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Identifying functional adaptations associated with pathogenicity in bacteria.
by Nicole E Wheeler
Institution: | University of Canterbury |
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Year: | 2017 |
Posted: | 02/01/2018 |
Record ID: | 2198426 |
Full text PDF: | http://hdl.handle.net/10092/13713 |
Next generation sequencing technologies have provided us with a wealth of information on geneticvariation, but predicting the functional significance of this variation is a difficult task. This thesissummarises the development of a profile hidden Markov model based approach we call deltabitscore(DBS). The approach identifies orthologous proteins that have diverged at the amino acid sequencelevel in a way that is likely to impact biological function. I present the benchmarking of this approachusing several widely used datasets and its application to various biological questions. I then outlinethe extension of this method from a pairwise comparative method to one that can be scaled for thecomparison of hundreds or thousands of bacterial genomes. I demonstrate the utility of the method foridentifying associations between genetic variation and phenotypes of interest, and discussmethodological considerations and extensions that must be made in order for this approach tofunction effectively on a large scale.
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