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Aligning functional network constraint to evolutionary outcomes

Wollenberg Valero, Katharina C.

Authors

Katharina C. Wollenberg Valero



Abstract

Background. Functional constraint through genomic architecture is suggested to be an important dimension of genome evolution, but quantitative evidence for this idea is rare. In this contribution, existing evidence and discussions on genomic architecture as constraint for convergent evolution, rapid adaptation, and genic adaptation are summarized into alternative, testable hypotheses. Network architecture statistics from protein-protein interaction networks are then used to calculate differences in evolutionary outcomes on the example of genomic evolution among yeast, and the results are used to evaluate statistical support for these longstanding hypotheses. Results.A discriminant function analysis lent statistical support to classifying the yeast interactome into hub, intermediate and peripheral nodes based on network neighborhood connectivity, betweenness centrality, and average shortest path length. Quantitative support for the existence of genomic architecture as mechanistic basis for evolutionary constraint is then revealed through utilizing these statistical parameters of the protein-protein interaction network in combination with estimators of protein evolution. Conclusions.As functional genetic networks are becoming increasingly available, it will now be possible to evaluate functional genetic network constraint against variables describing complex phenotypes and environments, for better understanding of commonly observed deterministic patterns of evolution in non-model organisms. The hypothesis framework and methodological approach outlined herein may help to quantify the extrinsic versus intrinsic dimensions of evolutionary constraint, and result in a better understanding of how fast, effectively, or deterministically organisms adapt.

Citation

Wollenberg Valero, K. C. (2020). Aligning functional network constraint to evolutionary outcomes. BMC evolutionary biology, 20(1), Article 58. https://doi.org/10.1186/s12862-020-01613-8

Journal Article Type Article
Acceptance Date Apr 15, 2020
Online Publication Date May 24, 2020
Publication Date May 24, 2020
Deposit Date Apr 14, 2020
Publicly Available Date Apr 20, 2020
Journal BMC Evolutionary Biology
Print ISSN 1471-2148
Electronic ISSN 1471-2148
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 20
Issue 1
Article Number 58
DOI https://doi.org/10.1186/s12862-020-01613-8
Keywords Evolution; Constraint; Adaptation; Systems biology
Public URL https://hull-repository.worktribe.com/output/1591942
Publisher URL https://bmcevolbiol.biomedcentral.com/articles/10.1186/s12862-020-01613-8

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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.


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Copyright Statement
© The Author(s). 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the
data made available in this article, unless otherwise stated in a credit line to the data.





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