|
| Status |
Public on Oct 01, 2015 |
| Title |
Tjilkuri-H-CG-2-b |
| Sample type |
SRA |
| |
|
| Source name |
Tjilkuri,developing head,control treatment,season 2
|
| Organism |
Triticum turgidum subsp. durum |
| Characteristics |
variety name: Tjilkuri
water deficit stress tolerance: Sensitive
treatment group: Control Group (CG)
tissue: Developing head (H)
growing season: Season 2
plant id number: No. 41
|
| Treatment protocol |
Please see Methods, Liu et al.(2015)
|
| Growth protocol |
Please see Methods, Liu et al.(2015)
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was isolated using the TriPure reagent. Small RNA was excised and purified from TBE urea polyacrylamide gel.
Small RNA libraries were constructed using NEB Next Multiplex Small RNA Library Prep Set for Illumina (New England Biolabs, UK) following the manufacturer’s instructions.
|
| |
|
| Library strategy |
miRNA-Seq |
| Library source |
transcriptomic |
| Library selection |
size fractionation |
| Instrument model |
Illumina HiSeq 2500 |
| |
|
| Description |
Ti2-H-CG-b
|
| Data processing |
Novel miRNA: Raw data were processed by trimming 3' adapter sequences. The non-redundant (NR) set of 3' adapter trimmed reads of 19-26 bp in length were filtered to remove low quality reads. Clean sRNA-seq data was used to identify candidate pre-miRNA hairpins from the International Wheat Genome Sequencing Consortium’s (IWGSC) Chromosomal Survey Sequences (CSS). For each NR 3' adapter trimmed read, all perfect alignment locations in the IWGSC CSS were identified. Using a subset of reads and CSS contigs involved in those perfect alignments, we also identified all imperfect alignments (two-five mismatches). The candidate pre-miRNA hairpins were defined using all pairwise combinations of perfect to imperfect alignments of a given read within a CSS contig. Additional constraints were applied such that the perfect and imperfect alignments were in opposite orientations and separated by 54-1000 bp. A NR set of these regions ±20 bp, were processed by RNAFold and then miRcheck to ascertain if they could form hairpin structures and have characteristics associated with the miRNA biogenesis pathway in plants with a read coverage profile. All candidate miRNA hairpin sequences were classified into one of eight categories (A-H, where A has a read coverage profile matching our expectations for a true miRNA) using three Boolean metrics based on their read coverage profile. Putative miRNA hairpins were further characterised by identifying if their sequence contained any perfect matches to the 35,828 mature miRNAs from miRBase v21 to determine novel miRNA hairpins. Please see Methods, Liu et al.(2015) for details.
|
| |
|
| Submission date |
May 28, 2015 |
| Last update date |
May 15, 2019 |
| Contact name |
Jason A Able |
| E-mail(s) |
jason.able@adelaide.edu.au
|
| Organization name |
University of Adelaide
|
| Department |
School of Agriculture, Food and Wine
|
| Lab |
Able Lab
|
| Street address |
GN10b, Waite Main Buiding, Waite Road
|
| City |
Urrbrae |
| State/province |
SA |
| ZIP/Postal code |
5064 |
| Country |
Australia |
| |
|
| Platform ID |
GPL20257 |
| Series (1) |
| GSE69339 |
Genome-wide identification of differentially expressed microRNAs in leaves and the developing head of four durum genotypes during water deficit stress |
|
| Relations |
| BioSample |
SAMN03742343 |
| SRA |
SRX1042018 |
