Development and application of bioinformatics tools for computational marker discovery and the integration and visualisation of plant genetic and genomic data

Christopher Michael Duran (2011). Development and application of bioinformatics tools for computational marker discovery and the integration and visualisation of plant genetic and genomic data PhD Thesis, School of Agriculture and Food Sciences, The University of Queensland.

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Author Christopher Michael Duran
Thesis Title Development and application of bioinformatics tools for computational marker discovery and the integration and visualisation of plant genetic and genomic data
School, Centre or Institute School of Agriculture and Food Sciences
Institution The University of Queensland
Publication date 2011-07
Thesis type PhD Thesis
Supervisor Associate Professor David Edwards
Dr Jacqueline Batley
Professor Kaye Basford
Total pages 306
Total colour pages 25
Total black and white pages 281
Language eng
Subjects 07 Agricultural and Veterinary Sciences
Abstract/Summary Brassica and barley are key crops for Australian agriculture and the export economy, and are the focal species for this thesis. Production of these crops is often limited by environmental factors including drought and soil salinity. The genomes of cultivated Brassica species and barley are both large and complex in comparison with other crops of agronomic importance such as rice and, at the start of this project, were still unresolved using the genome sequencing technology of the time. The rice genome has been sequenced and is used extensively as a model organism for monocot crop species, specifically the cereals. The Arabidopsis genome has also been sequenced and, although not an agronomically important plant in its own right, the species has a very small genome and is the model organism for dicot species. These model organisms play an important role, along with marker-based genetic studies, in understanding the underlying function and structure of important crop species. Genetic markers play a major role in our understanding of heritable traits. The bulk of variation at the nucleotide level is often not visible at the phenotypic level. This DNA variation is frequently exploited in molecular genetic marker systems, and the application of molecular markers to advance research and commercial activities is now well established. DNA based markers have many advantages over phenotypic markers in that they are highly heritable, relatively easy to assay, and are not affected by the environment. In modern genetic analysis, two sequence based marker systems predominate: Single Nucleotide Polymorphisms (SNPs) and Simple Sequence Repeats (SSRs). This thesis presents novel computational tools for the discovery of SNP and SSR markers using publicly available sequence data, taking advantage of the redundant nature of public data sources. Furthermore, this thesis argues the importance of data storage and visualisation techniques for the downstream analysis and interpretation of the wealth of genetic and genome data available in modern public repositories. To address these needs, presented is an integrated storage management and visualisation solution for sequence-based markers in the form of the autoSNPdb database. It is further argued that biologically relevant annotations and the integration of discovered data with existing resources is paramount to elucidating the function and role of sequences with underlying sequence variation. In the current genomics era, molecular genetic markers are bridging the divide between phenotypic traits and the increasingly available sequence information. The visualisation and comparison of genetic mapping resources and physical maps enables researchers to identify the genomic context for markers associated with traits of interest. Furthermore, genetic linkage studies provide vital information on genome organization and the association of heritable traits with known genetic markers. Of particular importance to researchers and breeders working with crop species is the transferability of this information from a model species to their species or variants of interest. Comparative mapping between genetic linkage groups and physical maps allows for the association of heritable traits with regions of sequenced genomes. This thesis presents the development of improved tools for the comparative visualisation of genetic, physical and genomic maps. Also presented is the construction of an integrated genetic and genomic mapping resource for the important dicot crop species, Brassica, and its closely related model organism, Arabidopsis.
Keyword Bioinformatics
Comparative genomics
molecular markers
Single Nucleotide Polymorphisms
simple sequence repeats
Additional Notes Colour pages: 32,49,62,68,69,70,71,73,74,75,85,117,121,151,152,165,182,189,228,229,232,233,234,236,239 Landscape pages: 196,225,275,276,277,278,279

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Created: Mon, 14 Nov 2011, 10:16:34 EST by Mr Christopher Duran on behalf of Library - Information Access Service