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Posadas-García YS, Espinosa-Soto C. Early effects of gene duplication on the robustness and phenotypic variability of gene regulatory networks. BMC Bioinformatics 2022; 23:509. [DOI: 10.1186/s12859-022-05067-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 11/18/2022] [Indexed: 11/29/2022] Open
Abstract
Abstract
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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2
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Manicka S, Marques-Pita M, Rocha LM. Effective connectivity determines the critical dynamics of biochemical networks. J R Soc Interface 2022; 19:20210659. [PMID: 35042384 PMCID: PMC8767216 DOI: 10.1098/rsif.2021.0659] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 12/02/2021] [Indexed: 11/12/2022] Open
Abstract
Living systems comprise interacting biochemical components in very large networks. Given their high connectivity, biochemical dynamics are surprisingly not chaotic but quite robust to perturbations-a feature C.H. Waddington named canalization. Because organisms are also flexible enough to evolve, they arguably operate in a critical dynamical regime between order and chaos. The established theory of criticality is based on networks of interacting automata where Boolean truth values model presence/absence of biochemical molecules. The dynamical regime is predicted using network connectivity and node bias (to be on/off) as tuning parameters. Revising this to account for canalization leads to a significant improvement in dynamical regime prediction. The revision is based on effective connectivity, a measure of dynamical redundancy that buffers automata response to some inputs. In both random and experimentally validated systems biology networks, reducing effective connectivity makes living systems operate in stable or critical regimes even though the structure of their biochemical interaction networks predicts them to be chaotic. This suggests that dynamical redundancy may be naturally selected to maintain living systems near critical dynamics, providing both robustness and evolvability. By identifying how dynamics propagates preferably via effective pathways, our approach helps to identify precise ways to design and control network models of biochemical regulation and signalling.
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Affiliation(s)
- Santosh Manicka
- Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, USA
- Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal
| | - Manuel Marques-Pita
- Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, USA
- Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal
- Universidade Lusófona, CICANT and COPELABS, Campo Grande 388, 1700-097 Lisbon, Portugal
| | - Luis M. Rocha
- Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, USA
- Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal
- Binghamton University, State University of New York, Binghamton, NY, USA
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3
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Borriello E, Walker SI, Laubichler MD. Cell phenotypes as macrostates of the GRN dynamics. JOURNAL OF EXPERIMENTAL ZOOLOGY PART B-MOLECULAR AND DEVELOPMENTAL EVOLUTION 2020; 334:213-224. [DOI: 10.1002/jez.b.22938] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 02/16/2020] [Accepted: 02/17/2020] [Indexed: 01/04/2023]
Affiliation(s)
- Enrico Borriello
- ASU‐SFI Center for Biosocial Complex SystemsArizona State UniversityTempe Arizona
| | - Sara I. Walker
- ASU‐SFI Center for Biosocial Complex SystemsArizona State UniversityTempe Arizona
- Beyond Center for Fundamental Concepts in ScienceArizona State UniversityTempe Arizona
- School of Earth and Space ExplorationArizona State UniversityTempe Arizona
- Blue Marble Space Institute of ScienceSeattle Washington
| | - Manfred D. Laubichler
- ASU‐SFI Center for Biosocial Complex SystemsArizona State UniversityTempe Arizona
- Santa Fe InstituteSanta Fe New Mexico
- Marine Biological LaboratoryWoods Hole Massachusetts
- School of Life SciencesArizona State UniversityTempe Arizona
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4
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Blankers T, Berdan EL, Hennig RM, Mayer F. Physical linkage and mate preference generate linkage disequilibrium for behavioral isolation in two parapatric crickets. Evolution 2019; 73:777-791. [PMID: 30820950 PMCID: PMC6593781 DOI: 10.1111/evo.13706] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 02/04/2019] [Indexed: 12/23/2022]
Abstract
Behavioral isolation is a potent barrier to gene flow and a source of striking diversity in the animal kingdom. However, it remains unclear if the linkage disequilibrium (LD) between sex‐specific traits required for behavioral isolation results mostly from physical linkage between signal and preference loci or from directional mate preferences. Here, we test this in the field crickets Gryllus rubens and G. texensis. These closely related species diverged with gene flow and have strongly differentiated songs and preference functions for the mate calling song rhythm. We map quantitative trait loci for signal and preference traits (pQTL) as well as for gene expression associated with these traits (eQTL). We find strong, positive genetic covariance between song traits and between song and preference. Our results show that this is in part explained by incomplete physical linkage: although both linked pQTL and eQTL couple male and female traits, major effect loci for different traits were never on the same chromosome. We suggest that the finely tuned, highly divergent preference functions are likely an additional source of LD between male and female traits in this system. Furthermore, pleiotropy of gene expression presents an underappreciated mechanism to link sexually dimorphic phenotypes.
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Affiliation(s)
- Thomas Blankers
- Department of Behavioral Physiology, Humboldt-Universität zu Berlin, Berlin, Germany.,Leibniz Institute for Evolution and Biodiversity Science, Museum für Naturkunde Berlin, Berlin, Germany.,Current address: Department of Evolutionary and Population Biology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Emma L Berdan
- Leibniz Institute for Evolution and Biodiversity Science, Museum für Naturkunde Berlin, Berlin, Germany.,Current address: Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
| | - R Matthias Hennig
- Department of Behavioral Physiology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Frieder Mayer
- Leibniz Institute for Evolution and Biodiversity Science, Museum für Naturkunde Berlin, Berlin, Germany.,Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany
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5
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Correia RB, Gates AJ, Wang X, Rocha LM. CANA: A Python Package for Quantifying Control and Canalization in Boolean Networks. Front Physiol 2018; 9:1046. [PMID: 30154728 PMCID: PMC6102667 DOI: 10.3389/fphys.2018.01046] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 07/13/2018] [Indexed: 01/11/2023] Open
Abstract
Logical models offer a simple but powerful means to understand the complex dynamics of biochemical regulation, without the need to estimate kinetic parameters. However, even simple automata components can lead to collective dynamics that are computationally intractable when aggregated into networks. In previous work we demonstrated that automata network models of biochemical regulation are highly canalizing, whereby many variable states and their groupings are redundant (Marques-Pita and Rocha, 2013). The precise charting and measurement of such canalization simplifies these models, making even very large networks amenable to analysis. Moreover, canalization plays an important role in the control, robustness, modularity and criticality of Boolean network dynamics, especially those used to model biochemical regulation (Gates and Rocha, 2016; Gates et al., 2016; Manicka, 2017). Here we describe a new publicly-available Python package that provides the necessary tools to extract, measure, and visualize canalizing redundancy present in Boolean network models. It extracts the pathways most effective in controlling dynamics in these models, including their effective graph and dynamics canalizing map, as well as other tools to uncover minimum sets of control variables.
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Affiliation(s)
- Rion B. Correia
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States
- CAPES Foundation, Ministry of Education of Brazil, Brasília, Brazil
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Alexander J. Gates
- Center for Complex Networks Research, Northeastern University, Boston, MA, United States
| | - Xuan Wang
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States
| | - Luis M. Rocha
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
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6
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Green RM, Fish JL, Young NM, Smith FJ, Roberts B, Dolan K, Choi I, Leach CL, Gordon P, Cheverud JM, Roseman CC, Williams TJ, Marcucio RS, Hallgrímsson B. Developmental nonlinearity drives phenotypic robustness. Nat Commun 2017; 8:1970. [PMID: 29213092 PMCID: PMC5719035 DOI: 10.1038/s41467-017-02037-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Accepted: 11/02/2017] [Indexed: 12/22/2022] Open
Abstract
Robustness to perturbation is a fundamental feature of complex organisms. Mutations are the raw material for evolution, yet robustness to their effects is required for species survival. The mechanisms that produce robustness are poorly understood. Nonlinearities are a ubiquitous feature of development that may link variation in development to phenotypic robustness. Here, we manipulate the gene dosage of a signaling molecule, Fgf8, a critical regulator of vertebrate development. We demonstrate that variation in Fgf8 expression has a nonlinear relationship to phenotypic variation, predicting levels of robustness among genotypes. Differences in robustness are not due to gene expression variance or dysregulation, but emerge from the nonlinearity of the genotype–phenotype curve. In this instance, embedded features of development explain robustness differences. How such features vary in natural populations and relate to genetic variation are key questions for unraveling the origin and evolvability of this feature of organismal development. Developmental processes often involve nonlinearities, but the consequences for translating genotype to phenotype are not well characterized. Here, Green et al. vary Fgf8 signaling across allelic series of mice and show that phenotypic robustness in craniofacial shape is explained by a nonlinear effect of Fgf8 expression.
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Affiliation(s)
- Rebecca M Green
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Jennifer L Fish
- Department of Biological Sciences, University of Massachusetts Lowell, Lowell, MA, 01854, USA
| | - Nathan M Young
- Department of Orthopaedic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, 94110, USA
| | - Francis J Smith
- Department of Craniofacial Biology, School of Dental Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Benjamin Roberts
- Department of Biological Sciences, University of Massachusetts Lowell, Lowell, MA, 01854, USA
| | - Katie Dolan
- Department of Biological Sciences, University of Massachusetts Lowell, Lowell, MA, 01854, USA
| | - Irene Choi
- Department of Craniofacial Biology, School of Dental Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Courtney L Leach
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Paul Gordon
- Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - James M Cheverud
- Department of Biology, Loyola University Chicago, Chicago, IL, 60660, USA
| | - Charles C Roseman
- Department of Animal Biology, University of Illinois Urbana Champaign, Urbana, IL, 61801, USA
| | - Trevor J Williams
- Department of Craniofacial Biology, School of Dental Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Ralph S Marcucio
- Department of Orthopaedic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, 94110, USA.
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.
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7
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Spiraling Complexity: A Test of the Snowball Effect in a Computational Model of RNA Folding. Genetics 2016; 206:377-388. [PMID: 28007889 DOI: 10.1534/genetics.116.196030] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Accepted: 03/03/2017] [Indexed: 01/07/2023] Open
Abstract
Genetic incompatibilities can emerge as a byproduct of genetic divergence. According to Dobzhansky and Muller, an allele that fixes in one population may be incompatible with an allele at a different locus in another population when the two alleles are brought together in hybrids. Orr showed that the number of Dobzhansky-Muller incompatibilities (DMIs) should accumulate faster than linearly-i.e., snowball-as two lineages diverge. Several studies have attempted to test the snowball effect using data from natural populations. One limitation of these studies is that they have focused on predictions of the Orr model, but not on its underlying assumptions. Here, we use a computational model of RNA folding to test both predictions and assumptions of the Orr model. Two populations are allowed to evolve in allopatry on a holey fitness landscape. We find that the number of inviable introgressions (an indicator for the number of DMIs) snowballs, but does so more slowly than expected. We show that this pattern is explained, in part, by the fact that DMIs can disappear after they have arisen, contrary to the assumptions of the Orr model. This occurs because DMIs become progressively more complex (i.e., involve alleles at more loci) as a result of later substitutions. We also find that most DMIs involve >2 loci, i.e., they are complex. Reproductive isolation does not snowball because DMIs do not act independently of each other. We conclude that the RNA model supports the central prediction of the Orr model that the number of DMIs snowballs, but challenges other predictions, as well as some of its underlying assumptions.
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8
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9
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10
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Gutiérrez J, Maere S. Modeling the evolution of molecular systems from a mechanistic perspective. TRENDS IN PLANT SCIENCE 2014; 19:292-303. [PMID: 24709144 DOI: 10.1016/j.tplants.2014.03.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2013] [Revised: 03/09/2014] [Accepted: 03/11/2014] [Indexed: 06/03/2023]
Abstract
Systems biology-inspired genotype-phenotype mapping models are increasingly being used to study the evolutionary properties of molecular biological systems, in particular the general emergent properties of evolving systems, such as modularity, robustness, and evolvability. However, the level of abstraction at which many of these models operate might not be sufficient to capture all relevant intricacies of biological evolution in sufficient detail. Here, we argue that in particular gene and genome duplications, both evolutionary mechanisms of potentially major importance for the evolution of molecular systems and of special relevance to plant evolution, are not adequately accounted for in most GPM modeling frameworks, and that more fine-grained mechanistic models may significantly advance understanding of how gen(om)e duplication impacts molecular systems evolution.
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Affiliation(s)
- Jayson Gutiérrez
- Department of Plant Systems Biology, VIB, 9052 Ghent, Belgium; Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium
| | - Steven Maere
- Department of Plant Systems Biology, VIB, 9052 Ghent, Belgium; Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium.
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11
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Cuypers TD, Hogeweg P. A synergism between adaptive effects and evolvability drives whole genome duplication to fixation. PLoS Comput Biol 2014; 10:e1003547. [PMID: 24743268 PMCID: PMC3990473 DOI: 10.1371/journal.pcbi.1003547] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2013] [Accepted: 02/11/2014] [Indexed: 11/23/2022] Open
Abstract
Whole genome duplication has shaped eukaryotic evolutionary history and has been associated with drastic environmental change and species radiation. While the most common fate of WGD duplicates is a return to single copy, retained duplicates have been found enriched for highly interacting genes. This pattern has been explained by a neutral process of subfunctionalization and more recently, dosage balance selection. However, much about the relationship between environmental change, WGD and adaptation remains unknown. Here, we study the duplicate retention pattern postWGD, by letting virtual cells adapt to environmental changes. The virtual cells have structured genomes that encode a regulatory network and simple metabolism. Populations are under selection for homeostasis and evolve by point mutations, small indels and WGD. After populations had initially adapted fully to fluctuating resource conditions re-adaptation to a broad range of novel environments was studied by tracking mutations in the line of descent. WGD was established in a minority (≈30%) of lineages, yet, these were significantly more successful at re-adaptation. Unexpectedly, WGD lineages conserved more seemingly redundant genes, yet had higher per gene mutation rates. While WGD duplicates of all functional classes were significantly over-retained compared to a model of neutral losses, duplicate retention was clearly biased towards highly connected TFs. Importantly, no subfunctionalization occurred in conserved pairs, strongly suggesting that dosage balance shaped retention. Meanwhile, singles diverged significantly. WGD, therefore, is a powerful mechanism to cope with environmental change, allowing conservation of a core machinery, while adapting the peripheral network to accommodate change. The evolution of eukaryotes is characterized by drastic changes in their genome content. Genome expansions have often occurred by duplication of the entire genome. It is generally not know whether organisms gain any adaptive advantage from these mutations. However, they appear to become fixed in response to environmental change. Many interesting whole genome duplications happened long ago in eukaryotic evolutionary history during periods of turbulent genome and species evolution. Genomic data analysis alone cannot resolve the evolutionary mechanisms and consequences of whole genome duplication. Here, we modeled evolution with whole genome duplications in a Virtual Cell model. Simulating populations that undergo a range of different environmental changes we found that next to often increasing fitness directly, whole genome duplications made lineages more evolvable and hence more able to adapt to harsh new environments. Although most duplicates are deleted in subsequent evolution, genes with many interaction partners were retained preferentially, increasing regulatory complexity. Interestingly however, we found that innovation happened most likely in the more loosely connected and less essential genes.
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Affiliation(s)
- Thomas D. Cuypers
- Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, the Netherlands
- * E-mail:
| | - Paulien Hogeweg
- Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, the Netherlands
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12
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Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks. Methods 2013; 62:39-55. [PMID: 23726941 DOI: 10.1016/j.ymeth.2013.05.013] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2012] [Revised: 11/30/2012] [Accepted: 05/21/2013] [Indexed: 12/21/2022] Open
Abstract
This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions.
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13
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Marques-Pita M, Rocha LM. Canalization and control in automata networks: body segmentation in Drosophila melanogaster. PLoS One 2013; 8:e55946. [PMID: 23520449 PMCID: PMC3592869 DOI: 10.1371/journal.pone.0055946] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2012] [Accepted: 01/03/2013] [Indexed: 12/19/2022] Open
Abstract
We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics--a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity--with the ultimate goal of explaining how do cells and tissues 'compute'.
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Affiliation(s)
- Manuel Marques-Pita
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
- Indiana University, Bloomington, Indiana, United States of America
| | - Luis M. Rocha
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
- Indiana University, Bloomington, Indiana, United States of America
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14
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Kuijper B, Pen I, Weissing FJ. A Guide to Sexual Selection Theory. ANNUAL REVIEW OF ECOLOGY EVOLUTION AND SYSTEMATICS 2012. [DOI: 10.1146/annurev-ecolsys-110411-160245] [Citation(s) in RCA: 151] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Mathematical models have played an important role in the development of sexual selection theory. These models come in different flavors and they differ in their assumptions, often in a subtle way. Similar questions can be addressed by modeling frameworks from population genetics, quantitative genetics, evolutionary game theory, or adaptive dynamics, or by individual-based simulations. Confronted with such diversity, nonspecialists may have difficulties judging the scope and limitations of the various approaches. Here we review the major modeling frameworks, highlighting their pros and cons when applied to different research questions. We also discuss recent developments, where classical models are enriched by including more detail regarding genetics, behavior, demography, and population dynamics. It turns out that some seemingly well-established conclusions of sexual selection theory are less general than previously thought. Linking sexual selection to other processes such as sex-ratio evolution or speciation also reveals that enriching the theory can lead to surprising new insights.
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Affiliation(s)
- Bram Kuijper
- Theoretical Biology Group, Center for Ecological and Evolutionary Studies, University of Groningen, 9747 AG Groningen, The Netherlands;, ,
- Behavior and Evolution Group, Department of Zoology, University of Cambridge, CB2 3EJ Cambridge, United Kingdom
| | - Ido Pen
- Theoretical Biology Group, Center for Ecological and Evolutionary Studies, University of Groningen, 9747 AG Groningen, The Netherlands;, ,
| | - Franz J. Weissing
- Theoretical Biology Group, Center for Ecological and Evolutionary Studies, University of Groningen, 9747 AG Groningen, The Netherlands;, ,
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15
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Hindré T, Knibbe C, Beslon G, Schneider D. New insights into bacterial adaptation through in vivo and in silico experimental evolution. Nat Rev Microbiol 2012; 10:352-65. [PMID: 22450379 DOI: 10.1038/nrmicro2750] [Citation(s) in RCA: 112] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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16
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Cuypers TD, Hogeweg P. Virtual genomes in flux: an interplay of neutrality and adaptability explains genome expansion and streamlining. Genome Biol Evol 2012; 4:212-29. [PMID: 22234601 PMCID: PMC3318439 DOI: 10.1093/gbe/evr141] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The picture that emerges from phylogenetic gene content reconstructions is that genomes evolve in a dynamic pattern of rapid expansion and gradual streamlining. Ancestral organisms have been estimated to possess remarkably rich gene complements, although gene loss is a driving force in subsequent lineage adaptation and diversification. Here, we study genome dynamics in a model of virtual cells evolving to maintain homeostasis. We observe a pattern of an initial rapid expansion of the genome and a prolonged phase of mutational load reduction. Generally, load reduction is achieved by the deletion of redundant genes, generating a streamlining pattern. Load reduction can also occur as a result of the generation of highly neutral genomic regions. These regions can expand and contract in a neutral fashion. Our study suggests that genome expansion and streamlining are generic patterns of evolving systems. We propose that the complex genotype to phenotype mapping in virtual cells as well as in their biological counterparts drives genome size dynamics, due to an emerging interplay between adaptation, neutrality, and evolvability.
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Affiliation(s)
- Thomas D Cuypers
- Department of Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.
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17
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Hogeweg P. Toward a theory of multilevel evolution: long-term information integration shapes the mutational landscape and enhances evolvability. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2012; 751:195-224. [PMID: 22821460 DOI: 10.1007/978-1-4614-3567-9_10] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Most of evolutionary theory has abstracted away from how information is coded in the genome and how this information is transformed into traits on which selection takes place. While in the earliest stages of biological evolution, in the RNA world, the mapping from the genotype into function was largely predefined by the physical-chemical properties of the evolving entities (RNA replicators, e.g. from sequence to folded structure and catalytic sites), in present-day organisms, the mapping itself is the result of evolution. I will review results of several in silico evolutionary studies which examine the consequences of evolving the genetic coding, and the ways this information is transformed, while adapting to prevailing environments. Such multilevel evolution leads to long-term information integration. Through genome, network, and dynamical structuring, the occurrence and/or effect of random mutations becomes nonrandom, and facilitates rapid adaptation. This is what does happen in the in silico experiments. Is it also what did happen in biological evolution? I will discuss some data that suggest that it did. In any case, these results provide us with novel search images to tackle the wealth of biological data.
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Affiliation(s)
- Paulien Hogeweg
- Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, The Netherlands.
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18
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Norrström N, Getz WM, Holmgren NMA. Selection against accumulating mutations in niche-preference genes can drive speciation. PLoS One 2011; 6:e29487. [PMID: 22216293 PMCID: PMC3246506 DOI: 10.1371/journal.pone.0029487] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2011] [Accepted: 11/29/2011] [Indexed: 11/18/2022] Open
Abstract
Our current understanding of sympatric speciation is that it occurs primarily through disruptive selection on ecological genes driven by competition, followed by reproductive isolation through reinforcement-like selection against inferior intermediates/heterozygotes. Our evolutionary model of selection on resource recognition and preference traits suggests a new mechanism for sympatric speciation. We find speciation can occur in three phases. First a polymorphism of functionally different phenotypes is established through evolution of specialization. On the gene level, regulatory functions have evolved in which some alleles are conditionally switched off (i.e. are silent). These alleles accumulate harmful mutations that potentially may be expressed in offspring through recombination. Second mating associated with resource preference invades because harmful mutations in parents are not expressed in the offspring when mating assortatively, thereby dividing the population into two pre-zygotically isolated resource-specialist lineages. Third, silent alleles that evolved in phase one now accumulate deleterious mutations over the following generations in a Bateson-Dobzhansky-Muller fashion, establishing a post-zygotic barrier to hybridization.
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Affiliation(s)
- Niclas Norrström
- Systems Biology Research Centre, University of Skövde, Skövde, Sweden
| | - Wayne M. Getz
- Department of Environmental Sciences, Policy and Management, University of California, Berkeley, California, United States of America
- School of Mathematical Sciences, University of KwaZulu-Natal, Durban, South Africa
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19
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Uller T, Helanterä H. From the origin of sex-determining factors to the evolution of sex-determining systems. QUARTERLY REVIEW OF BIOLOGY 2011; 86:163-80. [PMID: 21954700 DOI: 10.1086/661118] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Sex determination is typically classified as either genotypic or environmental. However, this dichotomy obscures the developmental origin and evolutionary modification of determinants of sex, and therefore hinders an understanding of the processes that generates diversity in sex-determining systems. Recent research on reptiles and fish emphasizes that sex determination is a multifactorial regulatory process that is best understood as a threshold dichotomy rather than as the result of genetically inherited triggers of development. Here we critically assess the relationship between the developmental origin of sex-determining factors and evolutionary transitions in sex-determining systems. Our perspective emphasizes the importance of both genetic and nongenetic causes in evolution of sex determination and may help to generate predictions with respect to the evolutionary patterns of sex-determining systems and the underlying diversity of developmental and genetic regulatory networks.
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Affiliation(s)
- Tobias Uller
- Edward Grey Institute, Department of Zoology, University of Oxford Oxford OX1 3PS United Kingdom.
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20
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Ten Tusscher KH, Hogeweg P. Evolution of networks for body plan patterning; interplay of modularity, robustness and evolvability. PLoS Comput Biol 2011; 7:e1002208. [PMID: 21998573 PMCID: PMC3188509 DOI: 10.1371/journal.pcbi.1002208] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2010] [Accepted: 08/08/2011] [Indexed: 11/30/2022] Open
Abstract
A major goal of evolutionary developmental biology (evo-devo) is to understand how multicellular body plans of increasing complexity have evolved, and how the corresponding developmental programs are genetically encoded. It has been repeatedly argued that key to the evolution of increased body plan complexity is the modularity of the underlying developmental gene regulatory networks (GRNs). This modularity is considered essential for network robustness and evolvability. In our opinion, these ideas, appealing as they may sound, have not been sufficiently tested. Here we use computer simulations to study the evolution of GRNs' underlying body plan patterning. We select for body plan segmentation and differentiation, as these are considered to be major innovations in metazoan evolution. To allow modular networks to evolve, we independently select for segmentation and differentiation. We study both the occurrence and relation of robustness, evolvability and modularity of evolved networks. Interestingly, we observed two distinct evolutionary strategies to evolve a segmented, differentiated body plan. In the first strategy, first segments and then differentiation domains evolve (SF strategy). In the second scenario segments and domains evolve simultaneously (SS strategy). We demonstrate that under indirect selection for robustness the SF strategy becomes dominant. In addition, as a byproduct of this larger robustness, the SF strategy is also more evolvable. Finally, using a combined functional and architectural approach, we determine network modularity. We find that while SS networks generate segments and domains in an integrated manner, SF networks use largely independent modules to produce segments and domains. Surprisingly, we find that widely used, purely architectural methods for determining network modularity completely fail to establish this higher modularity of SF networks. Finally, we observe that, as a free side effect of evolving segmentation and differentiation in combination, we obtained in-silico developmental mechanisms resembling mechanisms used in vertebrate development.
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Affiliation(s)
- Kirsten H Ten Tusscher
- Theoretical Biology and Bioinformatics Group, Department of Biology, Utrecht University, Utrecht, The Netherlands.
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21
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MCKINNON JEFFREYS, PIEROTTI MICHELEER. Colour polymorphism and correlated characters: genetic mechanisms and evolution. Mol Ecol 2010; 19:5101-25. [DOI: 10.1111/j.1365-294x.2010.04846.x] [Citation(s) in RCA: 231] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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22
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Nowick K, Stubbs L. Lineage-specific transcription factors and the evolution of gene regulatory networks. Brief Funct Genomics 2010; 9:65-78. [PMID: 20081217 DOI: 10.1093/bfgp/elp056] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Nature is replete with examples of diverse cell types, tissues and body plans, forming very different creatures from genomes with similar gene complements. However, while the genes and the structures of proteins they encode can be highly conserved, the production of those proteins in specific cell types and at specific developmental time points might differ considerably between species. A full understanding of the factors that orchestrate gene expression will be essential to fully understand evolutionary variety. Transcription factor (TF) proteins, which form gene regulatory networks (GRNs) to act in cooperative or competitive partnerships to regulate gene expression, are key components of these unique regulatory programs. Although many TFs are conserved in structure and function, certain classes of TFs display extensive levels of species diversity. In this review, we highlight families of TFs that have expanded through gene duplication events to create species-unique repertoires in different evolutionary lineages. We discuss how the hierarchical structures of GRNs allow for flexible small to large-scale phenotypic changes. We survey evidence that explains how newly evolved TFs may be integrated into an existing GRN and how molecular changes in TFs might impact the GRNs. Finally, we review examples of traits that evolved due to lineage-specific TFs and species differences in GRNs.
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Affiliation(s)
- Katja Nowick
- Department of Cell and Developmental Biology, Institute for Genomic Biology, University of Illinois, 1206 W. Gregory Drive, Urbana, IL 61802, USA
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23
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Abstract
We develop a model for speciation due to postzygotic incompatibility generated by autoimmune reactions. The model is based on frequency-dependent interactions between host plants and their pathogens, which can generate disruptive selection and give rise to speciation if distant phenotypes become reproductively isolated. Based on recent experimental evidence from Arabidopsis, we assume that at the molecular level, incompatibility between host strains is caused by epistatic interactions between two proteins in the plant immune system--the guard and the guardee. Within each plant strain, immune reactions occur when the guardee protein is modified by a pathogen effector, and the guard subsequently binds to the guardee, thus precipitating an immune response. When guard and guardee proteins come from phenotypically distant parents, a hybrid's immune system can be triggered by erroneous interactions between these proteins even in the absence of pathogen attack, leading to severe autoimmune reactions in hybrids. This generates a Dobzhnasky-Muller incompatibility due to immune reactions. Our model shows how phenotypic variation generated by frequency-dependent host-pathogen interactions can lead to such postzygotic incompatibilities between extremal types, and hence to speciation.
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Affiliation(s)
- Iaroslav Ispolatov
- Department of Zoology, University of British Columbia, Vancouver, B.C., Canada
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