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| Status |
Public on Jun 21, 2024 |
| Title |
cold_water_3 |
| Sample type |
SRA |
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| Source name |
intestinal function disorder model induced by cold water in mice
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| Organism |
Mus musculus |
| Characteristics |
cell type: Proximal jejunum tissue
treatment: cold water
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| Treatment protocol |
The mice were divided into control group that were subjected once daily at 9 am to gastric instillation with 1ml water of room temperature (20-25℃)and cold water group that were subjected once daily at 8 am to gastric instillation with 1ml water of low temperature (0-4℃), for 14 consecutive days.
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| Growth protocol |
All the mice were housed in a temperature (22℃)-controlled environment.
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| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was extracted using Trizol reagent (Invitrogen, CA, USA) following the manufacturer's procedure. The total RNA quantity and purity were analysis of Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA) with RIN number >7.0. Approximately 5 ug of total RNA was used to deplete ribosomal RNA according to the manuscript of the Epicentre Ribo-Zero Gold Kit (Illumina, San Diego, USA). Following purification, the poly(A)- or poly(A)+ RNA fractions is fragmented into small pieces using divalent cations under elevated temperature. Then the cleaved RNA fragments were reverse-transcribed to create the final cDNA library in accordance with 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). And then we performed the paired-end sequencing on an Illumina Hiseq 4000 at the (lc-bio, China) following the vendor's recommended protocol.
RNA libraries were prepared for sequencing using standard Illumina protocols
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 4000 |
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| Data processing |
cutadapt-1.9 (cutadapt.readthedocs.io/en/stable/)was used to remove the reads that contained adapter contamination, low quality bases and undetermined bases. Then sequence quality was verified using FastQC v0.10.1 (www.bioinformatics.babraham.ac.uk/projects/fastqc/). We used hisat2-2.0.4 (ccb.jhu.edu/software/hisat2/)to map reads to the genome, Ensembl v96 (command line: hisat2 -1 R1.fastq.gz -2 R2.fastq.gz -S mapped.sam).
The mapped reads of each sample were assembled using StringTie (http://ccb.jhu.edu/software/stringtie/,version:stringtie-1.3.4d.Linux_x86_64) with default parameters (command line: ~stringtie -p 4 -G genome.gtf -o output.gtf -l sample input.bam). Then, all transcriptomes from all samples were merged to reconstruct a comprehensive transcriptome using gffcompare software(http://ccb.jhu.edu/software/stringtie/gffcompare.shtml,version:gffcompare-0.9.8.Linux_x86_64). After the final transcriptome was generated, StringTie and ballgown(http://www.bioconductor.org/packages/release/bioc/html/ballgown.html) were used to estimate the expression levels of all transcripts and perform expression level for mRNAs by calculating FPKM (FPKM = [total_exon_fragments / mapped_reads(millions) × exon_length(kB)]),(command line: ~stringtie -e -B -p 4 -G merged.gtf -o samples.gtf samples.bam).
The differentially expressed mRNAs were selected with fold change > 2 or fold change < 0.5 and p value < 0.05 by R package edgeR(https://bioconductor.org/packages/release/bioc/html/edgeR.html) or DESeq2(http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html),and then analysis GO enrichment and KEGG enrichment to the differentially expressed mRNAs.
Genome_build: ensembl.org/pub/release-101/fasta/mus_musculus/dna/
Supplementary_files_format_and_content: tab-delimited text files include FPKM values for each Sample
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| Submission date |
Jun 21, 2021 |
| Last update date |
Jun 21, 2024 |
| Contact name |
Li juan Sun |
| E-mail(s) |
sljwilling@sina.cn
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| Organization name |
Northwest University
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| Street address |
229 Taibai North Road, Xi'an
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| City |
Xi'an |
| ZIP/Postal code |
710000 |
| Country |
China |
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| Platform ID |
GPL21103 |
| Series (1) |
| GSE178571 |
Distinct actions of the cold water on host metabolism, gut barrier and microbiome-metabolites gut-brain modules in mice |
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| Relations |
| BioSample |
SAMN19796923 |
| SRA |
SRX11188477 |
| 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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