Abstract
Association or linkage disequilibrium mapping is alternative to identify QTLs in plants. In this study we used SSR based sorghum diversity research set (SDRS) of 107 sorghum accessions. The representative set included a geographically diverse collection of accessions from 27 countries in Asia and Africa. For association analysis 98 sorghum SSR markers were selected from three previously published linkage maps. Phenotypic data was recorded for 26 morphological traits. Different association models were used to identify QTLs controlling major agronomic traits including both single QTL approaches as well as a multiple QTL approach. All models revealed loci having different strength of association with morphological traits. A total of 14 common significant SSR loci were identified by three different models of association analysis namely, single-QTL models with the effects of population structure, single-QTL models with the effects of population structure and familial relatedness, and multiple-QTL model with the effects of population structure. These loci were associated with 12 different morphological traits including days to heading, days to flowering, culm length, number of tillers, number of panicles and panicle length. Comparing results from different models may be an efficient way to detect reliable associations in the genome-wide association studies.
