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SwinePan for pig graph-based pangenome and multiomics data mining

    • 1State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong 510642, China;
    • 2National and Regional Livestock and Poultry Gene Bank, Guangdong Gene Bank of Livestock and Poultry, South China Agricultural University, Guangzhou, Guangdong 510642, China;
    • 3Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong 510642, China;
    • 4Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu, Guangdong 527300, China;
    • 5Guangdong Zhongxin Breeding Technology Company, Limited, Guangzhou, Guangdong 511458, China
    • 6 These authors contributed equally to this work.
Published September 16, 2026. https://doi.org/10.1101/gr.281750.125
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cover of Genome Research Vol 36 Issue 10
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Abstract

Pigs are one of the most important livestock species worldwide. Although multiple high-quality reference genomes exist, reliance on a single linear reference limits the detection of structural variants (SVs) and the characterization of population-specific genetic diversity. To address this limitation, we developed SwinePan, a comprehensive and integrated multiomic database for pigs built on a graph-based pangenome framework. SwinePan incorporates a variome derived from the graph-based pangenome, covering 2598 individuals across 35 breeds, including 185,759 SVs, 117 million SNPs, and 6.8 million indels. The database also integrates transcriptomic data from liver, loin muscle, abdominal fat, and backfat, along with more than 150,000 phenotypic records. The online toolkit deployed in SwinePan enables genome-wide association studies (GWAS), expression quantitative trait locus (eQTL) mapping, and colocalization, whereas interactive modules visualize population structure and multiomic associations, streamlining candidate gene and variant exploration. Additionally, two proof-of-concept analyses demonstrate how SwinePan pinpoints trait-associated loci and deciphers their potential regulatory mechanisms.

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