ArticleAnimals : an open access journal from MDPI2023
Increased Accuracy of Genomic Prediction Using Preselected SNPs from GWAS with Imputed Whole-Genome Sequence Data in Pigs.
Article in Animals : an open access journal from MDPI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Multi-ancestry genome-wide association meta-analysis identifies candidate genes for computed tomography-based carcass composition traits in pigs.Genetics, selection, evolution : GSE · 2025Pooled it
- A benchmarking of genomic selection models for predicting grain-yield related traits using haplotype-based and genome-wide association study-based markers in rice.The plant genome · 2026Article
- Integrated Multi-Omics Analysis Reveals the Role of the Gut Microbiota-Metabolite-Endocrine Axis in Post-Weaning Estrus Recovery in Tibetan Pigs.Animals : an open access journal from MDPI · 2026Article
- Causal variants in animal genomes: approaches to identification, phenotypic impact, and implications for selective breeding.BMC genomics · 2026Review
- Improving genomic prediction accuracy of complex traits by integrating massive types of functional annotation information.Nature communications · 2026Article
- Multi-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp.Scientific reports · 2025Article
- Genome Selection for Fleece Traits in Inner Mongolia Cashmere Goats Based on GWAS Prior Marker Information.Animals : an open access journal from MDPI · 2025Article
- Genomic Selection for Economic Traits in Inner Mongolia Cashmere Goats by Integrating GWAS Prior Information.Veterinary sciences · 2025Article
- Improving genomic prediction in pigs by integrating multi-population data and prior knowledge.BMC genomics · 2025Article
- GPS: Harnessing data fusion strategies to improve the accuracy of machine learning-based genomic and phenotypic selection.Plant communications · 2025Article
- Integrating Genomic Selection and Genome-Wide Association Study to Enhance Reproductive Traits in Thai Swamp Buffalo.Animals : an open access journal from MDPI · 2025Article
- Identification and Functional Validation ofGenes · 2025Article
- Metabolic marker-assisted genomic prediction improves hybrid breeding.Plant communications · 2025Article
- Increased genomic predictive ability in mango using GWAS-preselected variants and fixed-effect SNPs.Frontiers in plant science · 2025Article
- Genomic Prediction of Semen Traits in Boars Incorporating Biological Interactions.International journal of molecular sciences · 2024Article
- Effect of host breeds on gut microbiome and fecal metabolome in commercial pigs.BMC veterinary research · 2024Article
- GWAS Enhances Genomic Prediction Accuracy of Caviar Yield, Caviar Color and Body Weight Traits in Sturgeons Using Whole-Genome Sequencing Data.International journal of molecular sciences · 2024Article
Corrections and comments
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
Abstract
Enhancing the accuracy of genomic prediction is a key goal in genomic selection (GS) research. Integrating prior biological information into GS methods using appropriate models can improve prediction accuracy for complex traits. Genome-wide association study (GWAS) is widely utilized to identify potential candidate loci associated with complex traits in livestock and poultry, offering essential genomic insights. In this study, a GWAS was conducted on 685 Duroc × Landrace × Yorkshire (DLY) pigs to extract significant single-nucleotide polymorphisms (SNPs) as genomic features. We compared two GS models, genomic best linear unbiased prediction (GBLUP) and genomic feature BLUP (GFBLUP), by using imputed whole-genome sequencing (WGS) data on 651 Yorkshire pigs. The results revealed that the GBLUP model achieved prediction accuracies of 0.499 for backfat thickness (BFT) and 0.423 for loin muscle area (LMA). By applying the GFBLUP model with GWAS-based SNP preselection, the average prediction accuracies for BFT and LMA traits reached 0.491 and 0.440, respectively. Specifically, the GFBLUP model displayed a 4.8% enhancement in predicting LMA compared to the GBLUP model. These findings suggest that, in certain scenarios, the GFBLUP model may offer superior genomic prediction accuracy when compared to the GBLUP model, underscoring the potential value of incorporating genomic features to refine GS models.
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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.