Regulation of woody plant development by gibberellin catabolic and signaling genes

Gibberellin (GA) is a growth promoting hormone implicated in regulating a diversity of plant processes. This dissertation examines the role of GA metabolic and signaling genes in woody plant growth and development. Transgenic modifications, expression analysis, physiological/biochemical assays, biometric measurements and histological analysis were used to understand the regulatory roles these genes play in the model woody plant, Populus. Our results highlight the importance of GA regulatory genes in woody perennial growth, including: phenology, wood formation, phenotypic plasticity, and growth/survival under field conditions. We characterize two putative Populus orthologs of the SHORT INTERNODES (SHI) gene from Arabidopsis, a negative regulator of GA signaling. RNAi-mediated suppression of Populus SHI-like genes increased several growth-related traits, including extent of xylem proliferation, in a dose-dependent manner. Three Populus genes, sharing sequence homology to the positive regulator of GA signaling gene PHOTOPERIOD-RESPONSIVE 1 (PHOR1) from Solanum, are up-regulated in GA-deficient and insensitive plants suggesting a conserved role in GA signaling. We demonstrate that Populus PHOR1-like genes have overlapping and divergent function(s). Two PHOR1-like genes are highly expressed in roots, predominantly affect root growth (e.g., morphology, starch quantity and gravitropism), and induced by short-days (SD). The other PHOR1-like gene is ubiquitously expressed with a generalized function in root and shoot development. The effects of GA catabolic and signaling genes on important traits (e.g., adaptive and productivity traits) were studied in a multi-year field trial. Transgenics overexpressing GA 2-oxidase (GA2ox) and DELLA genes showed tremendous variation in growth, form, foliage, and phenology (i.e., vegetative and reproductive). Observed gradients in trait modifications were correlated to transgene expression levels, in a manner suggesting a dose-dependent relationship. We explore GA2ox and DELLA genes involvement in mediating growth responses to immediate short-term drought stress, and SD photoperiods, signaling prolonged periods of stress (e.g., winter bud dormancy). GA2ox and DELLA genes show substantial up-regulation in response to drought and SDs. Transgenics overexpressing homologs of these genes subjected to drought and SD photoperiods show hypersensitive growth restraint and increased stress resistances. These results suggest growth cessation (i.e., dormancy) in response to adverse conditions is mediated by GA regulatory genes.

Space trajectories optimization using variable-chromosome-length genetic algorithms

The problem of optimal design of a multi-gravity-assist space trajectories, with free number of deep space maneuvers (MGADSM) poses multi-modal cost functions. In the general form of the problem, the number of design variables is solution dependent. To handle global optimization problems where the number of design variables varies from one solution to another, two novel genetic-based techniques are introduced: hidden genes genetic algorithm (HGGA) and dynamic-size multiple population genetic algorithm (DSMPGA). In HGGA, a fixed length for the design variables is assigned for all solutions. Independent variables of each solution are divided into effective and ineffective (hidden) genes. Hidden genes are excluded in cost function evaluations. Full-length solutions undergo standard genetic operations. In DSMPGA, sub-populations of fixed size design spaces are randomly initialized. Standard genetic operations are carried out for a stage of generations. A new population is then created by reproduction from all members based on their relative fitness. The resulting sub-populations have different sizes from their initial sizes. The process repeats, leading to increasing the size of sub-populations of more fit solutions. Both techniques are applied to several MGADSM problems. They have the capability to determine the number of swing-bys, the planets to swing by, launch and arrival dates, and the number of deep space maneuvers as well as their locations, magnitudes, and directions in an optimal sense. The results show that solutions obtained using the developed tools match known solutions for complex case studies. The HGGA is also used to obtain the asteroids sequence and the mission structure in the global trajectory optimization competition (GTOC) problem. As an application of GA optimization to Earth orbits, the problem of visiting a set of ground sites within a constrained time frame is solved. The J2 perturbation and zonal coverage are considered to design repeated Sun-synchronous orbits. Finally, a new set of orbits, the repeated shadow track orbits (RSTO), is introduced. The orbit parameters are optimized such that the shadow of a spacecraft on the Earth visits the same locations periodically every desired number of days.