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Sample GSM4238352

Query DataSets for GSM4238352

Status

Public on Dec 31, 2019

Title

T1_2

Sample type

SRA

Source name

leaf

Organism

Solanum lycopersicum

Characteristics

treatment: para-hydroxybenzoic acid concentration of 15 mM/L
cultivar: Diana
tissue: leaf
age: one month after planted

Treatment protocol

one month later, we treat the S. lycopersicum plants with different concentration of p-Hydroxybenzoic acid (0mmol/L, 15mmol/L and 30mmol/L) for 2 day.

Growth protocol

Tomato seeds were planted in plug plate (Wei Nong company, Taizhou, China).

Extracted molecule

total RNA

Extraction protocol

All samples were frozen in liquid nitrogen and stored at –80°C. Total RNA was extracted using Trizol reagent (Invitrogen, CA, USA) following the manufacturer’s instructions. DNase I (TaKaRa, Dalian, China) was used to treat RNA samples to avoid genomic DNA contamination. The quantity and purity of the total RNA was measured with a Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA) (RIN number >7.0). Equal parts of RNA samples for the same treatment were mixed for transcriptome sequencing and sRNA sequencing. Subsequently, the total mixed RNA sample for leaves was prepared for degradome sequencing.
RNA libraries were prepared for sequencing using standard Illumina protocols

Library strategy

ncRNA-Seq

Library source

transcriptomic

Library selection

size fractionation

Instrument model

Illumina HiSeq 4000

Data processing

Adaptor sequences, poly-N reads and low quality reads were removed using FastQC (V 0.11.5) and Trimmomatic (V 0.36) software to obtain clean reads from raw data (containing more than 50% bases with Q ≤ 30)
Trinity software was used to perform de novo assembly with a k-mer length of 25 and other default parameters. The transcripts were clustered with a TGI clustering tool, and the longest transcripts were defined as unigenes.
We used InterProScan(v 2.0) program to search functional annotation in the multiple protein databases.
FEELnc(V 0.1.1), PLncPRO(V 1.1), RNAplonc(V 1.0) were used to predict LncRNA and the union obtained by the three software predictions as the total LncRNA
RSEM was used to calculate FPKM in each sample. Then, the DESeq R software package was used for comparing differential expression. In multiple tests and analysis, we used FDR to identify the P-value threshold

Submission date

Dec 30, 2019

Last update date

Dec 31, 2019

Contact name

Liang Guoting

E-mail(s)

lgt1984@wfust.edu.cn

Organization name

Weifang University of Science and Technology

Street address

No.1299, Jinguang street