Effect of Genetic Differences Among Herds on Accuracy of Selection and Expected Genetic Change

Spike, P.L.; Freeman, A.E.

doi:10.3168/jds.s0022-0302(77)83971-4

Cited by 12 publications

(7 citation statements)

References 20 publications

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“…Cundiff (1975) suggested the genetic variance between herds may be as high as that within herds. Spike (1978) also reported the same conclusion. It means ignoring connectedness can have significant risk which can increase prediction error of comparison for BVs across herds two-fold.…”

Section: Relationship Between Connectedness and Biassupporting

confidence: 75%

The effect of connectedness on the bias and accuracy for prediction of breeding value in swine herds

Soga

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Section: Relationship Between Connectedness and Biassupporting

confidence: 75%

The effect of connectedness on the bias and accuracy for prediction of breeding value in swine herds

Soga

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“…Analyses of genetic differences among herds and flocks have suggested that genetic variance among units may be as large as that within units [3,24]. Similar results were reported in dairy cattle herds [39] before widespread use of artificial insemination (AI). Gene flow via AI can create extensive genetic connections among units, but AI is currently not widely used in sheep; fewer than 2% of ewes in the USA are bred using AI [28].…”

Section: Introductionmentioning

confidence: 80%

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

2007

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-Comparing predicted breeding values (BV) among animals in different managementunits (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.connectedness / genetic evaluation / bias / genetic groups / breeding value

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“…Previous research (Lewis et al, 1999) suggested that the variance of flock means in these terminal sire breeds was approximately equal to the within-flock additive variance. Similar values for the additive variance among production units were reported in other species before the widespread use of AI (Cundiff et al, 1975;Spike and Freeman, 1978). Therefore, σ 2 was set to 0.25 for all scenarios.…”

Section: Simulationmentioning

confidence: 94%

Assessing genetic gain, inbreeding, and bias attributable to different flock genetic means in alternative sheep sire referencing schemes1

Kuehn

Notter

Lewis

2008

Journal of Animal Science

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Flocks participating in sire referencing schemes can achieve greater genetic gains than those achievable by within-flock selection. However, requirements for joining these schemes can be prohibitive to some producers. The objectives of this study were to determine whether less restrictive schemes or schemes of shorter duration could achieve rates of gain and reduce inbreeding as efficiently as continuous sire referencing schemes (SRS) and to investigate whether bias from different genetic means could be reduced by these alternative schemes. Pedigree and performance data for a single trait with a within-flock heritability of 0.25 were simulated (50 replications) for 15 flocks with 40 to 140 ewes per flock. Founder genetic means for each flock were sampled from a normal distribution with mean 0 and SD equal to the trait's genetic SD. After 10 yr of random mating, flocks had the opportunity to join an SRS and begin selection for the simulated trait. Yearling rams were chosen as reference sires randomly from the top one-sixth of the population ranked on BLUP EBV. Every year, in each flock, 3 reference sires were mated to 10 ewes. Six sire referencing scenarios were considered, in which all flocks participated in a SRS for 1) 15 yr; 2) 5 yr before discontinuing the scheme;

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Effect of Genetic Differences Among Herds on Accuracy of Selection and Expected Genetic Change

Cited by 12 publications

References 20 publications

The effect of connectedness on the bias and accuracy for prediction of breeding value in swine herds

The effect of connectedness on the bias and accuracy for prediction of breeding value in swine herds

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

Assessing genetic gain, inbreeding, and bias attributable to different flock genetic means in alternative sheep sire referencing schemes1

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