P0369 Development and Use of a Sorghum Nested Association Mapping Population

David Jordan , The Univ of Qld, Qld Alliance for Agric and Food Innovation, Warwick, Australia
Emma Mace , Department of Employment, Economic Development and Innovation, Warwick, Australia
Alan W Cruickshank , Department of Employment, Economic Development and Innovation, Warwick, Australia
Colleen H Hunt , Agri-Science Queensland, DEEDI, Toowoomba, Australia
Graeme L Hammer , The University of Queensland, Queensland Alliance for Agriculture and Food Innovation, St Lucia QLD , Australia
Robert G Henzell , Department of Employment, Economic Development and Innovation (retired), Warwick, Australia
Loss of genetic diversity in elite breeding populations is often identified as a potential impediment to future genetic gain and the use of diverse unadapted germplasm in breeding has been suggested as one way of combating this problem but is often impractical due to the poor performance of progeny from crosses between adapted and unadapted parent lines. This study describes the development of a large sorghum nested association mapping (NAM) population based around a reference parent design specifically developed to solve these problems. Each subpopulation was derived from a large Bc1F1 population using a single elite line as the recurrent parent. Inbred lines were then derived by selection for key agronomic characteristics. To date more than 4000 lines from 100 subpopulations have been developed sampling the entire diversity of sorghum including wild relatives. The resulting populations can be evaluated for quantitative traits in field conditions without the confounding effects of major adaptation genes. Multi-environment phenotypic data is available for many of the populations and a subset of the populations have been subjected to whole genome scans with DArT markers and subsequently used for QTL analysis. In addition 28 of the exotic lines and the elite parent have been resequenced providing a direct link to the genotyped and phenotyped NAM populations. Combined with accurate environmental characterisation using simulation modelling the resulting resource is providing a unique opportunity to not only fast-track gene discovery through the identification of functional sequence polymorphisms but also to contribute to genetic progress in elite breeding programs.