Author(s) |
Hathorn, Adrian Mark
Tier, Bruce
Wu, Harry
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Publication Date |
2012
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Abstract |
The invention of high-throughput genotyping technologies, in particular the single nucleotide polymorphism (SNP) chip, has prompted a revolution in the field of genetics. With the potential of genotyping literally hundreds of thousands of molecular markers at an affordable price, the once distant prospect of establishing an individuals genetic value without need of its pedigree has now become a reality. This thesis is primarily concerned with the use of genotypic data for 'genomic selection' - a novel and computationally intensive method of selection that uses all available genotypic data to estimate an individuals genetic potential. The efficiency of this method is considered within the broader context of the genetic improvement of Pinus radiata. We begin by introducing the reader to a basic application of SNP markers in an analysis of population structure and linkage disequilibrium (LD) for three of the five native Pinus radiata populations located on the west coast of California. We show that although these populations are geographically distinct, estimates of genetic distance derived from marker genotypes suggest that all three once belonged to the same population. Levels of LD are shown to be orders of magnitude higher within genes than outside the genes.
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Link | |
Title |
The Use of Genotypic Information for the Genetic Improvement of 'Pinus radiata'
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Type of document |
Thesis Doctoral
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Entity Type |
Publication
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Name | Size | format | Description | Link |
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closed/MARCXML.xml | 2.871 KB | MARCXML.xml | View document | |
closed/SOURCE01.pdf | 61.168 KB | application/pdf | Right of Access | View document |
administrative/MODS.xml | 4.189 KB | MODS.xml | View document | |
closed/SOURCE02.pdf | 97.339 KB | application/pdf | Candidate certification | View document |
preservation/ThesisHathornAdrianPhD2010Archive.pdf | 3351.499 KB | application/pdf | Archive | View document |
openpublished/ThesisHathornAdrianPhD2010.pdf | 3301.905 KB | application/pdf | Thesis | View document |