两个母猪系免疫性状的全基因组关联的多元分析。

Multivariate genome-wide associations for immune traits in two maternal pig lines.

机构信息

Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany.

BHZP GmbH, An der Wassermühle 8, 21368, Dahlenburg-Ellringen, Germany.

出版信息

BMC Genomics. 2023 Aug 28;24(1):492. doi: 10.1186/s12864-023-09594-w.

DOI:10.1186/s12864-023-09594-w

PMID:37641029

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10463314/

Abstract

BACKGROUND

Immune traits are considered to serve as potential biomarkers for pig's health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between immune traits can be used to identify pleiotropic genetic markers. Therefore, genome-wide association study (GWAS) approaches are required to explore the joint genetic foundation for health biomarkers. Usually, GWAS explores phenotypes in a univariate (uv), trait-by-trait manner. Besides two uv GWAS methods, four multivariate (mv) GWAS approaches were applied on combinations out of 22 immune traits for Landrace (LR) and Large White (LW) pig lines.

RESULTS

In total 433 (LR: 351, LW: 82) associations were identified with the uv approach implemented in PLINK and a Bayesian linear regression uv approach (BIMBAM) software. Single Nucleotide Polymorphisms (SNPs) that were identified with both uv approaches (n = 32) were mostly associated with immune traits such as haptoglobin, red blood cell characteristics and cytokines, and were located in protein-coding genes. Mv GWAS approaches detected 647 associations for different mv immune trait combinations which were summarized to 133 Quantitative Trait Loci (QTL). SNPs for different trait combinations (n = 66) were detected with more than one mv method. Most of these SNPs are associated with red blood cell related immune trait combinations. Functional annotation of these QTL revealed 453 immune-relevant protein-coding genes. With uv methods shared markers were not observed between the breeds, whereas mv approaches were able to detect two conjoint SNPs for LR and LW. Due to unmapped positions for these markers, their functional annotation was not clarified.

CONCLUSIONS

This study evaluated the joint genetic background of immune traits in LR and LW piglets through the application of various uv and mv GWAS approaches. In comparison to uv methods, mv methodologies identified more significant associations, which might reflect the pleiotropic background of the immune system more accurately. In genetic research of complex traits, the SNP effects are generally small. Furthermore, one genetic variant can affect several correlated immune traits at the same time, termed pleiotropy. As mv GWAS methods consider strong dependencies among traits, the power to detect SNPs can be boosted. Both methods revealed immune-relevant potential candidate genes. Our results indicate that one single test is not able to detect all the different types of genetic effects in the most powerful manner and therefore, the methods should be applied complementary.

摘要

背景

免疫特性被认为是猪健康的潜在生物标志物。一些免疫特性表现出中高遗传力，表明这些表型存在遗传变异性。考虑到之前已经建立的免疫特性之间的遗传相关性，可以用于识别多效性遗传标记。因此，需要全基因组关联研究（GWAS）方法来探索健康生物标志物的共同遗传基础。通常，GWAS 以单变量（uv）、逐个性状的方式探索表型。除了两种 uvGWAS 方法外，还应用了四种多变量（mv）GWAS 方法，对长白猪（LR）和大白猪（LW）猪系的 22 种免疫特性进行了组合。

结果

总共在 PLINK 中实施的 uv 方法和贝叶斯线性回归 uv 方法（BIMBAM）软件中鉴定了 433 个（LR：351，LW：82）关联。通过两种 uv 方法鉴定的单核苷酸多态性（SNP）（n=32）主要与结合珠蛋白、红细胞特征和细胞因子等免疫特性相关，并且位于蛋白质编码基因中。不同 mv 免疫特性组合的 mvGWAS 方法检测到 647 个关联，这些关联被总结为 133 个数量性状基因座（QTL）。不同性状组合的 SNP（n=66）被多种 mv 方法检测到。这些 SNP 中的大多数与红细胞相关的免疫特性组合有关。这些 QTL 的功能注释显示了 453 个与免疫相关的蛋白质编码基因。在品种之间，uv 方法没有观察到共享标记，而 mv 方法能够检测到 LR 和 LW 的两个共同 SNP。由于这些标记的位置未映射，因此未对其功能进行注释。

结论

本研究通过应用各种 uv 和 mvGWAS 方法，评估了 LR 和 LW 仔猪免疫特性的共同遗传背景。与 uv 方法相比，mv 方法鉴定出更多显著的关联，这可能更准确地反映免疫系统的多效性背景。在复杂性状的遗传研究中，SNP 效应通常较小。此外，一个遗传变异可以同时影响几个相关的免疫性状，称为多效性。由于 mvGWAS 方法考虑了性状之间的强依赖性，因此可以提高检测 SNP 的能力。两种方法都揭示了与免疫相关的潜在候选基因。我们的研究结果表明，单一测试不能以最有效的方式检测到所有不同类型的遗传效应，因此，这些方法应该互补应用。