Estimation of variance components and prediction of breeding values using pooled data.
Data on performance of animals are, in several situations, collected at the group rather than individual level. Genetic evaluations in farm animals, however, are based on phenotypic information collected at the individual level. Therefore, it would be very attractive to extend genetic evaluations by incorporating information collected at the group level. In this paper we show the use of data collected at the group level for the estimation of variance components and the prediction of breeding values. We outline a general procedure that can be applied in different farm animal species. In the present work this procedure was applied to BW, for which pooled, as well as individual, observations were available, thus allowing for a comparison of the estimates, and to egg production, for which only pooled data were available. For BW at 19 and 27 wk the estimated heritabilities based on individual observations were very similar to those based on pooled observations. For BW at 43 and 51 wk, heritability estimates based on individual and pooled data were different, which can be caused by the emergence of competition effects. The accuracy of EBV predicted from pooled observations was about 70 to 80% of the accuracy of EBV predicted from individual observations. This result quantifies the loss deriving from the use of pooled instead of individual observations. Results show that estimation of variance components and breeding values from pooled data instead of individual observations is theoretically and practically feasible.
Animal Breeding and Genomics Centre, Wageningen University, PO Box 338, 6700 AH Wageningen, the Netherlands. filippo.biscarini@wur.nl
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F
Biscarini
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Bovenhuis
J A M
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van Arendonk
D000818:Animals; D001835:Body Weight; D001947:Breeding; D002645:Chickens / Q000235:genetics / Q000502:physiology*; D005260:Female; D014644:Genetic Variation; D008297:Male; D008957:Models, Genetic; D010058:Oviposition / Q000235:genetics*; D012641:Selection, Genetic