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Designing a microarray experiment to estimate dominance in maize (Zea mays L.)

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Abstract

Experiments using cDNA microarrays for the identification of genes with certain expression patterns require a thoughtfully planned design. This study was conducted to determine an optimal design for a microarray experiment to estimate differential gene expression between hybrids and their parental inbred lines in maize (i.e. dominance). It has two features: the contrasts of interest contain more than two genotypes and the procedure may be customised to other microarray experiments where different effects may influence hybridisation signals. A mixed model was used to include all important effects. Impacts during growth of the plant material were taken into consideration as well as those occurring during hybridisation. The results of a preliminary experiment were used to determine which effects were to be included in the model, and data from another microarray experiment were used to estimate variance components. In order to select good designs, an optimality criterion adapted to the problem of differential gene expression between hybrids and their parental inbred lines was defined. Two approaches were used to determine an optimal design: the first one simplifies the problem by dividing it into several subproblems, whereas the second is more sophisticated and uses a simulated annealing (SA) algorithm. We found that the first approach constitutes a useful means for designing microarray experiments to study this problem. Using the more sophisticated SA approach the design can be further improved.

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Acknowledgements

This project was supported by the DFG (German Research Foundation) in the framework program “Heterosis in Plants” (research grants HO 2249/6-1 and PI 377/7-1). Work on the mutant rtcs in F.H.S laboratory is supported by DFG Grant HO2249/4-1.

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Correspondence to H.-P. Piepho.

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Communicated by R. Bernardo

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Keller, B., Emrich, K., Hoecker, N. et al. Designing a microarray experiment to estimate dominance in maize (Zea mays L.). Theor Appl Genet 111, 57–64 (2005). https://doi.org/10.1007/s00122-005-1977-9

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  • DOI: https://doi.org/10.1007/s00122-005-1977-9

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