解开遗传密码:鸡细胞介导免疫的全基因组关联研究和基因组富集分析。

IF 3.5 2区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Somayeh Kianpoor, Alireza Ehsani, Rasoul Vaez Torshizi, Ali Akbar Masoudi, Mohammad Reza Bakhtiarizadeh
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引用次数: 0

摘要

背景:家禽免疫系统对于抵御传染病、保持健康和生产力至关重要。细胞介导的免疫反应(CMIs)保护生物体免受细胞内病原体的侵害。本研究旨在通过对与鸡的细胞介导免疫反应有关的几个系统基因组富集分析(GSEA),丰富全基因组关联研究(GWAS)的结果:为了研究细胞免疫系统的功能,根据二硝基氯苯(DNCB)溶液浸渍前后皮肤厚度的差异收集了表型数据。此外,还使用 Illumina 60k SNP BeadChip 对阿里安肉鸡和乌尔米耶土鸡 F2 代的 312 只杂交鸡进行了基因分型。使用带有 FDR 的一般线性模型 (GLM) 结果:GWAS 发现了与 CMI 性状相关的 147 个 SNP,涉及 1363 个基因。这些基因在 8 个 KEGG 通路、22 个 Reactome 通路和 18 个生物过程中明显富集。通过 PPI 网络分析,确定了 26 个枢纽基因。三个枢纽基因 PSMA3、PSMC2 和 PSMB4 几乎富集在所有与细胞免疫相关的通路中,包括蛋白酶体、白细胞介素-1 信号转导和程序性细胞死亡通路,这使它们成为参与 CMI 的重要候选基因。此外,MAP3K8、NLRC5、UBB、CASP6、DAPK2、TNFRSF6B、TNFSF15 和 PIK3CD 基因被鉴定为多个功能通路中的关键基因。在干扰素-γ QTL中总共发现了10个SNPs,在细胞介导免疫反应QTL区域发现了2个SNPs,从而鉴定出12个细胞免疫反应相关基因,这些基因在之前的研究中被报告为重要候选基因:结论:本研究中的后GWAS分析发现了调控鸡细胞免疫生物学过程的关键基因。因此,选择表达这些基因的鸡可以提高鸡的免疫力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unlocking the genetic code: a comprehensive Genome-Wide association study and gene set enrichment analysis of cell-mediated immunity in chickens.

Background: The poultry immune system is essential for protecting against infectious diseases and maintaining health and productivity. Cell-mediated immune responses (CMIs) protect organisms against intracellular pathogens. This study aimed to enrich the findings of genome-wide association studies (GWAS) by including several systematic gene set enrichment analyses (GSEA) related to cell-mediated immune responses in chickens.

Methods: To investigate the function of the cellular immune system, phenotypic data were collected based on the differences in skin thickness before and after impregnation with dinitrochlorobenzene (DNCB) solution. Additionally, 312 hybrid birds of the F2 generation of Arian broiler chickens and Urmia native chickens were genotyped using the Illumina 60k SNP BeadChip. A general linear model (GLM) with an FDR < 5% was used for the association analysis. Functional enrichment analysis of the identified candidate genes was performed using the Enrichr database. A protein‒protein interaction (PPI) network was constructed using the STRING database. In addition, colocalization analysis was applied to identify QTLs related to the immune system.

Results: GWAS revealed 147 SNPs associated with the CMI trait, which were related to 1363 genes. These genes were significantly enriched in eight KEGG pathways, 22 Reactome pathways, and 18 biological processes. PPI network analysis led to the identification of 26 hub genes. The three hub genes PSMA3, PSMC2 and PSMB4 were enriched in almost all pathways related to cellular immunity, including the proteasome, interleukin-1 signaling, and programmed cell death pathways, which makes them important candidates involved in CMI. In addition, the MAP3K8, NLRC5, UBB, CASP6, DAPK2, TNFRSF6B, TNFSF15, and PIK3CD genes were identified as key genes in several functional pathways. A total of 10 SNPs were found in interferon-gamma QTLs, and two SNPs were found in the cell-mediated immune response QTL region, leading to the identification of 12 cellular immune response-related genes that were reported as important candidates in previous studies.

Conclusion: The post-GWAS analysis in this study led to the identification of key genes that regulate the biological processes of cellular immunity in chickens. Therefore, selecting birds that excel in expressing such genes can improve immunity in chickens.

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来源期刊
BMC Genomics
BMC Genomics 生物-生物工程与应用微生物
CiteScore
7.40
自引率
4.50%
发文量
769
审稿时长
6.4 months
期刊介绍: BMC Genomics is an open access, peer-reviewed journal that considers articles on all aspects of genome-scale analysis, functional genomics, and proteomics. BMC Genomics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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