期刊
GENETICS SELECTION EVOLUTION
卷 53, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s12711-021-00671-w
关键词
-
资金
- BBSRC ISPG [BBS/E/D/30002275]
- Genus plc
- Innovate UK [102271]
- Swedish Research Council for Sustainable Development Formas [2016-01386]
- [BB/N004736/1]
- [BB/N015339/1]
- [BB/L020467/1]
- [BB/M009254/1]
- Formas [2016-01386] Funding Source: Formas
- BBSRC [BB/N004736/1, BB/M009254/1, BB/N015339/1] Funding Source: UKRI
- Innovate UK [102271] Funding Source: UKRI
This study conducted a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds and identified 264 significant SNP associations across 27 genomic regions. The results confirm the polygenic architecture of backfat thickness and highlight the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways in fat deposition in pigs. Additionally, several less well-understood metabolic pathways were found to contribute to backfat development, such as those related to phosphate, calcium, and vitamin D homeostasis.
Background Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10(-6) and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据