Maize harbours tremendous natural diversity, which can be used for improvement.  In our ongoing effort to characterize molecular and functional diversity in the maize genome, we have developed germplasm and analysis tools to carry out high-resolution association studies in maize.  These association approaches has focused on developing and adapting structured association and family-based association methods.  These association approaches have proven effective in identifying useful nucleotide polymorphisms in genes involved in aluminium tolerance and kernel quality.  However, while standard association mapping in maize provides high resolution, this approach can result in less statistical power.  To exploit both high resolution and statistical power, in collaboration with several other groups we are developing a platform for the dissection of complex traits in maize by utilizing nested association mapping approaches.  In the summer of 2006, mapping on the maize nested association mapping began with the evaluation of 26 population for nearly 40 traits.  Additionally, we are helping to create bioinformatic analysis tools and databases to make these results accessible to both geneticists and breeders.