128-4 QTL Discovery for Abiotic Stress - How Do We Know What We Don't Know.

See more from this Division: C07 Genomics, Molecular Genetics and Biotechnology
See more from this Session: Symposium--QTL That Matter

Monday, November 7, 2016: 3:49 PM
Phoenix Convention Center North, Room 123

Scott C. Chapman, CSIRO, St. Lucia, QLD, AUSTRALIA and David Jordan, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Warwick, Australia
Abstract:
QTL for stress adaptation are difficult to detect due to challenges in phenotyping a specific trait, and in the relationship to yield. We use real data from sorghum breeding trials to provide inputs to simulation models to generate populations of genotypes, together with data on their leaf area, biomass, N content, etc every day of the season, i.e. we can generate databases that represent the entire complexity of extremely high density phenotyping (imagine you could measure everything, every day). With these data, we are able to test questions related to how 'large' a QTL needs to be to have an impact on yield, and whether indirect phenotyping could help us or not in determining this. This allows us to undertake virtual assessments of the value of new phenotyping technologies in breeding and identification of QTL.

See more from this Division: C07 Genomics, Molecular Genetics and Biotechnology
See more from this Session: Symposium--QTL That Matter