{"title":"大型白猪蛋白质效率和生产性能的单变异全基因组关联研究及区域遗传力定位","authors":"Esther Oluwada Ewaoluwagbemiga, Audald Lloret-Villas, Adéla Nosková, Hubert Pausch, Claudia Kasper","doi":"10.1186/s12711-025-00993-z","DOIUrl":null,"url":null,"abstract":"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. 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. 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.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"12 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Single-variant genome-wide association study and regional heritability mapping of protein efficiency and performance traits in Large White pigs\",\"authors\":\"Esther Oluwada Ewaoluwagbemiga, Audald Lloret-Villas, Adéla Nosková, Hubert Pausch, Claudia Kasper\",\"doi\":\"10.1186/s12711-025-00993-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. 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. 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.\",\"PeriodicalId\":55120,\"journal\":{\"name\":\"Genetics Selection Evolution\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genetics Selection Evolution\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s12711-025-00993-z\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, DAIRY & ANIMAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetics Selection Evolution","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s12711-025-00993-z","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
Single-variant genome-wide association study and regional heritability mapping of protein efficiency and performance traits in Large White pigs
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. 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. 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.
期刊介绍:
Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.