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Title: Inferences on the genetic control of quantitative traits from selection experiments
Author: Heath, Simon Charles
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 1995
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The main aim of this thesis is the development of methods for analysing data from selection experiments to make inferences about the genetic control of the selected trait. A series of methods for data analysis are developed and applied to both simulated and experimental datasets under infinitesimal (polygenic) genetic models, discrete locus models and mixed inheritance models (which are a combination of polygenic and discrete locus models). The experimental dataset is from a replicated selection experiment on mice in which an F2 population formed from an inbred cross was divergently selected on body weight for 20 generations. The experimental data are initially analysed assuming the infinitesimal model using a Derivative Free Restricted Maximum Likelihood package (Meyer) to produce estimates of genetic parameters. An extension to the package is then developed to allow the variance components of change continuously over time, in effect regressing the variance components on generation number. This method allows for changes to variance components over and above what would be predicted from the infinitesimal model, thereby detecting deviations from the model. When applied to simulated data the method detects no change in additive genetic variance when a polygenic model with a large number of genes (16384) is simulated, but detects significant decreases in the additive variance, as expected, when a smaller number (32) are used. Analysis of the experimental data indicates that the additive and environment variance components increase over the course of the experiment, significantly so in the Low selected lines. Overall there is an estimated increase in phenotype variance of 56% in the Low lines and 14% in the High lines.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available