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The efficiency of designs for fine-mapping of quantitative trait loci using combined linkage disequilibrium and linkage

Abstract : In a simulation study, different designs were compared for efficiency of fine-mapping of QTL. The variance component method for fine-mapping of QTL was used to estimate QTL position and variance components. The design of many families with small size gave a higher mapping resolution than a design with few families of large size. However, the difference is small in half sib designs. The proportion of replicates with the QTL positioned within 3 cM of the true position is 0.71 in the best design, and 0.68 in the worst design applied to 128 animals with a phenotypic record and a QTL explaining 25% of the phenotypic variance. The design of two half sib families each of size 64 was further investigated for a hypothetical population with effective size of 1000 simulated for 6000 generations with a marker density of 0.25 cM and with marker mutation rate $4 \times 10^{-4}$ per generation. In mapping using bi-allelic markers, $42 {\sim} 55 {\%}$ of replicated simulations could position QTL within 0.75 cM of the true position whereas this was higher for multi allelic markers ($48 {\sim} 76 {\%}$). The accuracy was lowest (48%) when mutation age was 100 generations and increased to 68% and 76% for mutation ages of 200 and 500 generations, respectively, after which it was about 70% for mutation ages of 1000 generations and older. When effective size was linearly decreasing in the last 50 generations, the accuracy was decreased (56 to 70%). We show that half sib designs that have often been used for linkage mapping can have sufficient information for fine-mapping of QTL. It is suggested that the same design with the same animals for linkage mapping should be used for fine-mapping so gene mapping can be cost effective in livestock populations.
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Sang Lee, Julius van der Werf. The efficiency of designs for fine-mapping of quantitative trait loci using combined linkage disequilibrium and linkage. Genetics Selection Evolution, BioMed Central, 2004, 36 (2), pp.145-161. ⟨10.1051/gse:2003056⟩. ⟨hal-00894479⟩

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