ArticleBMC genetics2011
Accuracy of genomic selection in simulated populations mimicking the extent of linkage disequilibrium in beef cattle.
Article in BMC genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 85 citations in OpenAlex.
- Leveraging Fst and Genetic Distance to Optimize Reference Sets for Enhanced Cross-Population Genomic Prediction.Animals : an open access journal from MDPI · 2026Article
- Indirect Genomic Predictions for Indicine Cattle Breeds With SNP Effects From a Multi-Breed Genomic Evaluation.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Comparison of GBLUP and WGBLUP in genomic selection for beef cattle under different LD patterns and mixed multi-population scenarios: a simulation study.BMC genomics · 2025Article
- Effect of using preselected markers from imputed whole-genome sequence for genomic prediction in Angus cattle.Genetics, selection, evolution : GSE · 2025Article
- Assessing the Impact of Different Mixing Strategies on Genomic Prediction Accuracy for Beef Cattle Breeding Values in Multi-Breed Genomic Prediction.Animals : an open access journal from MDPI · 2025Article
- Weighted GBLUP in Simulated Beef Cattle Populations: Impact of Reference Population, Marker Density, and Heritability.Animals : an open access journal from MDPI · 2025Article
- Optimizing purebred selection to improve crossbred performance.Frontiers in genetics · 2024Article
- Strategies of preserving genetic diversity while maximizing genetic response from implementing genomic selection in pulse breeding programs.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Imputation of non-genotyped F1 dams to improve genetic gain in swine crossbreeding programs.Journal of animal science · 2022Article
- Optimal population size to detect quantitative trait loci in Korean native chicken: a simulation study.Animal bioscience · 2022Article
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- Exploring the size of reference population for expected accuracy of genomic prediction using simulated and real data in Japanese Black cattle.BMC genomics · 2021Article
- Non-additive association analysis using proxy phenotypes identifies novel cattle syndromes.Nature genetics · 2021Article
- Marker genotyping error effects on genomic predictions under different genetic architectures.Molecular genetics and genomics : MGG · 2021Article
- Assessment of genomic prediction accuracy using different selection and evaluation approaches in a simulated Korean beef cattle population.Asian-Australasian journal of animal sciences · 2020Article
- Estimation of Variance Components and Genomic Prediction for Individual Birth Weight Using Three Different Genome-Wide SNP Platforms in Yorkshire Pigs.Animals : an open access journal from MDPI · 2020Article
- Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals.Frontiers in genetics · 2020Article
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- Article
- Genome-Wide SNP Data Revealed the Extent of Linkage Disequilibrium, Persistence of Phase and Effective Population Size in Purebred and Crossbred Buffalo Populations.Frontiers in genetics · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe success of genomic selection depends mainly on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), the number of animals in the training set (TS) and the heritability (h2) of the trait. The extent of LD depends on the genetic structure of the population and the density of markers. The aim of this study was to calculate accuracy of direct genomic estimated breeding values (DGEBV) using best linear unbiased genomic prediction (GBLUP) for different marker densities, heritabilities and sizes of the TS in simulated populations that mimicked previously reported extent and pattern of LD in beef cattle.
resultsThe accuracy of DGEBV increased significantly (p < 0.05) with the increase in the number of bulls in the TS (480, 960 or 1920), trait h2 (0.10, 0.25 or 0.40) and marker densities (40 k or 800 k). Increasing the number of animals in the TS by 4-fold and using their phenotypes to estimate marker effects was not sufficient to maintain or increase the accuracy of DGEBV obtained using estimated breeding values (EBVs) when the trait h2 was lower than 0.40 for both marker densities. Comparing to expected accuracies of parent average (PA), the gains by using DGEBV would be of 27%, 13% and 10% for trait h2 equal to 0.10, 0.25 and 0.40, respectively, considering the scenario with 40 k markers and 1920 bulls in TS.
conclusionsAs reported in dairy cattle, the size of the TS and the extent of LD have major impact on the accuracy of DGEBV. Based on the findings of this simulation study, large TS, as well as dense marker panels, aiming to increase the level of LD between markers and QTL, will likely be needed in beef cattle for successful implementation of genomic selection.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.