Computational protocol: Constitutive expression of NF-κB inducing kinase in regulatory T cells impairs suppressive function and promotes instability and pro-inflammatory cytokine production

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Protocol publication

[…] Each RNA sample was labeled using the Ambion MessageAmp Premier RNA Amplification Kit and hybridized to an Illumina MouseRef 8 v2 Expression BeadChip Array. Image processing and expression analysis were performed using Illumina BeadArray Reader and GenomeStudio (v. 2010.1) Gene Expression module (v. 1.6.0) software. Intensity (.idat) files were produced by the BeadArray reader (Illumina scanner system). Intensity files, along with the BeadChip decode file (.dmap) were loaded to GenomeStudio’s Gene Expression module to generate probe/gene level signal intensity data (normalized and raw), perform QA/QC, and perform high level data visualization. Raw data were Lumi quantile normalized and log transformed before applying a 1.8 fold cutoff for differential regulation between WT and NIKtg Tregs. All microarray and microRNA array data are available at GEO with the reference number GSE80757 ( = GSE80757).To generate lists of genes that are regulated between conventional CD4+ T cells and Tregs from the Immgen database, we used the population comparison tool and compared “T_4FP3 + 25 + _Sp” with “T_4FP3-_Sp”, submitted by T. Heng in the Benoist-Mathis lab, Joslin Diabetes Center. We used Venny ( to compare our list of genes that were regulated >1.8 fold between WT and NIKtg Tregs with the Immgen-generated lists of genes upregulated and downregulated in Tregs vs. Tconv. For GSEA analysis, we used these Immgen-generated lists of genes upregulated and downregulated in Tregs vs. Tconv as our gene sets. Enrichment of these gene sets in our microarray expression dataset was performed using the Gene Set Enrichment Analysis software from the Broad Institute,. The metric for ranking genes was log2 ratio of classes, and permutation type was gene set. […]

Pipeline specifications

Software tools GenomeStudio, VENNY, GSEA
Databases ImmGen
Application miRNA array analysis
Organisms Mus musculus
Diseases Autoimmune Diseases