Suppr超能文献

一项全基因组关联研究确定了长白猪群体中商业性状的候选区域和基因。

A genome-wide association study identified candidate regions and genes for commercial traits in a Landrace population.

作者信息

Ma Guojian, Tan Xihong, Yan Ying, Zhang Tianyang, Wang Jianhua, Chen Xiaoling, Xu Jingya

机构信息

Breeding Department, Wuhan COFCO Meat Co., Ltd., Wuhan, Hubei, China.

COFCO Nutrition and Health Research Institute, Beijing, China.

出版信息

Front Genet. 2025 Jan 6;15:1505197. doi: 10.3389/fgene.2024.1505197. eCollection 2024.

Abstract

Backfat thickness (BFT) and feed conversion ratio (FCR) are important commercial traits in the pig industry. With the increasing demand for human health and meat production, identifying functional genomic regions and genes associated with these commercial traits is critical for enhancing production efficiency. In this research, we conducted a genome-wide association study (GWAS) on a Landrace population comprising 4,295 individuals with chip data for BFT and FCR. Our analysis revealed a total of 118 genome-wide significant signals located on chromosomes SSC1, SSC2, SSC7, SSC12, and SSC13, respectively. Furthermore, we identified 10 potential regions associated with the two traits and annotated the genes within these regions. In addition, enrichment analysis was also performed. Notably, candidate genes such as , , and were found to be associated with BFT, whereas , , and genes were related to the FCR. Our findings provide valuable insights into the genetic architecture of these two traits and offer guidance for future pig breeding efforts.

摘要

背膘厚度(BFT)和饲料转化率(FCR)是养猪业重要的商业性状。随着对人类健康和肉类生产需求的增加,识别与这些商业性状相关的功能基因组区域和基因对于提高生产效率至关重要。在本研究中,我们对一个包含4295头个体的长白猪群体进行了全基因组关联研究(GWAS),这些个体具有BFT和FCR的芯片数据。我们的分析分别在SSC1、SSC2、SSC7、SSC12和SSC13号染色体上共发现了118个全基因组显著信号。此外,我们确定了与这两个性状相关的10个潜在区域,并对这些区域内的基因进行了注释。另外,还进行了富集分析。值得注意的是,发现 、 和 等候选基因与BFT相关,而 、 和 基因与FCR相关。我们的研究结果为这两个性状的遗传结构提供了有价值的见解,并为未来的猪育种工作提供了指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7a9/11743953/509a1d69c875/fgene-15-1505197-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验