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In planta Identification of Putative Pathogenicity Factors from the Chickpea Pathogen Ascochyta rabiei by De novo Transcriptome Sequencing Using RNA-Seq and Massive Analysis of cDNA Ends.

Fondevilla S, Krezdorn N, Rotter B, Kahl G, Winter P - Front Microbiol (2015)

Bottom Line: Since pathogenicity factors are usually secreted, we predicted the A. rabiei secretome, yielding 550 putatively secreted proteins.MACE identified 596 transcripts that were up-regulated during infection.An analysis of these genes identified a collection of candidate pathogenicity factors and unraveled the pathogen's strategy for infecting its host.

View Article: PubMed Central - PubMed

Affiliation: Plant Molecular Biology, Institute for Molecular Bioscience, Goethe-University of Frankfurt Frankfurt am Main, Germany.

ABSTRACT
The most important foliar diseases in legumes worldwide are ascochyta blights. Up to now, in the Ascochyta-legume pathosystem most studies focused on the identification of resistance genes in the host, while very little is known about the pathogenicity factors of the fungal pathogen. Moreover, available data were often obtained from fungi growing under artificial conditions. Therefore, in this study we aimed at the identification of the pathogenicity factors of Ascochyta rabiei, causing ascochyta blight in chickpea. To identify potential fungal pathogenicity factors, we employed RNA-seq and Massive Analysis of cDNA Ends (MACE) to produce comprehensive expression profiles of A. rabiei genes isolated either from the fungus growing in absence of its host or from fungi infecting chickpea leaves. We further provide a comprehensive de novo assembly of the A. rabiei transcriptome comprising 22,725 contigs with an average length of 1178 bp. Since pathogenicity factors are usually secreted, we predicted the A. rabiei secretome, yielding 550 putatively secreted proteins. MACE identified 596 transcripts that were up-regulated during infection. An analysis of these genes identified a collection of candidate pathogenicity factors and unraveled the pathogen's strategy for infecting its host.

No MeSH data available.


Related in: MedlinePlus

Workflow followed for de novo A. rabiei transcriptome assembly.
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Figure 1: Workflow followed for de novo A. rabiei transcriptome assembly.

Mentions: A summary of the workflow followed for the assembly of the A. rabiei transcriptome from RNA-Seq and MACE sequences is shown in Figure 1. RNA-Seq and MACE reads were first separately assembled using the Trinity software (Grabherr et al., 2011), indicating that the reads were strand-specific for improving the quality of the assembly. To reduce sequence redundancy, the scaffolds obtained from these separate assemblies were combined by the CAP3 software using default parameters (Huang and Madan, 1999). Both, the resulting contigs and singletons, were retained and sequences smaller than 200 bp were discarded. This set of sequences is called the A. rabiei transcriptome along the paper. To further remove redundant transcripts, singletons displaying >80% sequence similarity to CAP3-derived contigs were eliminated. This set of sequences is called the “reduced A. rabiei transcriptome.”


In planta Identification of Putative Pathogenicity Factors from the Chickpea Pathogen Ascochyta rabiei by De novo Transcriptome Sequencing Using RNA-Seq and Massive Analysis of cDNA Ends.

Fondevilla S, Krezdorn N, Rotter B, Kahl G, Winter P - Front Microbiol (2015)

Workflow followed for de novo A. rabiei transcriptome assembly.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664620&req=5

Figure 1: Workflow followed for de novo A. rabiei transcriptome assembly.
Mentions: A summary of the workflow followed for the assembly of the A. rabiei transcriptome from RNA-Seq and MACE sequences is shown in Figure 1. RNA-Seq and MACE reads were first separately assembled using the Trinity software (Grabherr et al., 2011), indicating that the reads were strand-specific for improving the quality of the assembly. To reduce sequence redundancy, the scaffolds obtained from these separate assemblies were combined by the CAP3 software using default parameters (Huang and Madan, 1999). Both, the resulting contigs and singletons, were retained and sequences smaller than 200 bp were discarded. This set of sequences is called the A. rabiei transcriptome along the paper. To further remove redundant transcripts, singletons displaying >80% sequence similarity to CAP3-derived contigs were eliminated. This set of sequences is called the “reduced A. rabiei transcriptome.”

Bottom Line: Since pathogenicity factors are usually secreted, we predicted the A. rabiei secretome, yielding 550 putatively secreted proteins.MACE identified 596 transcripts that were up-regulated during infection.An analysis of these genes identified a collection of candidate pathogenicity factors and unraveled the pathogen's strategy for infecting its host.

View Article: PubMed Central - PubMed

Affiliation: Plant Molecular Biology, Institute for Molecular Bioscience, Goethe-University of Frankfurt Frankfurt am Main, Germany.

ABSTRACT
The most important foliar diseases in legumes worldwide are ascochyta blights. Up to now, in the Ascochyta-legume pathosystem most studies focused on the identification of resistance genes in the host, while very little is known about the pathogenicity factors of the fungal pathogen. Moreover, available data were often obtained from fungi growing under artificial conditions. Therefore, in this study we aimed at the identification of the pathogenicity factors of Ascochyta rabiei, causing ascochyta blight in chickpea. To identify potential fungal pathogenicity factors, we employed RNA-seq and Massive Analysis of cDNA Ends (MACE) to produce comprehensive expression profiles of A. rabiei genes isolated either from the fungus growing in absence of its host or from fungi infecting chickpea leaves. We further provide a comprehensive de novo assembly of the A. rabiei transcriptome comprising 22,725 contigs with an average length of 1178 bp. Since pathogenicity factors are usually secreted, we predicted the A. rabiei secretome, yielding 550 putatively secreted proteins. MACE identified 596 transcripts that were up-regulated during infection. An analysis of these genes identified a collection of candidate pathogenicity factors and unraveled the pathogen's strategy for infecting its host.

No MeSH data available.


Related in: MedlinePlus