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. 2012 Aug;94(4):223-34.
doi: 10.1017/S0016672312000407.

Fine-mapping quantitative trait loci with a medium density marker panel: efficiency of population structures and comparison of linkage disequilibrium linkage analysis models

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Free PMC article

Fine-mapping quantitative trait loci with a medium density marker panel: efficiency of population structures and comparison of linkage disequilibrium linkage analysis models

Dana L Roldan et al. Genet Res (Camb). 2012 Aug.
Free PMC article

Abstract

Recently, a Haley-Knott-type regression method using combined linkage disequilibrium and linkage analyses (LDLA) was proposed to map quantitative trait loci (QTLs). Chromosome of 5 and 25 cM with 0·25 and 0·05 cM, respectively, between markers were simulated. The differences between the LDLA approaches with regard to QTL position accuracy were very limited, with a significantly better mean square error (MSE) with the LDLA regression (LDLA_reg) in sparse map cases; the contrary was observed, but not significantly, in dense map situations. The computing time required for the LDLA variance components (LDLA_vc) model was much higher than the LDLA_reg model. The precision of QTL position estimation was compared for four numbers of half-sib families, four different family sizes and two experimental designs (half-sibs, and full- and half-sibs). Regarding the number of families, MSE values were lowest for 15 or 50 half-sib families, differences not being significant. We observed that the greater the number of progenies per sire, the more accurate the QTL position. However, for a fixed population size, reducing the number of families (e.g. using a small number of large full-sib families) could lead to less accuracy of estimated QTL position.

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Figures

Fig. 1
Fig. 1
Errors (cM) distribution of the linkage method and two LDLA methods with a 15 half-sib family design for a 5 cM (left side) and 25 cM (right side) chromosomal region and for the two marker densities (0·25 cM (upper) and 0·05 cM (lower)). LA, linkage analysis; LDLA_reg and LDLA_vc, LDLA analysis by regression model and IBD-based variance component, respectively. The blue triangle is the true QTL location.
Fig. 2
Fig. 2
LRT averaged over 100 replicates in each tested position (from 0·05 cM marker spacing and 15 sires) for LA and LDLA_reg and IBD-based variance component (LDLA_vc) models. LRT=2(log LQTL−log Lno QTL). Shaded box, LA; solid triangle, LDLA_reg; solid diamond, LDLA_vc.

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