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    Use of RNA secondary structure for evolutionary relationships : investigating RNase P and RNase MRP : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Genetics at Massey University, New Zealand
    (Massey University, 1998) Collins, Lesley Joan
    Bioinformatics is applied here to examine whether RNA secondary structure data can reflect distant evolutionary relationships. This is important when there is little confidence in sequence data such as when looking at the evolution of RNase MRP (MRP). RNase P (P) and RNase MRP (MRP) are ribonucleoproteins (RNPs) that are involved in RNA processing and due to functional and secondary structure similarities, are thought to be evolutionary related. P activity is found in all cells, and fits the criteria for inclusion in the RNA world (Jeffares et al. 1998). MRP is found only in eukaryotes with essential functions in both the nucleus and mitochondria. The RNA components of P and MRP (pRNA and mrpRNA) cannot be aligned with any certainty, which leads to a lack of confidence in any phylogenetic trees constructed from them. If MRP evolved from P only in eukaryotes then it is an exception to the general process of the transfer of catalytic activity from RNA, to ribonucleoproteins, to proteins (Jeffares et al. 1998). An alternative possibility that MRP evolved with P in the RNA world (and has since been lost from all but the eukaryotes) is raised and examined. Quantitative comparisons of the pRNA and mrpRNA biological secondary structures have found that the third possibility of an organellar origin of MRP is unlikely Results show that biological secondary structure can be used in the evaluation of an evolutionary relatedness between MRP and P and may be extended to other catalytic RNA molecules. Although there are many protein families, this may be the first evidence of the existence of a family of RNA molecules, although it would be a very small family. Secondary structures derived with folding programs from pRNA and mrpRNA sequences are examined for use in the characterisation of catalytic RNA sequences. The high AT content in organellar genomes may hinder the identification of their catalytic RNA sequences. A search strategy is developed here to address this problem and is used to identify putative pRNA sequences in the chloroplast genomes of four green plants. A maize chloroplast pRNA-like sequence is examined in more detail and shows many characteristics seen in known pRNA sequences. Folding programs show some potential for the characterisation of possible catalytic RNA sequences with only a small bias in the results due to sequence length and AT content.
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    Beyond BLASTing : ribonucleoprotein evolution via structural prediction and ancestral sequence reconstruction
    (Massey University, 2016) Daly, Toni K
    Primary homology in DNA and protein sequence has long been used to infer a relationship between similar sequences. However gene sequence, and thus protein sequence, can change over time. In evolutionary biology that time can be millions of years and related sequences may become unrecognisable via primary homology. This is demonstrated most effectively in chapter 4a (figure 10). Conversely the number of possible folds that proteins can adopt is limited by the attractions between residues and therefore the number of possible folds is not infinite. This means that folds may arise via convergence between evolutionarily unrelated DNA sequences. This thesis aims to look at a process to will wring more information from the primary protein sequence than is usually used and finds other factors that can support or refute the placement of a protein sequence within the family in question. Two quite different proteins; the Major Vault Protein whose monomers make up the enigmatic vault particle and the argonaute family of proteins (AGO and PIWI) that appear to have a major hand in quelling parasitic nucleic acid and control of endogenous gene expression, are used to demonstrate the flexibility of the workflow. Principally the method relies on prediction of three-dimensional structure. This requires at least a partially solved crystal structure but once one exists this method should be suitable for any protein. Whole genome sequencing is now a routine practice but annotation of the resultant sequence lags behind for lack of skilled personnel. Automated pipeline data does a good job in annotating close homologs but more effort is needed for correct annotation of the exponentially growing data bank of uncharacterised (and wrongly characterised) proteins. Lastly, in deference to budding biologists the world over, I have tried to find free stable software that can be used on an ordinary personal computer and by a researcher with minimal computer literacy to help with this task.