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Multiple-interval mapping (MIM) analyzes multiple marker intervals simultaneously to fit multiple putative QTLs.
MIM uses multiple marker intervals concurrently to fit several potential QTL in the model, thereby increasing power and precision (Kao et al. 1999).
Among all available mapping methods, the multiple-QTL approach is particularly suitable for complex trait analysis since it uses simultaneously multiple marker intervals with possible inclusion of epistasis terms in QTL mapping model [ 23].
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Extension to the multiple marker interval GTL detection is also discussed.
These results suggest the presence of one QTL with pleiotropic effects on multiple traits or multiple QTL within the marker interval.
When multiple marker loci that were mapped within a 5 cM interval were associated with a trait, they were considered as a single QTL.
The merit of this relationship in trait haplotyping includes the incorporation of interferences between adjacent marker intervals into the estimation and test of haplotype effects when multiple markers are modelled simultaneously.
This mapping approach efficiently integrates effects of multiple QTLs, epistasis, and QTL-by-environment, by first conducting a whole genome scan for candidate marker intervals.
Thus, we identified 38 ethnically different marker intervals (Table 3).
We also determined 95% confidence intervals of genetic distances of the adjacent marker intervals.
For those marker intervals and ten surrounding intervals, the posterior probability was averaged across replicates.
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