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HyLight: Strain aware assembly of low coverage metagenomes

Author

Listed:
  • Xiongbin Kang

    (Hunan University
    Bielefeld University)

  • Wenhai Zhang

    (Hunan University)

  • Yichen Li

    (Hunan University)

  • Xiao Luo

    (Hunan University)

  • Alexander Schönhuth

    (Bielefeld University)

Abstract

Different strains of identical species can vary substantially in terms of their spectrum of biomedically relevant phenotypes. Reconstructing the genomes of microbial communities at the level of their strains poses significant challenges, because sequencing errors can obscure strain-specific variants. Next-generation sequencing (NGS) reads are too short to resolve complex genomic regions. Third-generation sequencing (TGS) reads, although longer, are prone to higher error rates or substantially more expensive. Limiting TGS coverage to reduce costs compromises the accuracy of the assemblies. This explains why prior approaches agree on losses in strain awareness, accuracy, tendentially excessive costs, or combinations thereof. We introduce HyLight, a metagenome assembly approach that addresses these challenges by implementing the complementary strengths of TGS and NGS data. HyLight employs strain-resolved overlap graphs (OG) to accurately reconstruct individual strains within microbial communities. Our experiments demonstrate that HyLight produces strain-aware and contiguous assemblies at minimal error content, while significantly reducing costs because utilizing low-coverage TGS data. HyLight achieves an average improvement of 19.05% in preserving strain identity and demonstrates near-complete strain awareness across diverse datasets. In summary, HyLight offers considerable advances in metagenome assembly, insofar as it delivers significantly enhanced strain awareness, contiguity, and accuracy without the typical compromises observed in existing approaches.

Suggested Citation

  • Xiongbin Kang & Wenhai Zhang & Yichen Li & Xiao Luo & Alexander Schönhuth, 2024. "HyLight: Strain aware assembly of low coverage metagenomes," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-52907-0
    DOI: 10.1038/s41467-024-52907-0
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    References listed on IDEAS

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    1. Riccardo Vicedomini & Christopher Quince & Aaron E. Darling & Rayan Chikhi, 2021. "Strainberry: automated strain separation in low-complexity metagenomes using long reads," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
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