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Sample GSM4658634

Query DataSets for GSM4658634

Status

Public on Oct 19, 2020

Title

sRNA -SG15_WH - Rep2

Sample type

SRA

Source name

Developing grain tissue

Organism

Triticum turgidum subsp. durum

Characteristics

genotype: L6 (Stres-sensitive)
treatment group: Water-deficit plus heat stress (WH)
time-point (dpa, days post anthesis): 15DPA

Treatment protocol

Four treatment groups were: control group (CG), pre-anthesis water-deficit stress group (WS), post-anthesis heat stress group (HS) and water-deficit plus heat stress group (WH). All plants were well-watered from germination to booting. Water-deficit stress was applied to WS and WH by maintaining the soil water content at 6% (half of the field capacity) from booting until harvest (Liu et al., 2019). Heat stress was applied by placing plants in a growth chamber at 37°C/27°C with a 12h photoperiod. HS and WH plants were treated with heat for 24h at multiple reproductive time-points consecutively [5, 15, 25, 35, and 45 days post anthesis (DPA)] (Liu et al., 2019). After 24h, plants were moved back to the standard conditions and remained there between each treatment time-point. Flag leaf samples were collected at each DPA.

Growth protocol

Stress-tolerant genotype DBA Aurora and stress-sensitive genotype L6 (University of Adelaide breeding line, UAD1301020-8) were grown in controlled glasshouse conditions as previously described (Liu et al., 2019). Briefly, 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 from a total of 120 samples (2 genotypes × 4 treatments × 5 time-points × 3 biological replicates) 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 118 sRNA libraries were constructed using the NEBNext® Multiplex Small RNA Library Prep Kit. Eight 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

Jul 07, 2020

Last update date

Oct 19, 2020

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