Reference : Marker imputation with low-density marker panels in Dutch Holstein cattle.
Scientific journals : Article
Life sciences : Genetics & genetic processes
http://hdl.handle.net/2268/83661
Marker imputation with low-density marker panels in Dutch Holstein cattle.
English
Zhang, Zhiyan [> > > >]
Druet, Tom mailto [Université de Liège - ULg > Département de productions animales > GIGA-R : Génomique animale >]
2010
Journal of Dairy Science
American Dairy Science Association
93
11
5487-94
Yes (verified by ORBi)
International
0022-0302
1525-3198
Champaign
IL
[en] Animals ; Cattle/genetics ; Genetic Linkage ; Genetic Markers/genetics ; Genome-Wide Association Study/methods/veterinary ; Genotype ; Netherlands ; Polymorphism, Single Nucleotide/genetics ; Reproducibility of Results ; Selection, Genetic
[en] The availability of high-density bovine genotyping arrays made implementation of genomic selection possible in dairy cattle. Development of low-density single nucleotide polymorphism (SNP) panels will allow the extension of genomic selection to a larger portion of the population. Prediction of ungenotyped markers, called imputation, is a strategy that allows using the same low-density chips for all traits (and for different breeds). In the present study, we evaluated the accuracy of imputation with low-density genotyping arrays in the Dutch Holstein population. Five different sizes of genotyping arrays were tested, from 384 to 6,000 SNP. According to marker density, the overall allelic imputation error rate obtained with the program DAGPHASE, which relies on linkage disequilibrium and linkage, ranged from 11.7 to 2.0%, and that obtained with the program CHROMIBD, which relies on linkage and the set of all genotyped ancestors, ranged from 10.7 to 3.3%. However, imputation efficiency was influenced by the relationship between low-density and high-density genotyped animals. Animals with both parents genotyped had particularly low imputation error rates: <1% with 1,500 SNP or more. In summary, missing marker alleles can be predicted with 3 to 4% errors with approximately 1 SNP/Mb (approximately 3,000 markers). The CHROMIBD program proved more efficient than DAGPHASE only at lower marker densities or when several genotyped ancestors were available. Future studies are required to measure the effect of these imputation error rates on accuracy of genomic selection with low-density SNP panels.
http://hdl.handle.net/2268/83661
10.3168/jds.2010-3501
Copyright (c) 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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