Estimating the purebred–crossbred genetic correlation for uniformity of eggshell color in laying hens

Springer Science and Business Media LLC - Tập 48 - Trang 1-13 - 2016
Han A. Mulder1, Jeroen Visscher2, Julien Fablet3
1Animal Breeding and Genomics Centre, Wageningen University & Research, Wageningen, The Netherlands
2Institut de Sélection Animale B.V., Hendrix Genetics, Boxmeer, The Netherlands
3Institut de Sélection Animale S.A.S., Hendrix Genetics, Ploufragan, France

Tóm tắt

Uniformity of eggs is an important aspect for retailers because consumers prefer homogeneous products. One of these characteristics is the color of the eggshell, especially for brown eggs. Existence of a genetic component in environmental variance would enable selection for uniformity of eggshell color. Therefore, the objective of this study was to quantify the genetic variance in environmental variance of eggshell color in purebred and crossbred laying hens, to estimate the genetic correlation between environmental variance of eggshell color in purebred and crossbred laying hens and to estimate genetic correlations between environmental variance at different times of the laying period. We analyzed 167,651 and 79,345 eggshell color records of purebred and crossbred laying hens, respectively. The purebred and crossbred laying hens originated mostly from the same sires. Since eggshell color records of crossbred laying hens were collected per cage, these records could be related only to cage and sire family. A double hierarchical generalized linear sire model was used to estimate the genetic variance of the mean of eggshell color and its environmental variance. Approximate standard errors for heritability and the genetic coefficient of variation for environmental variance were derived. The genetic variance in environmental variance at the log scale was equal to 0.077 and 0.067, for purebred and crossbred laying hens, respectively. The genetic coefficient of variation for environmental variance was equal to 0.28 and 0.26, for purebred and crossbred laying hens, respectively. A genetic correlation of 0.70 was found between purebred and crossbred environmental variance of eggshell color, which indicates that there is some reranking of sires for environmental variance of eggshell color in purebred and crossbred laying hens. Genetic correlations between environmental variance of eggshell color in different laying periods were generally higher than 0.85, except between early laying and mid or late laying periods. Our results indicate that genetic selection can be efficient to improve uniformity of eggshell color in purebreds and crossbreds, ideally by applying combined crossbred and purebred selection. This methodology can be used to estimate genetic correlations between purebred and crossbred lines for uniformity of other traits and species.

Tài liệu tham khảo

Hennessy DA. Slaughterhouse rules: animal uniformity and regulating for food safety in meat packing. Am J Agric Econ. 2005;87:600–9. Wolc A, Arango J, Jankowski T, Dunn I, Settar P, Fulton JE, et al. Genome-wide association study for egg production and quality in layer chickens. J Anim Breed Genet. 2014;131:173–82. Zhang LC, Ning ZH, Xu GY, Hou ZC, Yang N. Heritabilities and genetic and phenotypic correlations of egg quality traits in brown-egg dwarf layers. Poult Sci. 2005;84:1209–13. Hill WG, Mulder HA. Genetic analysis of environmental variation. Genet Res. 2010;92:381–95. Sell-Kubiak E, Bijma P, Knol EF, Mulder HA. Comparison of methods to study uniformity of traits: application to birth weight in in pigs. J Anim Sci. 2015;93:900–11. Kapell DNRG, Ashworth CJ, Knap PW, Roehe R. Genetic parameters for piglet survival, litter size and birth weight or its variation within litter in sire and dam lines using Bayesian analysis. Livest Sci. 2011;135:215–24. Wolc A, Arango J, Settar P, Fulton JE, O’Sullivan NP, Preisinger R, et al. Genome-wide association analysis and genetic architecture of egg weight and egg uniformity in layer chickens. Anim Genet. 2012;43(Suppl 1):87–96. Wei M, van der Werf JHJ. Genetic correlation and heritabilities for purebred and crossbred performance in poultry egg production traits. J Anim Sci. 1995;73:2220–6. Besbes B, Gibson JP. Genetic variation of egg production traits in purebred and crossbred laying hens. Anim Sci. 1999;68:433–9. Hidalgo AM, Bastiaansen JWM, Lopes MS, Harlizius B, Groenen MAM, de Koning DJ. Accuracy of predicted genomic breeding values in purebred and crossbred Pigs. G3 (Bethesda). 2015;5:1575–83. Habier D, Götz KU, Dempfle L. Estimation of genetic parameters on test stations using purebred and crossbred progeny of sires of the Bavarian Pietrain. Livest Sci. 2007;107:142–51. Serenius T, Stalder KJ, Puonti M. Impact of dominance effects on sow longevity. J Anim Breed Genet. 2006;123:355–61. Wei M, van der Steen HAM. Comparison of reciprocal recurrent selection with pure-line selection systems in animal breeding (a review). Anim Breed Abstr. 1991;59:281–98. Bijma P, Bastiaansen JWM. Standard error of the genetic correlation: how much data do we need to estimate a purebred–crossbred genetic correlation? Genet Sel Evol. 2014;46:79. Cavero D, Schmutz M, Icken W, Preisinger R. Attractive eggshell color as a breeding goal. Lohmann Inf. 2012;47:15–21. Rönnegård L, Felleki M, Fikse F, Mulder HA, Strandberg E. Genetic heterogeneity of residual variance: estimation of variance components using double hierarchical generalized linear models. Genet Sel Evol. 2010;42:8. Felleki M, Lee D, Lee Y, Gilmour AR, Rönnegård L. Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models. Genet Res (Camb). 2012;94:307–17. Mulder HA, Rönnegård L, Fikse WF, Veerkamp RF, Strandberg E. Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models. Genet Sel Evol. 2013;45:23. Hoaglin DC, Welsh RE. The hat matrix in regression and ANOVA. Am Stat. 1978;32:17–22. Mulder HA, Bijma P, Hill WG. Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance. Genetics. 2007;175:1895–910. Sae-Lim P, Kause A, Janhunen M, Vehvilainen H, Koskinen H, Gjerde B, et al. Genetic (co)variance of rainbow trout (Oncorhynchus mykiss) body weight and its uniformity across production environments. Genet Sel Evol. 2015;47:46. Felleki M, Lundeheim N. Genetic control of residual variance in teat number in pigs. Proc Assoc Adv Anim Breed Genet. 2012;20:538–41. Lynch M, Walsh B. Genetics and analysis of quantitative traits. Sunderland: Sinauer Associates, Inc., Publishers; 1998. Sell-Kubiak E, Duijvesteijn N, Lopes MS, Janss LLG, Knol EF, Bijma P, et al. Genome-wide association study reveals novel loci for litter size and its variability in a Large White pig population. BMC Genomics. 2015;16:1049. Lee Y, Nelder JA. Double hierarchical generalized linear models. Appl Stat. 2006;55:139–85. Wolc A, Arango J, Settar P, Fulton JE, O’Sullivan NP, Preisinger R, et al. Analysis of egg production in layer chickens using a random regression model with genomic relationships. Poult Sci. 2013;92:1486–91. Hansen TF, Pelabon C, Houle D. Heritability is not evolvability. Evol Biol. 2011;38:258–77. Houle D. Comparing evolvability and variability of quantitative traits. Genetics. 1992;130:195–204. Schaeffer LR, Dekkers JCM. Random regressions in animal models for test-day production in dairy cattle. In Proceedings of the 5th world congress on genetics applied to livestock production, 7–12 Aug 1994; Guelph. 1994;18:443–6. Meyer K, Kirkpatrick M. Up hill, down dale: quantitative genetics of curvaceous traits. Philos Trans R Soc B Biol Sci. 2005;360:1443–55. Ibanez-Escriche N, Varona L, Sorensen D, Noguera JL. A study of heterogeneity of environmental variance for slaughter weight in pigs. Animal. 2008;2:19–26. Bijma P, Van Arendonk JAM. Maximising genetic gain for the sire line of a crossbreeding scheme utilising both purebred and crossbred information. Anim Sci. 1998;66:529–42. Mulder HA, Bijma P, Hill WG. Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance. Genet Sel Evol. 2008;40:37–59.