High resolution estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR)

Abstract

Quantification of the relative abundance of genetic traits has broad applications for biomarker discovery, diagnostics, and assessing gene expression in biological research. Relative quantification of genes is traditionally done with the 2^−ΔΔCT method using quantitative real-time polymerase chain reaction (qPCR) data, which is often limited in resolution beyond orders of magnitude difference. The latest techniques for quantification of nucleic acids employ digital PCR or microarrays which involve lengthy sample preparation and complex instrumentation. In this work, we describe a quantitative ratiometric regression PCR (qRR-PCR) method for computing relative abundance of genetic traits in a sample with high resolution from a single duplexed real-time quantitative PCR assay. Instead of comparing the individual cycle threshold (Ct) values as is done for the 2^−ΔΔCT method, our qRR-PCR algorithm leverages the innate relationship of co-amplified PCR targets to measure their relative quantities using characteristic curves derived from the normalized ratios of qPCR fluorescence curves. We demonstrate the utility of this technique for discriminating the fractional abundance of mixed alleles with resolution below 5%.