ArticleJournal of animal science2019
Genome-wide association study and genomic predictions for exterior traits in Yorkshire pigs1.
Article in Journal of animal science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Genome-Wide Association Study of Rib Number and Total Thoracolumbar Vertebrae Number in a Jishen Black Pig Population.Veterinary sciences · 2026Article
- A genome-wide association study on growth traits of Korean commercial pig breeds using Bayesian methods.Animal bioscience · 2024Article
- A Whole Genome Sequencing-Based Genome-Wide Association Study Reveals the Potential Associations of Teat Number in Qingping Pigs.Animals : an open access journal from MDPI · 2022Article
- Single-marker and haplotype-based genome-wide association studies for the number of teats in two heavy pig breeds.Animal genetics · 2021Article
- Comparison of three statistical approaches for feature selection for fine-scale genetic population assignment in four pig breeds.Tropical animal health and production · 2021Article
- 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
- Genomic Analysis Using Bayesian Methods under Different Genotyping Platforms in Korean Duroc Pigs.Animals : an open access journal from MDPI · 2020Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The objectives of this study were to identify informative genomic regions that affect the exterior traits of purebred Korean Yorkshire pigs and to investigate and compare the accuracy of genomic prediction for response variables. Phenotypic data on body height (BH), body length (BL), and total teat number (TTN) from 2,432 Yorkshire pigs were used to obtain breeding values including as response variable the estimated breeding value (EBV) and 2 types of deregressed EBVs-one including the parent average (DEBVincPA) and the other excluding it (DEBVexcPA). A final genotype panel comprising 46,199 SNP markers was retained for analysis after quality control for common SNPs. The BayesB and BayesC methods-with various π and weighted response variables (EBV, DEBVincPA, or DEBVexcPA)-were used to estimate SNP effects, through the genome-wide association study. The significance of genomic windows (1 Mb) was obtained at 1.0% additive genetic variance and was subsequently used to identify informative genomic regions. Furthermore, SNPs with a high model frequency (≥0.90) were considered informative. The accuracy of genomic prediction was estimated using a 5-fold cross-validation with the K-means clustering method. Genomic accuracy was measured as the genomic correlation between the molecular breeding value and the individual weighted response variables (EBV, DEBVincPA, or DEBVexcPA). The number of identified informative windows (1 Mb) for BH, BL, and TTN was 4, 3, and 4, respectively. The number of significant SNPs for BH, BL, and TTN was 6, 4, and 5, respectively. Diversity π did not influence the accuracy of genomic prediction. The BayesB method showed slightly higher genomic accuracy for exterior traits than BayesC method in this study. In addition, the genomic accuracy using DEBVincPA as response variable was higher than that using other response variables. Therefore, the genomic accuracy using BayesB (π = 0.90) with DEBVinPA as a response variable was the most effective in this study. The genomic accuracy values for BH, BL, and TTN were calculated to be 0.52, 0.60, and 0.51, respectively.
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