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Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

ABSTRACT: Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i) contain a secretion signal, (ii) are encoded by in planta induced genes, (iii) have similarity to haustorial proteins, (iv) are small and cysteine rich, (v) contain a known effector motif or a nuclear localization signal, (vi) are encoded by genes with long intergenic regions, (vii) contain internal repeats, and (viii) do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.

SUBMITTER: Saunders DG

PROVIDER: S-EPMC3253089 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

Saunders Diane G O DG Win Joe J Cano Liliana M LM Szabo Les J LJ Kamoun Sophien S Raffaele Sylvain S

PloS one 20120106 1

Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge ...[more]

PMID: 22238666

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Project description:The rust fungi (Pucciniales) with 7000+ species comprise one of the largest orders of Fungi, and one for which taxonomy at all ranks remains problematic. Here we provide a taxonomic framework, based on 16 years of sampling that includes ca. 80 % of accepted genera including type species wherever possible, and three DNA loci used to resolve the deeper nodes of the rust fungus tree of life. Pucciniales are comprised of seven suborders - Araucariomycetineae subord. nov., Melampsorineae, Mikronegeriineae, Raveneliineae subord. nov., Rogerpetersoniineae subord. nov., Skierkineae subord. nov., and Uredinineae - and 18 families - Araucariomycetaceae fam. nov., Coleosporiaceae, Crossopsoraceae fam. nov., Gymnosporangiaceae, Melampsoraceae, Milesinaceae fam. nov., Ochropsoraceae fam. & stat. nov., Phakopsoraceae, Phragmidiaceae, Pileolariaceae, Pucciniaceae, Pucciniastraceae, Raveneliaceae, Rogerpetersoniaceae fam. nov., Skierkaceae fam. & stat. nov., Sphaerophragmiaceae, Tranzscheliaceae fam. & stat. nov., and Zaghouaniaceae. The new genera Araucariomyces (for Aecidium fragiforme and Ae. balansae), Neoolivea (for Olivea tectonae), Rogerpetersonia (for Caeoma torreyae), and Rossmanomyces (for Chrysomyxa monesis, Ch. pryrolae, and Ch. ramischiae) are proposed. Twenty-one new combinations and one new name are introduced for: Angiopsora apoda, Angiopsora chusqueae, Angiopsora paspalicola, Araucariomyces balansae, Araucariomyces fragiformis, Cephalotelium evansii, Cephalotelium neocaledoniense, Cephalotelium xanthophloeae, Ceropsora weirii, Gymnotelium speciosum, Lipocystis acaciae-pennatulae, Neoolivea tectonae, Neophysopella kraunhiae, Phakopsora pipturi, Rogerpetersonia torreyae, Rossmanomyces monesis, Rossmanomyces pryrolae, Rossmanomyces ramischiae, Thekopsora americana, Thekopsora potentillae, Thekopsora pseudoagrimoniae, and Zaghouania notelaeae. Higher ranks are newly defined with consideration of morphology, host range and life cycle. Finally, we discuss the evolutionary and diversification trends within Pucciniales. Citation: Aime MC, McTaggart AR (2020). A higher-rank classification for rust fungi, with notes on genera. Fungal Systematics and Evolution 7: 21-47. doi: 10.3114/fuse.2021.07.02.

Project description:Wheat yellow (stripe) rust caused by Puccinia striiformis f. sp. tritici (PST) is one of the most devastating diseases of wheat worldwide. To design effective breeding strategies that maximize the potential for durable disease resistance it is important to understand the molecular basis of PST pathogenicity. In particular, the characterisation of the structure, function and evolutionary dynamics of secreted effector proteins that are detected by host immune receptors can help guide and prioritize breeding efforts. However, to date, our knowledge of the effector repertoire of cereal rust pathogens is limited.We re-sequenced genomes of four PST isolates from the US and UK to identify effector candidates and relate them to their distinct virulence profiles. First, we assessed SNP frequencies between all isolates, with heterokaryotic SNPs being over tenfold more frequent (5.29 ± 2.23 SNPs/kb) than homokaryotic SNPs (0.41 ± 0.28 SNPs/kb). Next, we implemented a bioinformatics pipeline to integrate genomics, transcriptomics, and effector-focused annotations to identify and classify effector candidates in PST. RNAseq analysis highlighted transcripts encoding secreted proteins that were significantly enriched in haustoria compared to infected tissue. The expression of 22 candidate effector genes was characterised using qRT-PCR, revealing distinct temporal expression patterns during infection in wheat. Lastly, we identified proteins that displayed non-synonymous substitutions specifically between the two UK isolates PST-87/7 and PST-08/21, which differ in virulence to two wheat varieties. By focusing on polymorphic variants enriched in haustoria, we identified five polymorphic effector candidates between PST-87/7 and PST-08/21 among 2,999 secreted proteins. These allelic variants are now a priority for functional validation as virulence/avirulence effectors in the corresponding wheat varieties.Integration of genomics, transcriptomics, and effector-directed annotation of PST isolates has enabled us to move beyond the single isolate-directed catalogues of effector proteins and develop a framework for mining effector proteins in closely related isolates and relate these back to their defined virulence profiles. This should ultimately lead to more comprehensive understanding of the PST pathogenesis system, an important first step towards developing more effective surveillance and management strategies for one of the most devastating pathogens of wheat.

Project description:BackgroundRust fungi constitute the largest group of plant fungal pathogens. However, a paucity of data, including genomic sequences, transcriptome sequences, and associated molecular markers, hinders the development of inhibitory compounds and prevents their analysis from an evolutionary perspective. Gymnosporangium yamadae and G. asiaticum are two closely related rust fungal species, which are ecologically and economically important pathogens that cause apple rust and pear rust, respectively, proved to be devastating to orchards. In this study, we investigated the transcriptomes of these two Gymnosporangium species during the telial stage of their lifecycles. The aim of this study was to understand the evolutionary patterns of these two related fungi and to identify genes that developed by selection.ResultsThe transcriptomes of G. yamadae and G. asiaticum were generated from a mixture of RNA from three biological replicates of each species. We obtained 49,318 and 54,742 transcripts, with N50 values of 1957 and 1664, for G. yamadae and G. asiaticum, respectively. We also identified a repertoire of candidate effectors and other gene families associated with pathogenicity. A total of 4947 pairs of putative orthologues between the two species were identified. Estimation of the non-synonymous/synonymous substitution rate ratios for these orthologues identified 116 pairs with Ka/Ks values greater than1 that are under positive selection and 170 pairs with Ka/Ks values of 1 that are under neutral selection, whereas the remaining 4661 genes are subjected to purifying selection. We estimate that the divergence time between the two species is approximately 5.2 Mya.ConclusionThis study constitutes a de novo assembly and comparative analysis between the transcriptomes of the two rust species G. yamadae and G. asiaticum. The results identified several orthologous genes, and many expressed genes were identified by annotation. Our analysis of Ka/Ks ratios identified orthologous genes subjected to positive or purifying selection. An evolutionary analysis of these two species provided a relatively precise divergence time. Overall, the information obtained in this study increases the genetic resources available for research on the genetic diversity of the Gymnosporangium genus.

Dataset Information

Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

Publications

Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

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