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Sample GSM4210604

Query DataSets for GSM4210604

Status

Public on Nov 08, 2020

Title

Perennial_ryegrass drought treatment rep2

Sample type

SRA

Source name

leaf

Organism

Lolium perenne

Characteristics

tissue: leaf
treatment: drought
genotype: WT

Treatment protocol

Arabidopsis plants were subjected to 42 oC for 12hs, or 4 oC for 6hs. For drought treatment, 14-day-old seedlings were withheld water for 2 weeks. All stress treated plants were recovered at control condition for 5 days.

Growth protocol

Seeds were sowed into plastic pots containing peat soil and vermiculite (1:1 of v/v) after 5 days of stratification at 4oC. The plants were maintained in growth chambers controlled at 22/18oC (day/night), 65% relative humidity, 16 h photoperiod and 150 μmol quanta m–2 s–1 photosynthetically active radiation. All plants were irrigated with nutrient solution twice each week before stress treatments.

Extracted molecule

total RNA

Extraction protocol

The leaves of control and stress treated bermudagrass plants were collected for RAN isolation following the standard Qiagen RNeasy mini kit protocol. RNA purity and integrity was checked using the NanoPhotometer® spectrophotometer (IMPLEN, CA, USA) and RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA), respectively.
RNA libraries were prepared for sequencing using standard Illumina protocols

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2000

Description

T04

Data processing

Library preparation for Transcriptome sequencing:A total amount of 1 μg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext®Ultra™ RNA Library Prep Kit for Illumina®(NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. Fragmentation was carried out using divalent cations under elevated temperature in NEBNext First Strand Synthesis Reaction Buffer（5X）. First strand cDNA was synthesized using random hexamer primer and M-MuLV Reverse Transcriptase. Second strand cDNA synthesis was subsequently performed using DNA Polymerase I and RNase H . Remaining overhangs were converted into blunt ends via exonuclease/polymerase activities. After adenylation of 3’ ends of DNA fragments, NEBNext Adaptor with hairpin loop structure were ligated to prepare for hybridization. In order to select cDNA fragments of preferentially 240 bp in length, the library fragments were purified with AMPure XP system (Beckman Coulter, Beverly, USA). Then 3 μl USER Enzyme (NEB, USA) was used with size-selected, adaptor-ligated cDNA at 37°C for 15 min followed by 5 min at 95°C before PCR. Then PCR was performed with Phusion High-Fidelity DNA polymerase, Universal PCR primers and Index (X) Primer. At last, PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system.
Clustering and sequencing:The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq 2000 platform and paired-end reads were generated.
Quality control: Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. In this step, clean data(clean reads) were obtained by removing reads containing adapter, reads containing ploy-N and low quality reads from raw data. At the same time, Q20, Q30, GC-content and sequence duplication level of the clean data were calculated. All the downstream analyses were based on clean data with high quality.
Transcriptome assembly: The left files (read1 files) from all libraries/samples were pooled into one big left.fq.gz file, and right files (read2 files) into one big right.fq.gz file. Transcriptome assembly was accomplished based on the left.fq.gz and right.fq.gz using Trinity (Grabherr et al, 2011) with min_kmer_cov set to 2 by default and all other parameters set default.
Gene functional annotation: Gene function was annotated based on the following databases: NR (NCBI non-redundant protein sequences)；Pfam (Protein family)；KOG/COG/eggNOG (Clusters of Orthologous Groups of proteins)；Swiss-Prot (A manually annotated and reviewed protein sequence database)；KEGG (Kyoto Encyclopedia of Genes and Genomes)；GO (Gene Ontology).
Genome_build: Differential expression analysis: Gene expression levels were estimated by RSEM (Li et al, 2011) for each sample. Differential expression analysis of two conditions/groups was performed using the DESeq R package (1.10.1). DESeq provide statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate. Genes with an adjusted P-value <0.05 found by DESeq were assigned as differentially expressed.
Supplementary_files_format_and_content: raw counts of sequencing reads

Submission date

Dec 09, 2019

Last update date

Nov 08, 2020

Contact name

Zhulong Chan

E-mail(s)

zlchan@mail.hzau.edu.cn

Organization name

Huazhong Agricultural University

Department

College of Horticulture and Forestry Sciences