3 research outputs found
Functional mapping of quantitative trait loci (QTLs) associated with plant performance in a wheat MAGIC mapping population
In crop genetic studies, the mapping of longitudinal data describing the spatio-temporal
nature of agronomic traits can elucidate the factors influencing their formation and
development. Here, we combine the mapping power and precision of a MAGIC wheat
population with robust computational methods to track the spatio- temporal dynamics
of traits associated with wheat performance. NIAB MAGIC lines were phenotyped
throughout their lifecycle under smart house conditions. Growth models were fitted to
the data describing growth trajectories of plant area, height, water use and senescence
and fitted parameters were mapped as quantitative traits. Trait data from single time
points were also mapped to determine when and how markers became and ceased to
be significant. Assessment of temporal dynamics allowed the identification of marker-trait
associations and tracking of trait development against the genetic contribution of key
markers. We establish a data-driven approach for understanding complex agronomic
traits and accelerate research in plant breeding
Genotypic variations in leaf and whole-plant water use efficiencies are closely related in bread wheat genotypes under well-watered and water-limited conditions during grain filling
Colombia's cyberinfrastructure for biodiversity: Building data infrastructure in emerging countries to foster socioeconomic growth
Science and innovation are not a luxury but a prerequisite for social and economic development (Annan, 2003)