|
| Status |
Public on Aug 10, 2019 |
| Title |
sRNA apical spikelets |
| Sample type |
SRA |
| |
|
| Source name |
Spikelets
|
| Organism |
Oryza sativa |
| Characteristics |
cultivar: Mahalaxmi
location on panicle: Apical spikelets
tissue: Spikelets
maturity: 6th days after fertilization
|
| Treatment protocol |
The indiviual plants were tagged on the days of anthesis. The spikelets were sampled from the apical and basal regions of the panicle on the 6th days after fertilization
|
| Growth protocol |
Seeds of Oryza sativa cv. Mahalaxmi were germinated on nursery bed and transplanted in field. Pesticides and fertilizers were applied as per the requirement
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was extracted from the individual spikelet samples using Plant RNA purification reagent (Invitrogen). The quality of the RNA was checked for integrity on bioanalyzer, and only the RNA preparation with RNA integrity (RIN) greater than 7.0 was considered for the downstream application.
Ion Total-Seq Kit v2.0 (Thermo Fisher) was used for enrichment of the sRNA population in the individual RNA preparation, ligation of barcoded adapters to sRNAs and conversion of the sRNAs to cDNAs.
The cDNA libraries of sRNAs prepared was verified for size distribution using Agilent 2100 Bioanalyzer. The individual libraries were diluted to 100 pM and pooled in equimolar concentrations for clonal amplification and sequencing. The clonal amplification was done on ion sphere particles (ISs) by emulsion PCR. ISPs positive templates were loaded on Ion PI chip kit (Thermo Fisher) after denaturing and sequencing was on the Ion Proton System
|
| |
|
| Library strategy |
miRNA-Seq |
| Library source |
transcriptomic |
| Library selection |
size fractionation |
| Instrument model |
Ion Torrent Proton |
| |
|
| Data processing |
The sRNA raw reads were subjected to bioinformatics analysis using Fastx Toolkit by which the read quality and length below 17 were trimmed. The filtered reads were mapped on the rice genome using SHRiMP package.
Quantification of the known miRNAs was done using miRDeep2 software, which generated normalized counts utilizing information on the mapped data and known precursors.
The unique reads were searched for the known sequences in the miRBase 22.1 for the identification of the known miRNAs.
The sRNA sequences were then mapped on rice genome for the identification of possible novel miRNAs and their precursors.
The basic criteria described in literature were followed for putative miRNA prediction, including the length of the precursors, formation of hairpin, MFEI value of the precursors, and others.
Genome_build: NCBI Build 4.0, Rfam
Supplementary_files_format_and_content: Excel sheet of known and novel miRNAs and the related information on their ientification
|
| |
|
| Submission date |
Aug 09, 2019 |
| Last update date |
Aug 10, 2019 |
| Contact name |
Birendra Prasad Shaw |
| E-mail(s) |
bpsils@yahoo.com
|
| Phone |
9437488362
|
| Organization name |
Institute of Life Sciences
|
| Street address |
Nalco Square, Besides Kalinga Hospital
|
| City |
Bhubaneswar |
| State/province |
Odisha |
| ZIP/Postal code |
751023 |
| Country |
India |
| |
|
| Platform ID |
GPL27029 |
| Series (1) |
| GSE135614 |
Identification of known and novel miRNAs in the apical and basal spikelets of rice Oryza sativa cv. Mahalaxmi |
|
| Relations |
| BioSample |
SAMN12542084 |
| SRA |
SRX6686101 |
