Managing the risk of comparing estimated breeding values across flocks or herds through connectedness: a review and application

Abstract

Comparing predicted breeding values (BV) among animals in different management units (e.g. flocks, herds) is challenging if units have different genetic means. Unbiased estimates of differences in BV may be obtained by assigning base animals to genetic groups according to their unit of origin, but units must be connected to estimate group effects. If many small groups exist, error of BV prediction may be increased. Alternatively, genetic groups can be excluded from the statistical model, which may bias BV predictions. If adequate genetic connections exist among units, bias is reduced. Several measures of connectedness have been proposed, but their relationships to potential bias in BV predictions are not well defined. This study compares alternative strategies to connect small units and assesses the ability of different connectedness statistics to quantify potential bias in BV prediction. Connections established using common sires across units were most effective in reducing bias. The coefficient of determination of the mean difference in predicted BV was a perfect indicator of potential bias remaining when comparing individuals in separate units. However, this measure is difficult to calculate; correlated measures such as prediction errors of differences in unit means and correlations among prediction errors are suggested as practical alternatives.

Measuring connectedness among herds in mixed linear models: From theory to practice in large-sized genetic evaluations

“…It is worth noting that the need for links decreases with the number of progeny per sire, but not with the number of sires per herd. These theoretical results were confirmed by Kuehn et al [13]. Formula (5) may be used as a rule of thumb when choosing the value of χ.…”

“…Kuehn et al [13] examined the importance of connectedness and weighed the merits of CD, r ij and CR ij . They compared different connectedness scenarios and found that only CD showed a consistent relationship with bias reduction across all scenarios tested.…”

“…They compared different connectedness scenarios and found that only CD showed a consistent relationship with bias reduction across all scenarios tested. However, as stated by [13], "the CD is difficult 147 to calculate for routine genetic evaluation due to storage and processing time involved in calculating both the inverse of the coefficient matrix and the (noninverted) relationship matrix". They advocated measuring connectedness by other criterions, highly correlated to CD, but easier to compute.…”

Evaluation of connectedness between herds for three pig breeds in China

“…Laloë et al (1996) compared PEV with CI and CD and concluded that CD combines aspects of genetic variability and PEV, and is thus a method of choice to assess the connectedness. Kuehn et al (2007) also argued that CD was a perfect indicator of potential bias remaining when comparing individuals in separate units. However, if the primary objective of measuring connectedness is to identify herds where EBVs are poorly estimated in comparison to those of other herds so that remedial action can be taken, then a method that assesses only the accuracy of such comparisons would be most appropriate.…”

Heterogeneous variances and genetics by environment interactions in genetic evaluation of crossbred lambs

“…The sufficiency of the design was explored by quantifying the strength of connections using prediction error correlations (Lewis et al, 2005;Kuehn et al, 2007 and. Using 5WT as the example trait, and a heritability of 0.20, connectedness correlations were derived among farms and breed-index categories.…”