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Engineering and Analyzing Multicellular Systems pp 165–188Cite as

Identification of Mutations in Laboratory-Evolved Microbes from Next-Generation Sequencing Data Using breseq

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1151))

Abstract

Next-generation DNA sequencing (NGS) can be used to reconstruct eco-evolutionary population dynamics and to identify the genetic basis of adaptation in laboratory evolution experiments. Here, we describe how to run the open-source breseq computational pipeline to identify and annotate genetic differences found in whole-genome and whole-population NGS data from haploid microbes where a high-quality reference genome is available. These methods can also be used to analyze mutants isolated in genetic screens and to detect unintended mutations that may occur during strain construction and genome editing.

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Acknowledgements

D.E.D. was supported by a University of Texas at Austin CPRIT Cancer Research Traineeship. Development of breseq has been supported by an NSF Postdoctoral Research Fellowship in Biological Informatics (DBI-0630687) and by grants from the NSF BEACON Center for the Study of Evolution in Action (DBI-0939454), NIH (R00-GM087550), and CPRIT (RP130124) to J.E.B. Additional programmers and users who have provided valuable feedback and bug reports are thanked in the breseq documentation.

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Authors and Affiliations

  1. Department of Molecular Biosciences, Center for Systems and Synthetic Biology, Center for Computational Biology and Bioinformatics, Institute for Cellular and Molecular Biology, The University of Texas at Austin, 1 University Station A5300, Austin, TX, 78712, USA

    Daniel E. Deatherage & Jeffrey E. Barrick

Authors
  1. Daniel E. Deatherage
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  2. Jeffrey E. Barrick
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Corresponding author

Correspondence to Jeffrey E. Barrick .

Editor information

Editors and Affiliations

  1. School of Life Sciences, University of Science & Technology of China,, Hefei, Anhui, China

    Lianhong Sun

  2. Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

    Wenying Shou

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Deatherage, D.E., Barrick, J.E. (2014). Identification of Mutations in Laboratory-Evolved Microbes from Next-Generation Sequencing Data Using breseq . In: Sun, L., Shou, W. (eds) Engineering and Analyzing Multicellular Systems. Methods in Molecular Biology, vol 1151. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0554-6_12

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  • DOI: https://doi.org/10.1007/978-1-4939-0554-6_12

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0553-9

  • Online ISBN: 978-1-4939-0554-6

  • eBook Packages: Springer Protocols

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