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Status |
Public on Jan 08, 2020 |
Title |
Zn minus root-rep1 miRNA-seq |
Sample type |
SRA |
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Source name |
Root
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Organism |
Oryza sativa Japonica Group |
Characteristics |
cultivar: Nipponbare tissue: the whole root system developmental stage: 4 week old seedling
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Treatment protocol |
After growing in the nutrient solution (with 1.5 µM ZnSO4) for one week, uniform seedlings were used for Zn deficiency treatment. For Zn deficiency, no ZnSO4 was added to the nutrient solution, while normal 1.5 µM ZnSO4 was used for the control treatment. Roots and shoots of rice seedlings were collected after Zn-deficient treatment for two weeks. For Zn-resupply treatment, Zn-deficient seedlings were transferred to nomal nutrient solution containing 1.5 µM ZnSO4 for three days. After Zn-resupply treatment, roots and shoots were collected for analyses at the same time point as collecting the Zn-deficient samples (four hours after illumination).
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Growth protocol |
Seeds of the rice (Oryza sativa L. japonica) were surface sterilized in 10% (v/v) H2O2 for 20 min and rinsed with sterile water. Seeds were then transferred to seedling trays floating on sterile water for germination. After growing in the sterile water for 10 days, seedlings were transferred to a plastic container with 2.5 L Yoshida solution (Yoshida et al. 1976). The fresh nutrient solution was replenished every 2 day, and the pH was adjusted to 5.6. Plants were grown in a growth chamber under controlled conditions. The light intensity was approximately 180 μmol m-2 s-1 at shoot height with a day/night cycle of 16 h/8 h at 26°C/24°C. The relative humidity was 50%.
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Extracted molecule |
total RNA |
Extraction protocol |
Rice shoots and roots were collected after Zn-deficiency and Zn-resupply treatments. Eighteen samples (Zn-plus shoot, Zn-minus shoot, Zn-resupply shoot, Zn-plus root, Zn-minus root, Zn-resupply root, each with three biological replicates) were harvested for small RNA library construction and sequencing. Roots and shoots from three rice seedlings were collected and mixed together as one sample. Total RNAs were extracted from samples using Trizol reagent (Invitrogen, Carlsbad, CA). RNA abundances and purity were tested following the manufacture of RNA 6000 Nano LabChip Kit (Agilent, CA, USA). Approximately 1.0 μg of total RNA was used to prepare a small RNA library according to the protocol of TruSeq Small RNA Sample Prep Kits (Illumina, San Diego, USA). Single-end sequencing with a length of about 50 bp was conducted on an Illumina Hiseq2500 at the LC-BIO (Hangzhou, China).
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Library strategy |
miRNA-Seq |
Library source |
transcriptomic |
Library selection |
size fractionation |
Instrument model |
Illumina HiSeq 2500 |
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Data processing |
The raw reads were performed on an in-house program ACGT101-miR (LC Sciences, Houston, Texas, USA) to remove adaptor sequences, low-complexity sequences, junk reads, repeat sequences, and the reads that matched the common non-coding RNA families (tRNA, rRNA, snoRNA, and snRNA) deposited in Rfam database (http://www.sanger.ac.uk/software/Rfam). Subsequently, unique sequences with length of 20-24 nucleotide (nt) were mapped to rice miRNA precursors in miRBase 22.0 by BLAST to identify known miRNAs and novel 3p- and 5p- derived miRNAs. Length variation at both 3’ and 5’ ends, and one nt mismatch of the miRNA sequence for the alignment were allowed. The unique sequences mapping to rice mature miRNAs in the precursors were identified as known miRNAs. The unique sequences mapping to the opposite arm of known rice miRNA precursor hairpin were considered to be novel 5p- or 3p- derived miRNA candidates. The remaining sequences were mapped to miRNA precursors of other plant species in miRBase 22.0 by BLAST, and the mapped pre-miRNAs were further aligned with the rice genome to determine their genomic locations. The remaining unmapped sequences were further aligned with the rice genome, and the flanking sequences with a length of 120 nt were collected for secondary structure prediction using RNAfold software (http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi). The criteria for novel miRNA prediction and characterization were based on the previous study (Axtell and Meyers 2018), described as follows: (1) number of nucleotides in one bulge in stem is ≤12; (2) number of base pairs in the stem region of the predicted hairpin is ≥16; (3) the free energy for miRNA precursor should be ≤ -15 kCal/mol; (4) length of hairpin is larger than 50 but less than 300 nt; (5) number of nucleotides in one bulge of the mature region should be ≤4; (6) number of biased errors in one bulge of the mature region should be ≤2; (7) number of biased bulges in the mature region should be ≤2; (8) number of mismatches in mature region should be ≤4; (9) number of base pairs in the mature region of the predicted hairpin should be ≥12; (10) percent of mature sequence in the stem should be ≥80. Genome_build: Rfam database (http://www.sanger.ac.uk/software/Rfam) Supplementary_files_format_and_content: Excel file, with all miRNAs detected and their expression levels in samples
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Submission date |
May 10, 2019 |
Last update date |
Jan 08, 2020 |
Contact name |
Houqing Zeng |
E-mail(s) |
zenghq@hznu.edu.cn
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Phone |
+8657328865199
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Organization name |
Hangzhou Normal University
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Street address |
NO.2318, Yuhangtang Rd, Yuhang District
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City |
Hangzhou |
ZIP/Postal code |
311121 |
Country |
China |
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Platform ID |
GPL18525 |
Series (2) |
GSE131003 |
Integrated analysis of microRNA and mRNA expression profiles of rice seedlings in response to zinc deficiency and recovery (miRNA-seq) |
GSE131004 |
Integrated analysis of microRNA and mRNA expression profiles of rice seedlings in response to zinc deficiency and recovery |
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Relations |
BioSample |
SAMN11618438 |
SRA |
SRX5817429 |
Supplementary data files not provided |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
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