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Reconstruction of ancestral genomes in presence of gene gain and loss

Pavel Avdeyev, Shuai Jiang, Sergey Aganezov, Fei Hu, Max A. Alekseyev
doi: https://doi.org/10.1101/040196
Pavel Avdeyev
*Computational Biology Institute & Department of Mathematics, The George Washington University, Washington, DC, U.S.A.
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Shuai Jiang
*Computational Biology Institute & Department of Mathematics, The George Washington University, Washington, DC, U.S.A.
†Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, U.S.A.
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Sergey Aganezov
*Computational Biology Institute & Department of Mathematics, The George Washington University, Washington, DC, U.S.A.
‡Department of Higher Mathematics, ITMO University, St. Petersburg, Russia
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Fei Hu
†Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, U.S.A.
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Max A. Alekseyev
*Computational Biology Institute & Department of Mathematics, The George Washington University, Washington, DC, U.S.A.
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  • For correspondence: maxal@gwu.edu
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Abstract

Since most dramatic genomic changes are caused by genome rearrangements as well as gene duplications and gain/loss events, it becomes crucial to understand their mechanisms and reconstruct ancestral genomes of the given genomes. This problem was shown to be NP-complete even in the “simplest” case of three genomes, thus calling for heuristic rather than exact algorithmic solutions. At the same time, a larger number of input genomes may actually simplify the problem in practice as it was earlier illustrated with MGRA, a state-of-the-art software tool for reconstruction of ancestral genomes of multiple genomes.

One of the key obstacles for MGRA and other similar tools is presence of breakpoint reuses when the same breakpoint region is broken by several different genome rearrangements in the course of evolution. Furthermore, such tools are often limited to genomes composed of the same genes with each gene present in a single copy in every genome. This limitation makes these tools inapplicable for many biological datasets and degrades the resolution of ancestral reconstructions in diverse datasets.

We address these deficiencies by extending the MGRA algorithm to genomes with unequal gene contents. The developed next-generation tool MGRA2 can handle gene gain/loss events and shares the ability of MGRA to reconstruct ancestral genomes uniquely in the case of limited breakpoint reuse. Furthermore, MGRA2 employs a number of novel heuristics to cope with higher breakpoint reuse and process datasets inaccessible for MGRA. In practical experiments, MGRA2 shows superior performance for simulated and real genomes as compared to other ancestral genomes reconstruction tools. The MGRA2 tool is distributed as an open-source software and can be downloaded from GitHub repository http://github.com/ablab/mgra/. It is also available in the form of a web-server at http://mgra.cblab.org, which makes it readily accessible for inexperienced users.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 19, 2016.
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Reconstruction of ancestral genomes in presence of gene gain and loss
Pavel Avdeyev, Shuai Jiang, Sergey Aganezov, Fei Hu, Max A. Alekseyev
bioRxiv 040196; doi: https://doi.org/10.1101/040196
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Reconstruction of ancestral genomes in presence of gene gain and loss
Pavel Avdeyev, Shuai Jiang, Sergey Aganezov, Fei Hu, Max A. Alekseyev
bioRxiv 040196; doi: https://doi.org/10.1101/040196

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