1. A high-density quantitative nuclease protection microarray platform for high throughput analysis of gene expression
- Author
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David C. Henderson, V.S.R.K. Maddula, Xristo Zarate, M.P. Rounseville, Bruce Seligmann, David W. Galbraith, John A. Luckey, and Kevin M. Bourzac
- Subjects
Microarray ,Sample processing ,Nuclease Protection Assays ,Bioengineering ,Computational biology ,Applied Microbiology and Biotechnology ,Cell Line ,Databases, Genetic ,Gene expression ,Humans ,Microarray platform ,Oligonucleotide Array Sequence Analysis ,Genetics ,Nuclease ,biology ,Reverse Transcriptase Polymerase Chain Reaction ,Gene Expression Profiling ,Sequence Analysis, DNA ,General Medicine ,High-Throughput Screening Assays ,High throughput analysis ,Highly sensitive ,Gene Expression Regulation ,biology.protein ,DNA microarray ,DNA Probes ,Biotechnology - Abstract
The quantitative nuclease protection assay (qNPA) is a very simple and highly sensitive method for measuring mRNA transcripts, can be used on a variety of sample types, and is amenable to high-throughput sample processing. We have combined the power of the qNPA assay with the density of a DNA microarray to create a qNPA Microarray platform. This platform is compatible with common laboratory equipment: it uses fluorescence-based detection, can be analyzed with common microarray scanners, and is in an SBS footprint with 96-well layout for high-throughput applications. Here, we demonstrate the characteristics of a qNPA Microarray slide that contains up to 1700 gene elements per well. We show that the new platform can reliably detect transcripts at levels as low as 10 fM with median CVs below 12%. On a standardized set of samples, the qNPA Microarray detected the same trends in gene expression as the original qNPA technology, real time qPCR, and Affymetrix GeneChip DNA Microarrays. Given its ease of use, compatibility with multiple sample types, high-throughput capabilities, and its integration with standard laboratory equipment, the qNPA Microarray is a powerful new platform for gene expression research.
- Published
- 2011
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