ArticleGenetics, selection, evolution : GSE2021
Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency.
Article in Genetics, selection, evolution : GSE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.
- Comparison of two multi-trait association testing methods and sequence-based fine mapping of six additive QTL in Swiss Large White pigs.BMC genomics · 2023Pooled it
- Integrating longitudinal metabolite profiles improves phenotype prediction in pigs in a trait- and timepoint-dependent manner.Genetics, selection, evolution : GSE · 2026Article
- Review
- Genome-Wide Association Studies on the Autosomes and Chromosome X Uncover Genetic Basis of Reproductive Traits in Yorkshire Pigs.Animals : an open access journal from MDPI · 2026Article
- Sequence-based genome-wide association study reveals genetic and metabolic mechanisms underlying feed efficiency-related traits in beef cattle.Journal of animal science and biotechnology · 2026Article
- Integrating Longitudinal Metabolite Profiles Improves Trait Prediction in Pigs in a Trait- and Timepoint-Dependent Manner.bioRxiv : the preprint server for biology · 2025Article
- Single-variant genome-wide association study and regional heritability mapping of protein efficiency and performance traits in Large White pigs.Genetics, selection, evolution : GSE · 2025Article
- Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs.BMC genomics · 2024Article
- A genome-wide association study identified candidate regions and genes for commercial traits in a Landrace population.Frontiers in genetics · 2024Article
- Article
- Article
- Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs.Scientific reports · 2022Article
- Genome-Wide Association Analysis and Genetic Parameters for Feed Efficiency and Related Traits in Yorkshire and Duroc Pigs.Animals : an open access journal from MDPI · 2022Article
- Genome-Wide Association Study of Feed Efficiency Related Traits in Ducks.Animals : an open access journal from MDPI · 2022Article
- Quality of breeding value predictions from longitudinal analyses, with application to residual feed intake in pigs.Genetics, selection, evolution : GSE · 2022Article
- Application of Bayesian genomic prediction methods to genome-wide association analyses.Genetics, selection, evolution : GSE · 2022Review
- Differences in liver microRNA profiling in pigs with low and high feed efficiency.Journal of animal science and technology · 2022Article
- Fine Mapping of a Major Backfat QTL Reveals a Causal Regulatory Variant Affecting theFrontiers in genetics · 2022Article
- A High-Density Genetic Linkage Map and Fine Mapping of QTL For Feed Conversion Efficiency in Common Carp (Frontiers in genetics · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundFeed efficiency is a major driver of the sustainability of pig production systems. Understanding the biological mechanisms that underlie these agronomic traits is an important issue for environment questions and farms' economy. This study aimed at identifying genomic regions that affect residual feed intake (RFI) and other production traits in two pig lines divergently selected for RFI during nine generations (LRFI, low RFI; HRFI, high RFI).
resultsWe built a whole dataset of 570,447 single nucleotide polymorphisms (SNPs) in 2426 pigs with records for 24 production traits after both imputation and prediction of genotypes using pedigree information. Genome-wide association studies (GWAS) were performed including both lines (global-GWAS) or each line independently (LRFI-GWAS and HRFI-GWAS). Forty-five chromosomal regions were detected in the global-GWAS, whereas 28 and 42 regions were detected in the HRFI-GWAS and LRFI-GWAS, respectively. Among these 45 regions, only 13 were shared between at least two analyses, and only one was common between the three GWAS but it affects different traits. Among the five quantitative trait loci (QTL) detected for RFI, two were close to QTL for meat quality traits and two pinpointed novel genomic regions that harbor candidate genes involved in cell proliferation and differentiation processes of gastrointestinal tissues or in lipid metabolism-related signaling pathways. In most cases, different QTL regions were detected between the three designs, which suggests a strong impact of the dataset structure on the detection power and could be due to the changes in allelic frequencies during the establishment of lines.
conclusionsIn addition to efficiently detecting known and new QTL regions for feed efficiency, the combination of GWAS carried out per line or simultaneously using all individuals highlighted chromosomal regions that affect production traits and presented significant changes in allelic frequencies across generations. Further analyses are needed to estimate whether these regions correspond to traces of selection or result from genetic drift.
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