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Sample GSM3223569 Query DataSets for GSM3223569
Status Public on Jul 26, 2019
Title Control Garganega berries 3
Sample type SRA
 
Source name berries
Organism Vitis vinifera
Characteristics tissue: berries
sample type: control berries
strain/cultivar: Vitis vinifera cv. Garganega
Treatment protocol Among the 1000 sterilized berries, 500 berries were inoculated with B. cinerea by syringae injection while the remaining 500 berries were injected with sterile water and were used as negative control. Garganega berries were then incubated into sterile 24-well plates under controlled conditions (15°C/15h dark; 18°C/9h light) to induced noble rot.
Growth protocol B. cinerea B05.10 liquid cultures were produced in three flasks inoculating 7 x 106 conidia/ml into 125 ml of potato dextrose broth (Formedium, Hunstanton, UK). After 7 days of incubation at 22°C and shaking at 120 rpm, B. cinerea mycelia were recovered by filtration, frozen and ground in liquid nitrogen. Vitis vinifera cv. Garganega bunches were harvested in October 2014 in Monteforte d’Alpone (Verona, Italy) and withered into the Pasqua Vigneti e Cantine winery facility located in Verona. Healthy grapes were collected at the commercial ripening stage (soluble solids content = 18.5 ± 0.25°Brix) and placed into perforated plastic boxes (plateaux, about 5 kg each) in a ventilated withering facility under natural conditions (17–20°C, 78–82% relative humidity). Randomly selected replicates were subjected weekly to Brix degrees determination using a DBR35 digital refractometer (Giorgio Bormac, Carpi, Italy) while three dedicated plateaux were weighed weekly using a CH50K50 electronic balance (Kern, Balingen, Germany) in order to determine the weight loss of the berry bunches. After one month of withering, berry Brix degree was about 26.6 and the percentage of weight loss was ~30% of the initial weigh. At this stage, 1000 Garganega berries (with pedicels) were sampled, surface sterilized for 5 minutes in 70% Ethanol and dried in sterility.
Extracted molecule total RNA
Extraction protocol Infected/uninfected berry pericarps were ground into liquid nitrogen and total RNA was isolated from 200 mg of powders using the Spectrum™ Plant Total RNA Kit (Sigma-Aldrich, St. Louis, MO, USA). The RNA quantity, integrity and purity were controlled using a Nanodrop 2000 instrument (Thermo Scientific, Wilmington, DE, USA) and a Bioanalyzer Chip RNA 7500 serie II (Agilent).
For each sample, unstranded library was prepared from 2.5 µg of total RNA using the Illumina TruSeq Library Prep Kit v2 (Illumina, San Diego, CA).
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina NextSeq 500
 
Description Control Garganega berries, inoculated with water
Data processing de-multiplexing: all raw reads related to the same sample (originally spread over multiple FASTQ files) were merged into a single FASTQ file of R1 or R2 reads for the given sample.
data filtering: raw reads were subjected to quality control by using the IlluQC software, that is part of the NGS QC Toolkit [Patel RK, Jain M. NGS QC Toolkit: a toolkit for quality control of next generation sequencing data. PLoS One. 2012;7(2):e30619. doi: 10.1371/journal.pone.0030619. Epub 2012 Feb 1. PubMed PMID: 22312429; PubMed Central PMCID: PMC3270013.] with default parameters (i.e.: quality cutoff: 20; required % of nucleotides in reads with quality score at least equal to quality cutoff: 70%).
mapping: filtered reads were mapped against a mixed reference genome (Botrytis cinerea + Vitis vinifera) by using TopHat (version 2.0.11) [Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009 May 1;25(9):1105-11. doi: 10.1093/bioinformatics/btp120. Epub 2009 Mar 16. PubMed PMID: 19289445; PubMed Central PMCID: PMC2672628.].
gene-level summarization: mapped reads were summarized at the gene-level into a count-matrix by using the htseq-count tool from the HTSeq library [Anders S, Pyl PT, Huber W. HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015 Jan 15;31(2):166-9. doi: 10.1093/bioinformatics/btu638. Epub 2014 Sep 25. PubMed PMID: 25260700; PubMed Central PMCID: PMC4287950].
gene-level count matrices were then used to perform differential expression analyses by using edgeR [Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010 Jan 1;26(1):139-40. doi: 10.1093/bioinformatics/btp616. Epub 2009 Nov 11. PubMed PMID: 19910308; PubMed Central PMCID: PMC2796818]. Only genes having at least 3 mapped reads in at least 3 samples of the above count matrix were tested for differential expression.
Genome_build: whole-genome sequences and annotations for Vitis vinifera (genome annotation release: V1) were obtained from the Grape genome database [Vitulo N, Forcato C, Carpinelli EC, Telatin A, Campagna D, D'Angelo M, Zimbello R, Corso M, Vannozzi A, Bonghi C, Lucchin M, Valle G. A deep survey of alternative splicing in grape reveals changes in the splicing machinery related to tissue, stress condition and genotype. BMC Plant Biol. 2014 Apr 17;14:99. doi: 10.1186/1471-2229-14-99. PubMed PMID: 24739459; PubMed Central PMCID: PMC4108029]. Whole-genome sequences and annotations for Botrytis cinerea (Ensembl-fungi release 28; Botrytis cinerea strain: B05.10; Genome assembly: ASM15095v2) were obtained from the Ensembl Fungi data portal [Kersey PJ, Lawson D, Birney E, Derwent PS, Haimel M, Herrero J, Keenan S, Kerhornou A, Koscielny G, Kähäri A, Kinsella RJ, Kulesha E, Maheswari U, Megy K, Nuhn M, Proctor G, Staines D, Valentin F, Vilella AJ, Yates A. Ensembl Genomes: extending Ensembl across the taxonomic space. Nucleic Acids Res. 2010 Jan;38(Database issue):D563-9. doi: 10.1093/nar/gkp871. Epub 2009 Nov 1. PubMed PMID: 19884133; PubMed Central PMCID: PMC2808935]. Both sets of genomic data were downloaded on August 5, 2015.
Supplementary_files_format_and_content: file “Gene_level_count matrix_Botrytis cinerea.xls”: Microsoft Excel file including 2 sheets: (1.) “rawCounts__allGenes” = gene-level raw counts matrix produced by the hts-count software for 11702 annotated Botrytis cinerea genes across all 9 samples assayed by RNA-Seq; (2) “normCounts__edgeR_testedGenes” = gene-level matrix of edgeR-normalized counts limited to 10881 genes passing abundance filter (ie: with at least 3 raw counts in at least 3 samples) across 6 samples (ie: 3 replicates of the two conditions under contrast). File “Gene_level_count matrix_Garganega.xls”: Microsoft Excel file including 2 sheets: (1.) “rawCounts__allGenes” = gene-level raw counts matrix produced by the hts-count software for 29970 annotated Vitis vinifera genes across all 9 samples assayed by RNA-Seq; (2) “normCounts__edgeR_testedGenes” = gene-level matrix of edgeR-normalized counts limited to 22253 genes passing abundance filter (ie: with at least 3 raw counts in at least 3 samples) across 6 samples (ie: 3 replicates of the two conditions under contrast).
 
Submission date Jun 26, 2018
Last update date Jul 26, 2019
Contact name Teresa Colombo
Organization name Consiglio Nazionale delle Ricerche (CNR)
Department Institute of Molecular Biology and Pathology (IBPM)
Street address p.le A. Moro 7
City Rome
ZIP/Postal code 00185
Country Italy
 
Platform ID GPL24368
Series (2)
GSE116274 Whole-transcriptome RNA-seq analysis of grapevine-Botrytis cinerea interaction during latent infection of berries (“noble rot”)
GSE116741 Whole-transcriptome analysis of grapevine-Botrytis cinerea interaction during latent infection of berries
Relations
BioSample SAMN09488324

Supplementary data files not provided
Raw data are available in SRA
Processed data are available on Series record

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