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Ultra-deep, long-read nanopore sequencing of mock microbial community standards

View ORCID ProfileSamuel M. Nicholls, View ORCID ProfileJoshua C. Quick, Shuiquan Tang, View ORCID ProfileNicholas J. Loman
doi: https://doi.org/10.1101/487033
Samuel M. Nicholls
1Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, UK
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Joshua C. Quick
1Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, UK
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Shuiquan Tang
2Zymo Research Corporation, Irvine, California, USA
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Nicholas J. Loman
1Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, UK
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Abstract

Background Long sequencing reads are information-rich: aiding de novo assembly and reference mapping, and consequently have great potential for the study of microbial communities. However, the best approaches for analysis of long-read metagenomic data are unknown. Additionally, rigorous evaluation of bioinformatics tools is hindered by a lack of long-read data from validated samples with known composition.

Methods We sequenced two commercially-available mock communities containing ten microbial species (ZymoBIOMICS Microbial Community Standards) with Oxford Nanopore GridION and PromethION. Both communities and the ten individual species isolates were also sequenced with Illumina technology.

Data We generated 14 and 16 Gbp from GridION flowcells and 146 and 148 Gbp from PromethION flowcells for the even and log communities respectively. Read length N50 was 5.3 Kbp and 5.2 Kbp for the even and log community, respectively. Basecalls and corresponding signal data are made available (4.2 TB in total).

Results Alignment to Illumina-sequenced isolates demonstrated the expected microbial species at anticipated abundances, with the limit of detection for the lowest abundance species below 50 cells (GridION). De novo assembly of metagenomes recovered long contiguous sequences without the need for pre-processing techniques such as binning.

Conclusions We present ultra-deep, long-read nanopore datasets from a well-defined mock community. These datasets will be useful for those developing bioinformatics methods for long-read metagenomics and for the validation and comparison of current laboratory and software pipelines.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 10, 2018.
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Ultra-deep, long-read nanopore sequencing of mock microbial community standards
Samuel M. Nicholls, Joshua C. Quick, Shuiquan Tang, Nicholas J. Loman
bioRxiv 487033; doi: https://doi.org/10.1101/487033
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Ultra-deep, long-read nanopore sequencing of mock microbial community standards
Samuel M. Nicholls, Joshua C. Quick, Shuiquan Tang, Nicholas J. Loman
bioRxiv 487033; doi: https://doi.org/10.1101/487033

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