|
| Status |
Public on May 08, 2019 |
| Title |
HDM_allergy_Disease [3998594013_D] |
| Sample type |
RNA |
| |
|
| Source name |
HDM_allergy_Disease
|
| Organism |
Mus musculus |
| Characteristics |
mouse strain: C57BL/6
mouse model: House dust mite (HDM) allergy
condition: Disease
infection protocol: Female C57BL/6/J mice were sensitized with 10 mg HDM (Greer) and 2 mg Imject Alum in 200 ml PBS or Alum alone as control by intraperitoneal injections on days 0 and 14, followed by intratracheal challenge with 10 mg HDM in 20 ml of PBS or PBS on days 21 and 24. Lung samples were collected from individual HDM and PBS control treated mice on day 25.
tissue: lung
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Tissues were collected in TRI-Reagent (Sigma-Aldrich) (for Toxoplasma gondii samples –tissues were collected and samples were stored in RNAlater (Ambion), and then transferred to TRI-Reagent). Total RNA was extracted using the RiboPure™ Kit (Ambion).
|
| Label |
biotin
|
| Label protocol |
cRNA was prepared from 200 ng tissue total RNA using the Illumina TotalPrep RNA Amplification Kit (Ambion). Quality was checked using an RNA 6000 Nano kit (Agilent) using a BioAnalyzer 2100 (Agilent). Biotinylated cRNA samples were randomized.
|
| |
|
| Hybridization protocol |
1.5 µg cRNA was then hybridized to Mouse WG-6 v2.0 bead chips (Illumina) according to the manufacturer’s protocols.
|
| Scan protocol |
Standard Illumina scanning protocol
|
| Description |
raw data file: MRC57.txt
Disease samples from House dust mite (HDM) allergy infection model
|
| Data processing |
Microarray data was processed in GeneSpring GX v14.8 (Agilent Technologies). Flags were used to filter out the probe sets that did not result in a ‘present’ call in at least 10% of the samples, with the ‘present’ lower cut-off of 0.99. Signal values were then set to a threshold level of 10, log2 transformed, and per-chip normalised using 75th percentile shift algorithm. Next, per-gene normalisation was applied by dividing each messenger RNA transcript by the median intensity of all the samples. Next, transcripts were filtered to select the most variable probes: those that had a minimum of 1.5-fold expression change compared with the median intensity across all samples, in greater than 10% of all samples.
|
| |
|
| Submission date |
Sep 12, 2018 |
| Last update date |
May 08, 2019 |
| Contact name |
Akul Singhania |
| E-mail(s) |
akul.singhania@crick.ac.uk
|
| Phone |
+442037963319
|
| Organization name |
The Francis Crick Institute
|
| Street address |
1 Midland Road
|
| City |
London |
| ZIP/Postal code |
NW1 1AT |
| Country |
United Kingdom |
| |
|
| Platform ID |
GPL17543 |
| Series (2) |
| GSE119849 |
Global transcriptional profiling unveils the interferon network in blood and tissues across different diseases [microarray_lung_6] |
| GSE119856 |
Global transcriptional profiling unveils the interferon network in blood and tissues across different diseases |
|
