Initial activities were focused on isolation and characterization of fruit ripening-related genes from tomato. Screening of four tomato cDNA libraries at low stringency with 10 fruit development and ripening-related genes yielded ~3000 positives clones. Microarray expression analysis of half of these positives in mature green and breaker stage fruits resulted in eight ripening-induced genes. RNA gel-blot analysis and previously published data confirmed expression for seven of the eight. One novel gene, designated LeEREBP1, was chosen for further characterization. LeEREBP1 encodes an AP2/ERF-domain transcription factor and is ethylene inducible. The expression profiles of LeEREBP1 parallel previously characterized ripening-related genes from tomato. Transgenic plants with increased and decreased expression of LeEREBP1 were generated and are currently being characterized to define the function of LeEREBP1.
A large public tomato EST dataset was mined to gain insight into the tomato transcriptome. By clustering genes according to the respective expression profiles of individual tissues, tissue and developmental expression patterns were generated and genes with similar functions grouped together. Tissues effectively clustered for relatedness according to their profiles confirming the integrity of the approach used to calculate gene expression. Statistical analysis of EST prevalence in fruit and pathogenesis-related libraries resulted in 333 genes being classified as fruit ripening-induced, 185 as fruit ripening-repressed, and 169 as pathogenesis-related. We performed a parallel analysis on public EST data for grape and compared the results for ripening-induced genes to tomato to identify similar and distinct ripening factors in addition to candidates for conserved regulators of fruit ripening.
An online interactive database for tomato gene expression data - Tomato Expression Database (TED) was implemented. TED contains normalized expression data for approximately 12,000 ESTs over ten time points during fruit development. It also contains comprehensive annotation of each EST. Through TED, we provide multiple approaches to pursue analysis of specific genes of interest and/or access the larger microarray dataset to identify sets of genes that may behave in a pattern of interest. In addition, a set of useful data mining and data visualization tools were developed and are under continuing expansion.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/257 |
| Date | 30 September 2004 |
| Creators | Fei, Zhangjun |
| Contributors | Giovannoni, James, Binzel, Marla |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | 4404863 bytes, 539005 bytes, electronic, application/pdf, text/plain, born digital |
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