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| Status |
Public on Jan 08, 2020 |
| Title |
Zn resupply root-rep2 mRNA-seq |
| Sample type |
SRA |
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| Source name |
Root
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| Organism |
Oryza sativa |
| Characteristics |
cultivar: L. japonica cv. Nipponbare
tissue: the whole root system
developmental stage: 4 week old seedling
treatment: Zn resupply
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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).
Total RNA was extracted using Trizol reagent (Invitrogen, CA, USA), and the quantity and the purity were analyzed by Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA). The RIN value (RNA integrity number) of all RNA samples were more than 8.0. Ten µg of total RNA of each sample was subjected to isolate Poly (A) mRNA with poly-T oligoattached magnetic beads (Invitrogen, Carlsbad, CA). After purification, the mRNA is fragmented into small pieces using divalent cations under elevated temperature. The cleaved RNA fragments were then reverse-transcribed to create cDNA libraries according to the protocol for the mRNA-Seq sample preparation kit (Illumina, San Diego, USA). The average insert size for the paired-end libraries was 300 bp (±50 bp). The paired-end sequencing was performed on an Illumina Hiseq4000 at the LC-BIO (Hangzhou, China).
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 4000 |
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| Description |
sample name in processed data file:
ZRR_2
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| Data processing |
The initial base calling and quality filtering of the reads generated with the Illumina analysis pipeline (Fastq format) were conducted using a custom Perl script and the default parameters of the Illumina pipeline (http://www.illumina.com). Additional filtering for poor-quality bases was performed using the FASTX-toolkit available in the FastQC software package (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
The rice reference genome (https://rapdb.dna.affrc.go.jp/) was indexed by Bowtie2 to facilitate the read mapping. The read mapping was performed using the Tophat software package (Trapnell et al. 2009). Tophat allows multiple alignments per read (up to 40) and a maximum of two mismatches when mapping the reads to the reference genome.
Reads were first mapped directly to the genome using indexing and the unmapped reads were used to identify novel splicing events. The aligned read files were processed by Cufflinks to measure the relative abundances of the transcripts by using the normalized RNA-seq fragment counts.
The estimated gene abundance was measured in terms of the fragments per kilobase of transcript per million mapped reads (FPKM). The differentially expressed genes (DEGs) between the two treatments were identified using Cuffdiff. Only the genes with a log2 fold change ≥1 or ≤−1, and an adjusted P-value (FDR≤0.05) were considered as significantly DEGs.
Genome_build: The rice reference genome (https://rapdb.dna.affrc.go.jp/)
Supplementary_files_format_and_content: one excel file includes FPKM values for each sample
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| Submission date |
May 09, 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 |
GPL23013 |
| Series (2) |
| GSE130980 |
Integrated analysis of microRNA and mRNA expression profiles of rice seedlings in response to zinc deficiency and recovery (mRNA-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 |
SAMN11613477 |
| SRA |
SRX5813957 |
| 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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