequence Resource for Fusarium andiyazi Causing Pokkah Boeng Disease of Sugarcane in China

Sugarcane pokkah boeng disease (PBD) is emerging as a prevalent foliar disease in China. This airborne disease is caused by the Fusarium species complex. To investigate the diversity and evolution of Fusarium spp., we performed whole-genome sequencing of Fusarium andiyazi YN28 using a combination of Oxford Nanopore and Illumina technology. The F. andiyazi YN28 genome was sequenced, assembled, and annotated. A high-quality genome was assembled into 24 contigs with an N₅₀ of 2.80 Mb. The genome assembly generated a total size of 44.1 Mb with a GC content of 47.64%. In total, 15,508 genes were predicted, including 794 genes related to the carbohydrate-active enzymes, 397 noncoding RNA, 155 genes associated with transporter classification, 4,550 genes linked to pathogen-host interactions, and 269 genes involved in effector proteins. Collectively, our results will provide insight into the host-pathogen interactions and will facilitate the breeding of new varieties of sugarcane resistant to PBD.[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.

Accurate plant pathogen effector protein classification ab initio with deepredeff: an ensemble of convolutional neural networks

Background

Plant pathogens cause billions of dollars of crop loss every year and are a major threat to global food security. Effector proteins are the tools such pathogens use to infect the cell, predicting effectors de novo from sequence is difficult because of the heterogeneity of the sequences. We hypothesised that deep learning classifiers based on Convolutional Neural Networks would be able to identify effectors and deliver new insights.

Results

We created a training set of manually curated effector sequences from PHI-Base and used these to train a range of model architectures for classifying bacteria, fungal and oomycete sequences. The best performing classifiers had accuracies from 93 to 84%. The models were tested against popular effector detection software on our own test data and data provided with those models. We observed better performance from our models. Specifically our models showed greater accuracy and lower tendencies to call false positives on a secreted protein negative test set and a greater generalisability. We used GRAD-CAM activation map analysis to identify the sequences that activated our CNN-LSTM models and found short but distinct N-terminal regions in each taxon that was indicative of effector sequences. No motifs could be observed in these regions but an analysis of amino acid types indicated differing patterns of enrichment and depletion that varied between taxa.

Conclusions

Small training sets can be used effectively to train highly accurate and sensitive deep learning models without need for the operator to know anything other than sequence and without arbitrary decisions made about what sequence features or physico-chemical properties are important. Biological insight on subsequences important for classification can be achieved by examining the activations in the model

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04293-3.

Reference genome assembly for Australian Ascochyta lentis isolate Al4

Ascochyta lentis causes ascochyta blight in lentil (Lens culinaris Medik.) and yield loss can be as high as 50%. With careful agronomic management practices, fungicide use, and advances in breeding resistant lentil varieties, disease severity and impact to farmers have been largely controlled. However, evidence from major lentil producing countries, Canada and Australia, suggests that A. lentis isolates can change their virulence profile and level of aggressiveness over time and under different selection pressures. In this paper, we describe the first genome assembly for A. lentis for the Australian isolate Al4, through the integration of data from Illumina and PacBio SMRT sequencing. The Al4 reference genome assembly is almost 42 Mb in size and encodes 11,638 predicted genes. The Al4 genome comprises 21 full-length and gapless chromosomal contigs and two partial chromosome contigs each with one telomere. We predicted 31 secondary metabolite clusters, and 38 putative protein effectors, many of which were classified as having an unknown function. Comparison of A. lentis genome features with the recently published reference assembly for closely related A. rabiei show that genome synteny between these species is highly conserved. However, there are several translocations and inversions of genome sequence. The location of secondary metabolite clusters near transposable element and repeat-rich genomic regions was common for A. lentis as has been reported for other fungal plant pathogens.

Genome sequence of Monilinia vaccinii-corymbosi sheds light on mummy berry disease infection of blueberry and mating type

Mummy berry disease, caused by the fungal pathogen Monilinia vaccinii-corymbosi (Mvc), is one of the most economically important diseases of blueberries in North America. Mvc is capable of inducing two separate blighting stages during its life cycle. Infected fruits are rendered mummified and unmarketable. Genomic data for this pathogen is lacking, but could be useful in understanding the reproductive biology of Mvc and the mechanisms it deploys to facilitate host infection. In this study, PacBio sequencing and Hi-C interaction data were utilized to create a chromosome-scale reference genome for Mvc. The genome comprises nine chromosomes with a total length of 30 Mb, an N50 length of 4.06 Mb, and an average 413X sequence coverage. A total of 9399 gene models were predicted and annotated, and BUSCO analysis revealed that 98% of 1,438 searched conserved eukaryotic genes were present in the predicted gene set. Potential effectors were identified, and the mating-type (MAT) locus was characterized. Biotrophic effectors allow the pathogen to avoid recognition by the host plant and evade or mitigate host defense responses during the early stages of fruit infection. Following locule colonization, necrotizing effectors promote the mummification of host tissues. Potential biotrophic effectors utilized by Mvc include chorismate mutase for reducing host salicylate and necrotrophic effectors include necrosis-inducing proteins and hydrolytic enzymes for macerating host tissue. The MAT locus sequences indicate the potential for homothallism in the reference genome, but a deletion allele of the MAT locus, characterized in a second isolate, indicates heterothallism. Further research is needed to verify the roles of individual effectors in virulence and to determine the role of the MAT locus in outcrossing and population genotypic diversity.

The identification of a transposon affecting the asexual reproduction of the wheat pathogen Zymoseptoria tritici

Zymoseptoria tritici, the causal agent of Septoria tritici blotch, is a fungal wheat pathogen that causes significant global yield losses. Within Z. tritici populations, quantitative differences in virulence among different isolates are commonly observed; however, the genetic components that underpin these differences remain elusive. In this study, intraspecific comparative transcriptomic analysis was used to identify candidate genes that contribute to differences in virulence on the wheat cultivar WW2449. This led to the identification of a multicopy gene that was not expressed in the high-virulence isolate when compared to the medium- and low-virulence isolates. Further investigation suggested this gene resides in a 7.9-kb transposon. Subsequent long-read sequencing of the isolates used in the transcriptomic analysis confirmed that this gene did reside in an active Class II transposon, which is composed of four genes named REP9-1 to -4. Silencing and overexpression of REP9-1 in two distinct genetic backgrounds demonstrated that its expression alone reduces the number of pycnidia produced by Z. tritici during infection. The REP9-1 gene identified within a Class II transposon is the first discovery of a gene in a transposable element that influences the virulence of Z. tritici. This discovery adds further complexity to genetic loci that contribute to quantitative virulence in this important pathogen.

ONT-Based Draft Genome Assembly and Annotation of Alternaria atra

Species of Alternaria (phylum Ascomycota, family Pleosporaceae) are known as serious plant pathogens, causing major losses on a wide range of crops. Alternaria atra (previously known as Ulocladium atrum) can grow as a saprophyte on many hosts and causes Ulocladium blight on potato. It has been reported that it can also be used as a biocontrol agent against Botrytis cinerea. Here, we present a scaffold-level reference genome assembly for A. atra. The assembly contains 43 scaffolds with a total length of 39.62 Mbp, with scaffold N₅₀ of 3,893,166 bp, L₅₀ of 4, and the longest 10 scaffolds containing 89.9% of the assembled data. RNA-sequencing-guided gene prediction using BRAKER resulted in 12,173 protein-coding genes with their functional annotation. This first high-quality reference genome assembly and annotation for A. atra can be used as a resource for studying evolution in the highly complicated Alternaria genus and might help in understanding the mechanisms defining its role as pathogen or biocontrol agent.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Current population structure and pathogenicity patterns of Ascochyta rabiei in Australia

Ascochyta blight disease, caused by the necrotrophic fungus Ascochyta rabiei, is a major biotic constraint to chickpea production in Australia and worldwide. Detailed knowledge of the structure of the pathogen population and its potential to adapt to our farming practices is key to informing optimal management of the disease. This includes understanding the molecular diversity among isolates and the frequency and distribution of the isolates that have adapted to overcome host resistance across agroecologically distinct regions. Thanks to continuous monitoring efforts over the past 6 years, a comprehensive collection of A. rabiei isolates was collated from the major Australian chickpea production regions. To determine the molecular structure of the entire population, representative isolates from each collection year and growing region have been genetically characterized using a DArTseq genotyping-by-sequencing approach. The genotyped isolates were further phenotyped to determine their pathogenicity levels against a differential set of chickpea cultivars and genotype-phenotype associations were inferred. Overall, the Australian A. rabiei population displayed a far lower genetic diversity (average Nei's gene diversity of 0.047) than detected in other populations worldwide. This may be explained by the presence of a single mating-type in Australia, MAT1-2, limiting its reproduction to a clonal mode. Despite the low detected molecular diversity, clonal selection appears to have given rise to a subset of adapted isolates that are highly pathogenic on commonly employed resistance sources, and that are occurring at an increasing frequency. Among these, a cluster of genetically similar isolates was identified, with a higher proportion of highly aggressive isolates than in the general population. The discovery of distinct genetic clusters associated with high and low isolate pathogenicity forms the foundation for the development of a molecular pathotyping tool for the Australian A. rabiei population. Application of such a tool, along with continuous monitoring of the genetic structure of the population will provide crucial information for the screening of breeding material and integrated disease management packages.

A pair of effectors encoded on a conditionally dispensable chromosome of Fusarium oxysporum suppress host-specific immunity

Many plant pathogenic fungi contain conditionally dispensable (CD) chromosomes that are associated with virulence, but not growth in vitro. Virulence-associated CD chromosomes carry genes encoding effectors and/or host-specific toxin biosynthesis enzymes that may contribute to determining host specificity. Fusarium oxysporum causes devastating diseases of more than 100 plant species. Among a large number of host-specific forms, F. oxysporum f. sp. conglutinans (Focn) can infect Brassicaceae plants including Arabidopsis (Arabidopsis thaliana) and cabbage. Here we show that Focn has multiple CD chromosomes. We identified specific CD chromosomes that are required for virulence on Arabidopsis, cabbage, or both, and describe a pair of effectors encoded on one of the CD chromosomes that is required for suppression of Arabidopsis-specific phytoalexin-based immunity. The effector pair is highly conserved in F. oxysporum isolates capable of infecting Arabidopsis, but not of other plants. This study provides insight into how host specificity of F. oxysporum may be determined by a pair of effector genes on a transmissible CD chromosome.

Yu Ayukawa, Shuta Asai, et al. report the genome sequence of a Fusarium oxysporum isolate and demonstrate that it contains different conditionally dispensable chromosomes which are important to confer virulence on specific hosts, like Arabidopsis thaliana or cabbage. Altogether, these results provide further insight into the mechanisms underlying F. oxysporum pathogenicity.

Effectors of Plant Necrotrophic Fungi

Plant diseases caused by necrotrophic fungal pathogens result in large economic losses in field crop production worldwide. Effectors are important players of plant-pathogen interaction and deployed by pathogens to facilitate plant colonization and nutrient acquisition. Compared to biotrophic and hemibiotrophic fungal pathogens, effector biology is poorly understood for necrotrophic fungal pathogens. Recent bioinformatics advances have accelerated the prediction and discovery of effectors from necrotrophic fungi, and their functional context is currently being clarified. In this review we examine effectors utilized by necrotrophic fungi and hemibiotrophic fungi in the latter stages of disease development, including plant cell death manipulation. We define "effectors" as secreted proteins and other molecules that affect plant physiology in ways that contribute to disease establishment and progression. Studying and understanding the mechanisms of necrotrophic effectors is critical for identifying avenues of genetic intervention that could lead to improved resistance to these pathogens in plants.

Genome-wide mapping of histone modifications during axenic growth in two species of Leptosphaeria maculans showing contrasting genomic organization

Leptosphaeria maculans 'brassicae' (Lmb) and Leptosphaeria maculans 'lepidii' (Lml) are closely related phytopathogenic species that exhibit a large macrosynteny but contrasting genome structure. Lmb has more than 30% of repeats clustered in large repeat-rich regions, while the Lml genome has only a small amount of evenly distributed repeats. Repeat-rich regions of Lmb are enriched in effector genes, expressed during plant infection. The distinct genome structures of Lmb and Lml provide an excellent model for comparing the organization of pathogenicity genes in relation to the chromatin landscape in two closely related phytopathogenic fungi. Here, we performed chromatin immunoprecipitation (ChIP) during axenic culture, targeting histone modifications typical for heterochromatin or euchromatin, combined with transcriptomic analysis to analyze the influence of chromatin organization on gene expression. In both species, we found that facultative heterochromatin is enriched with genes lacking functional annotation, including numerous effector and species-specific genes. Notably, orthologous genes located in H3K27me3 domains are enriched with effector genes. Compared to other fungal species, including Lml, Lmb is distinct in having large H3K9me3 domains associated with repeat-rich regions that contain numerous species-specific effector genes. Discovery of these two distinctive heterochromatin landscapes now raises questions about their involvement in the regulation of pathogenicity, the dynamics of these domains during plant infection and the selective advantage to the fungus to host effector genes in H3K9me3 or H3K27me3 domains.

Genome assembly of Scorias spongiosa and comparative genomics provide insights into ecological adaptation of honeydew-dependent sooty mould fungi

Sooty moulds are fungi of economic importance and with unique lifestyle mainly growing on insect honeydew. However, the lack of genomic data hinders investigation of genetic mechanisms underlying their ecological adaptation. With long-read sequencing technology, we generated the genome of Scorias spongiosa, an extraordinary sooty mould fungus associated with honeydew of colony aphids and producing large fruiting bodies. A 24.21 Mb high-quality genome assembly with a N50 length of 3.37 Mb was obtained. The genome contained 7758 protein coding genes, 97.13% of which were homologous to known genes, and approximately 0.29 Mb repeat sequences. Comparative genomics showed S. spongiosa lost relatively more gene families and contained fewer species-specific genes and gene families, with many CAZyme families and sugar transporters reduced or absent. This study not only promotes understanding of the ecological adaptation of sooty moulds, but also provides valuable genomic data resource for future comparative genomic and genetic studies.

A genome-wide genetic linkage map and reference quality genome sequence for a new race in the wheat pathogen Pyrenophora tritici-repentis

Pyrenophora tritici-repentis is an ascomycete fungus that causes tan spot of wheat. The disease has a worldwide distribution and can cause significant yield and quality losses in wheat production. The fungal pathogen is homothallic in nature, which means it can undergo sexual reproduction by selfing to produce pseudothecia on wheat stubble for seasonal survival. Since homothallism precludes the development of bi-parental fungal populations, no genetic linkage map has been developed for P. tritici-repentis for mapping and map-based cloning of fungal virulence genes. In this work, we created two heterothallic strains by deleting one of the mating type genes in each of two parental isolates 86-124 (race 2) and AR CrossB10 (a new race) and developed a bi-parental fungal population between them. The draft genome sequences of the two parental isolates were aligned to the Pt-1C-BFP reference sequence to mine single nucleotide polymorphisms (SNPs). A total of 225 SNP markers were developed for genotyping the entire population. Additionally, 75 simple sequence repeat, and two gene markers were also developed and used in the genotyping. The resulting linkage map consisted of 13 linkage groups spanning 5,075.83 cM in genetic distance. Because the parental isolate AR CrossB10 is a new race and produces Ptr ToxC, it was sequenced using long-read sequencing platforms and de novo assembled into contigs. The majority of the contigs were further anchored into chromosomes with the aid of the linkage maps. The whole genome comparison of AR CrossB10 to the reference genome of M4 revealed a few chromosomal rearrangements. The genetic linkage map and the new AR CrossB10 genome sequence are valuable tools for gene cloning in P. tritici-repentis.

Effectors of Puccinia striiformis f. sp. tritici Suppressing the Pathogenic-Associated Molecular Pattern-Triggered Immune Response Were Screened by Transient Expression of Wheat Protoplasts

Puccinia striiformis f. sp. tritici (Pst) is an important pathogen of wheat (Triticum aestivum L.) stripe rust, and the effector protein secreted by haustoria is a very important component involved in the pathogenic process. Although the candidate effector proteins secreted by Pst haustoria have been predicted to be abundant, few have been functionally validated. Our study confirmed that chitin and flg22 could be used as elicitors of the pathogenic-associated molecular pattern-triggered immune (PTI) reaction in wheat leaves and that TaPr-1-14 could be used as a marker gene to detect the PTI reaction. In addition, the experimental results were consistent in wheat protoplasts. A rapid and efficient method for screening and identifying the effector proteins of Pst was established by using the wheat protoplast transient expression system. Thirty-nine Pst haustorial effector genes were successfully cloned and screened for expression in the protoplast. We identified three haustorial effector proteins, PSEC2, PSEC17, and PSEC45, that may inhibit the response of wheat to PTI. These proteins are localized in the somatic cytoplasm and nucleus of wheat protoplasts and are highly expressed during the infection and parasitism of wheat.

Agroinfiltration for transient gene expression and characterisation of fungal pathogen effectors in cool-season grain legume hosts

KEY MESSAGE

Modified pEAQ-HT-DEST1 vectors were used for agroinfiltration in legumes. We demonstrate protein expression and export in pea, lentil, and faba bean; however, the method for chickpea was not successful. Agroinfiltration is a valuable research method for investigating virulence and avirulence effector proteins from pathogens and pests, where heterologous effector proteins are transiently expressed in plant leaves and hypersensitive necrosis responses and other effector functions can be assessed. Nicotiana benthamiana is widely used for agroinfiltration and the characterisation of broad-spectrum effectors. The method has also been used in other plant species including field pea, but not yet developed for chickpea, lentil, or faba bean. Here, we have modified the pEAQ-HT-DEST1 vector for expression of 6 × histidine-tagged green-fluorescent protein (GFP) and the known necrosis-inducing broad-spectrum effector necrosis and ethylene-inducing peptide (Nep1)-like protein (NLP). Modified pEAQ-based vectors were adapted to encode signal peptide sequences for apoplast targeting of expressed proteins. We used confocal microscopy to assess the level of GFP expression in agroinfiltrated leaves. While at 3 days after infiltration in N. benthamiana, GFP was expressed at a relatively high level, expression in field pea and faba bean at the same time point was relatively low. In lentil, an expression level of GFP similar to field pea and faba bean at 3 days was only observed after 5 days. Chickpea leaf cells were transformed at low frequency and agroinfiltration was concluded to not be successful for chickpea. We concluded that the pEAQ vector is suitable for testing host-specific effectors in field pea, lentil, and faba bean, but low transformation efficiency limits the utility of the method for chickpea.

Tandem DNA repeats contain cis-regulatory sequences that activate biotrophy-specific expression of Magnaporthe effector gene PWL2

During plant infection, fungi secrete effector proteins in coordination with distinct infection stages. Thus, the success of plant infection is determined by precise control of effector gene expression. We analysed the PWL2 effector gene of the rice blast fungus Magnaporthe oryzae to understand how effector genes are activated specifically during the early biotrophic stages of rice infection. Here, we used confocal live-cell imaging of M. oryzae transformants with various PWL2 promoter fragments fused to sensitive green fluorescent protein reporter genes to determine the expression patterns of PWL2 at the cellular level, together with quantitative reverse transcription PCR analyses at the tissue level. We found PWL2 expression was coupled with sequential biotrophic invasion of rice cells. PWL2 expression was induced in the appressorium upon penetration into a living rice cell but greatly declined in the highly branched hyphae when the first-invaded rice cell was dead. PWL2 expression then increased again as the hyphae penetrate into living adjacent cells. The expression of PWL2 required fungal penetration into living plant cells of either host rice or nonhost onion. Deletion and mutagenesis experiments further revealed that the tandem repeats in the PWL2 promoter contain 12-base pair sequences required for expression. We conclude that PWL2 expression is (a) activated by an unknown signal commonly present in living plant cells, (b) specific to biotrophic stages of fungal infection, and (c) requires 12-base pair cis-regulatory sequences in the promoter.

Gene Expression of Putative Pathogenicity-Related Genes in Verticillium dahliae in Response to Elicitation with Potato Extracts and during Infection Using Quantitative Real-Time PCR

Quantitative real-time PCR was used to monitor the expression of 15 Verticillium dahliae's genes, putatively involved in pathogenicity, highly (HAV) and weakly aggressive (WAV) V. dahliae isolates after either (i) elicitation with potato leaf, stem, or root extracts, or (ii) inoculation of potato detached petioles. These genes, i.e., coding for Ras-GAP-like protein, serine/threonine protein kinase, Ubiquitin-conjugating enzyme variant-MMS2, NADH-ubiquinone oxidoreductase, Thioredoxin, Pyruvate dehydrogenase E1 VdPDHB, myo-inositol 2-dehydrogenase, and HAD-superfamily hydrolase, showed differential upregulation in the HAV versus WAV isolate in response to plant extracts or after inoculation of potato leaf petioles. This suggests their potential involvement in the observed differential aggressiveness between isolates. However, other genes like glucan endo-1,3-alpha-glucosidase and nuc-1 negative regulatory protein VdPREG showed higher activity in the WAV than in the HAV in response to potato extracts and/or during infection. This, in contrast, may suggest a role in their lower aggressiveness. These findings, along with future functional analysis of selected genes, will contribute to improving our understanding of V. dahliae's pathogenesis. For example, expression of VdPREG negatively regulates phosphorus-acquisition enzymes, which may indicate a lower phosphorus acquisition activity in the WAV. Therefore, integrating the knowledge about the activity of both genes enhancing pathogenicity and those restraining it will provide a guild line for further functional characterization of the most critical genes, thus driving new ideas towards better Verticillium wilt management.

FINDER: an automated software package to annotate eukaryotic genes from RNA-Seq data and associated protein sequences

BACKGROUND

Gene annotation in eukaryotes is a non-trivial task that requires meticulous analysis of accumulated transcript data. Challenges include transcriptionally active regions of the genome that contain overlapping genes, genes that produce numerous transcripts, transposable elements and numerous diverse sequence repeats. Currently available gene annotation software applications depend on pre-constructed full-length gene sequence assemblies which are not guaranteed to be error-free. The origins of these sequences are often uncertain, making it difficult to identify and rectify errors in them. This hinders the creation of an accurate and holistic representation of the transcriptomic landscape across multiple tissue types and experimental conditions. Therefore, to gauge the extent of diversity in gene structures, a comprehensive analysis of genome-wide expression data is imperative.

RESULTS

We present FINDER, a fully automated computational tool that optimizes the entire process of annotating genes and transcript structures. Unlike current state-of-the-art pipelines, FINDER automates the RNA-Seq pre-processing step by working directly with raw sequence reads and optimizes gene prediction from BRAKER2 by supplementing these reads with associated proteins. The FINDER pipeline (1) reports transcripts and recognizes genes that are expressed under specific conditions, (2) generates all possible alternatively spliced transcripts from expressed RNA-Seq data, (3) analyzes read coverage patterns to modify existing transcript models and create new ones, and (4) scores genes as high- or low-confidence based on the available evidence across multiple datasets. We demonstrate the ability of FINDER to automatically annotate a diverse pool of genomes from eight species.

CONCLUSIONS

FINDER takes a completely automated approach to annotate genes directly from raw expression data. It is capable of processing eukaryotic genomes of all sizes and requires no manual supervision-ideal for bench researchers with limited experience in handling computational tools.

Genome sequencing and comparative genomic analysis of highly and weakly aggressive strains of Sclerotium rolfsii, the causal agent of peanut stem rot

BACKGROUND

Stem rot caused by Sclerotium rolfsii is a very important soil-borne disease of peanut. S. rolfsii is a necrotrophic plant pathogenic fungus with an extensive host range and worldwide distribution. It can infect peanut stems, roots, pegs and pods, leading to varied yield losses. S. rolfsii strains GP3 and ZY collected from peanut in different provinces of China exhibited a significant difference in aggressiveness on peanut plants by artificial inoculation test. In this study, de-novo genome sequencing of these two distinct strains was performed aiming to reveal the genomic basis of difference in aggressiveness.

RESULTS

Scleotium rolfsii strains GP3 and ZY, with weak and high aggressiveness on peanut plants, exhibited similar growth rate and oxalic acid production in laboratory. The genomes of S. rolfsii strains GP3 and ZY were sequenced by Pacbio long read technology and exhibited 70.51 Mb and 70.61 Mb, with contigs of 27 and 23, and encoded 17,097 and 16,743 gene models, respectively. Comparative genomic analysis revealed that the pathogenicity-related gene repertoires, which might be associated with aggressiveness, differed between GP3 and ZY. There were 58 and 45 unique pathogen-host interaction (PHI) genes in GP3 and ZY, respectively. The ZY strain had more carbohydrate-active enzymes (CAZymes) in its secretome than GP3, especially in the glycoside hydrolase family (GH), the carbohydrate esterase family (CBM), and the polysaccharide lyase family (PL). GP3 and ZY also had different effector candidates and putative secondary metabolite synthetic gene clusters. These results indicated that differences in PHI, secreted CAZymes, effectors and secondary metabolites may play important roles in aggressive difference between these two strains.

CONCLUSIONS

The data provided a further understanding of the S. rolfsii genome. Genomic comparison provided clues to the difference in aggressiveness of S. rolfsii strains.

Deciphering the Monilinia fructicola Genome to Discover Effector Genes Possibly Involved in Virulence

Brown rot is the most economically important fungal disease of stone fruits and is primarily caused by Monilinia laxa and Monlinia fructicola. Both species co-occur in European orchards although M. fructicola is considered to cause the most severe yield losses in stone fruit. This study aimed to generate a high-quality genome of M. fructicola and to exploit it to identify genes that may contribute to pathogen virulence. PacBio sequencing technology was used to assemble the genome of M. fructicola. Manual structural curation of gene models, supported by RNA-Seq, and functional annotation of the proteome yielded 10,086 trustworthy gene models. The genome was examined for the presence of genes that encode secreted proteins and more specifically effector proteins. A set of 134 putative effectors was defined. Several effector genes were cloned into Agrobacterium tumefaciens for transient expression in Nicotiana benthamiana plants, and some of them triggered necrotic lesions. Studying effectors and their biological properties will help to better understand the interaction between M. fructicola and its stone fruit host plants.