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Genet Sel Evol. 2004 Mar-Apr;36(2):145-61.

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

Author information

1
School of Rural Science and Agriculture, University of New England, Armidale, NSW 2351, Australia. slee7@metz.une.edu.au

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 x10(-4) per generation. In mapping using bi-allelic markers, 42 approximately 55 of replicated simulations could position QTL within 0.75 cM of the true position whereas this was higher for multi allelic markers (48 approximately 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.

PMID:
15040896
PMCID:
PMC2697183
DOI:
10.1186/1297-9686-36-2-145
[Indexed for MEDLINE]
Free PMC Article

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