ArticleEvolutionary applications2022
Genome-wide association study and genomic prediction for intramuscular fat content in Suhuai pigs using imputed whole-genome sequencing data.
Article in Evolutionary applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Gene expression profiling by RNA-sequencing reveals regulators of intramuscular fat in Black Slavonian pigs.Scientific reports · 2026Article
- Enhancing genomic prediction for key production traits in chickens through ultrasound phenotyping and multi-model comparative analysis.Journal of animal science and biotechnology · 2026Article
- Candidate Genes, Markers, Signatures of Selection, and Quantitative Trait Loci (QTLs) and Their Association with Economic Traits in Livestock: Genomic Insights and Selection.International journal of molecular sciences · 2025Review
- Genome-Wide Association Study of Gluteus Medius Muscle Size in a Crossbred Pig Population.Veterinary sciences · 2025Article
- Integrated transcriptomics and metabolomics reveal the molecular characteristics and metabolic regulatory mechanisms among different muscles in Minxian black fur sheep.BMC genomics · 2025Article
- Identification of new candidate genes affecting drip loss in pigs based on genomics and transcriptomics data.Journal of animal science · 2025Article
- Single-Cell RNA Sequencing Reveals the Cellular Landscape ofInternational journal of molecular sciences · 2024Article
- Construction of a co-expression network affecting intramuscular fat content and meat color redness based on transcriptome analysis.Frontiers in genetics · 2024Article
- Genome-wide association study and genomic prediction for intramuscular fat content in Suhuai pigs using imputed whole-genome sequencing data.Evolutionary applications · 2022Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integrating the single-nucleotide polymorphisms (SNPs) significantly affecting target traits from imputed whole-genome sequencing (iWGS) data into the genomic prediction (GP) model is an economic, efficient, and feasible strategy to improve prediction accuracy. The objective was to dissect the genetic architecture of intramuscular fat content (IFC) by genome wide association studies (GWAS) and to investigate the accuracy of GP based on pedigree-based BLUP (PBLUP) model, genomic best linear unbiased prediction (GBLUP) models and Bayesian mixture (BayesMix) models under different strategies. A total of 482 Suhuai pigs were genotyped using an 80 K SNP chip. Furthermore, 30 key samples were selected for resequencing and were used as a reference panel to impute the 80 K chip data to the WGS dataset. The 80 K data and iWGS data were used to perform GWAS and test GP accuracies under different scenarios. GWAS results revealed that there were four major regions affecting IFC. Two important functional candidate genes were found in the two most significant regions, including protein kinase C epsilon (
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