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Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
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Benchmarking genome assemblers for four bacterial models based on contiguity, correctness, and completeness.

Hanzel Rojas-Miranda1, Vanessa Madrigal-Ly2, Jose Arturo Molina-Mora3

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|November 29, 2025
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Summary

Benchmarking de novo genome assembly strategies reveals hybrid approaches using Unicycler offer optimal contiguity, correctness, and completeness for bacterial genomes. Moderate sequencing coverage is sufficient for high-quality results.

Keywords:
De Novo genome assembly3 C criterionBenchmarkingPan-assemblyProkaryotes

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • De novo genome assembly reconstructs genomes without a reference.
  • Assembly outcomes vary based on sequencing technology and algorithms.
  • Pan-assembly encompasses diverse assemblies for a single genome.

Purpose of the Study:

  • To benchmark pan-assemblies for prokaryotic models (B. henselae, E. coli, P. aeruginosa, X. fastidiosa).
  • To evaluate the impact of sequencing attributes on assembly metrics (contiguity, correctness, completeness).
  • To identify optimal conditions for de novo genome assembly.

Main Methods:

  • Comparative analysis of short-read, long-read, and hybrid sequencing strategies.
  • Evaluation of different assembly algorithms (Unicycler, Megahit, Canu, Wengan).
  • Assessment of assembly quality using the 3C criteria (contiguity, correctness, completeness).

Main Results:

  • Short-read strategies yield high correctness and completeness but low contiguity.
  • Long-read strategies provide high contiguity but lower completeness and accuracy.
  • Hybrid strategies, particularly with Unicycler, offer the best overall performance across all 3C metrics.
  • Assembly quality is not significantly improved by excessive coverage depth beyond a minimum threshold.

Conclusions:

  • The hybrid approach using Unicycler is the most effective general strategy for de novo bacterial genome assembly.
  • Optimized experimental and bioinformatics conditions can be derived from pan-assembly benchmarking.
  • High-quality genome assemblies are achievable with moderate sequencing coverage, reducing costs.