Mouse gene 1.1 st array

Total RNA from offspring livers was extracted using an RNeasy Mini kit (Qiagen, Venlo, The Netherlands). RNA concentration and purity were assessed using a Nano Drop ND-1000 spectrophotometer (Isogen, IJsselstein, The Netherlands). RNA quality was measured on an Agilent 2100 bioanalyzer (Agilent Technologies, Amsterdam, The Netherlands). All RNA samples had an RNA integrity number >8.0. RNA (100 ng) was labeled with whole transcript sense target assay and hybridized to Affymetrix Mouse Gene 1.1 ST arrays (Affymetrix, Santa Clara, CA). Microarrays were analyzed using MADMAX pipeline for statistical analysis of microarray data (25 (link)). Signal intensities were normalized with the robust multichip average method and probes were annotated (26 (link)). Microarray data are available through the Gene Expression Omnibus database (accession number GSE123009).

mRNA expression was profiled using Mouse Gene 1.1 ST arrays (Affymetrix, Santa Clara, CA) which cover over 26,000 RefSeq transcripts. miRs were profiled using SurePrint G3 Mouse miRNA 8 × 60 K Microarray kits (Agilent, Santa Clara, CA) designed based on miRbase release 17. This approach to profiling mRNAs and miRs was selected after a comprehensive evaluation of platforms. Microarrays, RT-qPCR and sequencing each has strengths and weaknesses that make each appropriate for specific study goals^{54 (link)}. Whereas sequencing offers advantages over microarrays or RT-qPCR in that the information extracted with sequencing can be more complex, the study by Mestdagh and colleagues showed Agilent arrays performed well compared with other hybridization technologies and were best at capturing small expression differences compared with all other methods^{54 (link)}. The amount of RNA required for high quality next generation sequencing was greater than the RNA we could obtain from lung neutrophils isolated from a single mouse with pneumonia. Studies in the literature show that microarrays fared well compared with other methods and was indeed superior at detecting small differences in expression of miRs^{54 (link)}.

Microarray data were generated in duplicates by the microarray core facility of the Institut Curie (D. Gentien) using Affymetrix Mouse Gene 1.1 ST arrays (targeting 21041 genes). Raw data were normalized with the Robust Multiarray Average (RMA) method available in the Bioconductor R package oligo and the “pd.mogene.1.1.st.v1” annotation package. For rescue experiments, given the observed batch bias between the first and second replicates, the data were then batch-corrected using a linear model (Limma R package). Differential gene expression analysis was done using the RankProduct R package, and significantly underexpressed or overexpressed genes were identified with a minimum adjusted P-value of 15% and a minimum value of fold change equal to 2. Hierarchical clustering analysis was performed using Cluster 3.0, and heat maps were generated with TreeView.