A Dynamic Gene Network Model to Predict Floral Transition Time in Maize.

The developmental transition from the vegetative stage to reproductive stage (floral transition) is a significant event in plant growth and development. Because this floral transition can influence patterns of growth, water use and biomass partitioning to reproductive structures, the accurate prediction of small differences in flowering time in elite germplasm is central to the understanding of maize adaptation and can influence selection decisions in maize breeding. While knowledge about the genetic architecture controlling the floral transition in maize is advanced, a quantitative synthesis of this knowledge that integrates environment and genetic controls of flowering time for prediction in elite germplasm is lacking. To this end, a gene regulatory network model to simulate flowering time is proposed based on gene expression dynamics of id1 and dlf1 mutants, the early flowering GASPE landrace and the wild type B73.  A dynamic gene network model comprised of four genes is proposed and validated using double mutant phenotypic data. The proposed gene to phenotype model demonstrates a working example that leverages knowledge in model organisms for the utilization of genome information to predict flowering time in elite germplasm.