ArticleJournal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie2021
Accounting for genetic architecture for body weight improves accuracy of predicting breeding values in a commercial line of broilers.
Article in Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Enhancing genomic prediction for key production traits in chickens through ultrasound phenotyping and multi-model comparative analysis.Journal of animal science and biotechnology · 2026Article
- Weighted GBLUP in Simulated Beef Cattle Populations: Impact of Reference Population, Marker Density, and Heritability.Animals : an open access journal from MDPI · 2025Article
- Genetic Strategies for Enhancing Rooster Fertility in Tropical and Humid Climates: Challenges and Opportunities.Animals : an open access journal from MDPI · 2025Review
- Improving the accuracy of genomic prediction for meat quality traits using whole genome sequence data in pigs.Journal of animal science and biotechnology · 2023Article
- Accounting for genetic architecture for body weight improves accuracy of predicting breeding values in a commercial line of broilers.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BLUP (best linear unbiased prediction) is the standard for predicting breeding values, where different assumptions can be made on variance-covariance structure, which may influence predictive ability. Herein, we compare accuracy of prediction of four derived-BLUP models: (a) a pedigree relationship matrix (PBLUP), (b) a genomic relationship matrix (GBLUP), (c) a weighted genomic relationship matrix (WGBLUP) and (d) a relationship matrix based on genomic features that consisted of only a subset of SNP selected on a priori information (GFBLUP). We phenotyped a commercial population of broilers for body weight (BW) in five successive weeks and genotyped them using a 50k SNP array. We compared predictive ability of univariate models using conservative cross-validation method, where each full-sib group was divided into two folds. Results from cross-validation showed, with WGBLUP model, a gain in accuracy from 2% to 7% compared with GBLUP model. Splitting the additive genetic matrix into two matrices, based on significance level of SNP (G
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