|Title||Genomic variation in dairy cattle - Identification and use|
|Source||Wageningen University. Promotor(en): Johan van Arendonk, co-promotor(en): Henk Bovenhuis. - [S.l.] : S.n. - ISBN 9789085040095|
Animal Breeding and Genomics
|Publication type||Dissertation, internally prepared|
|Keyword(s)||melkvee - genomen - genetische variatie - kwantitatieve kenmerken - loci - melkproductie - bouw (dier) - pleiotropie - genetische verbetering - genetische merkers - dierveredeling - moleculaire genetica - dairy cattle - genomes - genetic variation - quantitative traits - loci - milk production - conformation - pleiotropy - genetic improvement - genetic markers - animal breeding - molecular genetics|
|Categories||Cattle / Races, Selection, Genetics / Molecular Genetics|
|Abstract||The development of molecular techniques has offered possibilities to identify quantitative trait loci (QTL). Studies in dairy cattle have mainly focused on milk production traits. This thesis first gives an overview of the main identified QTL for milk production traits. Subsequently, a study to detect QTL affecting 27 conformation traits and functional traits was performed. A granddaughter design consisting of 20 Holstein-Friesian grandsires and 833 sons was analyzed by multi-marker regression. This across-family analysis suggested the presence of 61 QTL. Ten of these QTL exceeded the genomewise significance threshold. These were mainly QTL affecting body size traits and udder conformation traits.
When QTL-information is used to select for a certain trait, genetic progress in other traits may be influenced as well, due to pleiotropic effects of QTL, or due to closely linked QTL. A method was developed to identify regions affecting multiple traits. The method is based on the covariance between marker contrasts from single-trait regression analysis for different traits. Application of this method to data on fifteen traits (milk production, udder conformation, udder health and fertility traits) in our granddaughter design resulted in 59 multiple trait quantitative trait regions (MQR). Most MQR were found on BTA 6, 13, 14, 19, 22, 23 and 25.
QTL-information can be used in breeding schemes (marker-assisted selection, MAS) to increase the rate of genetic improvement. A number of multi-stage dairy cattle breeding schemes was evaluated, studying the impact of increased preselection using QTL-information. Response in multi-stage MAS-schemes was 4.5% to 31.3% higher than response in corresponding schemes without QTL-information. In some of the MAS-schemes with a reduced number of progeny tested bulls, genetic progress was identical to or higher than genetic progress in the original schemes. The results indicate opportunities to improve current breeding schemes. The gains depend on the amount of genomic variation explained by QTL.
Currently available pedigrees and methods offer excellent opportunities to identify more QTL, thus increasing the fraction of the genomic variation explained by QTL. New initiatives, like sequencing the bovine genome, will further facilitate the identification of genomic variation, and its use.