It is recognized that an iterative comparative analysis of large-scale homologous RNAs significantly promote the understanding of an RNA family. The Gutell lab is renowned for maintaining high quality RNA sequence alignments and accurately predicted RNA secondary structures using this approach. While the current available alignment and structure data are mainly obtained by trained domain experts with extensive manual effort, it is highly desired that this process is automated and replicable given the exponentially growing number of RNA sequence data and the amount of time required for expert training. In this thesis, we learn the processes involved in comparative analysis by manually aligning a non-coding RNA family, IVS sequences, with the supervision of Dr. Gutell. Each process is then simulated by mathematical objective functions and algorithms. We also evaluate the current available RNA analysis packages that aim each of the processes. Finally, a new RNA sequence alignment algorithm incorporating structure information that can be extended for different alignment tasks is proposed. / text

The expression of numerous plant mRNAs is attenuated by RNA sequence elements located in the 5' and 3' untranslated regions (UTRs). For example, in plants and many higher eukaryotes, roughly 35% of genes encode mRNAs that contain one or more upstream open reading frames (uORFs) in the 5' UTR. For this dissertation I have analyzed the pattern of conservation of such mRNA sequence elements. In the first set of studies, I have taken a comparative transcriptomics approach to address which RNA sequence elements are conserved between various families of angiosperm plants. Such conservation indicates an element's fundamental importance to plant biology, points to pathways for which it is most vital, and suggests the mechanism by which it acts. Conserved motifs were detected in 3% of genes. These include di-purine repeat motifs, uORF-associated motifs, putative binding sites for PUMILIO-like RNA binding proteins, small RNA targets, and a wide range of other sequence motifs. Due to the scanning process that precedes translation initiation, uORFs are often translated, thereby repressing initiation at the an mRNA's main ORF. As one might predict, I found a clear bias against the AUG start codon within the 5' untranslated region (5' UTR) among all plants examined. Further supporting this finding, comparative analysis indicates that, for ~42% of genes, AUGs and their resultant uORFs reduce carrier fitness. Interestingly, for at least 5% of genes, uORFs are not only tolerated, but enriched. The remaining uORFs appear to be neutral. Because of their tangible impact on plant biology, it is critical to differentiate how uORFs affect translation and how, in many cases, their inhibitory effects are neutralized. In pursuit of this aim, I developed a computational model of the initiation process that uses five parameters to account for uORF presence. In vivo translation efficiency data from uORF-containing reporter constructs were used to estimate the model's parameters in wild type Arabidopsis. In addition, the model was applied to identify salient defects associated with a mutation in the subunit h of eukaryotic initiation factor 3 (eIF3h). The model indicates that eIF3h, by supporting re-initation during uORF elongation, facilitates uORF tolerance.

We describe the use of a tensor mode-1 higher-order singular value decomposition (HOSVD) in the analyses of alignments of 16S and 23S ribosomal RNA (rRNA) sequences, each encoded in a cuboid of frequencies of nucleotides across positions and organisms. This mode-1 HOSVD separates the data cuboids into combinations of patterns of nucleotide frequency variation across the positions and organisms, i.e., "eigenorganisms"' and corresponding nucleotide-specific segments of "eigenpositions," respectively, independent of a-priori knowledge of the taxonomic groups and their relationships, or the rRNA structures. We show that this mode-1 HOSVD provides a mathematical framework for modeling the sequence alignments where the mathematical variables, i.e., the significant eigenpositions and eigenorganisms, are consistent with current biological understanding of the 16S and 23S rRNAs. First, the significant eigenpositions identify multiple relations of similarity and dissimilarity among the taxonomic groups, some known and some previously unknown. Second, the corresponding eigenorganisms identify positions of nucleotides exclusively conserved within the corresponding taxonomic groups, but not among them, that map out entire substructures inserted or deleted within one taxonomic group relative to another. These positions are also enriched in adenosines that are unpaired in the rRNA secondary structure, the majority of which participate in tertiary structure interactions, and some also map to the same substructures. This demonstrates that an organism's evolutionary pathway is correlated and possibly also causally coordinated with insertions or deletions of entire rRNA substructures and unpaired adenosines, i.e., structural motifs which are involved in rRNA folding and function. Third, this mode-1 HOSVD reveals two previously unknown subgenic relationships of convergence and divergence between the Archaea and Microsporidia, that might correspond to two evolutionary pathways, in both the 16S and 23S rRNA alignments. This demonstrates that even on the level of a single rRNA molecule, an organism's evolutionary pathway is composed of different types of changes in structure in reaction to multiple concurrent evolutionary forces. / text