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Milk progesterone measures to improve genomic selection for fertility in dairy cows

Tenghe, Amabel M. M. (2017). Milk progesterone measures to improve genomic selection for fertility in dairy cows. Diss. (sammanfattning/summary) Sweden : Sveriges lantbruksuniv., Acta Universitatis agriculturae Sueciae, 1652-6880 ; 2017:37
ISBN 978-91-576-8847-7
eISBN 978-91-576-8848-4
[Doctoral thesis]

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Abstract

Improved reproductive performance has a substantial benefit for the overall profitability of dairy cattle farming by decreasing insemination and veterinary treatment costs, shortening calving intervals, and lowering the rate of involuntary culling. Unfortunately, the low heritability of classical fertility traits derived from calving and insemination data makes genetic improvement by traditional animal breeding slow. Therefore, there is an interest in finding novel measures of fertility that have a higher heritability or using genomic information to aid genetic selection for fertility. The overall objective of this thesis was to explore the use of milk progesterone (P4) records and genomic information to improve selection for fertility in dairy cows. In a first step, the use of in-line milk progesterone records to define endocrine fertility traits was investigated, and genetic parameters estimated. Several defined endocrine fertility traits were heritable, and showed a reasonable repeatability. Also, the genetic correlation of milk production traits with endocrine fertility traits were considerably lower than the correlations of milk production with classical fertility traits. In the next step 17 quantitative trait loci (QTL) associated with endocrine fertility traits, were identified on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25 in a genome-wide association study with single nucleotide polymorphisms. Further, fine-mapping of target regions on BTA 2 and 3, identified several associated variants and potential candidate genes underlying endocrine fertility traits. Subsequently, the optimal use of endocrine fertility traits in genomic evaluations was investigated; using empirical and theoretical predictions for single-trait models, I showed that endocrine fertility traits have more predictive ability than classical fertility traits. The accuracy of genomic prediction was also substantially improved when endocrine and classical fertility traits were combined in multi-trait genomic prediction. Finally, using deterministic predictions, the potential accuracy of multi-trait genomic selection when combining a cow training population measured for the endocrine trait commencement of luteal activity (C-LA), with a training population of bulls with daughter observations for a classical fertility trait was investigated. Results showed that for prediction of fertility, there is no benefit of investing in a cow training population when the breeding goal is based on classical fertility traits. However, when considering a more biological breeding goal for fertility like C-LA, accuracy is substantially improved when endocrine traits are available from a limited number of farms.

Authors/Creators:Tenghe, Amabel M. M.
Title:Milk progesterone measures to improve genomic selection for fertility in dairy cows
Series/Journal:Acta Universitatis agriculturae Sueciae (1652-6880)
Year of publishing :2017
Depositing date:5 April 2017
Volume:2017:37
Number of Pages:56
Papers/manuscripts:
NumberReferences
IA.M.M. Tenghe, B. Berglund, R.F. Veerkamp, and D.J. de Koning. 2016. Opportunities for genomic prediction for fertility using endocrine and classical fertility traits in dairy cattle. J. Anim. Sci.
IIA.M.M. Tenghe, A.C. Bouwman, B. Berglund, E. Strandberg, D.J. de Koning, and R.F. Veerkamp. 2016. Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle. J. Dairy Sci. 99:5470–5485
IIIA.M.M. Tenghe, A.C. Bouwman, B. Berglund, E. Strandberg, J.Y. Blom, and R.F. Veerkamp. 2015. Estimating genetic parameters for fertility in dairy cows from in-line milk progesterone profiles. J. Dairy Sci. 98:5763–73
IVA.M.M. Tenghe, A.C. Bouwman, B. Berglund, D.J. de Koning and R.F. Veerkamp. Improving accuracy of bulls ‘predicted genomic breeding values for fertility using daughters’ milk progesterone profiles (Submitted to Journal of Dairy Science)
Place of Publication:Sweden
Publisher:Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences
ISBN for printed version:978-91-576-8847-7
ISBN for electronic version:978-91-576-8848-4
ISSN:1652-6880
Language:English
Publication Type:Doctoral thesis
Full Text Status:Public
Agris subject categories.:L Animal production > L10 Animal genetics and breeding
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 402 Animal and Dairy Science > Animal and Dairy Science.
Agrovoc terms:dairy cattle, progesterone, fertility, animal breeding, genomic maps
Keywords:in-line milk progesterone, diary cow, fertility, genetic parameters
URN:NBN:urn:nbn:se:slu:epsilon-e-4085
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-4085
ID Code:14227
Faculty:VH - Faculty of Veterinary Medicine and Animal Science
Department:(VH) > Dept. of Animal Breeding and Genetics
External funders:European Commission
Deposited By: Miss Amabel M. M. Tenghe
Deposited On:06 Apr 2017 09:20
Metadata Last Modified:06 Apr 2017 09:20

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