Gene expression profiling of samples of limited RNA amounts by the NGS application whole transcriptome AmpliSeq-RNA on the Ion Torrent platform offers straightforward, fast, and affordable analysis of human T cell subpopulations.

Abstract

Abstract The diversity of T cell subpopulations demands a growing number of biomarkers to be studied from small samples. To bridge the gap between multicolor flow cytometry or classical qPCR and RNA-Seq, we applied highly multiplexed whole transcriptome AmpliSeq-RNA with 20,803 genes to perform sensitive and specific gene expression profiling (GEP). This study analyzed untouched primary human naïve and memory T cells and compared results to microarrays. Method 8 T cell subsets were isolated by FACS from 4 healthy donors without restimulation: CD4+ or CD8+ naïve (CCR7+CD45RA+), central memory (CCR7+CD45RA−), effector memory TEM (CCR7−CD45RA−) and TEMRA (CCR7−CD45RA+). AmpliSeq transcriptome human gene expression kit (Thermo Fisher) generated barcoded libraries from total RNA. 8–10 samples multiplexed per Ion 540 chip were sequenced on an Ion S5 System. Samples were also analyzed by Affymetrix HG-U133 Plus 2 genechips. Results The resulting Excel matrix of normalized reads [RPM = reads per million reads] had a dynamic range of more than 5 log units. Biological replicates of T cell subsets showed high correlation with r ≥ 0.925. Technical replicates (same libraries) demonstrated high reproducibility with r ≥ 0.995. A high concordance with genechip data were found for expression pattern of analyzed markers. For several very high or low abundant genes the AmpliSeq-RNA data were more sensitive and more specific than the hybridization-based genechip data. Conclusion AmpliSeq-RNA (counting PCR products by NGS) is an interesting alternative to perform straightforward GEP. The analysis of phenotypically well-defined T cell subsets without artificial in vitro stimulation allows more precise determination of in vivo relevant functions.