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Sample GSM5222598

Query DataSets for GSM5222598

Status

Public on May 24, 2021

Title

AuCC_L_sRNA

Sample type

SRA

Source name

Flag leaf tissue

Organism

Triticum turgidum subsp. durum

Characteristics

tissue: Flag leaf tissue
genotype: DBA Aurora
origin of the parental plants: Control group parents
progeny treatment: Control group

Treatment protocol

The treatment groups are: AuCC (DBA Aurora progeny treated with the control, originated from control group parents), AuCH (DBA Aurora progeny treated with heat stress, originated from control group parents), AuHC (DBA Aurora progeny treated with the control, originated from heat stress group parents), AuHH (DBA Aurora progeny treated with heat stress, originated from heat stress group parents). _L indicates flag leaf library and _G indicates developing grains library. Durum wheat plants were grown in pots (one plant per pot) in the glasshouse under controlled conditions as previously described [1]. Control group plants were grown under the standard growing temperature for the whole crop cycle. For the heat stress group, post-anthesis heat stress was applied at five timepoints [5, 15, 25, 35, and 45 days post anthesis (DPA)]. Plants were placed in a heat stress growth chamber at each timepoint under 37 °C/27 °C day/night temperature for 24h, then they were moved back to the standard growing conditions. All heat stress group plants had undergone five times of heat stress treatment. Flag leaf and developing grains of the main tiller were sampled from four biological replicates per treatment group at 5 DPA.

Growth protocol

Durum wheat variety DBA Aurora plants were grown in controlled glasshouse conditions as previously described (Liu et al., 2019). The standard growing conditions were 22°C/12°C (day/night) with a 12h photoperiod.

Extracted molecule

total RNA

Extraction protocol

Total RNA was extracted using the Tri reagent (Sigma-Aldrich) and treated with TURBO DNase (ThermoFisher Scientific). RNA concentration, quality and integrity was assessed by NanoDrop, gel electrophoresis and Bioanalyzer.
The sRNA libraries were constructed using the NEBNext® Multiplex Small RNA Library Prep Kit. The transcriptome libraries were constructed using the Illumina mRNA-Seq sample preparation kit. For degradome-seq, mRNA was enriched using oligo-d(T) magnetic beads. The enriched mRNA was mixed with biotinylated random primers and were ligated to 5' adaptors. First-strand cDNA was reverse-transcribed from ligated mRNA products and then amplified with PCR.

Library strategy

miRNA-Seq

Library source

transcriptomic

Library selection

size fractionation

Instrument model

Illumina NovaSeq 6000

Description

sRNA-seq processed data.xlsx

Data processing

sRNA-Seq: Small RNA sequencing analysis was performed using the ACGT101-miR program (LC Sciences, TX, USA). Raw reads were first processed by removing low-quality reads and adapter sequences to obtain clean sequences. Reads with a nucleotide (nt) length <18 nt or >25 nt were removed. Non-coding (nc) RNA families (rRNA, tRNA, snRNA and snoRNA), repeats and mRNA sequences were discarded using RFam, Repbase and durum wheat NCBI mRNA entries as references. Unique sRNA sequences were then obtained for each library. Conserved mature miRNAs and 5p- or 3p-derived miRNA variants were identified using BLAST search against the plant miRBase (Release 22.1). MIR (microRNA gene locus) and miRNA sequences from common plant species in the miRBase were used as references. Sequences mapped to the mature miRNA in the hairpin were identified as conserved mature miRNAs. Sequences mapped to the opposite arm of mature miRNA in the hairpin were identified as 5p- or 3p-derived variants. Single mismatch within the sequence and length variation at both 5p and 3p were allowed in the alignment. All the mapped miRNAs were aligned to the durum wheat genome (NCBI UID 3439611, assembly Svevo.v1) to determine their genomic location. The remaining unmatched sRNA sequences were used to identify novel durum miRNAs. Sequences were BLASTed to the durum wheat genome. To identify miRNA precursors, secondary hairpin structures containing matched sequences were predicted using RNAfold (http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi) from 120nt of flanking genome sequences.
mRNA-Seq: Prior to sequence assembly, low quality reads (those containing primer or adaptor sequence, and those with a sequencing quality score < 20) were removed. Clean reads were aligned to the durum reference genome using the HISAT package (V2.0). Aligned reads of each library were assembled and the transcript abundance were obtained using StringTie (V1.3.0). Normalised relative abundance was expressed in FPKM (Fragments Per Kilobase Million).
Degradome-Seq: Raw sequencing reads were processed using the ACGT101-DEG program (V4.1, LC Sciences) to remove low-quality reads, reads with adaptor and primer contamination, and reads that can be annotated as non-coding RNA families. The remaining clean reads were used to identify the degraded fragments of mRNAs that are targets of known and novel durum miRNAs with the CleaveLand package V4.0 and the ACGT101-DEG program (LC Sciences, TX, USA). The mRNA cleavage sites at the 10th position of miRNA alignment with P value < 0.05 were considered as significant.
Genome_build: Durum wheat genome (NCBI UID 3439611, assembly Svevo.v1)
Supplementary_files_format_and_content: Matrix table with abundance measurements of microRNAs (sRNA-seq), mRNAs (mRNA-seq) and mRNA targets (degradome-seq)

Submission date

Apr 01, 2021

Last update date

May 24, 2021

Contact name

Haipei Liu

E-mail(s)

haipei.liu@adelaide.edu.au

Organization name

The University of Adelaide

Street address

PMB1 Waite Building, School AFW