Major gene detection for fusiform rust resistance using Bayesian complex segregation analysis in loblolly pine |
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Authors: | Hua Li Sujit Ghosh Henry Amerson Bailian Li |
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Affiliation: | (1) Department of Forestry and Environmental Resources, North Carolina State University, Campus Box 8002, Raleigh, NC 27695, USA;(2) Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA |
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Abstract: | The presence of major genes affecting rust resistance of loblolly pine was investigated in a progeny population that was generated with a half-diallel mating of six parents. A Bayesian complex segregation analysis was used to make inference about a mixed inheritance model (MIM) that included polygenic effects and a single major gene effect. Marginalizations were achieved by using Gibbs sampler. A parent block sampling by which genotypes of a parent and its offspring were sampled jointly was implemented to improve mixing. The MIM was compared with a pure polygenic model (PM) using Bayes factor. Results showed that the MIM was a better model to explain the inheritance of rust resistance than the pure PM in the diallel population. A large major gene variance component estimate (> 50% of total variance), indicated the existence of major genes for rust resistance in the studied loblolly pine population. Based on estimations of parental genotypes, it appears that there may be two or more major genes affecting disease phenotypes in this diallel population. |
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