Abstract
The Next-Generation Sequencing technology has enormously eased the bacterial genome sequencing and several tens of thousands of genomes have been sequenced during the last 10 years. Most of the genome projects are published as draft version, however, for certain applications the complete genome sequence is required.
In this chapter, we describe the strategy that allowed the complete genome sequencing of Mycobacterium neoaurum NRRL B-3805, an industrial strain exploited for steroid production, using Ion Torrent sequencing reads and the genome of a close strain as the reference. This protocol can be applied to analyze the genetic variations between closely related strains; for example, to elucidate the point mutations between a parental strain and a random mutagenesis-derived mutant.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Fleischmann RD, Adams MD, White O et al (1995) Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 269:496–512
Binnewies TT, Motro Y, Hallin PF et al (2006) Ten years of bacterial genome sequencing: comparative-genomics-based discoveries. Funct Integr Genomics 6:165–185
Margulies M, Egholm M, Altman WE et al (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437:376–380
Shendure J, Porreca GJ, Reppas NB et al (2005) Accurate multiplex polony sequencing of an evolved bacterial genome. Science 309:1728–1732
Buermans HPJ, den Dunnen JT (2014) Next generation sequencing technology: advances and applications. Biochim Biophys Acta 1842:1932–1941
Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet 17:333–351
Land M, Hauser L, Jun SR et al (2015) Insights from 20 years of bacterial genome sequencing. Funct Integr Genomics 15:141–161
Koren S, Phillippy AM (2015) One chromosome, one contig: complete microbial genomes from long-read sequencing and assembly. Curr Opin Microbiol 23:110–120
Hoffmann S, Otto C, Kurtz S et al (2009) Fast mapping of short sequences with mismatches, insertions and deletions using index structures. PLoS Comput Biol 5:e1000502
Caboche S, Audebert C, Lemoine Y et al (2014) Comparison of mapping algorithms used in high-throughput sequencing: application to Ion Torrent data. BMC Genomics 15:264
Bonfield JK, Whitwham A (2010) Gap5—editing the billion fragment sequence assembly. Bioinformatics 26:1699–1703
Gurevich A, Saveliev V, Vyahhi N et al (2013) QUAST: quality assessment tool for genome assemblies. Bioinformatics 29:1072–1075
Hoffmann S, Otto C, Doose G et al (2014) A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection. Genome Biol 15:R34
Quinlan AR, Hall IM (2010) BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26:841–842
Li H, Handsaker B, Wysoker A et al (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078–2079
Li H (2011) A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27:2987–2993
Li H (2011) Improving SNP discovery by base alignment quality. Bioinformatics 27:1157–1158
Darling ACE, Mau B, Blattner FR et al (2004) Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res 14:1394–1403
Rissman AI, Mau B, Biehl BS et al (2009) Reordering contigs of draft genomes using the Mauve aligner. Bioinformatics 25:2071–2073
Bankevich A, Nurk S, Antipov D et al (2012) SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760
Li H, Durbin R (2010) Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26:589–595
McKenna A, Hanna M, Banks E et al (2010) The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303
DePristo MA, Banks E, Poplin R et al (2011) A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43:491–498
Van der Auwera GA, Carneiro MO, Hartl C et al (2013) From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics 43:11.10.1–11.1033
Vincent AT, Derome N, Boyle B et al (2016) Next-generation sequencing (NGS) in the microbiological world: how to make the most of your money. J Microbiol Methods. doi:10.1016/j.mimet.2016.02.016
Ajay SS, Parker SCJ, Abaan HO et al (2011) Accurate and comprehensive sequencing of personal genomes. Genome Res 21:1498–1505
Shtratnikova VY, Bragin EY, Dovbnya DV et al (2014) Complete genome sequence of sterol-transforming Mycobacterium neoaurum strain VKM Ac-1815D. Genome Announc 2:12–13
Rodríguez-García A, Fernández-Alegre E, Morales A et al (2016) Complete genome sequence of “Mycobacterium neoaurum” NRRL B-3805, an androstenedione (AD) producer for industrial biotransformation of sterols. J Biotechnol 224:64–65
Acknowledgments
This work was fully supported by a grant of the European Union program ERA-IB [MySterI (EIB.12.010)] through the APCIN call of the Spanish Ministry of Economy and Competitiveness (MINECO, Spain) (PCIN-2013-024-C02-01). The authors want to thank the European Union program ERA-IB; the Spanish Ministry of Economy and Competitiveness (MINECO, Spain) and the MySterI Consortium (INBIOTEC, Pharmins Ltd., University of York, SINTEF, Technische Universität Dortmund and Gadea Biopharma S.L.). We thank J. Merino, B. Martín and A. Casenave for their excellent technical assistance.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media LLC
About this protocol
Cite this protocol
Sola-Landa, A., Rodríguez-García, A., Barreiro, C., Pérez-Redondo, R. (2017). Genome Sequencing of Steroid Producing Bacteria Using Ion Torrent Technology and a Reference Genome. In: Barredo, JL., Herráiz, I. (eds) Microbial Steroids. Methods in Molecular Biology, vol 1645. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7183-1_4
Download citation
DOI: https://doi.org/10.1007/978-1-4939-7183-1_4
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-7182-4
Online ISBN: 978-1-4939-7183-1
eBook Packages: Springer Protocols