Sign epistasis caused by hierarchy within signalling cascades
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Supporting information
Published version
Author(s)
Nghe, Philippe
Kogenaru, Manjunatha
Tans, Sander J
Type
Journal Article
Abstract
Sign epistasis is a central evolutionary constraint, but its causal factors remain difficult to predict. Here we use the notion of parameterised optima to explain epistasis within a signalling cascade, and test these predictions in Escherichia coli. We show that sign epistasis arises from the benefit of tuning phenotypic parameters of cascade genes with respect to each other, rather than from their complex and incompletely known genetic bases. Specifically, sign epistasis requires only that the optimal phenotypic parameters of one gene depend on the phenotypic parameters of another, independent of other details, such as activating or repressing nature, position within the cascade, intra-genic pleiotropy or genotype. Mutational effects change sign more readily in downstream genes, indicating that optimising downstream genes is more constrained. The findings show that sign epistasis results from the inherent upstream-downstream hierarchy between signalling cascade genes, and can be addressed without exhaustive genotypic mapping.
Date Issued
2018-04-13
Date Acceptance
2018-02-27
Citation
NATURE COMMUNICATIONS, 2018, 9 (1)
ISSN
2041-1723
Publisher
NATURE PUBLISHING GROUP
Journal / Book Title
NATURE COMMUNICATIONS
Volume
9
Issue
1
Copyright Statement
© 2018 The Author(s). 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 license, and indicate if changes were made. The images or other third party
material in this article are included in the article
’
s Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
article
’
s Creative Commons license 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 license, visit
http://creativecommons.org/
licenses/by/4.0/.
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 license, and indicate if changes were made. The images or other third party
material in this article are included in the article
’
s Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
article
’
s Creative Commons license 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 license, visit
http://creativecommons.org/
licenses/by/4.0/.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000429921000008&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
EVOLUTION
NETWORKS
MODEL
LANDSCAPES
MUTATIONS
PROTEINS
PATHS
Publication Status
Published
Article Number
ARTN 1451
Date Publish Online
2018-04-13