Sample size for estimating gene expression of transgenic plants using group tests

Abstract

In the south-east and west-center of Mexico, the presence of transgenic maize has been detected (GM), even though the effects of cross-pollination between this maize and landraces such as Tripsacum and teosinte are unknown so far. It is therefore necessary to detect the presence of transgenic plants and to estimate the average gene expression of transgenes in regular crops. However, an analysis of each and every one of the plants would consume a lot of time and money as well. An alternative to reduce costs is to use test groups. This technique analyzes groups that possess tissues of several plants without individually inspecting them, keeping acceptable levels of accuracy at a lower cost. When a test group is used to estimate the average genetic expression it is important to determine the sample size and the number of groups for the estimation process. In this context and under conditions of normality, this paper presents two procedures, computational and analytical, for estimating the average gene expression of GM maize, providing examples to show the application of the proposed methods. Additionally, through simulation we reproduced several circumstances that a researcher might find, providing a computational algorithm in the statistical program R (R Development Core Team 2007) to create other scenarios. Both procedures ensure that, W confidence interval amplitude is lower or equal to the desired amplitude ω with γ probability. This is achieved because both methods consider the randomness of the sampling variance. However, we recommend the use of the formula proposed and analytical procedure, because it is accurate and easy to use.