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Accuracy of genomic...
Accuracy of genomic breeding values from endocrine and traditional fertility traits in dairy cows
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- Tenghe, Amabel (författare)
- Livestock Research, Wageningen UR,Wageningen University
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- Berglund, Britt (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för husdjursgenetik (HGEN),Department of Animal Breeding and Genetics
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- De Koning, Dirk-Jan (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för husdjursgenetik (HGEN),Department of Animal Breeding and Genetics
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(creator_code:org_t)
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- ISBN 9789086862849
- 2016
- 2016
- Engelska.
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Ingår i: Annual meeting of the European Association for Animal Production. - 1382-6077. ; 22, s. 287-287
- Relaterad länk:
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https://res.slu.se/i...
Abstract
Ämnesord
Stäng
- Endocrine fertility traits defined from progesterone concentration levels in milk have been suggested as alternative indicators for fertility in dairy cows because they are less biased by farm management decisions and more directly reflect a cow's reproductive physiology than traditional fertility traits. With the aim of enabling the use of endocrine fertility traits in genomic selection, we evaluated the added value (accuracy) of using endocrine fertility traits in genomic prediction of fertility. Endocrine and traditional fertility records were available for 2,447 Holstein cows with 5,339 lactations from Ireland, the Netherlands, Sweden, and the United Kingdom. The endocrine traits were commencement of luteal activity (CLA) and proportion of samples in luteal activity (PLA), and the traditional trait was calving to first service (CFS). Genomic estimated breeding values (GEBV) were derived using genomic BLUP in univariate and bivariate analysis, with 85,485 single nucleotide polymorphisms. The accuracies of GEBV were evaluated by 5-fold cross-validation. Accuracies of GEBV ranged from 0.04 to 0.15 across all traits for univariate analysis, and 0.02 to 0.49 for bivariate analysis, indicating low to modest predictive ability. Improved accuracies of GEBV for CFS were achieved in bivariate analysis where endocrine and traditional fertility traits were used, and there was a better predictive ability of CFS in bivariate analysis with CLA than with PLA. This first study on genomic predictions for fertility using endocrine traits suggests some improvement over using only the traditional traits. Further studies with larger training populations may show bigger improvements.
Ämnesord
- LANTBRUKSVETENSKAPER -- Bioteknologi med applikationer på växter och djur -- Genetik och förädling inom lantbruksvetenskap (hsv//swe)
- AGRICULTURAL SCIENCES -- Agricultural Biotechnology -- Genetics and Breeding in Agricultural Sciences (hsv//eng)
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