2018
DOI: 10.3168/jds.2017-14193
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Comparison of genomic predictions for lowly heritable traits using multi-step and single-step genomic best linear unbiased predictor in Holstein cattle

Abstract: The success and sustainability of a breeding program incorporating genomic information is largely dependent on the accuracy of predictions. For low heritability traits, large training populations are required to achieve high accuracies of genomic estimated breeding values (GEBV). By including genotyped and nongenotyped animals simultaneously in the evaluation, the single-step genomic BLUP (ssGBLUP) approach has the potential to deliver more accurate and less biased genomic evaluations. The aim of this study wa… Show more

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Cited by 41 publications
(43 citation statements)
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“…On average, inflation in GBLUP and ssGBLUP methods with 10k markers were declined by 4.16% and 3.26% using 50k, and 6.62% and 3.71% using 700k marker density, respectively. In accordance with the present results, less biased predictions were reported for the single-step approach compared with multi-step GBLUP and pedigree-based methods using simulated [65] and real data [55, 62, 66]. Guarini et al [66] observed lower biases of predictions for ssGBLUP (0.710 to 1.040) compared to multi-step GBLUP (0.630 to 1.310) for lowly heritable traits in Canadian Holstein cattle that were in consistent with our results.…”
Section: Resultssupporting
confidence: 91%
“…On average, inflation in GBLUP and ssGBLUP methods with 10k markers were declined by 4.16% and 3.26% using 50k, and 6.62% and 3.71% using 700k marker density, respectively. In accordance with the present results, less biased predictions were reported for the single-step approach compared with multi-step GBLUP and pedigree-based methods using simulated [65] and real data [55, 62, 66]. Guarini et al [66] observed lower biases of predictions for ssGBLUP (0.710 to 1.040) compared to multi-step GBLUP (0.630 to 1.310) for lowly heritable traits in Canadian Holstein cattle that were in consistent with our results.…”
Section: Resultssupporting
confidence: 91%
“…The ssGBLUP enables combining the pedigree-based relationship matrix (A) with the genomic relationship matrix (G) into a hybrid matrix (H). This increases the accuracy and reduces the prediction bias of GEBVs when compared to those yielded from multi-step genomic predictions (Aguilar et al, 2010;Lourenco et al, 2015;Guarini et al, 2018). Recent studies have evaluated the use of purebred information to predict crossbred performance using the ssGBLUP method Tusell et al, 2016;Pocrnic et al, 2019).…”
Section: Introductionmentioning
confidence: 99%
“…In the PR studies, the accuracy of prediction was 0.269 in the Angus population (Saatchi et al, 2011) and 0.64 in Nelore cattle (Boddhireddy et al, 2014). For CD, the highest accuracy was 0.516 in Brangus using GBLUP models (Lopes et al, 2018), and the prediction accuracy of different beef cattle breeds is around 0.45 among different models (Luan et al, 2009;Saatchi et al, 2011), while the accuracy in dairy cows was lower by 0.24-0.34 (Guarini et al, 2018).…”
Section: Genomic Selection For Reproductive Traits In Bovine and Buffalomentioning
confidence: 92%