Robustness and innovation in synthetic genotype networks

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• dc.contributor.author Santos Moreno, Javier
• dc.contributor.author Tasiudi, Eve
• dc.contributor.author Kusumawardhani, Hadiastri
• dc.contributor.author Stelling, Joerg
• dc.contributor.author Schaerli, Yolanda
• dc.date.accessioned 2023-09-21T07:01:43Z
• dc.date.available 2023-09-21T07:01:43Z
• dc.date.issued 2023
• dc.description.abstract Genotype networks are sets of genotypes connected by small mutational changes that share the same phenotype. They facilitate evolutionary innovation by enabling the exploration of different neighborhoods in genotype space. Genotype networks, first suggested by theoretical models, have been empirically confirmed for proteins and RNAs. Comparative studies also support their existence for gene regulatory networks (GRNs), but direct experimental evidence is lacking. Here, we report the construction of three interconnected genotype networks of synthetic GRNs producing three distinct phenotypes in Escherichia coli. Our synthetic GRNs contain three nodes regulating each other by CRISPR interference and governing the expression of fluorescent reporters. The genotype networks, composed of over twenty different synthetic GRNs, provide robustness in face of mutations while enabling transitions to innovative phenotypes. Through realistic mathematical modeling, we quantify robustness and evolvability for the complete genotype-phenotype map and link these features mechanistically to GRN motifs. Our work thereby exemplifies how GRN evolution along genotype networks might be driving evolutionary innovation.
• dc.format.mimetype application/pdf
• dc.identifier.citation Santos-Moreno J, Tasiudi E, Kusumawardhani H, Stelling J, Schaerli Y. Robustness and innovation in synthetic genotype networks. Nat Commun. 2023;14:2454. DOI: 10.1038/s41467-023-38033-3
• dc.identifier.doi http://dx.doi.org/10.1038/s41467-023-38033-3
• dc.identifier.issn 2041-1723
• dc.identifier.uri http://hdl.handle.net/10230/57933
• dc.language.iso eng
• dc.publisher Nature Research
• dc.relation.ispartof Nat Commun. 2023;14:2454
• dc.rights © The Author(s) 2023. 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/
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Evolvability
• dc.subject.keyword Regulatory networks
• dc.subject.keyword Robustness
• dc.subject.keyword Synthetic biology
• dc.title Robustness and innovation in synthetic genotype networks
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion