3 resultados para regulatory and signaling networks

em Digital Commons - Michigan Tech


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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.

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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.

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Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.