Many stress situations limit plant growth, resulting in crop production difficulties. Population growth, limited availability and over-utilization of arable land, and intolerant crop species have resulted in tremendous strain being placed on agriculturalists to produce enough to sustain the world's population. An understanding of the principles involved in plant resistance to environmental stress will enable scientists to harness these mechanisms to create stress-tolerant crop species, thus increasing crop production, and enabling the farming of previously unproductive land. This research project uses computational and bioinformatics techniques to explore the promoter regions of genes, encoding proteins that are up- or down-regulated in response to specific abiotic stresses, with the aim of identifying common patterns in the cis-elements governing the regulation of these abiotic stress responsive genes. An initial dataset of fifty known genes encoding for proteins reported to be up- or down-regulated in response to plant stresses that result in water-deficit at the cellular level viz. drought, low temperature, and salinity, were identified, and a postgreSQL database created to store relevant information pertaining to these genes and the proteins encoded by them. The genomic DNA was obtained where possible, and the promoter and intron regions identified. The Neural Network Promoter Prediction (NNPP) software package was used to predict the transcription start signal (TSS) and the promoter searching software tool, TESS (Transcription Element Search Software) used to identify known and user-defined cis-elements within the promoter regions of these genes. Currently available promoter prediction software analysis tools are reported to predict one promoter per kilobase of DNA, whilst functional promoters are thought to only occur one in 30-40 kilobases, which indicates that a large perccntage of predictions are likely to be false positives (pedersen et. al., 1999). NNPP was chosen as it was rated as the highest performing promoter prediction software tool by Fickett and Hatzigeorgiou (1997) in a thorough review of eukaryotic promoter prediction algorithms, however results were less than promising as very few predicted TSS were identified in the area 50 bps up- and downstream of the gene start site, where biologically functional TSSs are known to occur (Reese, 2000; Fickett and Hatzigeorgiou, 1997). TESS results seemed to support the hypothesis that drought, low-temperature and high salinity plant stress response proteins have similar as-elements in their promoter regions, and suggested links to various other gene regulation mechanisms viz. gibberellin-, light-, auxin- and development-regulated gene expression, highlighting the vast complexity of plant stress response processes. Although far from conclusive, results provide a valuable basis for future comparative promoter studies that will attempt to deduce possible common transcriptional initiation of abiotic stress response genes. / KMBT_363 / Adobe Acrobat 9.54 Paper Capture Plug-in
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:rhodes/vital:4074 |
| Date | 10 June 2013 |
| Creators | Maclear, Athlee |
| Publisher | Rhodes University, Faculty of Science, Biochemistry, Microbiology and Biotechnology |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis, Masters, MSc |
| Format | 177 p., pdf |
| Rights | Maclear, Athlee |
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