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Linkage disequilibrium (LD) information from closely linked markers has been widely used to fine-map quantitative trait loci (QTL). Steps needed for fine-mapping of QTL include inferring inheritance state of markers (haplotyping), estimating identity by descent (IBD) at QTL, and implementing the covariance structure based on IBD into a statistical model. Appropriate pedigree-genotype analysis can estimate more accurate inheritance state and haplotype configuration, which results in more accurate IBD probabilities. A variance component approach can implement covariance coefficients based on IBD probabilities in a mixed linear model to fit additive, dominance and epistasis QTL effects. We have also implemented a reversible jump Markov chain Monte Carlo (MCMC) method for multiple QTL mapping to account for confounding effects between closely linked QTL. Simulation results have shown that this method can improve the precision of mapping QTL. |
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