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. 2025 Jul 17;15(14):2114.
doi: 10.3390/ani15142114.

Genome-Wide Association Study of Immune Indices in Yaks

Daoning Yu  1   2   3 , Xiaoming Ma  1   2 , Chun Huang  1   2 , Tong Wang  1   2 , Mengfan Zhang  1   2 , Fen Feng  1   2 , Xiaoyun Wu  1   2 , Yongfu La  1   2 , Xian Guo  1   2 , Ping Yan  1   2 , Derong Zhang  3 , Chunnian Liang  1   2
Affiliations

Genome-Wide Association Study of Immune Indices in Yaks

Daoning Yu et al. Animals (Basel). .

Abstract

The yak is a vital livestock resource on the Qinghai-Tibet Plateau, renowned for its strong disease resistance and high-quality meat. However, various diseases pose significant threats to its health and lead to substantial economic losses. Current feeding management practices, along with available drugs and vaccines, have demonstrated limited effectiveness in preventing and controlling infectious diseases. Additionally, challenges such as drug resistance and the safety of animal products persist. Therefore, enhancing the disease-resistant breeding capacity of yaks is crucial. In this study, we examined 192 yaks by measuring the concentrations of 10 immune indicators in serum by using the ELISA method and conducting whole-genome resequencing, which identified 19,182,942 SNP loci. Through genome-wide association analysis, we detected 323 significant SNPs located near or within 125 candidate genes, most of which are associated with disease and significantly enriched in the TGF-β signaling pathway. Overall, our study identified a series of novel variants and candidate genes associated with disease resistance traits in yaks, providing important information for the molecular breeding of disease resistance in yaks. These results not only contribute to a deeper understanding of the function of disease resistance genes in yaks but also hold great potential for accelerating precision disease resistance breeding in yaks.

Keywords: GWAS; SNP; immune indices; resequencing; yak.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Figures

Figure 1
Figure 1
Heat map of correlation coefficient matrices for 10 immune traits.
Figure 2
Figure 2
(A). Principal component analysis results. (B). Linkage disequilibrium (LD) decay analysis. (C) Results of G-matrix analysis of genetic relationships among Niangya yak populations. The horizontal and vertical coordinates are 192 individual Niangya yaks. Each small square represents the genetic relationship between two individuals. The closer the color is to red, the closer the genetic relationship between two individuals is, and vice versa.
Figure 3
Figure 3
Manhattan and QQ plots of humoral immune correlations. (A) Immunoglobulin A, (B) Immunoglobulin G, and (C) Immunoglobulin M. The red dashed line is the threshold of −log10 (p-value), and points beyond the threshold range are significantly correlated sites.
Figure 4
Figure 4
Manhattan and QQ plots related to inflammation indicators. (A) C-reactive protein, (B) Haptoglobin. The red dashed line is the threshold of −log10 (p-value), and points beyond the threshold range are significantly correlated sites.
Figure 5
Figure 5
Cytokine-related Manhattan and QQ plots. (A) Interleukin-2, (B) Interleukin-4, (C) Interleukin-6, (D) Interferon γ, and (E) Tumor necrosis factor α. The red dashed line is the threshold of −log10 (p-value), and points beyond the threshold range are significantly correlated sites.
Figure 6
Figure 6
GO enrichment analysis of genes at significantly associated loci.
See this image and copyright information in PMC

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