Impact of genomic preselection on subsequent genetic evaluations with ssGBLUP using real data from pigs

Archive ouverte

Jibrila, Ibrahim | Vandenplas, Jeremie | ten Napel, Jan | Bergsma, Rob | Veerkamp, Roel F. | Calus, Mario P. L.

Edité par CCSD ; BioMed Central -

International audience. AbstractBackgroundEmpirically assessing the impact of preselection on genetic evaluation of preselected animals requires comparing scenarios that take different approaches into account, including scenarios without preselection. However, preselection is almost always performed in animal breeding programs, so it is difficult to have a dataset without preselection. Hence, most studies on preselection have used simulated datasets, and have concluded that genomic estimated breeding values (GEBV) from subsequent single-step genomic best linear unbiased prediction (ssGBLUP) evaluations are unbiased. The aim of this study was to investigate the impact of genomic preselection (GPS) on accuracy and bias in subsequent ssGBLUP evaluations, using data from a commercial pig breeding program.MethodsWe used data on average daily gain during performance testing, average daily gain throughout life, backfat thickness, and loin depth from one sire line and one dam line of pigs. As these traits have different weights in the breeding goals of the two lines, we analyzed the lines separately. For each line, we implemented a reference GPS scenario that kept all available data, against which the next two scenarios were compared. We then implemented two other scenarios with additional layers of GPS by removing all animals without progeny either (i) only in the validation generation, or (ii) in all generations. We conducted subsequent ssGBLUP evaluations for each GPS scenario, using all the data remaining after implementing the GPS scenario. Accuracy and bias were computed by comparing GEBV against progeny yield deviations of validation animals.ResultsResults for all traits and in both lines showed a marginal loss in accuracy due to the additional layers of GPS. Average accuracies across all GPS scenarios in the two lines were 0.39, 0.47, 0.56, and 0.60, for average daily gain during performance testing and throughout life, backfat thickness, and loin depth, respectively. Biases were largely absent, and when present, did not differ greatly between the GPS scenarios.ConclusionsWe conclude that the impact of preselection on accuracy and bias in subsequent ssGBLUP evaluations of selection candidates in pigs is generally minimal. We expect this conclusion to apply for other animal breeding programs as well, since preselection of any type or intensity generally has the same effect in animal breeding programs.

Suggestions

Du même auteur

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

Archive ouverte | Jibrila, Ibrahim | CCSD

International audience. AbstractBackgroundPreselection of candidates, hereafter referred to as preselection, is a common practice in breeding programs. Preselection can cause bias and accuracy loss in subsequent ped...

Efficient large-scale single-step evaluations and indirect genomic prediction of genotyped selection candidates

Archive ouverte | Vandenplas, Jeremie | CCSD

International audience. AbstractBackgroundSingle-step genomic best linear unbiased prediction (ssGBLUP) models allow the combination of genomic, pedigree, and phenotypic data into a single model, which is computatio...

Convergence behavior of single-step GBLUP and SNPBLUP for different termination criteria

Archive ouverte | Vandenplas, Jeremie | CCSD

International audience. Background: The preconditioned conjugate gradient (PCG) method is the current method of choice for iterative solving of genetic evaluations. The relative difference between two successive ite...

Chargement des enrichissements...