MADS-Box Transcription Factor ZtRlm1 Is Responsible for Virulence and Development of the Fungal Wheat Pathogen Zymoseptoria tritici

Mohammadi, Naser; Mehrabi, Rahim; Gohari, Amir Mirzadi; Roostaei, Mozaffar; Goltapeh, Ebrahim Mohammadi; Safaie, Naser; Kema, Gert H. J.

doi:10.3389/fmicb.2020.01976

Cited by 9 publications

(6 citation statements)

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“…However, the failure of yeast-like cells to transition into hyphae, or reduction of overall filamentation, results in reduced virulence. A fungus with a lower capacity for stomatal penetration limits the ability for subsequent intercellular colonisation and could severely delay or outright abolish virulence ( King et al., 2017 ; Mohammadi et al., 2020 ). For this reason, assays that easily identify “switching” mutants are a quick valuable screen for putatively identifying reduced virulence mutants.…”

Section: Introductionmentioning

confidence: 99%

Fungal plant pathogen “mutagenomics” reveals tagged and untagged mutations in Zymoseptoria tritici and identifies SSK2 as key morphogenesis and stress-responsive virulence factor

et al. 2023

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“Mutagenomics” is the combination of random mutagenesis, phenotypic screening, and whole-genome re-sequencing to uncover all tagged and untagged mutations linked with phenotypic changes in an organism. In this study, we performed a mutagenomics screen on the wheat pathogenic fungus Zymoseptoria tritici for altered morphogenetic switching and stress sensitivity phenotypes using Agrobacterium-mediated “random” T-DNA mutagenesis (ATMT). Biological screening identified four mutants which were strongly reduced in virulence on wheat. Whole genome re-sequencing defined the positions of the T-DNA insertion events and revealed several unlinked mutations potentially affecting gene functions. Remarkably, two independent reduced virulence mutant strains, with similarly altered stress sensitivities and aberrant hyphal growth phenotypes, were found to have a distinct loss of function mutations in the ZtSSK2 MAPKKK gene. One mutant strain had a direct T-DNA insertion affecting the predicted protein’s N-terminus, while the other possessed an unlinked frameshift mutation towards the C-terminus. We used genetic complementation to restore both strains’ wild-type (WT) function (virulence, morphogenesis, and stress response). We demonstrated that ZtSSK2 has a non-redundant function with ZtSTE11 in virulence through the biochemical activation of the stress-activated HOG1 MAPK pathway. Moreover, we present data suggesting that SSK2 has a unique role in activating this pathway in response to specific stresses. Finally, dual RNAseq-based transcriptome profiling of WT and SSK2 mutant strains revealed many HOG1-dependent transcriptional changes in the fungus during early infection and suggested that the host response does not discriminate between WT and mutant strains during this early phase. Together these data define new genes implicated in the virulence of the pathogen and emphasise the importance of a whole genome sequencing step in mutagenomic discovery pipelines.

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Section: Introductionmentioning

confidence: 99%

Fungal plant pathogen “mutagenomics” reveals tagged and untagged mutations in Zymoseptoria tritici and identifies SSK2 as key morphogenesis and stress-responsive virulence factor

et al. 2023

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“…Although the stages of development are known, a complete picture for the molecular mechanisms controlling development remain to be established. Efforts to elucidate this subject have focused on characterising virulence factors, focusing on small secreted effectors [42,44,[53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68], transcription factors and kinases [69][70][71][72][73][74]. A broader approach involves transcriptome profiling through the infection cycle, assessing systems-level adaptation to environmental changes and differences in host responses from cultivars with ranging susceptibilities [30,31,44,[75][76][77][78][79][80][81].…”

Section: Introductionmentioning

confidence: 99%

Fungal Pathogen Gene Selection for Predicting the Onset of Infection Using a Multi-Stage Machine Learning Approach

Thomas,

Stoner,

Costa

et al. 2023

Preprint

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Phytopathogenic fungi pose a serious threat to global food security. Next-generation sequencing technologies, such as transcriptomics, are increasingly used to profile infection, assess environmental adaptation and gauge host-responses. The accumulation of these large-scale data has created the opportunity to employ new computational methods to gain greater biological insights. Machine learning approaches, that learn to identify patterns in complex data sets, have recently been applied to the field of plant-pathogen interactions. Here, we apply a machine learning approach to transcriptomics data for the fungal pathogenZymoseptoria tritici, to predict the onset of infection as measured by timing of the appearance of necrosis. We present a method for identifying the most important genes that predict infection timings, accurately classify isolates as early and late infectors and predict the timing of infection of ‘novel’ isolates using only a subset of the data. These methods and the genes identified further demonstrate the use of these tools in the field of plant-pathogen interactions and have implications for the identification of biomarkers for disease monitoring and forecasting.Fungi that infect plants pose a serious threat to global food security. Methods to study these pathogens generate vast amounts of data that create new opportunities for computational tools to analyse them. Machine learning methods can learn patterns in complex data such as when genes are turned on or off in fungal plant pathogens. In this study we use machine learning approaches to predict the onset of infection in several isolates of an important fungal pathogen. We show that these methods can identify a small group of genes that are predictive of the infection onset. We can even use these methods on ‘novel’ isolates to infer the likely timing of disease development. Our work has implications for plant disease diagnosis, monitoring and forecasting.

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“…MADS-box genes play important regulatory roles in fruit growth and development, such as the FOREVER YOUNG FLOWER (FYF) gene, the SEPtype CMB1 gene, and auxin-related SlIAA9 in tomato (Solanum lycopersicon) (Molesini et al, 2020;Xie et al, 2014;; PaMADS7 of cherry (Cerasus pseudocerasus) (Qi et al, 2020); MA-MADS5 of banana (Musa nana) (Roy et al, 2012); and VEGETATIVE TO PRODUCTIVE TRANSITION 2 in wheat (Triticum aestivum) (Adamski et al, 2021). MADS-box genes are also involved in the plant stress response, such as Zymoseptoria tritici ZtRlm1; AtAGL16; and SiMADS51 in Setaria italica (Mohammadi et al, 2020;Zhao et al, 2020). Therefore, the MADS-box family is one of the driving factors of plant diversity and plays an important role in growth and development (Lai et al, 2022;Theissen & Saedler, 2001;Yamaguchi & Hirano, 2006) Pepper (Capsicum spp.)…”

Section: Introductionmentioning

confidence: 99%

Genome-wide identification, evolution, and expression characterization of the pepper MADS-box gene family

Gan

Feng

et al. 2022

Preprint

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MADS domain transcription factors play roles throughout the whole lifecycle of plants from seeding to flowering and fruitbearing. However, systematic research into MADS-box genes of the economically important vegetable crop pepper (Capsicum spp.) is still lacking. We identified 174, 207, and 72 MADS-box genes from the genomes of C. annuum, C. baccatum and C. chinense, respectively. These 453 MADS-box genes were divided into type I (Mα, Mβ, Mγ) and type II (MIKC* and MIKCC) based on their phylogenetic relationships. Collinearity analysis identified 144 paralogous genes and 195 orthologous genes in the three pepper species, and 70, 114, and 10 MADS-box genes specific to C. annuum, C. baccatum and C. chinense, respectively. Comparative genomic analysis highlighted functional differentiation among homologous MADS-box genes during pepper evolution. Tissue expression analysis revealed three main expression patterns: highly expressed in roots, stems, leaves and flowers (CaMADS93/CbMADS35/CcMADS58); only expressed in roots; and specifically expressed in flowers (Ca-MADS26/CbMADS31/CcMADS11). This study provides the basis for an in-depth study of the evolutionary features and biological functions of pepper MADS-box genes. Hosted fileessoar.10512212.1.docx available at https://authorea.com/users/542768/articles/601054genome-wide-identification-evolution-and-expression-characterization-of-the-pepper-madsbox-gene-family Core Ideas:• Genome-wide identification identified 454 MADS-box genes from Capsicum spp. Genomes.• Genome-wide identification revealed the evolutionary relationship of MADSbox gene family in Capsicum spp.• Most of the Capsicum MADS-box genes have been amplified on a large scale.• Most of the Capsicum MADS-box genes have undergone purification selection during evolution.• Tissue specific expression patterns of most MADS-box genes indicated their functional diversity. Genome-wide identification, evolution, and expression characterization of the pepper MADS-box gene familyZhicheng Gan,

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MADS-Box Transcription Factor ZtRlm1 Is Responsible for Virulence and Development of the Fungal Wheat Pathogen Zymoseptoria tritici

Cited by 9 publications

References 50 publications

Fungal plant pathogen “mutagenomics” reveals tagged and untagged mutations in Zymoseptoria tritici and identifies SSK2 as key morphogenesis and stress-responsive virulence factor

Fungal plant pathogen “mutagenomics” reveals tagged and untagged mutations in Zymoseptoria tritici and identifies SSK2 as key morphogenesis and stress-responsive virulence factor

Fungal Pathogen Gene Selection for Predicting the Onset of Infection Using a Multi-Stage Machine Learning Approach

Genome-wide identification, evolution, and expression characterization of the pepper MADS-box gene family

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