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,3
* Roslin Institute, Roslin, Midlothian EH25 9PS, U.K.;
and
Institut de Recerca i TecnologiaAgroalimentàries, Area de Producció Animal Centre UdL-IRTA, Lleida 25198, Spain;
and
Sygen International PLC, University of Cambridge, Department of Pathology, Cambridge CB2 1QP, U.K.;
and
Swedish University of Agricultural Sciences, Uppsala S-751 24, Sweden; and
and
Universitat Autònoma de Barcelona, Bellaterra, 08193 Catalunya, Spain.
2 Correspondence— phone: +44-131-5274460; fax: +44-131-4400434; E-mail: dj.dekoning{at}bbsrc.ac.uk.
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 pig lines and 10 chromosome regions using identity-by-descent (IBD) scores and variance component analyses. The IBD 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 IBD 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 IBD approach offers a fast alternative to LOKI.
Key Words: Best Linear Unbiased Prediction • Genomes • Least Squares • Pigs • Quantitative Trait Loci • Variance Components
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