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Open AccessTechnical Note

Robust Normalization of Luciferase Reporter Data

and *
Department of Biology, University of North Dakota, Grand Forks, ND 58202, USA
*
Author to whom correspondence should be addressed.
Current address: JMB—Center for Immunity and Immunotherapies, Seattle Children’s Hospital, Seattle, WA 98105, USA.
Methods Protoc. 2019, 2(3), 62; https://doi.org/10.3390/mps2030062
Received: 17 June 2019 / Revised: 14 July 2019 / Accepted: 22 July 2019 / Published: 25 July 2019
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Abstract

Transient Luciferase reporter assays are widely used in the study of gene regulation and intracellular cell signaling. In order to control for sample-to-sample variation in luminescence arising from variability in transfection efficiency and other sources, an internal control reporter is co-transfected with the experimental reporter. The luminescence of the experimental reporter is normalized against the control by taking the ratio of the two. Here we show that this method of normalization, “ratiometric”, performs poorly when the transfection efficiency is low and leads to biased estimates of relative activity. We propose an alternative methodology based on linear regression that is much better suited for the normalization of reporter data, especially when transfection efficiency is low. We compare the ratiometric method against three regression methods on both simulated and empirical data. Our results suggest that robust errors-in-variables (REIV) regression performs the best in normalizing Luciferase reporter data. We have made the R code for Luciferase data normalization using REIV available on GitHub. View Full-Text
Keywords: luciferase reporter; transfection efficiency; normalization; gene regulation; promoter; enhancer luciferase reporter; transfection efficiency; normalization; gene regulation; promoter; enhancer
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Repele, A.; Manu. Robust Normalization of Luciferase Reporter Data. Methods Protoc. 2019, 2, 62.

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