Limits...
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

Percentage of A. rabiei transcripts belonging to each GO Slim term for the GO categories (A) Biological process and (B) Molecular function. Only the 10 most frequent GO Slim terms are shown.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4664620&req=5

Figure 3: Percentage of A. rabiei transcripts belonging to each GO Slim term for the GO categories (A) Biological process and (B) Molecular function. Only the 10 most frequent GO Slim terms are shown.

Mentions: To infer the putative functions of A. rabiei transcripts we used BLAST. In order to favor informative hits, modified UniProtKB/Swiss-Prot, UniProtKB, RefSeq_protein, and nr databases, lacking uncharacterized protein or nucleotide sequences were used for BLASTing. Out of 22,725 transcripts representing the A. rabiei transcriptome, 14,116 could be annotated using this approach. Of these, 8421 matched to entries in the UniProtKB/Swiss-Prot data base, 5285 to UniProtKB and 410 to RefSeq_protein and nr database entries. The associated hits were searched for their respective Gene Ontology (GO) terms and classified into GO Slim terms using GoSlimViewer software. For the GO category “Biological process” the most represented GO Slim terms were “biosynthetic process,” “cellular nitrogen compounds metabolic process,” “transport,” “small molecule metabolic process,” and “catabolic process” (Figure 3). For the GO category “Molecular function,” the most abundant GO Slim terms were “ion binding,” “oxidoreductase activity,” “transmembrane transporter activity,” “DNA binding,” “kinase activity,” and “hydrolase activity, acting on glycosyl bonds” (Figure 3).


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)

Percentage of A. rabiei transcripts belonging to each GO Slim term for the GO categories (A) Biological process and (B) Molecular function. Only the 10 most frequent GO Slim terms are shown.
© Copyright Policy
Related In: Results  -  Collection

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

Figure 3: Percentage of A. rabiei transcripts belonging to each GO Slim term for the GO categories (A) Biological process and (B) Molecular function. Only the 10 most frequent GO Slim terms are shown.
Mentions: To infer the putative functions of A. rabiei transcripts we used BLAST. In order to favor informative hits, modified UniProtKB/Swiss-Prot, UniProtKB, RefSeq_protein, and nr databases, lacking uncharacterized protein or nucleotide sequences were used for BLASTing. Out of 22,725 transcripts representing the A. rabiei transcriptome, 14,116 could be annotated using this approach. Of these, 8421 matched to entries in the UniProtKB/Swiss-Prot data base, 5285 to UniProtKB and 410 to RefSeq_protein and nr database entries. The associated hits were searched for their respective Gene Ontology (GO) terms and classified into GO Slim terms using GoSlimViewer software. For the GO category “Biological process” the most represented GO Slim terms were “biosynthetic process,” “cellular nitrogen compounds metabolic process,” “transport,” “small molecule metabolic process,” and “catabolic process” (Figure 3). For the GO category “Molecular function,” the most abundant GO Slim terms were “ion binding,” “oxidoreductase activity,” “transmembrane transporter activity,” “DNA binding,” “kinase activity,” and “hydrolase activity, acting on glycosyl bonds” (Figure 3).

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