In commercial livestock populations, QTL detection methods often use existing half-sib family structures and ignore additional relationships within and between families. We reanalyzed the data from a large QTL confirmation experiment with 10 @entity1707 lines and 10 chromosome regions using @entity5748 ( @entity5748 ) scores and variance component analyses. The @entity5748 scores were obtained using a Monte Carlo Markov Chain method, as implemented in the LOKI software, and were used to model a putative QTL in a mixed animal model. The analyses revealed 61 QTL at a nominal 5% level (out of 650 tests). Twenty-seven QTL mapped to areas where QTL have been reported, and eight of these exceeded the threshold to claim confirmed linkage (P < 0.01). Forty-two of the putative QTL were detected previously using half-sib analyses, whereas 46 QTL previously identified by half-sib analyses could not be confirmed using the variance component approach. Some of the differences could be traced back to the underlying assumptions between the two methods. Using a deterministic approach to estimate @entity5748 scores on a subset of the data gave very similar results to LOKI. We have demonstrated the feasibility of applying variance component QTL analysis to a large amount of data, equivalent to a genome scan. In many situations, the deterministic @entity5748 approach offers a fast alternative to LOKI.

Full pedigree quantitative trait locus analysis in commercial XXXX using variance components.

@entity1707 :: ('9823', 'Species') :: ['pig'] @entity5748 :: ('MESH:D009105', 'Disease') :: ['identity-by-descent', 'IBD']
@entity1707 :: (9823,Species) :: ['pigs']
