Abstract
The objective of this study was to estimate genomic
breeding values for milk yield in crossbred dairy goats.
The research was based on data provided by 2 commercial
goat farms in the UK comprising 590,409 milk yield
records on 14,453 dairy goats kidding between 1987 and
2013. The population was created by crossing 3 breeds:
Alpine, Saanen, and Toggenburg. In each generation
the best performing animals were selected for breeding,
and as a result, a synthetic breed was created. The pedigree
file contained 30,139 individuals, of which 2,799
were founders. The data set contained test-day records
of milk yield, lactation number, farm, age at kidding,
and year and season of kidding. Data on milk composition
was unavailable. In total 1,960 animals were
genotyped with the Illumina 50K caprine chip. Two
methods for estimation of genomic breeding value were
compared—BLUP at the single nucleotide polymorphism
level (BLUP-SNP) and single-step BLUP. The
highest accuracy of 0.61 was obtained with single-step
BLUP, and the lowest (0.36) with BLUP-SNP. Linkage
disequilibrium (r2, the squared correlation of the alleles
at 2 loci) at 50 kb (distance between 2 SNP) was 0.18.
This is the first attempt to implement genomic selection
in UK dairy goats. Results indicate that the single-step
method provides the highest accuracy for populations
with a small number of genotyped individuals, where
the number of genotyped males is low and females are
predominant in the reference population.
Original language | English |
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Pages (from-to) | 3 - 2 |
Journal | Journal of Dairy Science |
Volume | 98 |
Issue number | 11 |
DOIs | |
Publication status | First published - 2015 |
Bibliographical note
1029822Keywords
- Dairy goat
- Milk yield
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Dive into the research topics of 'Estimation of genomic breeding values for milk yield in UK dairy goats'. Together they form a unique fingerprint.Impacts
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Transforming genomic selection in commercial breeding programmes for pigs, dairy goats and poultry
Hickey, J. M. (Participant), Coffey, M. (Participant), Mrode, R. (Participant), Conington, J. (Participant), Woolliams, J. (Participant), Archibald, A. L. (Participant), Tenesa, A. (Participant), Kranis, A. (Participant) & Visscher, P. (Participant)
Impact: Technological
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