Cotton (Gossypium hirsutum L.) is a crop of great commercial importance. To keep pace with the demands of consumers, the textile industry, and to remain competitive with synthetic fibers, cotton breeding must focus on improving fiber quality and yield. The utilization of molecular markers in dissecting these characters and associating them based on linkage disequilibrium offers an alternative to the more traditional method for mapping quantitative trait loci (QTL). Association mapping has been extensively used in human studies and has recently found application in crop plants, notably maize and rice. Upland cotton genotypes from the Regional Breeders Testing Network (RBTN) were subjected to association mapping. Our results demonstrate that integrating multi-environment data on yield components and fiber quality with molecular analysis of marker trait association can compliment and enhance traditional QTL mapping.