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Sci Data. 2015 Apr 14;2:150014. doi: 10.1038/sdata.2015.14. eCollection 2015.

Sequence data for Clostridium autoethanogenum using three generations of sequencing technologies.

Author information

1
Graduate School of Genome Science and Technology, University of Tennessee , Knoxville, Tennessee 37919, USA.
2
Biosciences Division, Oak Ridge National Laboratory , Oak Ridge, Tennessee 37831, USA.
3
Department of Plant and Microbial Biology, North Carolina State University , Raleigh, North Carolina 27695, USA.
4
Department of Biological and Agricultural Engineering, North Carolina State University , Raleigh, North Carolina 27695, USA.
5
LanzaTech , Skokie, Illinois 60077, USA.
6
Graduate School of Genome Science and Technology, University of Tennessee , Knoxville, Tennessee 37919, USA ; Biosciences Division, Oak Ridge National Laboratory , Oak Ridge, Tennessee 37831, USA.

Abstract

During the past decade, DNA sequencing output has been mostly dominated by the second generation sequencing platforms which are characterized by low cost, high throughput and shorter read lengths for example, Illumina. The emergence and development of so called third generation sequencing platforms such as PacBio has permitted exceptionally long reads (over 20 kb) to be generated. Due to read length increases, algorithm improvements and hybrid assembly approaches, the concept of one chromosome, one contig and automated finishing of microbial genomes is now a realistic and achievable task for many microbial laboratories. In this paper, we describe high quality sequence datasets which span three generations of sequencing technologies, containing six types of data from four NGS platforms and originating from a single microorganism, Clostridium autoethanogenum. The dataset reported here will be useful for the scientific community to evaluate upcoming NGS platforms, enabling comparison of existing and novel bioinformatics approaches and will encourage interest in the development of innovative experimental and computational methods for NGS data.

PMID:
25977818
PMCID:
PMC4409012
DOI:
10.1038/sdata.2015.14
[Indexed for MEDLINE]
Free PMC Article

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