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PGAP2: A comprehensive toolkit for prokaryotic pan-genome analysis based on fine-grained feature networks

Author

Listed:
  • Congfan Bu

    (China National Center for Bioinformation
    Chinese Academy of Sciences)

  • Hao Zhang

    (China National Center for Bioinformation
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Fengnian Zhang

    (University of Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Wenhao Liang

    (University of Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Hao Gao

    (China National Center for Bioinformation
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jing Zhao

    (China National Center for Bioinformation
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Fangming Lv

    (China National Center for Bioinformation
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Ruikun Xue

    (China National Center for Bioinformation
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Qian Liu

    (Chinese Academy of Sciences)

  • Zhewen Zhang

    (China National Center for Bioinformation
    Chinese Academy of Sciences)

  • Zhong Jin

    (Chinese Academy of Sciences)

  • Jingfa Xiao

    (China National Center for Bioinformation
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

Pan-genome analysis is a crucial method for studying genomic dynamics. By creating pan-genome maps for prokaryotic organisms, we can gain valuable insights into their genetic diversity and ecological adaptability. However, current analytical methods often struggle to balance accuracy and computational efficiency, and they tend to provide primarily qualitative results. This study introduces PGAP2, an integrated software package that simplifies various processes, including data quality control, pan-genome analysis, and result visualization. PGAP2 facilitates the rapid and accurate identification of orthologous and paralogous genes by employing fine-grained feature analysis within constrained regions. Our systematic evaluation with simulated and gold-standard datasets demonstrates that PGAP2 is more precise, robust, and scalable than state-of-the-art tools for large-scale pan-genome data. Furthermore, PGAP2 introduces four quantitative parameters derived from the distances between or within clusters, enabling detailed characterization of homology clusters. Finally, we validate our quantitative findings by applying PGAP2 to construct a pan-genomic profile of 2794 zoonotic Streptococcus suis strains. This analysis offers new insights into the genetic diversity of S. suis, thereby enhancing our understanding of its genomic structure. PGAP2 is freely available at https://github.com/bucongfan/PGAP2 .

Suggested Citation

  • Congfan Bu & Hao Zhang & Fengnian Zhang & Wenhao Liang & Hao Gao & Jing Zhao & Fangming Lv & Ruikun Xue & Qian Liu & Zhewen Zhang & Zhong Jin & Jingfa Xiao, 2025. "PGAP2: A comprehensive toolkit for prokaryotic pan-genome analysis based on fine-grained feature networks," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-64846-5
    DOI: 10.1038/s41467-025-64846-5
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    References listed on IDEAS

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