tissue: cotyledon genotype/variation: Tendral infection (physiological condition): virus infected (MNSV-chimeric) treatment: Virus infected samples were obtained from completely expanded cotyledons rubbed with carborundum (phi = 0.037 mm) and the corresponding viral inoculum (MNSV or WMV) in inoculation buffer (phosphate buffer 0.2M, pH = 8.0, beta-mercaptoethanol 0.1% (v/v), activated charcoal 0.03 g/ml).
Growth protocol
Plants were grown in a greenhouse at 16h/ligth/25-28C 8h/dark/18-20C
Extracted molecule
total RNA
Extraction protocol
Total RNA was extracted by using Trizol-Reagent and 300 ug were used for construction of sRNAs libraries. SRNAs were purified using 17% denaturing PAGE. Two adaptors were ligated to the 3' and 5' ends of melon sRNAs. The 3' adaptor was a pre-activated 5' adenylated oligo (5'rAppCTGTAGGCACCATCAAT3ddC 3') to avoid the circularization of sRNAs. 10 oligonucleotide 5' adaptor variants were used by modification of the four nucleotide identifier (barcode). After each ligation step, sRNA was purified using 17% denaturing PAGE. The purified ligated sRNA was reverse transcribed with SuperScript III Reverse Transcriptase and the cDNA was amplified by using AmpliTaq Gold DNA Polymerase and 3'PCR FusionB and 5' PCR FusionA primers. PCR primers contained the "A" and "B" tag sequences used by 454 technology during sequencing. DNA amplicons were gel-purified using 4% Metaphor agarose and isolated using a QIAEX II Gel Extraction Kit. Quantity and quality of DNA amplicons were measured using ND-1000 spectrophotometer and Experion Automated Electrophoresis System, respectively. The same amount of DNA amplicon from each library was pooled and sequenced by 454 Life Science technology.
Library strategy
RNA-Seq
Library source
transcriptomic
Library selection
size fractionation
Instrument model
454 GS
Description
small RNA sequencing 3'T cotyledon_MNSVchimeric_Tendral raw data file (original file name): FAI1VGH01.sff raw data file (original file name): FAJ8I4S01.sff Library strategy: BARCODE --> ATCGTAGACCGCUGAUA
Data processing
sRNA sequences were parsed from FASTA formatted files containing 447,180 reads from two independent 454 sequencing runs and assigned to specific libraries through identification of the sRNA/adaptor boundaries and barcode analysis. Sequences were analyzed with standard Python scripts [74] and the BioPython library [75]. Known sRNAs were identified by sequence similarity to nucleic acids deposited in publicly available databases by using the Blast algorithm [76] version 2.2.19 and allowing up to 2 mismatches. Databases and sequences used were: transfer RNA database (version 2009) [77], Plant small nucleolar RNA database (v1.2) [78], SILVA (ribosomal RNA database, v100) [79], The Arabidopsis small RNA Project (ASRP) database [33], Rfam database 10.0 [80], miRBase: the microRNA database (release 16) [34], The Plant Repeat databases [81], chloroplast genome sequence of Cucumis melo (unpublished data), mithocondrial genome sequence of Arabidopsis thaliana (GenBank accession Y08501), genome sequence of MNSV (GenBank accession AY122286.1), genome sequence of WMV (GenBank accession AY437609.1).
