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<p>The capacity of a plasmid to express genes is constrained by its length and copy number. However, the interplay between these parameters and their constraints on plasmid evolution have remained elusive due to the absence of comprehensive quantitative analyses. Here, we present ‘Pseudoalignment and Probabilistic Iterative Read Assignment’ (pseuPIRA), a computational method that overcomes previous computational bottlenecks, enabling rapid and accurate determination of plasmid copy numbers at large scale. We apply pseuPIRA to all microbial genomes in the NCBI RefSeq database with linked short-read sequencing data (4644 bacterial and archaeal genomes including 12,006 plasmids). The analysis reveals three scaling laws of plasmids: first, an inverse power-law correlation between plasmid copy number and plasmid length; second, a positive linear correlation between protein-coding genes and plasmid length; and third, a positive correlation between metabolic genes per plasmid and plasmid length, particularly for large plasmids. These scaling laws imply fundamental constraints on plasmid evolution and functional organization, indicating that as plasmids increase in length, they converge toward chromosomal characteristics in copy number and functional content.</p>

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Scaling laws of bacterial and archaeal plasmids

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月2日

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  • Rohan Maddamsetti,
  • Irida Shyti,
  • Maggie L. Wilson,
  • Hye-In Son,
  • Yasa Baig,
  • Zhengqing Zhou,
  • Jia Lu,
  • Lingchong You

摘要

The capacity of a plasmid to express genes is constrained by its length and copy number. However, the interplay between these parameters and their constraints on plasmid evolution have remained elusive due to the absence of comprehensive quantitative analyses. Here, we present ‘Pseudoalignment and Probabilistic Iterative Read Assignment’ (pseuPIRA), a computational method that overcomes previous computational bottlenecks, enabling rapid and accurate determination of plasmid copy numbers at large scale. We apply pseuPIRA to all microbial genomes in the NCBI RefSeq database with linked short-read sequencing data (4644 bacterial and archaeal genomes including 12,006 plasmids). The analysis reveals three scaling laws of plasmids: first, an inverse power-law correlation between plasmid copy number and plasmid length; second, a positive linear correlation between protein-coding genes and plasmid length; and third, a positive correlation between metabolic genes per plasmid and plasmid length, particularly for large plasmids. These scaling laws imply fundamental constraints on plasmid evolution and functional organization, indicating that as plasmids increase in length, they converge toward chromosomal characteristics in copy number and functional content.