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Estimation of additive and dominance genetic variance components for female fertility traits in Iranian Holstein cows

Published online by Cambridge University Press:  04 July 2018

H. Ghiasi ,
R. Abdollahi-Arpanahi ,
M. Razmkabir ,
M. Khaldari  and
R. Taherkhani
H. Ghiasi*
Affiliation:
Department of Animal Science, Faculty of Agricultural Science, Payame Noor University, Tehran, Iran
R. Abdollahi-Arpanahi
Affiliation:
Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, 465 Pakdasht, Iran
M. Razmkabir
Affiliation:
Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran
M. Khaldari
Affiliation:
Department of Animal Science, Faculty of Agriculture, Lorestan University, PO Box 465, 68137-1713, Khorram-Abad, Iran
R. Taherkhani
Affiliation:
Department of Animal Science, Faculty of Agricultural Science, Payame Noor University, Tehran, Iran
*
Author for correspondence: H. Ghiasi, E-mail: ghiasei@gmail.com
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Abstract

The aim of the current study was to estimate additive and dominance genetic variance components for days from calving to first service (DFS), a number of services to conception (NSC) and days open (DO). Data consisted of 25 518 fertility records from first parity dairy cows collected from 15 large Holstein herds of Iran. To estimate the variance components, two models, one including only additive genetic effects and another fitting both additive and dominance genetic effects together, were used. The additive and dominance relationship matrices were constructed using pedigree data. The estimated heritability for DFS, NSC and DO were 0.068, 0.035 and 0.067, respectively. The differences between estimated heritability using the additive genetic and additive-dominance genetic models were negligible regardless of the trait under study. The estimated dominance variance was larger than the estimated additive genetic variance. The ratio of dominance variance to phenotypic variance was 0.260, 0.231 and 0.196 for DFS, NSC and DO, respectively. Akaike's information criteria indicated that the model fitting both additive and dominance genetic effects is the best model for analysing DFS, NSC and DO. Spearman's rank correlations between the predicted breeding values (BV) from additive and additive-dominance models were high (0.99). Therefore, ranking of the animals based on predicted BVs was the same in both models. The results of the current study confirmed the importance of taking dominance variance into account in the genetic evaluation of dairy cows.

Keywords

Dairy cowdominance variancefertilitynon-additive
Type
Animal Research Paper
Information
The Journal of Agricultural Science , Volume 156 , Issue 4 , May 2018 , pp. 565 - 569
Copyright
Copyright © Cambridge University Press 2018 

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