High-throughput quantitative real-time polymerase chain reaction array for absolute and relative quantification of rhesus macaque types I, II, and III interferon and their subtypes.

Rhesus macaques provide a valuable research and preclinical model for cancer and infectious diseases, as nonhuman primates share immune pathways with humans. Interferons (IFNs) are key cytokines in both innate and adaptive immunity, so a detailed analysis of gene expression in peripheral blood and tissues may shed insight into immune responses. Macaques have 18 IFN genes, of which 14 encode for 13 distinct IFN-α subtypes, and one for IFN-ß. Here, we developed a high-throughput array to evaluate each of the IFN-α subtypes, as well as IFN-ß, IFN-γ and 2 subtypes of IFN-λ. With this array, expression of each IFN species may be quantified as relative to a reference (housekeeping) gene (ΔCq) or fitted to its own 4-point standard curve for absolute quantification (copy number per mass unit RNA). After validating the assay with IFN complementary DNA, we determined the IFN expression profile of peripheral blood mononuclear cells from 3 rhesus macaques in response to TLR agonists, and demonstrated that the profiles are consistent among animals. Furthermore, because the IFN expression profiles differ depending on the TLR stimuli, they suggest different biological functions for many of the IFN species measured, including individual subtypes of IFN-α.

Systematic method for determining an ideal housekeeping gene for real-time PCR analysis.

To standardize the amount of biological material between samples (e.g., number of cells or amount of tissue) for quantitative real-time reverse transcriptase PCR (qRT-PCR), the cycle of the target gene at which expression is detected (the cycle threshold, or Ct) is divided by the Ct of a gene either thought to be unaffected by experimental conditions or similarly expressed among donors. Genes that maintain cellular structure or homeostasis, referred to as housekeeping genes, or 18S ribosomal RNA are often used for this purpose. Although unstable or inconsistent housekeeping gene expression will misrepresent experimental effects on target gene expression, housekeeping genes are often chosen arbitrarily rather than systematically. We designed a simple and systematic approach towards selection of housekeeping genes based on Ct variance (as reflected by the standard deviation) and normality of distribution. We validated this approach by comparing stability and consistency of expression of 11 housekeeping genes across different types of cells, experimental treatments, and human donors. Finally, we demonstrated the consequences of inconsistent housekeeping gene expression on the calculation of target gene expression, and conclude that validation of stability of housekeeping gene expression by considering both distribution normality and standard deviation is straightforward and critical for proper experimental design.