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Grant support

We thank James Cotterell, Johannes Jaeger, Anton Crombach, Fyodor Kondrashov, Onuralp Soylemez, Karl Wotton, Jose M. Sancho, Kai Dierkes, and Ben Lenher for discussion. This work was supported by the la Caixa International PhD Programme.

Analysis of institutional authors

Jimenez AAuthorMunteanu AAuthorSharpe JCorresponding Author

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March 25, 2020
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Article

Dynamics of gene circuits shapes evolvability

Publicated to:Proceedings Of The National Academy Of Sciences Of The United States Of America. 112 (7): 2103-2108 - 2015-02-17 112(7), DOI: 10.1073/pnas.1411065112

Authors: Jiménez, A; Munteanu, A; Sharpe, J

Affiliations

and Institucio Catalana de Recerca i Estudis Avancats, 08010 Barcelona, Spain james.sharpe@crg.eu. - Author
and.;European Molecular Biology Laboratory-CRG Systems Biology Program, Centre for Genomic Regulation (CRG), and Universitat Pompeu Fabra, 08003 Barcelona, Spain - Author
CRG, European Mol Biol Lab, CRG Syst Biol Program, Barcelona 08003, Spain - Author
European Molecular Biology Laboratory-CRG Systems Biology Program, Centre for Genomic Regulation (CRG), and Universitat Pompeu Fabra, 08003 Barcelona, Spain - Author
Inst Catalana Recerca & Estudis Avancats, Barcelona 08010, Spain - Author
Univ Pompeu Fabra, Barcelona 08003, Spain - Author
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Abstract

To what extent does the dynamical mechanism producing a specific biological phenotype bias the ability to evolve into novel phenotypes? We use the interpretation of a morphogen gradient into a single stripe of gene expression as a model phenotype. Although there are thousands of three-gene circuit topologies that can robustly develop a stripe of gene expression, the vast majority of these circuits use one of just six fundamentally different dynamical mechanisms. Here we explore the potential for gene circuits that use each of these six mechanisms to evolve novel phenotypes such as multiple stripes, inverted stripes, and gradients of gene expression. Through a comprehensive and systematic analysis, we find that circuits that use alternative mechanisms differ in the likelihood of reaching novel phenotypes through mutation. We characterize the phenotypic transitions and identify key ingredients of the evolutionary potential, such as sensitive interactions and phenotypic hubs. Finally, we provide an intuitive understanding on how the modular design of a particular mechanism favors the access to novel phenotypes. Our work illustrates how the dynamical mechanism by which an organism develops constrains how it can evolve. It is striking that these dynamical mechanisms and their impact on evolvability can be observed even for such an apparently simple patterning task, performed by just three-node circuits.

Keywords

Design principlesDevelopmental constraintsDynamical mechanismEmergenceEvolutionEvolvabilityGenerationGenotype-phenotype mapsGenotype–phenotype mapsModelMorphogen gradientsNetworksPhenotypic innovationRobustness

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Proceedings Of The National Academy Of Sciences Of The United States Of America due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2015, it was in position 4/62, thus managing to position itself as a Q1 (Primer Cuartil), in the category Multidisciplinary Sciences.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 4.32, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-05, the following number of citations:

  • WoS: 28
  • Scopus: 19
  • Europe PMC: 15

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-05:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 147.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 147 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 19.958.
  • The number of mentions on the social network X (formerly Twitter): 23 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (JIMÉNEZ ASINS, ALBA) .

the author responsible for correspondence tasks has been SHARPE, JAMES.