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全基因组关联研究和三维表观基因组特征的综合分析揭示了 BMP2 基因调控约克夏猪腰肌深度。

Integrated analysis of genome-wide association studies and 3D epigenomic characteristics reveal the BMP2 gene regulating loin muscle depth in Yorkshire pigs.

机构信息

Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China.

Research Institute of Agricultural Biotechnology, Jingchu University of Technology, Jingmen 448000, China.

出版信息

PLoS Genet. 2023 Jun 20;19(6):e1010820. doi: 10.1371/journal.pgen.1010820. eCollection 2023 Jun.

DOI:10.1371/journal.pgen.1010820
PMID:37339141
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10313041/
Abstract

BACKGROUND

The lack of integrated analysis of genome-wide association studies (GWAS) and 3D epigenomics restricts a deep understanding of the genetic mechanisms of meat-related traits. With the application of techniques as ChIP-seq and Hi-C, the annotations of cis-regulatory elements in the pig genome have been established, which offers a new opportunity to elucidate the genetic mechanisms and identify major genetic variants and candidate genes that are significantly associated with important economic traits. Among these traits, loin muscle depth (LMD) is an important one as it impacts the lean meat content. In this study, we integrated cis-regulatory elements and genome-wide association studies (GWAS) to identify candidate genes and genetic variants regulating LMD.

RESULTS

Five single nucleotide polymorphisms (SNPs) located on porcine chromosome 17 were significantly associated with LMD in Yorkshire pigs. A 10 kb quantitative trait locus (QTL) was identified as a candidate functional genomic region through the integration of linkage disequilibrium and linkage analysis (LDLA) and high-throughput chromosome conformation capture (Hi-C) analysis. The BMP2 gene was identified as a candidate gene for LMD based on the integrated results of GWAS, Hi-C meta-analysis, and cis-regulatory element data. The identified QTL region was further verified through target region sequencing. Furthermore, through using dual-luciferase assays and electrophoretic mobility shift assays (EMSA), two SNPs, including SNP rs321846600, located in the enhancer region, and SNP rs1111440035, located in the promoter region, were identified as candidate SNPs that may be functionally related to the LMD.

CONCLUSIONS

Based on the results of GWAS, Hi-C, and cis-regulatory elements, the BMP2 gene was identified as an important candidate gene regulating variation in LMD. The SNPs rs321846600 and rs1111440035 were identified as candidate SNPs that are functionally related to the LMD of Yorkshire pigs. Our results shed light on the advantages of integrating GWAS with 3D epigenomics in identifying candidate genes for quantitative traits. This study is a pioneering work for the identification of candidate genes and related genetic variants regulating one key production trait (LMD) in pigs by integrating genome-wide association studies and 3D epigenomics.

摘要

背景

全基因组关联研究(GWAS)和 3D 表观基因组学的综合分析不足,限制了对与肉质相关性状的遗传机制的深入理解。随着 ChIP-seq 和 Hi-C 等技术的应用,猪基因组中顺式调控元件的注释已经建立,这为阐明遗传机制和鉴定与重要经济性状显著相关的主要遗传变异和候选基因提供了新的机会。在这些性状中,腰肉深度(LMD)是一个重要的性状,因为它影响瘦肉含量。在这项研究中,我们整合了顺式调控元件和全基因组关联研究(GWAS),以鉴定调节 LMD 的候选基因和遗传变异。

结果

在约克夏猪中,有 5 个单核苷酸多态性(SNP)位于猪 17 号染色体上,与 LMD 显著相关。通过连锁不平衡和连锁分析(LDLA)与高通量染色体构象捕获(Hi-C)分析的整合,确定了一个 10kb 的数量性状位点(QTL)作为候选功能基因组区域。基于 GWAS、Hi-C 元分析和顺式调控元件数据的综合结果,确定 BMP2 基因为 LMD 的候选基因。通过目标区域测序进一步验证了所确定的 QTL 区域。此外,通过双荧光素酶测定和电泳迁移率变动分析(EMSA),确定了两个 SNP,包括位于增强子区域的 SNP rs321846600 和位于启动子区域的 SNP rs1111440035,作为可能与 LMD 功能相关的候选 SNP。

结论

基于 GWAS、Hi-C 和顺式调控元件的结果,确定 BMP2 基因为调节 LMD 变异的重要候选基因。SNP rs321846600 和 rs1111440035 被确定为与约克夏猪 LMD 功能相关的候选 SNP。我们的研究结果表明,将 GWAS 与 3D 表观基因组学相结合,用于鉴定数量性状的候选基因具有优势。本研究通过整合全基因组关联研究和 3D 表观基因组学,鉴定了调节一个关键生产性状(LMD)的候选基因和相关遗传变异,这是一项开创性的工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/da41179f1ac6/pgen.1010820.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/8bc4cbe9cdd9/pgen.1010820.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/99bf13298988/pgen.1010820.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/6a1657482a33/pgen.1010820.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/5acc2242900d/pgen.1010820.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/f808b131d4e4/pgen.1010820.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/71a0032b9971/pgen.1010820.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/da41179f1ac6/pgen.1010820.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/8bc4cbe9cdd9/pgen.1010820.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/99bf13298988/pgen.1010820.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/6a1657482a33/pgen.1010820.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/5acc2242900d/pgen.1010820.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/f808b131d4e4/pgen.1010820.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/71a0032b9971/pgen.1010820.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f47/10313041/da41179f1ac6/pgen.1010820.g007.jpg

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