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An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population

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Abstract

Sequencing-based genome-wide association studies (GWAS) have facilitated the identification of causal associations between genetic variants and traits in diverse species. However, it is cost-prohibitive for the majority of research groups to sequence a large number of samples. Here, we carried out genotype imputation to increase the density of single nucleotide polymorphisms in a large-scale Swine F2 population using a reference panel including 117 individuals, followed by a series of GWAS analyses. The imputation accuracies reached 0.89 and 0.86 for allelic concordance and correlation, respectively. A quantitative trait nucleotide (QTN) affecting the chest vertebrate was detected directly, while the investigation of another QTN affecting the residual glucose failed due to the presence of similar haplotypes carrying wild-type and mutant allelesin the reference panel used in this study. A high imputation accuracy was confirmed by Sanger sequencing technology for the most significant loci. Two candidate genes, CPNE5 and MYH3, affecting meat-related traits were proposed. Collectively, we illustrated four scenarios in imputation-based GWAS that may be encountered by researchers, and our results will provide an extensive reference for future genotype imputation-based GWAS analyses in the future.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (31640046 and 31760656) and the National Key Research and Development Program of China (2020YFA0509500).

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Authors and Affiliations

  1. State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China

    Guorong Yan, Xianxian Liu, Shijun Xiao, Wenshui Xin, Wenwu Xu, Yiping Li, Tao Huang, Jiangtao Qin, Lei Xie, Junwu Ma, Zhiyan Zhang & Lusheng Huang

  2. Institute of Photomedicine, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, 200092, China

    Guorong Yan

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  1. Guorong Yan
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An Imputed Whole-genome Sequence-based GWAS Approach Pinpoints Causal Mutations for Complex Traits in a Specific Swine Populations

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Yan, G., Liu, X., Xiao, S. et al. An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population. Sci. China Life Sci. 65, 781–794 (2022). https://doi.org/10.1007/s11427-020-1960-9

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