An extended mixed inheritance model for detecting major genes affecting quantitative traits

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Jolly Shrivastava (Creator)
Institution
The University of North Carolina at Greensboro (UNCG )
Web Site: http://library.uncg.edu/
Advisor
David L. Remington

Abstract: "The objective of this research is to extend the mixed inheritance model developed by Zeng et al (2004) to detect the segregation of two major genes using phenotypic data from a half-diallel mating design. The model can be used to select parents which are segregating for major genes, both for breeding purposes and studies of adaptive evolution. The model can be used to find parents that are heterozygous for major genes, so the cost of QTL mapping just to determine whether a QTL is present can be avoided. A Bayesian approach using Gibbs sampling was used to develop this model. Genotypes of the parents and progeny are updated using "parent blocking" in which the genotypes of the parents and progeny are updated as a block. For this study, only additive effects of major genes were taken into account. In general, estimates of genetic parameters were accurate. When major gene effects were large (> 0.5 phenotypic standard deviation), the genotypes of the parents along with genetic parameters were estimated correctly. However, when major gene effects were small, transformation between major genes and polygenic effects occurred frequently and heterozygotes were sometimes incorrectly identified. Suggestions for further modifications of the model are made, including addition of dominance, epistatic, and genotype X environment interactions and modifications to improve the mixing of the chains."--Abstract from author supplied metadata.

Additional Information

Publication
Thesis
Language: English
Date: 2005
Keywords
mixed inheritance model, segregation, genes, phenotypic data, parents, breeding, adaptive evolution, heterozygous, Genotypes
Subjects
Quantitative genetics
Evolutionary genetics
Gene mapping