4 resultados para Transgenic rice
em Digital Commons - Michigan Tech
Resumo:
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
Resumo:
Secondary metabolites play an important role in plant protection against biotic and abiotic stress. In Populus, phenolic glycosides (PGs) and condensed tannins (CTs) are two such groups of compounds derived from the common phenylpropanoid pathway. The basal levels and the inducibility of PGs and CTs depend on genetic as well as environmental factors, such as soil nitrogen (N) level. Carbohydrate allocation, transport and sink strength also affect PG and CT levels. A negative correlation between the levels of PGs and CTs was observed in several studies. However, the molecular mechanism underlying such relation is not known. We used a cell culture system to understand negative correlation of PGs and CTs. Under normal culture conditions, neither salicin nor higher-order PGs accumulated in cell cultures. Several factors, such as hormones, light, organelles and precursors were discussed in the context of aspen suspension cells’ inability to synthesize PGs. Salicin and its isomer, isosalicin, were detected in cell cultures fed with salicyl alcohol, salicylaldehyde and helicin. At higher levels (5 mM) of salicyl alcohol feeding, accumulation of salicins led to reduced CT production in the cells. Based on metabolic and gene expression data, the CT reduction in salicin-accumulating cells is partly a result of regulatory changes at the transcriptional level affecting carbon partitioning between growth processes, and phenylpropanoid CT biosynthesis. Based on molecular studies, the glycosyltransferases, GT1-2 and GT1-246, may function in glycosylation of simple phenolics, such as salicyl alcohol in cell cultures. The uptake of such glycosides into vacuole may be mediated to some extent by tonoplast localized multidrug-resistance associated protein transporters, PtMRP1 and PtMRP6. In Populus, sucrose is the common transported carbohydrate and its transport is possibly regulated by sucrose transporters (SUTs). SUTs are also capable of transporting simple PGs, such as salicin. Therefore, we characterized the SUT gene family in Populus and investigated, by transgenic analysis, the possible role of the most abundantly expressed member, PtSUT4, in PG-CT homeostasis using plants grown under varying nitrogen regimes. PtSUT4 transgenic plants were phenotypically similar to the wildtype plants except that the leaf area-to-stem volume ratio was higher for transgenic plants. In SUT4 transgenics, levels of non-structural carbohydrates, such as sucrose and starch, were altered in mature leaves. The levels of PGs and CTs were lower in green tissues of transgenic plants under N-replete, but were higher under N-depleted conditions, compared to the levels in wildtype plants. Based on our results, SUT4 partly regulates N-level dependent PG-CT homeostasis by differential carbohydrate allocation.
Resumo:
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.
Resumo:
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.