Article (Scientific journals)
Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population
Hess, Melanie; Druet, Tom; Hess, Andrew et al.
2017In Genetics, Selection, Evolution, 49 (1), p. 54
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Abstract :
[en] Fitting covariates representing the number of haplotype alleles rather than single nucleotide polymorphism (SNP) alleles may increase genomic prediction accuracy if linkage disequilibrium between quantitative trait loci and SNPs is inadequate. The objectives of this study were to evaluate the accuracy, bias and computation time of Bayesian genomic prediction methods that fit fixed-length haplotypes or SNPs. Genotypes at 37,740 SNPs that were common to Illumina BovineSNP50 and high-density panels were phased for ~58,000 New Zealand dairy cattle. Females born before 1 June 2008 were used for training, and genomic predictions for milk fat yield (n = 24,823), liveweight (n = 13,283) and somatic cell score (n = 24,864) were validated within breed (predominantly Holstein–Friesian, predominantly Jersey, or admixed KiwiCross) in later-born females. Covariates for haplotype alleles of five lengths (125, 250, 500 kb, 1 or 2 Mb) were generated and rare haplotypes were removed at four thresholds (1, 2, 5 or 10%), resulting in 20 scenarios tested. Genomic predictions fitting covariates for either SNPs or haplotypes were calculated by using BayesA, BayesB or BayesN. This is the first study to quantify the accuracy of genomic prediction using haplotypes across the whole genome in an admixed population.
Disciplines :
Genetics & genetic processes
Animal production & animal husbandry
Author, co-author :
Hess, Melanie
Druet, Tom ;  Université de Liège > Département des productions animales (DPA) > GIGA-R : Génomique animale
Hess, Andrew
Garrick, Dorian
Language :
English
Title :
Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population
Publication date :
2017
Journal title :
Genetics, Selection, Evolution
ISSN :
0999-193X
eISSN :
1297-9686
Publisher :
EDP Sciences, Les Ulis, France
Volume :
49
Issue :
1
Pages :
54
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 04 July 2017

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