Comparison of the gene expression between two rice cultivars by microarray data
| Autor: | Chin,Hao-Kang, 秦浩剛 |
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| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 Rice (Oryza sativa) is the most important crop in the world, and it’s the staple food for more than one half of the global population. In recent years, a lot of researcher are devoted to studying the rice gene and rice breeding. 1998, the genome of a japonica rice cultivar has been completely sequenced by International Rice Genome Sequencing Project (IRGSP). The gathered genomic information have accelerate the research of some specific rice gene, such as pathogenic gene,anti-flood gene and anti-insect gene research, gene transformation, gene mapping. TCN1 and TNG67 are representative indica and japonica cultivars in Taiwan with fine characteristics in agriculture. The seedling, leaf and root tissues of these two rice cultivars were used in current study to understand the difference of gene expression between two subspecies by microarray data.. From the statistical analysis of this study, some subspecies-specific genes were found out. The enriched GO terms were implied the differential expression between cultivars or subspecies. These results may be further used in rice breeding for desired elite agricultural characteristics. The ANOVA resulted that 6% of probe-sets are significantly different between subspecies, 12% of probe-sets are significantly different among tissues, and 3% of probe-sets are significantly due to interaction between cultivars and tissues.After the clustering analysis, we select 58 genes that have significant expression between TCN1 and TNG67. The discriminant model were constructed to determine the sample from TCN1 or TNG67. The discriminability of model reaches 100%. That is, these 58 genes can be utilized as gene makers to determine the sample source comes from TCN1 or TNG67. In the gene function way, we select the most GO terms in group2. So, the gene function between position is the most different. It’s also can infer that the physiology reaction between three position of rice is not the same, photosynthesis is a good example. Basically, utilize GO enrichment to select gene function are almost molecular function, for example, DNA transcription、RNA translation and enzyme activity. This research provide an analysis method to understand how to analyze wide-range microarray data. We also use these method to find the different gene function or find some gene marker. And find out about the application of the microarray data through this research. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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