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Updated: Sep 11, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Single-variant genome-wide association study and regional heritability mapping of protein efficiency and performance
Esther Oluwada Ewaoluwagbemiga1,2, Audald Lloret-Villas2, Adéla Nosková2
1Agroscope, Animal GenoPhenomics, Tioleyre 4, 1725, Posieux, Switzerland.
Background:
Improvement of protein efficiency (PE) is a key factor for a sustainable pig production, as nitrogen excretion contributes substantially to environmental pollution. Protein efficiency has been shown to be heritable and genetically correlated with performance traits such as feed conversion ratio (FCR) and average daily feed intake (ADFI). This study aimed to identify genomic regions associated with these traits through single-variant genome-wide association studies (GWAS) and regional heritability mapping (RHM) using whole-genome sequence variants from low-pass sequencing of more than 1000 Swiss Large White pigs.
Results:
Genomic heritability estimates using ~ 15 million variants were moderate to high, ranging from 0.33 to 0.47. GWAS did not identify significant variants for PE and FCR, but identified 45 variants at suggestive significance levels for ADFI on chromosome 1 and one for ADG on chromosome 14. Similarly, RHM detected no significant regions for PE and FCR, but five suggestive regions for ADFI (chromosome 1) and one for ADG (chromosome 14). However, by combining leading signals from GWAS and RHM, i.e. overlapping leading variants and significant regions, we highlighted putative candidate genes for PE, including PHYKPL, COL23A1, PPFIBP2, GVIN1, SYT9, RBMXL2, ZNF215, and olfactory receptor genes.
Conclusions:
Combining GWAS and RHM allowed us to identify genomic regions that may influence PE and production traits. Our apparent difficulty in detecting significant regions for these traits probably reflects the relatively small sample size, differences in genetic architecture across study designs and experimental conditions, and that polymorphisms explaining large proportions of the trait variation may not segregate in this population. Nevertheless, we identified plausible functional candidate genes in the highlighted regions, including those involved in nutrient sensing, the urea cycle, and metabolic pathways, in particular IGF1-insulin, and that have previously been reported to be associated with nitrogen metabolism in cattle and with muscle and adipose tissue metabolism and feed intake in pigs. We also highlighted a range of noncoding RNAs. Their targets and roles in gene regulation should be further investigated in this context.
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