Estimation of genetic variation in residual variance in female and male broiler chickens

Abstract

In breeding programs, robustness of animals and uniformity of end product can be improved by exploiting genetic variation in residual variance. Residual variance can be defined as environmental variance after accounting for all identifiable effects. The aims of this study were to estimate genetic variance in residual variance of body weight, and to estimate genetic correlations between body weight itself and its residual variance and between female and male residual variance for broilers. The data sets comprised 26 972 female and 24 407 male body weight records. Variance components were estimated with ASREML. Estimates of the heritability of residual variance were in the range 0.029 (s.e. 5 0.003) to 0.047 (s.e. 5 0.004). The genetic coefficients of variation were high, between 0.35 and 0.57. Heritabilities were higher in females than in males. Accounting for heterogeneous residual variance increased the heritabilities for body weight as well. Genetic correlations between body weight and its residual variance were 20.41 (s.e. 5 0.032) and 20.45 (s.e. 5 0.040), respectively, in females and males. The genetic correlation between female and male residual variance was 0.11 (s.e. 5 0.089), indicating that female and male residual variance are different traits. Results indicate good opportunities to simultaneously increase the mean and improve uniformity of body weight of broilers by selection.

Genetic analysis of environmental variation

“…In this analysis, the strong assumption is made that there are no systematic environmental effects that influence the within-family variance, although heterogeneity of environmental or residual variance has been observed in many situations. The method used by Rowe et al (2006) gave upwardly biased estimates of genetic variance in V E of broiler body weights in the data of Mulder et al (2009), as the records spanned a long time period. More advanced methods have been developed that are aimed at reducing such bias (e.g.…”

“…More advanced methods have been developed that are aimed at reducing such bias (e.g. SanCristobal-Gaudy et al, 1998Sorensen & Waagepetersen, 2003;Mulder et al, 2009;Ro¨nnega˚rd et al, 2010). SanCristobal-Gaudy et al (1998) developed an EM-REML algorithm using expectationmaximisation and incorporating a structural model on the residual variance.…”

“…The DHGLM algorithm can be implemented in ASREML (Gilmour et al, 2006), but estimation of the genetic correlation between effects for mean and residual variance is not possible with the current algorithm (Ro¨nnega˚rd et al, 2010). Although less appealing in theory than GLM, the non-normality of squared residuals can be resolved by appropriate transformations (Mulder et al, 2009). …”

Breeding for robustness: the role of cortisol

“…This is a difficult endeavour and heritability of the character is low. Sensitivity to the environment may also contribute to the environmental variance of a trait, which has been shown to be under genetic control (SanCristobal-Gaudy et al, 2001;Sorensen and Waagepetersen, 2003;Ros et al, 2004;Mulder et al, 2007 and2008;Mulder et al, 2009). The reduction of trait variance by genetic selection is also known as canalizing selection or canalization (SanCristobal-Gaudy et al, 1998;Bolet et al, 2007;Garreau et al, 2008;Bodin et al, 2010).…”

Identification of differential duodenal gene expression levels and microbiota abundance correlated with differences in energy utilisation in chickens

“…Poor flock uniformity results in management problems, delayed growth, poor feed conversion ratios and rejected carcasses (Toudic 2006). Improvements in flock uniformity could increase the proportion of birds that reach their target weight within a given time, and therefore reduce numbers of birds falling outside the size standards set for automated processing-plant equipment (Bedford 2001), and benefit production efficiency (Mulder et al 2009).…”