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This article is part of the supplement: Proceedings of the 13th European workshop on QTL mapping and marker assisted selection

Open Access Proceedings

Simultaneous QTL detection and genomic breeding value estimation using high density SNP chips

Roel F Veerkamp1*, Klara L Verbyla12, Han A Mulder1 and Mario P L Calus1

Author Affiliations

1 Animal Breeding and Genomics Centre, ASG Wageningen UR, PO Box 65, 8200 AB Lelystad, The Netherlands

2 Biosciences Research Division, Department of Primary Industries Victoria, 1 Park Drive, Bundoora 3083, Australia

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BMC Proceedings 2010, 4(Suppl 1):S9  doi:10.1186/1753-6561-4-S1-S9

Published: 31 March 2010

Abstract

Background

The simulated dataset of the 13th QTL-MAS workshop was analysed to i) detect QTL and ii) predict breeding values for animals without phenotypic information. Several parameterisations considering all SNP simultaneously were applied using Gibbs sampling.

Results

Fourteen QTL were detected at the different time points. Correlations between estimated breeding values were high between models, except when the model was used that assumed that all SNP effects came from one distribution. The model that used the selected 14 SNP found associated with QTL, gave close to unity correlations with the full parameterisations.

Conclusions

Nine out of 18 QTL were detected, however the six QTL for inflection point were missed. Models for genomic selection were indicated to be fairly robust, e.g. with respect to accuracy of estimated breeding values. Still, it is worthwhile to investigate the number QTL underlying the quantitative traits, before choosing the model used for genomic selection.