Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance

Abstract

-In some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters, breeding goal, number of progeny per sire and breeding scheme on selection responses in mean and variance when applying index selection. Genetic parameters were obtained from the literature. Economic values for the mean and variance were derived for some standard non-linear profit equations, e.g. for traits with an intermediate optimum. The economic value of variance was in most situations negative, indicating that selection for reduced variance increases profit. Predicted responses in residual variance after one generation of selection were large, in some cases when the number of progeny per sire was at least 50, by more than 10% of the current residual variance. Progeny testing schemes were more efficient than sib-testing schemes in decreasing residual variance. With optimum traits, selection pressure shifts gradually from the mean to the variance when approaching the optimum. Genetic improvement of uniformity is particularly interesting for traits where the current population mean is near an intermediate optimum.heterogeneity of variance / index selection / uniformity / economic value / optimum trait

Genetic analysis of environmental variation

“…and optimum remain fairly constant, the latter if it shows trends or fluctuates. The same patterns in selective advantage for optimum traits can be achieved by deriving economic values for mean and variance (Mulder et al, 2008). Providing the position of the optimum remains constant, the trait mean converges at or close to the optimum, although it can be displaced somewhat by mutation and by a covariance of gene effects on mean and variance.…”

“…In practice, however, analysis and interpretation of data to reveal the genetic variance in heterogeneity is complicated by potential changes in genetic variance caused by selection, which are predictable under infinitesimal model assumptions, but not otherwise (Hill & Zhang, 2004 ;Mulder, 2007 ;Mulder et al, 2008).…”

“…As prediction of breeding values for environmental variance (A v ) can be regarded as predictions for a trait with a low heritability, records on large numbers of relatives are needed to get high accuracy. Selection index theory can be used to predict the accuracy of Aˆv based on family size and relationship (Mulder et al, , 2008, and examples are given in Table 4. Observations on clones, feasible in some plant species, are most effective in realizing high accuracy.…”

“…Observations on clones, feasible in some plant species, are most effective in realizing high accuracy. Half-sib progeny can provide higher accuracy than sibs, and so progeny testing may be more efficient than sib-testing schemes in reducing V E by selection (Mulder et al, 2008).…”

“…Selection for reduced variance is therefore of interest for traits with an optimum, and more generally there is a non-linear profit equation (Mulder et al, 2008). To bring the mean closer to the optimum and decrease the variance around it, selection both on mean and variance is needed.…”