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 372473
Title Identification Of Genes Involved In Milk Composition
Author(s) Visker, M.H.P.W.; Koks, P.D.; Schennink, A.; Poel, J.J. van der; Groenen, M.A.M.; Arendonk, J.A.M. van
Department(s) Animal Breeding and Genetics
Publication type Abstract in scientific journal or proceedings
Publication year 2008
Abstract The Dutch Milk Genomics Initiative aims at the identification of genes involved in natural genetic variation in milk properties, in particular milk-fat and milk-protein composition. DNA and milk samples have been collected from a population of 2000 Holstein Friesian cows in first lactation: 1000 cows descend from five proven sires and 1000 cows descend from 50 young bulls. This design enables estimation of genetic parameters (heritabilities and genetic correlations) as well as detection of QTLs and finemapping. Milk samples have been analyzed in detail, resulting in routine milk recording data (milk, fat and protein yield, fat and protein percentage), protein composition (all major milk proteins), and fat composition (individual fatty acids). Identification of genes is performed simultaneously via a candidate-gene and a genome-wide approach. DGAT1 was identified as a candidate-gene, because of its effects on milk-fat percentage. Our study reveals that the K232A polymorphism in DGAT1 has significant effects on fat composition as well. For the whole genome scan the selection of 1000 Holstein Friesian cows descending from five proven sires has been genotyped for 1500 SNPs. Genetic maps have been made, facilitating the ongoing identification of QTLs for a large number of milk traits. Our results will enable marker assisted differentiation and maker assisted selection by the breeding and dairy industry, in order to optimize milk quality and to develop innovative dairy products.
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