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| Status |
Public on Jan 18, 2020 |
| Title |
5 Wildtype sibling 3dpf |
| Sample type |
SRA |
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| Source name |
Danio rerio embryo (Tg(14xUAS:GFP-EWSR1-ERG) x Et(E1b:Gal4-VP16)s1101t, Tg(UAS:Kaede) s1999t), 3 days post fertilization
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| Organism |
Danio rerio |
| Characteristics |
genotype/variation: Wildtype: non-EWSR1-ERG-expressing control
biological replica: 3
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| Growth protocol |
Zebrafish were handled in compliance with the local animal welfare regulations and maintained according to standard protocols (http://ZFIN.org). Embryos were grown at 28,5°C in egg water (60µg/ml Instant Ocean sea salts).
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| Extracted molecule |
total RNA |
| Extraction protocol |
Embryos for RNA isolation were homogenized using Bullet Blender Homogenizer (Next Advance, Averill Park, NY); subsequently RNA was extracted using the RNeasy Micro Kit (Qiagen) according to the manufacturer’s instructions, and stored at -80°C. The integrity of the RNA was confirmed by Lab-on-chip analysis using the 2100 Bioanalyzer (Agilent Technologies).
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 2500 |
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| Data processing |
GeneTiles was used for quantification and visualization of the RNAseq data
Bowtie2 is used to align the reads in the fastq file to the genome (obtained from Ensemble). Bowtie2 generates SAM files that contain the reads together with the location on the genome.
Samtools is used to convert and compress the SAM files into a binary BAM file. Samtools is furthermore used to sort the reads in the BAM files based on the aligned read location in the genome, resulting in a sorted BAM file.
The BAM files is indexed to be able to quickly find the aligned reads based on a location in the genome, i.e. to be able to quickly search the BAM file. The index is a saved as a BAI file.
Using the available annotation from Ensemble we can search the BAM file for reads within a gene (using exon starting positions and lengths). This is done with a python script. The output of this script is a tab separated file (tsv) containing the read counts per gene.
We used DESeq, an R-script to perform statistical analysis. The DESeq script is used to normalise the reads per gene, based on (divided by) the total number of reads obtained per sample. Then variance and average of the measurement compared to the control can be expressed as a P-value, by calculating the dispersion per gene using DESeq. The size factors as well as the P-values are stored in ‘tsv’ files.
Using a script, all tsv files are combined into tsv files , e.g. per experiment, chromosome, per filtered results of most significant reads or highest ratio between measurement and control.
Genome_build: Zv9_toplevel
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| Submission date |
Oct 10, 2014 |
| Last update date |
Jan 19, 2020 |
| Contact name |
Wietske van der Ent |
| Organization name |
Leiden University, Institute of Biology Leiden
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| Street address |
Einsteinweg 55
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| City |
Leiden |
| ZIP/Postal code |
2333 CC |
| Country |
Netherlands |
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| Platform ID |
GPL18413 |
| Series (1) |
| GSE62273 |
Gene expression profiling of Tg(14xUAS:GFP-EWSR1-ERG) x Et(E1b:Gal4-VP16)s1101t, Tg(UAS:Kaede) s1999t zebrafish embryos at 3 days post fertilization |
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| Relations |
| BioSample |
SAMN03107138 |
| SRA |
SRX732525 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM1524332_IL-14-04-5_CAGATC_L002_R1_001.txt.gz |
304.2 Kb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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