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Metagenome

ABSTRACT: Epiphytic fungal communities present on the grapevine Metagenome

PROVIDER: PRJNA941299 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR24577149.fastq.gz	Fastqsanger.gz
	SRR24577150.fastq.gz	Fastqsanger.gz
	SRR24577151.fastq.gz	Fastqsanger.gz
	SRR24577152.fastq.gz	Fastqsanger.gz
	SRR24577153.fastq.gz	Fastqsanger.gz

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Next Generation Sequencing of grapevine wood pathogen infection in the presence of a root biocontrol agent.

Project description:The goals of this study are to compare NGS-derived transcriptome profiling (RNA-seq) from grapevine wood infected by a fungal pathogen in the presence of a root biological control agent. One of the goals was to obtain molecular data about the fungus pathogen (Phaeomoniella chlamydospora) during grapevine wood infection. Grapevine pathogen-infected wood mRNA profiles of 2-month-old plantlets (14 days post infection) were generated by deep sequencing, in triplicate, using Illumina Hiseq2500. The sequence reads that passed quality filters were analyzed by TopHat followed by Cufflinks. qRTaPCR validation was performed using SYBR Green assays. Using an optimized data analysis workflow, we mapped sequence reads to the grapevine genome (build IGGP 12x) and identified pathogen transcripts. RNAseq analyses, using a ribosomal RNA depletion technology for library preparation, provided identification of genes expressed by P. chlamydospora during infection: as for genes related to effector biosynthesis enzymes, carbohydrate-active enzymes and transcription regulators involved in known regulation pathways in fungi. Insights about P. oligandrum modulation of grapevine infection by this pathogen were also found. Our study represents the first detailed analysis of grapevine wood infection by a fungal pathogen generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive evaluation of mRNA content within grapevine wood tissue. We conclude that RNA-seq based transcriptome characterization would permit the dissection of complex biologic interactions.

2015-10-23 | E-MTAB-3966 | biostudies-arrayexpress

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