Browsing Department of Biochemistry by browse.metadata.advisor "Burger, Johan T."
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- ItemGenolve : a bioinformatics tool for the study of structure-driven genome evolution(Stellenbosch : Stellenbosch University, 2021-04) Fouche, Helene; Patterton, Hugh-G.; Burger, Johan T.; Stellenbosch University. Faculty of Science. Dept. of Biochemistry.ENGLISH SUMMARY : The process of structural genomic evolution, how one genome may have evolved into another via large-scale rearrangement events, has been a topic of study for the last few decades. Numerous genomic sorting models and algorithms that transform one genome into another using genome rearrangements exist. From a biological perspective, some of the models are more accurate than others. The rDCJ model is currently the best in this respect. In order to gain an in-depth understanding of the underlying mechanisms of genome evolution, knowledge of the different ways in which one genome may have evolved into another, is vital. At present, bioinformatic tools do exist that implement one or more of the genomic sorting models, however they output only one of an often-vast amount of equiprobable rearrangement scenarios. This thesis describes amendments made to the existing rDCJ genomic sorting model, which increases its biological accuracy. The amended model was incorporated into an algorithm that finds all of the most parsimonious rearrangement scenarios for sorting one genome into another. This allowed for the development of the open-source, command-line, bioinformatics tool, Genolve. When tested on simulated data, Genolve transformed one input genome into another 100% of the time, generating the full set of the most parsimonious sorting scenarios in its output. Unique to Genolve is also an output-summary of the average number and type of rearrangements present in the set of rearrangement scenarios. Application to two related strains of the yeast, Saccharomyces cerevisiae, illustrated the utility of the tool in analysing biological data. Making Genolve available as an open-source tool will allow researchers interested in the process of genomic evolution to conduct comprehensive studies in greater depth than was previously possible.