A complete bacterial genome assembled de novo using only nanopore sequencing data

Nicholas J Loman; Joshua Quick; Jared T Simpson

doi:10.1038/nmeth.3444

A complete bacterial genome assembled de novo using only nanopore sequencing data

Nicholas J Loman, Joshua Quick, Jared T Simpson

Biosciences

Research output: Contribution to journal › Article › peer-review

476 Citations (Scopus)

Abstract

We have assembled de novo the Escherichia coli K-12 MG1655 chromosome in a single 4.6-Mb contig using only nanopore data. Our method has three stages: (i) overlaps are detected between reads and then corrected by a multiple-alignment process; (ii) corrected reads are assembled using the Celera Assembler; and (iii) the assembly is polished using a probabilistic model of the signal-level data. The assembly reconstructs gene order and has 99.5% nucleotide identity.

Original language	English
Pages (from-to)	733-5
Number of pages	3
Journal	Nature Methods
Volume	12
Issue number	8
DOIs	https://doi.org/10.1038/nmeth.3444
Publication status	Published - Aug 2015

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10.1038/nmeth.3444

Development of robust analytical pipelines for the analysis of microbial community data from clinical samples
Loman, N. (Principal Investigator)
Medical Research Council
1/09/12 → 31/08/15
Project: Research Councils

Cite this

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title = "A complete bacterial genome assembled de novo using only nanopore sequencing data",

abstract = "We have assembled de novo the Escherichia coli K-12 MG1655 chromosome in a single 4.6-Mb contig using only nanopore data. Our method has three stages: (i) overlaps are detected between reads and then corrected by a multiple-alignment process; (ii) corrected reads are assembled using the Celera Assembler; and (iii) the assembly is polished using a probabilistic model of the signal-level data. The assembly reconstructs gene order and has 99.5\% nucleotide identity.",

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A complete bacterial genome assembled de novo using only nanopore sequencing data

Abstract

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Projects

Development of robust analytical pipelines for the analysis of microbial community data from clinical samples

Cite this