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.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Cloning and characterization of the genes involved in cambial growth in response to elevated [CO2]

Aspen (Populus tremuloides) trees growing under elevated [CO2] at a free-air CO2 enrichment (FACE) site have produced significantly more biomass compared to control trees. The molecular mechanisms underlying the observed increase in biomass productivity was investigated by producing transcriptomic profiles of the vascular cambium zone (VCZ) and leaves, followed by a comparative study to identify genes and pathways that showed significant changes following long-term exposure to elevated [CO2]. This study is mainly to verify if genetic modification of a few selected candidate genes including CAP1, CKX6, and ASML2 that are expressed in vascular cambium in response to elevated [CO2] can cause the changes in plant growth and development. To this end, these three genes were cloned into both sense and antisense constructs. Then antisense and sense transgenic lines of above-mentioned genes were developed. 15 events were generated for 5 constructs, which were confirmed with regular PCR and RT-PCR. Confirmed plants were planted in greenhouse for growth and phenotypic characterization. The expression of CAP1, CKX6 and ASML2 in antisense plants was measured by real-time RT-PCR, and the changes caused by gene interference in cambial growth were studies by analyzing the microscopic sections made from the antisense transgenic plants. It has been found that 1) CAP1 is mainly expressed in xylem and root. 2) RNAi suppression of CAP1 significantly affected height and diameter. 3) CAP1, ASML2 and CKX6 affected xylem and phloem cell proliferation and elongation. Due to the delay in regenerating sense transgenic plants, the characterization of sense transgenic plants is limited to growth only.

Systemic analysis of microarray data sets towards identifying genes regulating root development

Nitrogen and water are essential for plant growth and development. In this study, we designed experiments to produce gene expression data of poplar roots under nitrogen starvation and water deprivation conditions. We found low concentration of nitrogen led first to increased root elongation followed by lateral root proliferation and eventually increased root biomass. To identify genes regulating root growth and development under nitrogen starvation and water deprivation, we designed a series of data analysis procedures, through which, we have successfully identified biologically important genes. Differentially Expressed Genes (DEGs) analysis identified the genes that are differentially expressed under nitrogen starvation or drought. Protein domain enrichment analysis identified enriched themes (in same domains) that are highly interactive during the treatment. Gene Ontology (GO) enrichment analysis allowed us to identify biological process changed during nitrogen starvation. Based on the above analyses, we examined the local Gene Regulatory Network (GRN) and identified a number of transcription factors. After testing, one of them is a high hierarchically ranked transcription factor that affects root growth under nitrogen starvation. It is very tedious and time-consuming to analyze gene expression data. To avoid doing analysis manually, we attempt to automate a computational pipeline that now can be used for identification of DEGs and protein domain analysis in a single run. It is implemented in scripts of Perl and R.

PHYLOGENETIC ANALYSES, GENE DOSAGE EFFECT AND SELECTION IN MEMBERS OF THE LATERAL BOUNDARY DOMAIN (LBD) GENES TRANSCRIPTION FACTOR FAMILY

Wood formation is an economically and environmentally important process and has played a significant role in the evolution of terrestrial plants. Despite its significance, the molecular underpinnings of the process are still poorly understood. We have previously shown that four Lateral Boundary Domain (LBD) transcription factors have important roles in the regulation of wood formation with two (LBD1 and LBD4) involved in secondary phloem and ray cell development and two (LBD15 and LBD18) in secondary xylem formation. Here, we used comparative phylogenetic analyses to test potential roles of the four LBD genes in the evolution of woodiness. We studied the copy number and variation in DNA and amino acid sequences of the four LBDs in a wide range of woody and herbaceous plant taxa with fully sequenced and annotated genomes. LBD1 showed the highest gene copy number across the studied species, and LBD1 gene copy number was strongly and significantly correlated with the level of ray seriation. The lianas, cucumber and grape, with multiseriate ray cells showed the highest gene copy number (12 and 11, respectively). Because lianas’ growth habit requires significant twisting and bending, the less lignified ray parenchyma cells likely facilitate stem flexibility and maintenance of xylem conductivity. We further demonstrate conservation of amino acids in the LBD18 protein sequences that are specific to woody taxa. Neutrality tests showed evidence for strong purifying selection on these gene regions across various orders, indicating adaptive convergent evolution of LBD18. Structural modeling demonstrates that the conserved amino acids have a significant impact on the tertiary protein structure and thus are likely of significant functional importance.

DENITRIFICATION IN SOILS: FROM GENES TO ENVIRONMENTAL OUTCOMES

Denitrification is an important process of global nitrogen cycle as it removes reactive nitrogen from the biosphere, and acts as the primary source of nitrous oxide (N2O). This thesis seeks to gain better understanding of the biogeochemistry of denitrification by investigating the process from four different aspects: genetic basis, enzymatic kinetics, environmental interactions, and environmental consequences. Laboratory and field experiments were combined with modeling efforts to unravel the complexity of denitrification process under microbiological and environmental controls. Dynamics of denitrification products observed in laboratory experiments revealed an important role of constitutive denitrification enzymes, whose presence were further confirmed with quantitative analysis of functional genes encoding nitrite reductase and nitrous oxide reductase. A metabolic model of denitrification developed with explicit denitrification enzyme kinetics and representation of constitutive enzymes successfully reproduced the dynamics of N2O and N2 accumulation observed in the incubation experiments, revealing important regulatory effect of denitrification enzyme kinetics on the accumulation of denitrification products. Field studies demonstrated complex interaction of belowground N2O production, consumption and transport, resulting in two pulse pattern in the surface flux. Coupled soil gas diffusion/denitrification model showed great potential in simulating the dynamics of N2O below ground, with explicit representation of the activity of constitutive denitrification enzymes. A complete survey of environmental variables showed distinct regulation regimes on the denitrification activity from constitutive enzymes and new synthesized enzymes. Uncertainties in N2O estimation with current biogeochemical models may be reduced as accurate simulation of the dynamics of N2O in soil and surface fluxes is possible with a coupled diffusion/denitrification model that includes explicit representation of denitrification enzyme kinetics. In conclusion, denitrification is a complex ecological function regulated at cellular level. To assess the environmental consequences of denitrification and develop useful tools to mitigate N2O emissions require a comprehensive understanding of the regulatory network of denitrification with respect to microbial physiology and environmental interactions.