Fate of a Duplicate in a Network Context

Soyer, Orkun S.

doi:10.1002/9780470619902.ch12

Cited by 2 publications

(2 citation statements)

References 59 publications

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“…The relevance of selection to PPI network evolution has been a topic of considerable debate [82], particularly in the context of higher-order network features, such as modularity. A number of authors have argued that specific selection programs are required to generate modular networks, such as oscillation between different evolutionary goals [83][84][85][86][87][88]. However, previous work has shown that gene duplication by itself, in the absence of both natural selection and neofunctionalization, can generate modular networks [89,90].…”

Section: Discussionmentioning

confidence: 99%

Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

et al. 2012

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We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein’s neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.

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Section: Discussionmentioning

confidence: 99%

Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

et al. 2012

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“…The reason is that gene products construct phenotypic traits through their interactions with other gene products. Indeed, Soyer argues that many of the contradictions between theoretical predictions and empirical evidence regarding gene duplication may occur because of not taking into account the complexity of genetic interactions [ 51 ]. Therefore, we need to understand how the effect of a gene duplication percolates through the mesh of gene interactions.…”

Section: Introductionmentioning

confidence: 99%

Early effects of gene duplication on the robustness and phenotypic variability of gene regulatory networks

Posadas-García

Espinosa‐Soto

2022

BMC Bioinformatics

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Background Research on gene duplication is abundant and comes from a wide range of approaches, from high-throughput analyses and experimental evolution to bioinformatics and theoretical models. Notwithstanding, a consensus is still lacking regarding evolutionary mechanisms involved in evolution through gene duplication as well as the conditions that affect them. We argue that a better understanding of evolution through gene duplication requires considering explicitly that genes do not act in isolation. It demands studying how the perturbation that gene duplication implies percolates through the web of gene interactions. Due to evolution’s contingent nature, the paths that lead to the final fate of duplicates must depend strongly on the early stages of gene duplication, before gene copies have accumulated distinctive changes. Methods Here we use a widely-known model of gene regulatory networks to study how gene duplication affects network behavior in early stages. Such networks comprise sets of genes that cross-regulate. They organize gene activity creating the gene expression patterns that give cells their phenotypic properties. We focus on how duplication affects two evolutionarily relevant properties of gene regulatory networks: mitigation of the effect of new mutations and access to new phenotypic variants through mutation. Results Among other observations, we find that those networks that are better at maintaining the original phenotype after duplication are usually also better at buffering the effect of single interaction mutations and that duplication tends to enhance further this ability. Moreover, the effect of mutations after duplication depends on both the kind of mutation and genes involved in it. We also found that those phenotypes that had easier access through mutation before duplication had higher chances of remaining accessible through new mutations after duplication. Conclusion Our results support that gene duplication often mitigates the impact of new mutations and that this effect is not merely due to changes in the number of genes. The work that we put forward helps to identify conditions under which gene duplication may enhance evolvability and robustness to mutations.

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Fate of a Duplicate in a Network Context

Cited by 2 publications

References 59 publications

Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

Early effects of gene duplication on the robustness and phenotypic variability of gene regulatory networks

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