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Faster Pan-Genome Construction for Efficient Differentiation of Naturally Occurring and Engineered Plasmids with Plaster

Authors Qi Wang , R. A. Leo Elworth , Tian Rui Liu , Todd J. Treangen

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Author Details

Qi Wang
  • Systems, Synthetic, and Physical Biology (SSPB) Graduate Program, Rice University, Houston, TX 77005, USA
R. A. Leo Elworth
  • Department of Computer Science, Rice University, Houston, TX 77005, USA
Tian Rui Liu
  • Department of Computer Science, Rice University, Houston, TX 77005, USA
Todd J. Treangen
  • Department of Computer Science, Rice University, Houston, TX 77005, USA

Funding

  • Wang, Qi: Q. W. was supported by funds from Rice University and by funds from the National Institute for Neurological Disorders and Stroke (NINDS) of the National Institutes of Health under award number R21NS106640.
  • Elworth, R. A. Leo: R. A. L. E. was supported by the National Science Foundation (DMS-1547433) and was partially supported by the FunGCAT program from the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via the Army Research Office (ARO) under Federal Award No. W911NF-17-2-0089.
  • Liu, Tian Rui: T.R.L. was supported by funds from Rice University.
  • Treangen, Todd J.: T.J.T was supported by startup funds from Rice University and was partially supported by the FunGCAT program from the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via the Army Research Office (ARO) under Federal Award No. W911NF-17-2-0089.

Acknowledgements

The authors would like to thank Dr. Caleb Bashor for critical discussion and feedback, and Dr. Joanne Kamens from Addgene for providing full access to the synthetic plasmids utilized in this study. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the ODNI, IARPA, ARO, or the US Government.

Cite As Get BibTex

Qi Wang, R. A. Leo Elworth, Tian Rui Liu, and Todd J. Treangen. Faster Pan-Genome Construction for Efficient Differentiation of Naturally Occurring and Engineered Plasmids with Plaster. In 19th International Workshop on Algorithms in Bioinformatics (WABI 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 143, pp. 19:1-19:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.WABI.2019.19

Abstract

As sequence databases grow, characterizing diversity across extremely large collections of genomes requires the development of efficient methods that avoid costly all-vs-all comparisons [Marschall et al., 2018]. In addition to exponential increases in the amount of natural genomes being sequenced, improved techniques for the creation of human engineered sequences is ushering in a new wave of synthetic genome sequence databases that grow alongside naturally occurring genome databases. In this paper, we analyze the full diversity of available sequenced natural and synthetic plasmid genome sequences. This diversity can be represented by a data structure that captures all presently available nucleotide sequences, known as a pan-genome. In our case, we construct a single linear pan-genome nucleotide sequence that captures this diversity. To process such a large number of sequences, we introduce the plaster algorithmic pipeline. Using plaster we are able to construct the full synthetic plasmid pan-genome from 51,047 synthetic plasmid sequences as well as a natural pan-genome from 6,642 natural plasmid sequences. We demonstrate the efficacy of plaster by comparing its speed against another pan-genome construction method as well as demonstrating that nearly all plasmids align well to their corresponding pan-genome. Finally, we explore the use of pan-genome sequence alignment to distinguish between naturally occurring and synthetic plasmids. We believe this approach will lead to new techniques for rapid characterization of engineered plasmids. Applications for this work include detection of genome editing, tracking an unknown plasmid back to its lab of origin, and identifying naturally occurring sequences that may be of use to the synthetic biology community. The source code for fully reconstructing the natural and synthetic plasmid pan-genomes as well for plaster are publicly available and can be downloaded at https://gitlab.com/qiwangrice/plaster.git.

Subject Classification

ACM Subject Classification
  • Applied computing → Bioinformatics
  • Applied computing → Molecular sequence analysis
  • Applied computing → Computational genomics
Keywords
  • comparative genomics
  • sequence alignment
  • pan-genome
  • engineered plasmids

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