2 Search Results for "Elworth, Ryan A. Leo"


Document
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, and Todd J. Treangen

Published in: LIPIcs, Volume 143, 19th International Workshop on Algorithms in Bioinformatics (WABI 2019)


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.

Cite as

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)


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@InProceedings{wang_et_al:LIPIcs.WABI.2019.19,
  author =	{Wang, Qi and Elworth, R. A. Leo and Liu, Tian Rui and Treangen, Todd J.},
  title =	{{Faster Pan-Genome Construction for Efficient Differentiation of Naturally Occurring and Engineered Plasmids with Plaster}},
  booktitle =	{19th International Workshop on Algorithms in Bioinformatics (WABI 2019)},
  pages =	{19:1--19:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-123-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{143},
  editor =	{Huber, Katharina T. and Gusfield, Dan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2019.19},
  URN =		{urn:nbn:de:0030-drops-110492},
  doi =		{10.4230/LIPIcs.WABI.2019.19},
  annote =	{Keywords: comparative genomics, sequence alignment, pan-genome, engineered plasmids}
}
Document
DGEN: A Test Statistic for Detection of General Introgression Scenarios

Authors: Ryan A. Leo Elworth, Chabrielle Allen, Travis Benedict, Peter Dulworth, and Luay Nakhleh

Published in: LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)


Abstract
When two species hybridize, one outcome is the integration of genetic material from one species into the genome of the other, a process known as introgression. Detecting introgression in genomic data is a very important question in evolutionary biology. However, given that hybridization occurs between closely related species, a complicating factor for introgression detection is the presence of incomplete lineage sorting, or ILS. The D-statistic, famously referred to as the "ABBA-BABA" test, was proposed for introgression detection in the presence of ILS in data sets that consist of four genomes. More recently, D_FOIL - a set of statistics - was introduced to extend the D-statistic to data sets of five genomes. The major contribution of this paper is demonstrating that the invariants underlying both the D-statistic and D_FOIL can be derived automatically from the probability mass functions of gene tree topologies under the null species tree model and alternative phylogenetic network model. Computational requirements aside, this automatic derivation provides a way to generalize these statistics to data sets of any size and with any scenarios of introgression. We demonstrate the accuracy of the general statistic, which we call D_GEN, on simulated data sets with varying rates of introgression, and apply it to an empirical data set of mosquito genomes. We have implemented D_GEN and made it available, both as a graphical user interface tool and as a command-line tool, as part of the freely available, open-source software package ALPHA (https://github.com/chilleo/ALPHA).

Cite as

Ryan A. Leo Elworth, Chabrielle Allen, Travis Benedict, Peter Dulworth, and Luay Nakhleh. DGEN: A Test Statistic for Detection of General Introgression Scenarios. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 19:1-19:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{elworth_et_al:LIPIcs.WABI.2018.19,
  author =	{Elworth, Ryan A. Leo and Allen, Chabrielle and Benedict, Travis and Dulworth, Peter and Nakhleh, Luay},
  title =	{{DGEN: A Test Statistic for Detection of General Introgression Scenarios}},
  booktitle =	{18th International Workshop on Algorithms in Bioinformatics (WABI 2018)},
  pages =	{19:1--19:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-082-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{113},
  editor =	{Parida, Laxmi and Ukkonen, Esko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.19},
  URN =		{urn:nbn:de:0030-drops-93218},
  doi =		{10.4230/LIPIcs.WABI.2018.19},
  annote =	{Keywords: Introgression, genealogies, phylogenetic networks}
}
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