|
| Status |
Public on Oct 16, 2021 |
| Title |
HT29_ORF_CTH_39 |
| Sample type |
RNA |
| |
|
| Source name |
HT-29 CTH transduction, UniqueID 39
|
| Organism |
Homo sapiens |
| Characteristics |
cell_line: HT-29
orf: CTH
uniqueid: 39
arraybatch: E1
transductiondate: 2015-02-26
|
| Treatment protocol |
ORFs for IBD gene candidates were cloned into a GATEWAY® compatible polycistronic lentiviral expression vector, pLVX-EF1a-IRES-PURO/eGFP expressing an enhanced green fluorescent protein (eGFP) and puromycin N-acetyl-transferase fusion protein.
Proliferative HT-29 cells at 50% confluency in 12 well plate (Corning) were transduced in triplicate with the different ORFs (multiplicity of infection) MOI of 40-100 with 8µg/ml of polybrene (Sigma, Cat: H-9268).
Twenty-four hours post-transduction, media was changed and 3ug/ml puromycin (Millipore Sigma) was added.
The appearance and confluence of the cultures were recorded daily, and cells were grown for an average of 8 days (with a range of 5-27 days) to select successfully transduced cells and reach confluence before RNA extraction.
Transduction of the whole set of IBD gene candidate ORFs was performed in batches of about 15 ORFs, each done in triplicate, and including an empty vector control.
|
| Growth protocol |
The colorectal adenocarcinoma cell line HT-29 (ATCC HTB-38) was maintained at confluence between 20% and 80% at all times in McCoy’s 5A (Wisent, 317-010CL) 10% FBS. All experiments described herein were performed in cell at passages below 25.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
The RNeasy Plus Mini kit (#74036, Qiagen Inc Canada) according to manufacturer’s protocol.
The RNA samples were quantified, and quality controlled using an Agilent RNA 6000 Nano kit (Agilent, Cat No./ID 5067-1511) on 2100 Bioanalyzer system.
Number (RIN) below 8 were discarded; RIN values were routinely in the range of 9.2-10
|
| Label |
Cy3
|
| Label protocol |
Agilent One-Color Microarray-Based Exon Analysis Low Input Quick Amp WT Labeling kit using Cyanine 3-CTP label.
|
| |
|
| Hybridization protocol |
Samples were blocked with Agilent blocking reagent and incubated for 17h at 65C in the Agilent Microarray Hybridization oven
|
| Scan protocol |
Agilent SureScan Microarray scanner
|
| Data processing |
We used Limma v3.26.9 and sva v3.18.0 packages (Bioconductor v3.1-3.2) to load the fluorescence intensity files and handle the data into R V3.2.0. Arrays failing Agilent quality control according to the Agilent Feature Extraction software were flagged. Manual quality control of each array was also performed.
Quality control was performed within each batch of arrays. Fluorescence signal was processed to remove local background (bakgroundCorrect, method “normexp”) and then normalized using cyclic loess algorithm.
Batch effects were then corrected using ComBat for known batches and sva for unknown systematic artefacts (both from sva library v3.18.0). Given the experiment was performed in three parts (E1-E4 & P7, E5-E11, E14-E15), the batches from each part were combined first and then combined together.
To reduce impact of residual background, noise and batch effects on very low expression values, the fluorescence intensity values were truncated at 8, and translated down by the same amount.
Duplicated probes were combined, and repeated samples removed. The truncating threshold was determined based on the distribution of negative control probes and detected vs non-detected signals. Data provided includes only samples included in the final dataset.
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| |
|
| Submission date |
Oct 15, 2021 |
| Last update date |
Oct 16, 2021 |
| Contact name |
John D Rioux |
| Organization name |
Montreal Heart Institute
|
| Department |
Research Center
|
| Lab |
Genetics and genomic medecine of Inflammation
|
| Street address |
5000 Bélanger St.
|
| City |
Montréal |
| State/province |
QC |
| ZIP/Postal code |
H1T 1C8 |
| Country |
Canada |
| |
|
| Platform ID |
GPL30867 |
| Series (1) |
| GSE186001 |
Functional screen of Inflammatory bowel disease genes reveals key epithelial functions: Agilent Targeted Dataset |
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