Estimation of genetic parameters and response to selection for a continuous trait subject to culling before testing

Abstract

The consequences of assuming a zero environmental covariance between a binary trait 'test-status' and a continuous trait on the estimates of genetic parameters by restricted maximum likelihood and Gibbs sampling and on response from genetic selection when the true environmental covariance deviates from zero were studied. Data were simulated for two traits (one that culling was based on and a continuous trait) using the following true parameters, on the underlying scale: h² = 0.4; r(A) = 0.5; r(E) = 0.5, 0.0 or -0.5. The selection on the continuous trait was applied to five subsequent generations where 25 sires and 500 dams produced 1500 offspring per generation. Mass selection was applied in the analysis of the effect on estimation of genetic parameters. Estimated breeding values were used in the study of the effect of genetic selection on response and accuracy. The culling frequency was either 0.5 or 0.8 within each generation. Each of 10 replicates included 7500 records on 'test-status' and 9600 animals in the pedigree file. Results from bivariate analysis showed unbiased estimates of variance components and genetic parameters when true r(E) = 0.0. For r(E) = 0.5, variance components (13-19% bias) and especially (50-80%) were underestimated for the continuous trait, while heritability estimates were unbiased. For r(E) = -0.5, heritability estimates of test-status were unbiased, while genetic variance and heritability of the continuous trait together with were overestimated (25-50%). The bias was larger for the higher culling frequency. Culling always reduced genetic progress from selection, but the genetic progress was found to be robust to the use of wrong parameter values of the true environmental correlation between test-status and the continuous trait. Use of a bivariate linear-linear model reduced bias in genetic evaluations, when data were subject to culling.

Analysis of competition performance in dressage and show jumping of Dutch Warmblood horses

“…; Árnason et al . ). Ducro () showed that preselection in dressage horses resulted in a lower estimate of heritability for dressage competition and a biased estimation of breeding values.…”

“…When the cause of not participating is connected with the breeding goal (preselection), this might lead to a bias in the estimated breeding values (Klemetsdal 1994;Arnason 1999). Research has demonstrated the existence of preselection in sport horses (Bugislaus et al 2005;Albertsd ottir et al 2011;Arnason et al 2012). Ducro (2010) showed that preselection in dressage horses resulted in a lower estimate of heritability for dressage competition and a biased estimation of breeding values.…”

Investigating the impact of preselection on subsequent single-step genomic BLUP evaluation of preselected animals

“…Traditionally, preselection has mostly been based on correlated trait(s) that can be measured easily and cheaply early in life (e.g. [ 1 , 3 , 6 – 8 ]). In the genomic era, preselection is often based on genomic estimated breeding values (GEBV) of young selection candidates, and in the literature this type of preselection is called genomic or genotypic preselection (GPS; e.g.…”

Avoiding preselection bias in subsequent single‐step genomic BLUP evaluations of genomically preselected animals

“…In animal breeding programs, parents of the next generation are usually selected in multiple stages (e.g., Árnason et al., 2012; Meyer & Thompson, 1984; Xu et al., 1995), and the initial stages of this selection are referred to as preselection (e.g., Janhunen et al., 2014; Masuda et al., 2018; Patry & Ducrocq, 2011). Impact of preselection on subsequent genetic evaluations has been a subject of research for a long time in the field of animal breeding (e.g., Appel et al., 1998; Henderson, 1975; Masuda et al., 2018; Patry & Ducrocq, 2011a).…”