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Bioinformatics tools for evaluating microbial relationships

Posted on:2010-11-08Degree:Ph.DType:Dissertation
University:Washington State UniversityCandidate:Meng, DaFull Text:PDF
GTID:1441390002983449Subject:Engineering
Abstract/Summary:
Recent years have seen the rapid development of microbial genomics. The vast amounts of microbial genomic information make it possible to study microorganisms systematically. However, how to manipulate the huge amount of available data, how to retrieve genomic information effectively, and how to effectively process the large scale data are big challenges. To cope with these difficulties, more sophisticated informatics methods have been widely used and have become an essential part of genomics.;My research work is focused on developing new strategies for several of the challenges mentioned above. First, we describe a new software tool, PLasmid Analysis System and Marker IDentification (PLASMID), for selecting an optimal set of probes for the design of a classification microarray. The tool provides the user with several clustering methods, a probe ranking method, probe redundancy reduction, and probe selection using stepwise discriminant analysis. The software package has been applied to data from a mixed-plasmid microarray, a virtual mixed-genome microarray, and an expression microarray.;Second, to increase discrimination accuracy, we have developed a fusion algorithm that combines the information obtained from both Pulsed-Field Gel Electrophoresis (PFGE) and Multiple-Locus Variable-Number Tandem Repeat Analysis (MLVA) assays to obtain phylogenetic relationships. Results are assessed by comparison with phage-typing assays and with known epidemiological relationships. Our analysis shows that the fusion algorithm provides an improved ability to discriminate between bacterial isolates and to infer phylogenetic relationships compared with using either PFGE or MLVA analysis alone.;Many studies have shown that horizontal gene transfer (HGT) is common among microbes. HGT can lead to mosaic-like gene sequences in plasmids which makes it a challenge to build robust phylogenetic trees. Simply applying existing phylogenetic methods to study the evolution of plasmids may lead to questionable results. When multiple sequence alignment is used, most phylogenetic methods assume the sequences are homologous. We consider several features of plasmids that affect phylogeny analysis and introduce a method for establishing reliable phylogenetic relationships.
Keywords/Search Tags:Relationships, Microbial
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