Systematic Analysis of Bicistronic Reporter Assay Data

Jonathan L. Jacobs, Jonathan D. Dinman
Department of Cell Biology & Molecular Genetics, 2135 Microbiology Building
University of Maryland, College Park, MD 20742.

Get the paper from NAR Online.

PLEASE NOTE!!!

A formula error in the original text was subsequently found after publication in Expression [10]. The Online Tutorial and the Sample Excel File have the correct expression.

ONLINE TUTORIAL (Please be patient, this page may take a while to load.)

DOWNLOAD SAMPLE EXCEL FILE (68 kb, .xls)

If you have difficultly opening either of the above files, please contact Dr. Jonathan Dinman, dinman@umd.edu.

Abstract

Bicistronic reporter assay systems have become a mainstay of molecular biology. While the assays themselves encompass a broad range of diverse and unrelated experimental protocols, the numerical data garnered from these experiments often have similar statistical properties. In general, a primary data set measures the paired expression of two internally controlled reporter genes. The expression ratio of these two genes is then normalized to an external control reporter. The end result is a “ratio of ratios” that is inherently sensitive to propagation of the error contributed by each of the respective numerical components. The statistical analysis of this data therefore requires careful handling in order to control for the propagation of error and its potentially misleading effects. A careful survey of the literature found no consistent method for the statistical analysis of data generated from these important and informative assay systems. In this report, we present a detailed statistical framework for the systematic analysis of data obtained from bicistronic reporter assay systems. Specifically, a dual luciferase reporter assay was employed to measure the efficiency of four programmed -1 frameshift signals. These frameshift signals originate from the L-A virus, the SARS-associated Coronavirus, two computationally identified frameshift signals from two Saccharomyces cerevisiae genes. Furthermore, we successfully use our statistical methods to prove that the effects of anisomycin on programmed -1 frameshifting are statistically significant. A set of Microsoft Excel spreadsheets, which can be used as templates for data generated by dual reporter assay systems, and an online tutorial are available at our web site (http://dinmanlab.umd.edu/statistics). These spreadsheets could be easily adapted to any bicistronic reporter assay system.

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