|Thuillet, Anne-Celine - UNIVERSITY OF WISCONSIN|
|Yu, Jianming - CORNELL UNIVERSITY|
|Pressoir, Gael - CORNELL UNIVERSITY|
|Mitchell, Sharon - CORNELL UNIVERSITY|
|Doebley, John - UNIVERSITY OF WISCONSIN|
|Kresovich, Stephen - CORNELL UNIVERSITY|
|Goodman, Major - NORTH CAROLINA STATE UNIV|
Submitted to: Plant Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 17, 2005
Publication Date: December 7, 2005
Citation: Flint Garcia, S.A., Thuillet, A., Yu, J., Pressoir, G., Romero, S.M., Mitchell, S.E., Doebley, J., Kresovich, S., Goodman, M.M., Buckler Iv, E.S. 2005. Maize association population: a high resolution platform for quantitative trait locus dissection. Plant Journal. 44:1054-1064. Interpretive Summary: Maize (corn) is incredibly diverse in both its genetic makeup and the outward expression of these genes as traits. In order to efficiently use this diversity for crop improvement, geneticists and breeders must identify and understand the role of individual genes in dictating agronomically important traits. To do so requires that large, genetically diverse collections of plant material be made available for genomic research. To date, however, most research has been conducted with only one or two inbred lines. This study is important in that it makes available a set of 302 inbred lines which captures a large proportion of the diversity in public sector maize germplasm worldwide. Here we describe the population structure of this new research tool, as statistical models must correct for population structure to yield meaningful association analyses. Such association analyses are used by researchers to better pinpoint the genes underlying a particular trait.
Technical Abstract: Crop improvement and the dissection of complex genetic traits require germplasm diversity. Although this necessary phenotypic variability exists in diverse maize, most research is conducted using a limited number of inbred lines. An association population of 302 lines is now available-a valuable research tool that captures a large proportion of the maize germplasm pool. Provided that appropriate statistical models correcting for population structure are included, this tool can be used in association analyses to provide high resolution evaluation of multiple alleles. This study describes the population structure of the 302 lines, and investigates the relationship between population structure and various measures of phenotypic and breeding value. On average, our estimates of population structure account for 14% of phenotypic variation, roughly equivalent to a major QTL, with a high of 35%. As such, inclusion of population structure in association models is critical to meaningful analyses. This new association population of 302 lines has the potential to identify QTL that account for as low as 2% of the phenotypic variance for a trait, aiding in the dissection of complex traits and the planning of future projects to exploit the rich diversity present in maize.