Doctor of Philosophy (PhD)
First Committee Member
Jeffery Q. Shen
Second Committee Member
Third Committee Member
Fourth Committee Member
Fifth Committee Member
Number of Pages
The hormone abscisic acid (ABA) is biosynthesized by higher plants in response to various abiotic stresses such as drought and antagonizes the growth and germination-promoting hormone gibberellic acid (GA). The seed is a model system for studying desiccation tolerance and germination. The thin layer of cells surrounding the seed, the aleurone layer, plays a direct role in seed germination and an indirect role in desiccation tolerance. The goal of my research is to address the molecular mechanism underlying the responses of rice aleurone cells to ABA and GA, by taking a genomics approach. An accurate and complete annotation of the rice genome would greatly expand the results for such an approach. Without a complete annotation, key genes involved in the hormone signaling pathways may be missing. Since the sequencing of the rice (Oryza sativa) genome in 2002, over 57,000 putative and confirmed genes have been annotated; yet annotation of the rice genome is far from complete. Invention of the RNA-sequencing (RNA-seq) technologies provided a new high-throughput approach to genome annotation. To analyze RNA-seq data derived from rice aleurone cells treated with and without ABA, GA and a combination of these two hormones, I developed a software package, called Clustering Algorithm (CA). In combination with the popular transcript assembly software Cufflinks, I identified hundreds of potential novel genes in rice. Thorough filters were applied to minimize the number of false positives resulting in 553 high confidence novel genes. A subset of these novel genes were experimentally validated via qRT-PCR, and analysis of these genes indicated that these genes encode for proteins and/or microRNAs.
The CA software had some limitations: it requires a partially annotated reference genome, and it cannot identify exon/intron boundaries of the genes. To overcome these problems, I developed a novel algorithm dubbed the Tiling Assembly (TA). TA is reference annotation independent, and accurately identified exon/intron boundaries compared to popular transcript assembly software Cufflinks. Analyses of RNA-seq data with TA and Cufflinks, followed by application of the same thorough filters aforementioned, led to identification of 767 high confidence novel genes, far surpassing the previous number of novel genes previously identified. TA was applied to other organisms as well and was able to identify hundreds of high confidence novel genes in Drosophila, yeast, C. elegans and Arabidopsis. Therefore, for many organisms, TA is an invaluable tool for genome annotation based on RNA-seq data.
Defining the transcriptomes of rice aleurone cells treated with ABA, GA and both hormones helped address the crosstalk of ABA and GA signaling. There were 2,443 gene upregulated by ABA, 5,138 genes upregulated by GA and 4,273 genes upregulated by both ABA and GA in aleurone cells treated with the hormones for 4 hours. The 4 hour treatment was used because previous studies have shown that transcription of ABA induced some transcription factors reached a peak at 4 hours (Hoth et al., 2002). Out of the 2,443 ABA-inducible genes identified, 251 were induced by more than 4 fold. Using a bioinformatics approach, I identified a novel element that was overrepresented in the promoter regions of these 251 highly ABA-inducible genes. I named this element ABREN for ABA Responsive Element Novel. To determine whether or not this element plays a role in ABA induction, transient expression analyses via particle bombardment were performed on rice aleurone cells. Constructs containing the β-glucuronidase (GUS) reporter gene driven by a promoter containing ABRENs in both the promoter and 5’ UTR were introduced into the aleurone cells, then the cells were exposed to ABA and the reporter gene activity was measured. The results showed that when the ABREN in the promoter region was mutated, the level of ABA induction was significantly decreased, thus confirming ABREN’s role in ABA signaling. The discovery of this novel element will greatly help elucidate stress response pathways in plants. Overall, my research has advanced our understanding of the signaling network underlying plant responses to stresses and may help develop more stress resistant crops to meet the ever increasing food demands by the growing world population.
abscisic acid; bioinformatics; gibberellic acid; rice aleurone; RNA-sequencing
Bioinformatics | Biology | Plant Sciences
Watanabe, Kenneth Arthur, "A Bioinformatics Approach to Addressing the Responses of Rice Aleurone Cells to Hormones Abscisic Acid and Gibberellic Acid" (2016). UNLV Theses, Dissertations, Professional Papers, and Capstones. 2759.