After PMBC isolation, 1 million PBMC cells were lysed in 1 ml of TRIzol (Life technologies, Carlsbad, CA, USA) immediately and stored at -80C. The samples were thawed and RNA extracted following the manufacturer instructions. The quality of the RNA was assessed by using Nanodrop 2000 Spectrometer (Thermo Scientific, MA, USA) as well as by visualization of the integrity of the 28S and 18S band on Agilent Bioanalyzer 2100 (Agilent technologies, Santa Clara, CA, USA). Qualified total RNA was further purified by RNeasy micro kit (QIAGEN, GmBH, Germany) and removed genomic contamination by RNase-Free DNase Set (QIAGEN, GmBH, Germany). The purified RNA was stored at -80C.
Label
Biotin
Label protocol
Total RNA were amplified, labeled and purified by using the GeneChip 3IVT Express Kit (Affymetrix, Santa Clara, CA, USA) followed the manufacturer instructions to obtain biotin labeled cRNA.
Hybridization protocol
After hybridization on Human PrimeView Arrays for 16 h at 45C and 60 rpm in Hybridization Oven 640 (Affymetrix, Santa Clara, CA, USA), slides were washed and stained with a Fluidics Station 450 (Affymetrix, Santa Clara, CA, USA).
Scan protocol
Scanning was performed on a seventh-generation GeneChip Scanner 3000 (Affymetrix, Santa Clara, CA, USA). Affymetrix GCOS software was used to perform image analysis and generate raw intensity data.
Data processing
Initially, data quality was assessed by background level, 3 labeling bias, RNA quality and pair-wise correlation among samples. For the PrimeView chip, the customized CDF (version 22, ENTREZG) downloaded from the BrainArray website was performed in probe set mapping. IQR was applied for raw data filtering using the genefilter package, and the threshold was set to remove probes/genes with IQR less than the 50th percentile of the IQR across all probes/genes. Normalization was performed with RMA algorithm that includes global background adjustment and quantile normalization. The resulting matrix showed genes as rows and samples as columns was log2 transformed and used as input for linear modeling using the limma package. The limma package was performed to identify differentially expressed genes (DEG) at any time point post immunization, compared with baseline (Day 0). Empirical Bayes moderation of the standard error and Benjamini and Hochberg false-discovery rate (FDR) correction for multiple testing were employed, and the criteria for differentially expressed genes (DEG) were threshold fold change more than 1.3 and BH adjusted FDR less than 0.05.