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Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Joint estimation of (co) variance components and breeding values for mean and dispersion of days from calving to first service in Holstein cow

Heydar Ghiasi A D and Majbritt Felleki B C
+ Author Affiliations
- Author Affiliations

A Department of Animal Science, Faculty of Agricultural Science, Payame Noor University, Tehran, Iran.

B Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden.

C The Beijer Laboratories in Uppsala, Department of Animal Nutrition and Management, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden.

D Corresponding author. Email: ghiasi@ut.ac.ir

Animal Production Science 57(4) 760-766 https://doi.org/10.1071/AN15643
Submitted: 22 September 2015  Accepted: 11 January 2016   Published: 23 May 2016

Abstract

The present study explored the possibility of selection for uniformity of days from calving to first service (DFS) in dairy cattle. A double hierarchical generalised linear model with an iterative reweighted least-squares algorithm was used to estimate covariance components for the mean and dispersion of DFS. Data included the records of 27 113 Iranian Holstein cows (parity, 1–6) in 15 herds from 1981 to 2007. The estimated additive genetic variance for the mean and dispersion were 32.25 and 0.0139; both of these values had low standard errors. The genetic standard deviation for dispersion of DFS was 0.117, indicating that decreasing the estimated breeding value of dispersion by one genetic standard deviation can increase the uniformity by 12%. A strong positive genetic correlation (0.689) was obtained between the mean and dispersion of DFS. This genetic correlation is favourable since one of the aims of breeding is to simultaneously decrease the mean and increase the uniformity of DFS. The Spearman rank correlations between estimated breeding values in the mean and dispersion for sires with a different number of daughter observations were 0.907. In the studied population, the genetic trend in the mean of DFS was significant and favourable (–0.063 days/year), but the genetic trend in the dispersion of DFS was not significantly different from zero. The results obtained in the present study indicated that the mean and uniformity of DFS can simultaneously be improved in dairy cows.

Additional keywords: fertility, hierarchical model, uniformity.


References

Bagnato A, Oltenacu P (1994) Phenotypic evaluation of fertility traits and their association with milk production of Italian Friesian cattle. Journal of Dairy Science 77, 874–882.
Phenotypic evaluation of fertility traits and their association with milk production of Italian Friesian cattle.Crossref | GoogleScholarGoogle Scholar | 8169295PubMed |

Bodin L, Garcia M, Saleil G, Bolet G, Garreau H (2010) Results of 10 generations of canalising selection for rabbit birth weight. In ‘The 9th world congress on genetics applied to livestock production’, Leipzig, Germany. (Ed. Gesellschaft fur Tierzuchtwissenschaften eV (German Society for Animal Science)) pp. 1–4. (WCGALP Publishing)

Falconer DS, Robertson A (1956) Selection for environmental variability of body size in mice. Zeitschriftfür induktive Abstammungs-und Vererbungslehre 87, 385–391.

Felleki M, Lee D, Lee Y, Gilmour AR, Rönnegård L (2012) Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models. Genetical Research 94, 307–317.
Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models.Crossref | GoogleScholarGoogle Scholar |

Garreau H, Bolet G, Larzul C, Robert-Granie C, Saleil G, SanCristobal M, Bodin L (2008) Results of four generations of a canalising selection for rabbit birth weight. Livestock Science 119, 55–62.
Results of four generations of a canalising selection for rabbit birth weight.Crossref | GoogleScholarGoogle Scholar |

Ghiasi H (2011) Compression effect of different selection strategy on reproductive performance in Iranian Holstein Cows. PhD thesis, University of Tehran, Iran.

Ghiasi H, Pakdel A, Nejati-Javaremi A, Mehrabani-Yeganeh H, Honarvar M, González-Recio O, Carabaño MJ, Alenda R (2011) Genetic variance components for female fertility in Iranian Holstein cows. Livestock Science 139, 277–280.
Genetic variance components for female fertility in Iranian Holstein cows.Crossref | GoogleScholarGoogle Scholar |

Gilmour AR, Gogel BJ, Cullis BR, Welham SJ, Thompson R (2014) ‘ASReml user guide release 4.’ (VSN International: Hemel Hempstead, UK) Available at http://cdn.vsni.co.uk/downloads/asreml/release4/UserGuideFunctional.pdf [Verified 4 August 2014]

González-Recio O, Alenda R (2005) Genetic parameters for female fertility traits and a fertility index in Spanish dairy cattle. Journal of Dairy Science 88, 3282–3289.
Genetic parameters for female fertility traits and a fertility index in Spanish dairy cattle.Crossref | GoogleScholarGoogle Scholar | 16107418PubMed |

González-Recio O, Pérez-Cabal MA, Alenda R (2004) Economic value of female fertility and its relationship with profit in Spanish dairy cattle. Journal of Dairy Science 87, 3053–3061.
Economic value of female fertility and its relationship with profit in Spanish dairy cattle.Crossref | GoogleScholarGoogle Scholar | 15375068PubMed |

Gredler B, Fürst C, Sölkner J (2007) Analysis of new fertility traits for the joint genetic evaluation in Austria and Germany. Interbull Bulletin 37, 152–155.

Gutiérrez JP, Nieto B, Piqueras P, Ibáñez N, Salgado C (2006) Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice. Genetics, Selection, Evolution 38, 445–462.
Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice.Crossref | GoogleScholarGoogle Scholar | 16954039PubMed |

Gutiérrez JP, Varona L, Pun A, Morante R, Burgos A, Cervantes I, Pérez-Cabal MA (2011) Genetic parameters for growth of fiber diameter in alpacas. Journal of Animal Science 89, 2310–2315.
Genetic parameters for growth of fiber diameter in alpacas.Crossref | GoogleScholarGoogle Scholar | 21357447PubMed |

Hill WG, Mulder HA (2010) Genetic analysis of environmental variation. Genetics Research 92, 381–395.
Genetic analysis of environmental variation.Crossref | GoogleScholarGoogle Scholar | 21429270PubMed |

Ibáñez-Escriche N, Garcia M, Sorensen D (2010) GSEVMv.2: MCMC software to analyze genetically structured environmental variance models. Journal of Animal Breeding and Genetics 127, 249–251.
GSEVMv.2: MCMC software to analyze genetically structured environmental variance models.Crossref | GoogleScholarGoogle Scholar | 20536643PubMed |

James AD, Esslemont RJ (1979) The economics of calving intervals. Animal Production 29, 157–162.
The economics of calving intervals.Crossref | GoogleScholarGoogle Scholar |

Jamrozik J, Fatehi J, Kistemaker GJ, Schaeffer LR (2005) Estimates of genetic parameters for Canadian Holstein female reproduction traits. Journal of Dairy Science 88, 2199–2208.
Estimates of genetic parameters for Canadian Holstein female reproduction traits.Crossref | GoogleScholarGoogle Scholar | 15905449PubMed |

Kaufman PK, Enfield FD, Comstock RE (1977) Stabilizing selection for pupa weight in Triboliumcastaneum. Genetics 87, 327–341.

Larzul C, Le Roy P, Tribout T, Gogue J, SanCristobal M (2006) Canalizing selection on ultimate PH in pigs: consequences on meat quality. In ‘Proceedings of the 8th world congress on cenetics applied to livestock production’, Belo Horizonte, Brasil. Communication 13-09. (WCGALP Publishing: Belo Horizonte, Brazil)

Lee Y, Nelder JA (2006) Double hierarchical generalized linear models (with discussion). Journal of the Royal Statistical Society. Series A (General) 55, 139–185.
Double hierarchical generalized linear models (with discussion).Crossref | GoogleScholarGoogle Scholar | [Statistics in Society].

Mackay TF, Lyman RF (2005) Drosophila bristles and the nature of quantitative genetic variation. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 360, 1513–1527.
Drosophila bristles and the nature of quantitative genetic variation.Crossref | GoogleScholarGoogle Scholar | 16108138PubMed |

Martinez Alvaro M (2014) Divergent selection for residual variance of litter size in rabbits. MSc Thesis, UniversitatPolitècnica de València, Spain.

Morante R, Goyache F, Burgos A, Cervantes I, Pérez-Cabal MA, Gutiérrez JP (2009) Genetic improvement for alpaca fibre production in the Peruvian Altiplano: the Pacomarca experience. Animal Genetic Resources Information 45, 37–43.

Mulder HA, Bijma P, Hill WG (2008) Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance. Genetics, Selection, Evolution 40, 37–60.

Mulder H, Hill W, Vereijken A, Veerkamp R (2009) Estimation of genetic variation in residual variance in female and male broiler chickens. Animal 3, 1673–1680.
Estimation of genetic variation in residual variance in female and male broiler chickens.Crossref | GoogleScholarGoogle Scholar | 22443551PubMed |

Neves H, Carvalheiro R, Roso V, Queiroz S (2011) Genetic variability of residual variance of production traits in Nellore beef cattle. Livestock Science 142, 164–169.
Genetic variability of residual variance of production traits in Nellore beef cattle.Crossref | GoogleScholarGoogle Scholar |

Neves HH, Carvalheiro R, Queiroz SA (2012) Genetic and environmental heterogeneity of residual variance of weight traits in Nellore beef cattle. Genetics, Selection, Evolution 44, 19–30.
Genetic and environmental heterogeneity of residual variance of weight traits in Nellore beef cattle.Crossref | GoogleScholarGoogle Scholar | 22672564PubMed |

Odde K (1990) A review of synchronization of estrus in postpartum cattle. Journal of Animal Science 68, 817–830.

Pérez-Cabal MA, Cervantes I, Morante R, Burgos A, Goyache F, Gutiérrez JP (2010) Analysis of the existence of major genes affecting alpaca fiber traits. Journal of Animal Science 88, 3783–3788.
Analysis of the existence of major genes affecting alpaca fiber traits.Crossref | GoogleScholarGoogle Scholar | 20656969PubMed |

Pun A, Cervantes I, Nieto B, Salgado C, Pérez‐Cabal MA, Ibáñez‐Escriche N, Gutiérrez JP (2013) Genetic parameters for birth weight environmental variability in mice. Journal of Animal Breeding and Genetics 130, 404–414.

R Core Team (2015) ‘R: a language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna) Available at http://www.R-project.org/ [Verified 10 May 2015]

Rendel JM, Sheldon BL, Finlay DE (1966) Selection for canalization of the scute phenotype. II. American Naturalist 100, 13–31.
Selection for canalization of the scute phenotype. II.Crossref | GoogleScholarGoogle Scholar |

Ribeiro ES, Galvão KN, Thatcher WW, Santos JEP (2012) Economic aspects of applying reproductive technologies to dairy herds. Animal Reproduction Science 9, 370–387.

Rönnegård L, Valdar W (2012) Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability. BMC Genetics 13, 63–69.
Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability.Crossref | GoogleScholarGoogle Scholar | 22827487PubMed |

Rönnegård L, Felleki M, Fikse F, Mulder HA, Strandberg E (2010) Genetic heterogeneity of residual variance-estimation of variance components using double hierarchical generalized linear models. Genetics, Selection, Evolution 42, 8–17.
Genetic heterogeneity of residual variance-estimation of variance components using double hierarchical generalized linear models.Crossref | GoogleScholarGoogle Scholar | 20302616PubMed |

Rönnegård L, Felleki M, Fikse W, Mulder H, Strandberg E (2013) Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle. Journal of Dairy Science 96, 2627–2636.
Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle.Crossref | GoogleScholarGoogle Scholar | 23415533PubMed |

Rowe SJ, Ian MS, Santiago A, William GH (2006) Genetic heterogeneity of residual variance in broiler chickens. Genetics, Selection, Evolution 38, 617–635.
Genetic heterogeneity of residual variance in broiler chickens.Crossref | GoogleScholarGoogle Scholar | 17129563PubMed |

SanCristobal-Gaudy M, Elsen J, Bodin L, Chevalet C (1998) Prediction of the response to a selection forcanalisation of a continuous trait in animal breeding. Genetics, Selection, Evolution 30, 423–451.
Prediction of the response to a selection forcanalisation of a continuous trait in animal breeding.Crossref | GoogleScholarGoogle Scholar |

Shen X, Pettersson M, Rönnegård L, Carlborg Ö (2012) Inheritance beyond plain heritability: variance-controlling genes in Arabidopsis thaliana. PLOS Genetics 8, e1002839
Inheritance beyond plain heritability: variance-controlling genes in Arabidopsis thaliana.Crossref | GoogleScholarGoogle Scholar | 22876191PubMed |

Sorensen D, Waagepetersen R (2003) Normal linear models with genetically structured residual variance heterogeneity: a case study. Genetical Research 82, 207–222.
Normal linear models with genetically structured residual variance heterogeneity: a case study.Crossref | GoogleScholarGoogle Scholar | 15134199PubMed |

Sørensen P, de los Campos G, Morgante F, Mackay TF, Sorensen D (2015) Genetic control of environmental variation of two quantitative traits of Drosophila melanogaster revealed by whole-genome sequencing. Genetics 201, 487–497.
Genetic control of environmental variation of two quantitative traits of Drosophila melanogaster revealed by whole-genome sequencing.Crossref | GoogleScholarGoogle Scholar | 26269504PubMed |

Venables WN, Ripley BD (2002) ‘Modern applied statistics with S.’ 4th edn. (Springer: New York)

Whitlock MC, Fowler K (1999) The changes in genetic and environmental variance with inbreeding in Drosophila melanogaster. Genetics 152, 345–353.

Yang Y, Christensen OF, Sorensen D (2011) Analysis of a genetically structured variance heterogeneity model using the box–cox transformation. Genetical Research 93, 33–46.
Analysis of a genetically structured variance heterogeneity model using the box–cox transformation.Crossref | GoogleScholarGoogle Scholar |