Sharing reference data and including cows in the reference population improve genomic predictions in Danish Jersey
| Autor: | Peipei Ma, Guosheng Su, G.R. Wiggans, Mogens Sandø Lund, Bernt Guldbrandtsen, U. S. Nielsen, Gert Pedersen Aamand |
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| Rok vydání: | 2016 |
| Předmět: |
Male
0301 basic medicine Jersey cattle Genotype Denmark Population Breeding Biology Best linear unbiased prediction SF1-1100 genomic selection Danish 03 medical and health sciences Animal science reference population Animals Reference population education education.field_of_study Genome reliability Models Genetic 0402 animal and dairy science Reproducibility of Results Percentage point Genomics 04 agricultural and veterinary sciences Reference Standards 040201 dairy & animal science United States language.human_language Animal culture Reference data Fertility Phenotype 030104 developmental biology Linear Models language Cattle Female Animal Science and Zoology Genomic selection |
| Zdroj: | Su, G, Ma, P, Nielsen, U S, Aamand, G P, Wiggans, G, Guldbrandtsen, B & Lund, M S 2016, ' Sharing reference data and including cows in the reference population improve genomic predictions in Danish Jersey ', Animal, vol. 10, no. 6, pp. 1067-1075 . https://doi.org/10.1017/S1751731115001792 Animal, Vol 10, Iss 6, Pp 1067-1075 (2016) |
| ISSN: | 1751-7311 |
| DOI: | 10.1017/s1751731115001792 |
| Popis: | Small reference populations limit the accuracy of genomic prediction in numerically small breeds, such like Danish Jersey. The objective of this study was to investigate two approaches to improve genomic prediction by increasing size of reference population in Danish Jersey. The first approach was to include North American Jersey bulls in Danish Jersey reference population. The second was to genotype cows and use them as reference animals. The validation of genomic prediction was carried out on bulls and cows, respectively. In validation on bulls, about 300 Danish bulls (depending on traits) born in 2005 and later were used as validation data, and the reference populations were: (1) about 1050 Danish bulls, (2) about 1050 Danish bulls and about 1150 US bulls. In validation on cows, about 3000 Danish cows from 87 young half-sib families were used as validation data, and the reference populations were: (1) about 1250 Danish bulls, (2) about 1250 Danish bulls and about 1150 US bulls, (3) about 1250 Danish bulls and about 4800 cows, (4) about 1250 Danish bulls, 1150 US bulls and 4800 Danish cows. Genomic best linear unbiased prediction model was used to predict breeding values. De-regressed proofs were used as response variables. In the validation on bulls for eight traits, the joint DK-US bull reference population led to higher reliability of genomic prediction than the DK bull reference population for six traits, but not for fertility and longevity. Averaged over the eight traits, the gain was 3 percentage points. In the validation on cows for six traits (fertility and longevity were not available), the gain from inclusion of US bull in reference population was 6.6 percentage points in average over the six traits, and the gain from inclusion of cows was 8.2 percentage points. However, the gains from cows and US bulls were not accumulative. The total gain of including both US bulls and Danish cows was 10.5 percentage points. The results indicate that sharing reference data and including cows in reference population are efficient approaches to increase reliability of genomic prediction. Therefore, genomic selection is promising for numerically small population. |
| Databáze: | OpenAIRE |
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