TELLBASE: a novel tool of TELL-seq barcode-assisted scaffold assembler for bacterial genomes

Transposase enzyme linked long-read sequencing (TELL-seq) technology generates barcode-linked reads, facilitating whole-genome sequencing (WGS), and complete assembly with improved accuracy and reduced costs. Unlike mate-pair sequencing technology, TELL-seq employs a near-full-sequence tagging strategy that allows more efficient capture of comprehensive genomic information. However, assembly algorithms and software capable of fully leveraging the characteristics of TELL-seq technology to effectively assemble genomic sequences at the megabase-scale are lacking, particularly for bacteria and their plasmids. In this study, we present TELL-seq barcode-assisted scaffold assembler (TELLBASE), a de novo genome assembler designed specifically for assembling bacterial genomes using TELL-seq-derived linked reads. In assembly tests involving bacteria such as Acinetobacter baumannii, Klebsiella pneumoniae, Mycobacterium tuberculosis, and Staphylococcus aureus, TELLBASE exhibited exceptional efficacy in producing chromosome-level bacterial genomic sequences and successful identification of plasmids present in the sequenced strains. Comparative analysis revealed that TELLBASE significantly outperforms existing assemblers tailored for TELL-seq-derived linked reads, such as TuringAssembler and Ariadne, in terms of the completeness and accuracy of the assembled genomes. Therefore, TELLBASE shows promising potential for refining draft bacterial genomes and further applications in related fields. The package for TELLBASE is freely available on GitHub (https://github.com/sosie1/TELLBASE).

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Publication Details

Journal
Briefings in Bioinformatics
Published
2025-08-31
DOI
https://doi.org/10.1093/bib/bbaf504
Primary Topic
Genomics and Phylogenetic Studies
Type
article
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article

TELLBASE: a novel tool of TELL-seq barcode-assisted scaffold assembler for bacterial genomes

Qian Yu, Tiantao Kuang, Yutong Li, Chenqi Lu et al.
Briefings in Bioinformatics
Genomics and Phylogenetic Studies
article

TELLBASE: a novel tool of TELL-seq barcode-assisted scaffold assembler for bacterial genomes

Qian Yu, Tiantao Kuang, Yutong Li, Chenqi Lu, Tao Xu, Yi Zhang, Chen Chen, Wenhong Zhang, Jing Wu, Ning Jiang, Hanxiao Du, Ziqing Xiao, Yiwen Chen
article en

Abstract

Transposase enzyme linked long-read sequencing (TELL-seq) technology generates barcode-linked reads, facilitating whole-genome sequencing (WGS), and complete assembly with improved accuracy and reduced costs. Unlike mate-pair sequencing technology, TELL-seq employs a near-full-sequence tagging strategy that allows more efficient capture of comprehensive genomic information. However, assembly algorithms and software capable of fully leveraging the characteristics of TELL-seq technology to effectively assemble genomic sequences at the megabase-scale are lacking, particularly for bacteria and their plasmids. In this study, we present TELL-seq barcode-assisted scaffold assembler (TELLBASE), a de novo genome assembler designed specifically for assembling bacterial genomes using TELL-seq-derived linked reads. In assembly tests involving bacteria such as Acinetobacter baumannii, Klebsiella pneumoniae, Mycobacterium tuberculosis, and Staphylococcus aureus, TELLBASE exhibited exceptional efficacy in producing chromosome-level bacterial genomic sequences and successful identification of plasmids present in the sequenced strains. Comparative analysis revealed that TELLBASE significantly outperforms existing assemblers tailored for TELL-seq-derived linked reads, such as TuringAssembler and Ariadne, in terms of the completeness and accuracy of the assembled genomes. Therefore, TELLBASE shows promising potential for refining draft bacterial genomes and further applications in related fields. The package for TELLBASE is freely available on GitHub (https://github.com/sosie1/TELLBASE).

Briefings in BioinformaticsVol. 26(5)
Fudan University (CN), National Supercomputing Center in Wuxi (CN), Huashan Hospital (CN), Institute of Infection and Immunity (CA)
Openalex Percentile: Top 76%
Genomics and Phylogenetic Studies
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