Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 428945
Title The impact of genotyping different groups of animals on accuracy when moving from traditional to genomic selection
Author(s) Pszczola, M.J.; Strabel, T.; Arendonk, J.A.M. van; Calus, M.P.L.
Source Journal of Dairy Science 95 (2012)9. - ISSN 0022-0302 - p. 5412 - 5421.
DOI http://dx.doi.org/10.3168/jds.2012-5550
Department(s) LR - Animal Breeding & Genomics
LR - Backoffice
Animal Breeding and Genetics
Livestock Research
WIAS
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) estimated breeding values - relationship matrices - genetic evaluation - full pedigree - dairy-cattle - unified approach - holstein cattle - information - populations - prediction
Abstract Compared with traditional selection, the use of genomic information tends to increase the accuracy of estimated breeding values (EBV). The cause of this increase is, however, unknown. To explore this phenomenon, this study investigated whether the increase in accuracy when moving from traditional (AA) to genomic selection (GG) was mainly due to genotyping the reference population (GA) or the evaluated animals (AG). In it, a combined relationship matrix for simultaneous use of genotyped and ungenotyped animals was applied. A simulated data set reflected the dairy cattle population. Four differently designed (i.e., different average relationships within the reference population) small reference populations and 3 heritability levels were considered. The animals in the reference populations had high, moderate, low, and random (RND) relationships. The evaluated animals were juveniles. The small reference populations simulated difficult or expensive to measure traits (i.e., methane emission). The accuracy of selection was expressed as the reliability of (genomic) EBV and was predicted based on selection index theory using relationships. Connectedness between the reference populations and evaluated animals was calculated using the prediction error variance. Average (genomic) EBV reliabilities increased with heritability and with a decrease in the average relationship within the reference population. Reliabilities in AA and AG were lower than those in GG and were higher than those in GA (respectively, 0.039, 0.042, 0.052, and 0.048 for RND and a heritability of 0.01). Differences between AA and GA were small. Average connectedness with all animals in the reference population for all scenarios and reference populations ranged from 0.003 to 0.024; it was lowest when the animals were not genotyped (AA; e.g., 0.004 for RND) and highest when all the animals were genotyped (GG; e.g., 0.024 for RND). Differences present across designs of the reference populations were very small. Genomic relationships among animals in the reference population might be less important than those for the evaluated animals with no phenotypic observations. Thus, the main origin of the gain in accuracy when using genomic selection is due to genotyping the evaluated animals. However, genotyping only one group of animals will always yield less accurate estimates.
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