Human lung epithelial cells were grown overnight in F-12K medium. Subsequently, the cells were treated with crystalline silica (0 or 200 µg/ml) in serum-free medium for 2 hours, followed by total RNA isolation.
Extracted molecule
total RNA
Extraction protocol
Total RNA was isolated from A549 cells using the RNeasy Mini Kit (Qiagen, Inc, Valencia, CA) with on-column DNA digestion following the manufacturer's instructions.
Label
Biotin
Label protocol
Biotin-labeled cRNA was generated from 375 ng RNA samples each by employing the Illumina TotalPrep RNA Amplification Kit (Ambion, Inc, Austin, TX).
Hybridization protocol
Employing materials and protocols provided by Illumina, Inc., San Diego, CA, 750 ng of labeled cRNA sample was hybridized to the Sentrix Human HT-12 V3 BeadChip (Illumina, Inc.) for 20 hrs at 58C. Following hybridization, microarrays were washed to remove unbound and non-specifically hybridized target molecules, and stained with Cy3-streptavidin conjugate (Illumina, Inc).
Scan protocol
The arrays were scanned with the Illumina BeadStation 500 platform following the protocol provided by the manufacturer (Illumina, Inc).
Description
2H_A549_Si(0)_2 The labeling and hybridization of the microarrays were performed at the National Institute for Occupational Safety and Health (NIOSH), Morgantown, WV, and scanning was performed at the Center for Genomics Sciences, Alleghney-Singer Research Institute, Pittsburgh, PA.
Data processing
Array data were extracted using Illumina's BeadStudio software (Framework version 3.0.19.0). Normalization and statistical analysis of the expression data were carried out in R/Bioconductor using the ‘lumi’ and ‘limma’ packages. The ‘lumi’ Bioconductor package covered the data input, quality control, force positive background correction, variance stabilization, normalization and gene annotation (http://bioconductor.org/packages/2.2/bioc/vignettes/lumi/inst/doc/lumi.pdf). Robust spline normalization was used to generate the values in the matrix table. After normalization, Lumi code deletes undetected genes, resulting in a subset of genes detected on the array. A linear model analysis using the 'limma' package in R was conducted to identify differentially expressed genes. p values were calculated and log fold changes were converted to standard fold changes. Resulting raw p-values were corrected for false discovery rate using the Benjamini-Hochberg method.
