P0770
Genomic Dissection of Leaf and Panicle Architecture Traits in Sorghum using Nested Association Mapping

Olalere Marcus Olatoye , Kansas State University, Manhattan, KS
Sophie Bouchet , Kansas State University, Manhattan, KS
Geoffrey Morris , Kansas State University, Manhattan, KS
Tesfaye T. Tesso , Kansas State University, Manhattan, KS
Ramasamy Perumal , Kansas State University, Manhattan, KS
Sorghum is an important crop in many agroclimatic regions worldwide and has adapted to a wide range of conditions. Accordingly, global sorghum germplasm exhibits substantial variation in agroclimatic traits—traits that differ in germplasm from different agroclimatic zones—including many aspects of leaf and panicle architecture. Currently, our ability to improve sorghum adaptation and transfer useful alleles across different genetic backgrounds is constrained by our limited knowledge of the genomic regions that underlie agroclimatic traits. Nested Association Mapping (NAM), which uses multiple biparental families linked by a common parent, can improve dissection of agroclimatic traits by reducing the confounding effects of population structure and increasing the frequency of rare alleles. A sorghum NAM population comprised of 10 families and almost 2,500 recombinant inbred lines (RILs) has been developed and genotyped at approximately 100,000 SNPs with Genotyping-by-Sequencing (GBS). The population was phenotyped for leaf angle, leaf width, panicle compactness and primary rachis branch length in two contrasting environments (locations) in Kansas, semi-arid (Hays) and humid continental (Manhattan). Significant genotypic variation for these traits was observed. Association mapping confirmed several previously identified quantitative trait loci (QTL) and revealed many new QTL for leaf and panicle architecture. QTLs were found for leaf angle around the Dw3 region in chromosome 7. Likewise, for lower rachis branch length, we identified Sb07g023640 a flavin monooxygenase gene close to the Dw3 region on chromosome 7. The QTL identified will be helpful in marker-assisted selection for better adaptation and yield.
Handouts
  • PAG_2016.pdf (11.4 MB)