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Association or linkage disequilibrium mapping has become a very popular method for dissecting the genetic basis of complex traits in plants. The benefits of association mapping, compared with traditional quantitative trait locus mapping, is, for example, a relatively detailed mapping resolution and that it is far less time consuming since no mapping populations need to be generated. The surge of interest in association mapping has been fueled by recent developments in genomics that allows for rapid identification and scoring of genetic markers which has traditionally limited mapping experiments. With the decreasing cost of genotyping future emphasis will likely focus on phenotyping, which can be both costly and time consuming but which is crucial for obtaining reliable results in association mapping studies. In addition, association mapping studies are prone to the identification of false positives, especially if the experimental design is not rigorously controlled. For example, population structure has long been known to induce many false positives and accounting for population structure has become one of the main issues when implementing association mapping in plants. Also, with increasing numbers of genetic markers used, the problem becomes separating true from false positive and this highlights the need for independent validation of identified association. With these caveats in mind, association mapping nevertheless shows great promise for helping us understand the genetic basis of complex traits of both economic and ecological importance.
Hall et al. (Wed,) studied this question.