ArticleAnimals : an open access journal from MDPI2019
Genomic Prediction and Association Analysis with Models Including Dominance Effects for Important Traits in Chinese Simmental Beef Cattle.
Article in Animals : an open access journal from MDPI, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- Evaluation of Multi-Breed Genomic Prediction Models for Carcass and Reproductive Traits in Zebu Beef Cattle.Animal genetics · 2026Article
- Genome-Wide Association Studies of Growth and Carcass Traits in Charolais Cattle Based on High-Coverage Whole-Genome Resequencing.International journal of molecular sciences · 2025Article
- Identifying candidate genetic variants for egg number by analyzing over 1,000 fully sequenced layers.GigaScience · 2025Article
- Adipose gene expression profiles in Northern Finncattle, Mirandesa cattle, Yakutian cattle and commercial Holstein cattle.Scientific reports · 2024Article
- Genome-Wide Association Study for Milk Somatic Cell Score in Holstein Friesian Cows in Slovenia.Animals : an open access journal from MDPI · 2024Article
- Impact of inclusion non-additive effects on genome-wide association and variance's components in Scottish black sheep.Animal biotechnology · 2023Article
- Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP.Journal of applied genetics · 2022Article
- Assessing the Genetic Background and Selection Signatures of Huaxi Cattle Using High-Density SNP Array.Animals : an open access journal from MDPI · 2021Article
- Article
- Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size.BMC genomics · 2021Article
- Genome Wide Association Study of Beef Traits in Local Alpine Breed Reveals the Diversity of the Pathways Involved and the Role of Time Stratification.Frontiers in genetics · 2021Article
- Functional Analysis of Haplotypes in BovineAnimals : an open access journal from MDPI · 2020Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 1 country.
Funding
Abstract
Non-additive effects play important roles in determining genetic changes with regard to complex traits; however, such effects are usually ignored in genetic evaluation and quantitative trait locus (QTL) mapping analysis. In this study, a two-component genome-based restricted maximum likelihood (GREML) was applied to obtain the additive genetic variance and dominance variance for carcass weight (CW), dressing percentage (DP), meat percentage (MP), average daily gain (ADG), and chuck roll (CR) in 1233 Simmental beef cattle. We estimated predictive abilities using additive models (genomic best linear unbiased prediction (GBLUP) and BayesA) and dominance models (GBLUP-D and BayesAD). Moreover, genome-wide association studies (GWAS) considering both additive and dominance effects were performed using a multi-locus mixed-model (MLMM) approach. We found that the estimated dominance variances accounted for 15.8%, 16.1%, 5.1%, 4.2%, and 9.7% of the total phenotypic variance for CW, DP, MP, ADG, and CR, respectively. Compared with BayesA and GBLUP, we observed 0.5-1.1% increases in predictive abilities of BayesAD and 0.5-0.9% increases in predictive abilities of GBLUP-D, respectively. Notably, we identified a dominance association signal for carcass weight within
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Registered trials
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.