Abstract 2213: Evaluation of bias associated with high-multiplex, target-specific pre-amplification

We developed a novel PCR-based pre-amplification (PreAmp) technology that can increase the abundance of over 350 target genes one million-fold. To assess potential bias introduced by PreAmp we utilized ERCC RNA reference standards, a model system that quantifies measurement error in RNA analysis. We assessed three types of bias: amplification bias, dynamic range bias and fold-change bias. We show that our PreAmp workflow does not introduce significant amplification and fold-change bias under stringent conditions. We do detect dynamic range bias if a target gene is highly abundant and PreAmp occurred for 16 or more PCR cycles; however, this type of bias is correctable. To validate PreAmp performance in an actual gene expression profiling experiment, we analyzed a panel of genes that are regulated during differentiation using the NTera2 stem cell model system. We find that results generated using PreAmp are statistically equivalent to results obtained using standard qPCR without the pre-amplification step. Importantly, PreAmp maintains patterns of gene expression changes across samples; the same biological insights would be derived from a PreAmp experiment as with a standard gene expression profiling experiment. Our PreAmp technology can facilitate accurate analysis of extremely limited samples in gene expression profiling experiments. Citation Format: Steven T. Okino, Michelle Kong, Yan T. Wang. Evaluation of bias associated with high-multiplex, target-specific pre-amplification. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2213. doi:10.1158/1538-7445.AM2015-2213