Genetical genomics experiments combine information on phenotypic traits, molecular markers and gene expression to study the genetic mechanisms governing variation in complex traits. Such studies can be used, for example, to estimate heritabilities of mRNA transcript abundances, to map expression quantitative trait loci (eQTL), and to infer regulatory gene networks. Microarray experiments, however, can be extremely costly and time consuming, which may limit sample sizes and statistical power. Thus it is crucial to optimize experimental designs by carefully choosing the subjects to be assayed, and by cautiously controlling systematic factors affecting the system. Also, a rigorous strategy should be used for allocating mRNA samples across slides and dye labeling, so that effects of interest are not confounded with nuisance factors. In this presentation, we review some designs strategies for genetical genomics studies, including the selection of individuals for increased genetic dissimilarity and for a higher number of recombination events, as well as efficient microarray experiment layouts for various experimental goals.
eQTL; gene expression; optimal design; selective phenotyping; transcriptional profiling