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 417282
Title Genomic and pedigree-based genetic parameters for scarcely recorded traits when some animals are genotyped
Author(s) Veerkamp, R.F.; Mulder, H.A.; Thompson, R.; Calus, M.P.L.
Source Journal of Dairy Science 94 (2011)8. - ISSN 0022-0302 - p. 4189 - 4197.
DOI http://dx.doi.org/10.3168/jds.2011-4223
Department(s) LR - Backoffice
WIAS
Publication type Refereed Article in a scientific journal
Publication year 2011
Keyword(s) variance-components - energy-balance - information - selection
Abstract Genetic parameters were estimated using relationships between animals that were based either on pedigree, 43,011 single nucleotide polymorphisms, or a combination of these, considering genotyped and nongenotyped animals. The standard error of the estimates and a parametric bootstrapping procedure was used to investigate sampling properties of the estimated variance components. The data set contained milk yield, dry matter intake and body weight for 517 first-lactation heifers with genotypes and phenotypes, and another 112 heifers with phenotypes only. Multivariate models were fitted using the different relationships in ASReml software. Estimates of genetic variance were lower based on genomic relationships than using pedigree relationships. Genetic variances from genomic and pedigree relationships were, however, not directly comparable because they apply to different base populations. Standard errors indicated that using the genomic relationships gave more accurate estimates of heritability but equally accurate estimates of genetic correlation. However, the estimates of standard errors were affected by the differences in scale between the 2 relationship matrices, causing differences in values of the genetic parameters. The bootstrapping results (with genetic parameters at the same level), confirmed that both heritability and genetic correlations were estimated more accurately with genomic relationships in comparison with using the pedigree relationships. Animals without genotype were included in the analysis by merging genomic and pedigree relationships. This allowed all phenotypes to be used, including those from non-genotyped animals. This combination of genomic and pedigree relationships gave the most accurate estimates of genetic variance. When a small data set is available it might be more advantageous for the estimation of genetic parameters to genotype existing animals, rather than collecting more phenotypes.
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