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Combined line-cross and half-sib QTL analysis of crosses between outbred lines

Published online by Cambridge University Press:  15 August 2005

JONG-JOO KIM
Affiliation:
Department of Animal Science, Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA School of Biotechnology, Yeungnam University, Gyeongsan, Korea.
HONGHUA ZHAO
Affiliation:
Department of Animal Science, Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA
HAUKE THOMSEN
Affiliation:
Department of Animal Science, Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA Danish Institute of Agricultural Sciences, Research Centre Foulum, 8830 Tjele, Denmark.
MAX F. ROTHSCHILD
Affiliation:
Department of Animal Science, Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA
JACK C. M. DEKKERS
Affiliation:
Department of Animal Science, Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA
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Abstract

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Data from an F2 cross between breeds of livestock are typically analysed by least squares line-cross or half-sib models to detect quantitative trait loci (QTL) that differ between or segregate within breeds. These models can also be combined to increase power to detect QTL, while maintaining the computational efficiency of least squares. Tests between models allow QTL to be characterized into those that are fixed (LC QTL), or segregating at similar (HS QTL) or different (CB QTL) frequencies in parental breeds. To evaluate power of the combined model, data wih various differences in QTL allele frequencies (FD) between parental breeds were simulated. Use of all models increased power to detect QTL. The line-cross model was the most powerful model to detect QTL for FD>0·6. The combined and half-sib models had similar power for FD<0·4. The proportion of detected QTL declared as LC QTL decreased with FD. The opposite was observed for HS QTL. The proportion of CB QTL decreased as FD deviated from 0·5. Accuracy of map position tended to be greatest for CB QTL. Models were applied to a cross of Berkshire and Yorkshire pig breeds and revealed 160 (40) QTL at the 5% chromosome (genome)-wise level for the 39 growth, carcass composition and quality traits, of which 72, 54, and 34 were declared as LC, HS and CB QTL. Fourteen CB QTL were detected only by the combined model. Thus, the combined model can increase power to detect QTL and mapping accuracy and enable characterization of QTL that segregate within breeds.

Type
Research Article
Copyright
© 2005 Cambridge University Press