ArticleGenetics, selection, evolution : GSE2017
Genomic evaluation for a three-way crossbreeding system considering breed-of-origin of alleles.
Article in Genetics, selection, evolution : GSE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed, 81 citations in OpenAlex.
- Accurate determination of breed origin of alleles in a simulated smallholder crossbred dairy cattle population.Genetics, selection, evolution : GSE · 2025Article
- Evaluation of crossbreeding strategies for improved adaptation and productivity in African smallholder cattle farms.Genetics, selection, evolution : GSE · 2025Article
- Breed of origin analysis in genome-wide association studies: enhancing SNP-based insights into production traits in a commercial Brangus population.BMC genomics · 2024Article
- Unveiling the Genetic Mechanism of Meat Color in Pigs through GWAS, Multi-Tissue, and Single-Cell Transcriptome Signatures Exploration.International journal of molecular sciences · 2024Article
- Single-step genomic predictions for crossbred Holstein and Jersey cattle in the United States.JDS communications · 2024Article
- Developing flexible models for genetic evaluations in smallholder crossbred dairy farms.Journal of dairy science · 2023Article
- Segregation between breeds and local breed proportions in genetic and genomic models for crossbreds.Genetics, selection, evolution : GSE · 2023Article
- Multibreed genomic prediction using summary statistics and a breed-origin-of-alleles approach.Heredity · 2023Article
- A breed-of-origin of alleles model that includes crossbred data improves predictive ability for crossbred animals in a multi-breed population.Genetics, selection, evolution : GSE · 2023Article
- Validation with single-step SNPBLUP shows that evaluations can continue using a single mean of genotyped individuals, even with multiple breeds.Genetics, selection, evolution : GSE · 2023Article
- Genomic evaluation for two-way crossbred performance in cattle.Genetics, selection, evolution : GSE · 2023Article
- Predicting the impact of genotype-by-genotype interaction on the purebred-crossbred genetic correlation from phenotype and genotype marker data of parental lines.Genetics, selection, evolution : GSE · 2023Article
- Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information.Frontiers in genetics · 2023Article
- Estimation of dam line composition of 3-way crossbred animals using genomic information.Genetics, selection, evolution : GSE · 2022Article
- Genotyping and phenotyping strategies for genetic improvement of meat quality and carcass composition in swine.Genetics, selection, evolution : GSE · 2022Article
- Genomic Prediction Methods Accounting for Nonadditive Genetic Effects.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Breed of origin of alleles and genomic predictions for crossbred dairy cows.Genetics, selection, evolution : GSE · 2021Article
- Review: optimizing genomic selection for crossbred performance by model improvement and data collection.Journal of animal science · 2021Review
- Genomic prediction using a reference population of multiple pure breeds and admixed individuals.Genetics, selection, evolution : GSE · 2021Article
- Genomic Prediction of Average Daily Gain, Back-Fat Thickness, and Loin Muscle Depth Using Different Genomic Tools in Canadian Swine Populations.Frontiers in genetics · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenomic prediction of purebred animals for crossbred performance can be based on a model that estimates effects of single nucleotide polymorphisms (SNPs) in purebreds on crossbred performance. For crossbred performance, SNP effects might be breed-specific due to differences between breeds in allele frequencies and linkage disequilibrium patterns between SNPs and quantitative trait loci. Accurately tracing the breed-of-origin of alleles (BOA) in three-way crosses is possible with a recently developed procedure called BOA. A model that accounts for breed-specific SNP effects (BOA model), has never been tested empirically on a three-way crossbreeding scheme. Therefore, the objectives of this study were to evaluate the estimates of variance components and the predictive accuracy of the BOA model compared to models in which SNP effects for crossbred performance were assumed to be the same across breeds, using either breed-specific allele frequencies ([Formula: see text] model) or allele frequencies averaged across breeds ([Formula: see text] model). In this study, we used data from purebred and three-way crossbred pigs on average daily gain (ADG), back fat thickness (BF), and loin depth (LD).
resultsEstimates of variance components for crossbred performance from the BOA model were mostly similar to estimates from models [Formula: see text] and [Formula: see text]. Heritabilities for crossbred performance ranged from 0.24 to 0.46 between traits. Genetic correlations between purebred and crossbred performance ([Formula: see text]) across breeds ranged from 0.30 to 0.62 for ADG and from 0.53 to 0.74 for BF and LD. For ADG, prediction accuracies of the BOA model were higher than those of the [Formula: see text] and [Formula: see text] models, with significantly higher accuracies only for one maternal breed. For BF and LD, prediction accuracies of models [Formula: see text] and [Formula: see text] were higher than those of the BOA model, with no significant differences. Across all traits, models [Formula: see text] and [Formula: see text] yielded similar predictions.
conclusionsThe BOA model yielded a higher prediction accuracy for ADG in one maternal breed, which had the lowest [Formula: see text] (0.30). Using the BOA model was especially relevant for traits with a low [Formula: see text]. In all other cases, the use of crossbred information in models [Formula: see text] and [Formula: see text], does not jeopardize predictions and these models are more easily implemented than the BOA model.
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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.