ArticlePloS one2019
Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed, 41 citations in OpenAlex.
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- Recent progress in genomic prediction for Hanwoo cattle and its implications for beef quality: review.Animal bioscience · 2026Article
- Selection index for genetic improvement of beef performance in Huaxi cattle of Xinjiang, China.BMC genomics · 2026Article
- Evaluating Adjusted ssGBLUP Models for Genomic Prediction and Matrix Compatibility in South African Holstein Cattle.Animals : an open access journal from MDPI · 2026Article
- ReaGP: integrating residual units and attention mechanisms in convolution neural network for genomic prediction.Genetics, selection, evolution : GSE · 2026Article
- Comparative evaluation of SNP-weighted, Bayesian, and machine learning models for genomic prediction in Holstein cattle.BMC genomics · 2025Article
- Preliminary Evaluation of Blending, Tuning, and Scaling Parameters in ssGBLUP for Genomic Prediction Accuracy in South African Holstein Cattle.Animals : an open access journal from MDPI · 2025Article
- Ensemble of Bayesian alphabets via constraint weight optimization strategy improves genomic prediction accuracy.G3 (Bethesda, Md.) · 2025Article
- AdaptiveGS: an explainable genomic selection framework based on adaptive stacking ensemble machine learning.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Investigating the Performance of Frequentist and Bayesian Techniques in Genomic Evaluation.Biochemical genetics · 2025Article
- Genome-wide association analysis revealed novel candidate genes for body measurement traits in indigenous Gudali and crossbred Simgud in Cameroon.BMC genomics · 2025Article
- Variable selection strategies for genomic prediction of growth and carcass related traits in experimental Nellore cattle herds under different selection criteria.Scientific reports · 2025Article
- High-throughput seed quality analysis in faba bean: leveraging Near-InfraRed spectroscopy (NIRS) data and statistical methods.Food chemistry: X · 2024Article
- SABO-ILSTSVR: a genomic prediction method based on improved least squares twin support vector regression.Frontiers in genetics · 2024Article
- Evaluation of eight Bayesian genomic prediction models for three micronutrient traits in bread wheat (Triticum aestivum L.).The plant genome · 2023Article
- A dimensionality-reduction genomic prediction method without direct inverse of the genomic relationship matrix for large genomic data.Plant cell reports · 2023Article
- Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef Cattle.Foods (Basel, Switzerland) · 2023Article
- Selective genotyping to implement genomic selection in beef cattle breeding.Frontiers in genetics · 2023Article
- Comparing modeling methods of genomic prediction for growth traits of a tropical timber species,Frontiers in plant science · 2023Article
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chinese Simmental beef cattle are the most economically important cattle breed in China. Estimated breeding values for growth, carcass, and meat quality traits are commonly used as selection criteria in animal breeding. The objective of this study was to evaluate the accuracy of alternative statistical methods for the estimation of genomic breeding values. Analyses of the accuracy of genomic best linear unbiased prediction (GBLUP), BayesB, and elastic net (EN) were performed with an Illumina BovineHD BeadChip on 1,217 animals by applying 5-fold cross-validation. Overall, the accuracies ranged from 0.17 to 0.296 for ten traits, and the heritability estimates ranged from 0.36 to 0.63. The EN (alpha = 0.001) model provided the most accurate prediction, which was also slightly higher (0.2-2%) than that of GBLUP for most traits, such as average daily weight gain (ADG) and carcass weight (CW). BayesB was less accurate for each trait than were EN (alpha = 0.001) and GBLUP. These findings indicate the importance of using an appropriate variable selection method for the genomic selection of traits and suggest the influence of the genetic architecture of the traits we analyzed.
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