Functional analysis of rice bidirectional promoters

Bidirectional promoters regulate adjacent genes organized in a divergent fashion (head to head orientation). Several Reports pertaining to bidirectional promoters on a genomic scale exists in mammals. This work provides the essential background on theoretical and experimental work to carry out a genomic scale analysis of bidirectional promoters in plants. A computational study was performed to identify putative bidirectional promoters and the over-represented cis-regulatory motifs from three sequenced plant genomes: rice (Oryza sativa), Arabidopsis thaliana, and Populus trichocarpa using the Plant Cis-acting Regulatory DNA Elements (PLACE) and PLANT CARE databases. Over-represented motifs along with their possible function were described with the help of a few conserved representative putative bidirectional promoters from the three model plants. By doing so a foundation was laid for the experimental evaluation of bidirectional promoters in plants. A novel Agrobacterium tumefaciens mediated transient expression assay (AmTEA) was developed for young plants of different cereal species and the model dicot Arabidopsis thaliana. AmTEA was evaluated using five promoters (six constructs) and two reporter genes, gus and egfp. Efficacy and stability of AmTEA was compared with stable transgenics using the Arabidopsis DEAD-box RNA helicase family gene promoter. AmTEA was primarily developed to overcome the many problems associated with the development of transgenics and expression studies in plants. Finally a possible mechanism for the bidirectional activity of bidirectional promoters was highlighted. Deletion analysis using promoter-reporter gene constructs identified three rice promoters to be bidirectional. Regulatory elements located in the 5’- untranslated regions (UTR) of one of the genes of the divergent gene pair were found to be responsible for their bidirectional ctivity

The effects of soil moisture, field-scale toposequential position, and slope on yields in irrigated upland rice fields in Flores, Comayagua, Honduras

Rice (Oryza sativa L.) is an important cash crop in Honduras because of the rice lobby’s size, willingness to protest, and ability to negotiate favorable price guarantees on a year-to-year basis. Despite the availability of inexpensive irrigation in the study area in Flores, La Villa de San Antonio, Comayagua, the rice farmers do not cultivate the crop using prescribed methods such as land leveling, puddling, and water conservation structures. Soil moisture (Volumetric Water Content) was measured using a soil moisture probe after the termination of the first irrigation within the tillering/vegetative, panicle emergence/flowering, post-flowering/pre-maturation and maturation stages. Yield data was obtained by harvesting on 1 m2 plots in each soil moisture testing site. Data was analyzed to find the influence of toposequential position along transects, slope, soil moisture, and farmers on yields. The results showed that toposequential position was more important than slope and soil moisture on yields. Soil moisture was not a significant predictor of rice yields. Irrigation politics, precipitation, and land tenure were proposed as the major explanatory variables for this result.

Investigation into the impact of grain boundaries, film interface, and crystallographic orientation on the ionic conductivity of thin film gadolinium-doped ceria

The research reported in this dissertation investigates the impact of grain boundaries, film interface, and crystallographic orientation on the ionic conductivity of thin film Gd-doped CeO2 (GDC). Chapter 2 of this work addresses claims in the literature that submicron grain boundaries have the potential to dramatically increase the ionic conductivity of GDC films. Unambiguous testing of this claim requires directly comparing the ionic conductivity of single-crystal GDC films to films that are identical except for the presence of submicron grain boundaries. In this work techniques have been developed to grow GDC films by RF magnetron sputtering from a GDC target on single crystal r plane sapphire substrates. These techniques allow the growth of films that are single crystals or polycrystalline with 80 nm diameter grains. The ionic conductivities of these films have been measured and the data shows that the ionic conductivity of single crystal GDC is greater than that of the polycrystalline films by more than a factor of 4 over the 400-700°C temperature range. Chapter 3 of this work investigates the ionic conductivity of surface and interface regions of thin film Gd-doped CeO2. In this study, single crystal GDC films have been grown to thicknesses varying from 20 to 500 nm and their conductivities have been measured in the 500-700°C temperature range. Decreasing conductivity with decreasing film thickness was observed. Analysis of the conductivity data is consistent with the presence of an approximately 50 nm layer of less conductive material in every film. This study concludes that the surface and interface regions of thin film GDC are less conductive than the bulk single crystal regions, rather than being highly conductive paths. Chapter 4 of this work investigates the ionic conductivity of thin film Gd-doped CeO2 (GDC) as a function of crystallographic orientation. A theoretical expression has been developed for the ionic conductivity of the [100] and [110] directions in single crystal GDC. This relationship is compared to experimental data collected from a single crystal GDC film. The film was grown to a thickness of _300 nm and its conductivity measured along the [100] and [110] orientations in the 500-700°C temperature range. The experimental data shows no statistically significant difference in the conductivities of the [100] and [110] directions in single crystal GDC. This result agrees with the theoretical model which predicts no difference between the conductivities of the two directions.

DISSECTION OF STRESS RESPONSE NETWORKS REGULATING MULTIPLE STRESSES IN RICE

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.