Reproduction cost reduces demographic stochasticity and enhances inter-individual compatibility

Cunff, Yann Le; Pakdaman, Khashayar

doi:10.1016/j.jtbi.2014.07.008

Cited by 8 publications

(12 citation statements)

References 60 publications

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“…I also repeated many of the evolutionary simulations that I have presented but now considering sexual reproduction (see ‘Methods’). When including recombination, a biologically successful individual must not only produce an adequate phenotype, but also be genetically compatible with its potential mates (True & Haag, ; Palmer & Feldman, ; Le Cunff & Pakdaman, ). Therefore, recombination may obstruct access to different GAPs sharing a property under selection.…”

Section: Resultsmentioning

confidence: 99%

“…The model of gene regulatory networks that I employ has allowed addressing important topics in evolutionary biology (Fierst & Phillips, ). Such topics include the relationship between sexual reproduction and epistasis (Azevedo et al ., ; MacCarthy & Bergman, ; Martin & Wagner, ; Lohaus et al ., ), how network structure affects evolution (Siegal et al ., ; Espinosa‐Soto & Wagner, ; Pinho et al ., ), the evolution of evolvability (Ciliberti et al ., ; Kimbrell & Holt, ; Draghi & Wagner, ; Kimbrell, ; Whitacre & Bender, ; Espinosa‐Soto et al ., ; Fierst, ; Steiner, ), the effects of phenotypic plasticity on evolution (Masel, ; Espinosa‐Soto et al ., , b; Fierst, ; Pinho et al ., ), how hybrid incompatibility evolves (Palmer & Feldman, ; Le Cunff & Pakdaman, ) and even the role of gene network dynamics in the evolution of organismal complexity (Lohaus et al ., ). Importantly, the model has been rewarding when used to investigate how mutational robustness evolves (Wagner, ; Siegal & Bergman, ; Bergman & Siegal, ; Ciliberti et al ., ; Huerta‐Sánchez & Durrett, ; Kimbrell, ; Le Cunff & Pakdaman, , ; Fierst, ).…”

Section: Methodsmentioning

confidence: 99%

“…From this perspective, stationarity could be an aspect of GAPs that is crucial for the evolution of robustness. Indeed, several important studies have granted stationarity such a status by considering populations subject only to selection for stationarity when studying issues like the evolution of genetic compatibility (Le Cunff & Pakdaman, ) or the evolution of epistasis (Azevedo et al ., ; MacCarthy & Bergman, ). An open alternative is that stabilizing selection on many or most aspects of GAPs could be as effective as selection on stationarity for the evolution of mutational robustness.…”

Section: Introductionmentioning

confidence: 99%

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Selection for distinct gene expression properties favours the evolution of mutational robustness in gene regulatory networks

Espinosa‐Soto

2016

J of Evolutionary Biology

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Mutational robustness is a genotype's tendency to keep a phenotypic trait with little and few changes in the face of mutations. Mutational robustness is both ubiquitous and evolutionarily important as it affects in different ways the probability that new phenotypic variation arises. Understanding the origins of robustness is specially relevant for systems of development that are phylogenetically widespread and that construct phenotypic traits with a strong impact on fitness. Gene regulatory networks are examples of this class of systems. They comprise sets of genes that, through cross-regulation, build the gene activity patterns that define cellular responses, different tissues or distinct cell types. Several empirical observations, such as a greater robustness of wild-type phenotypes, suggest that stabilizing selection underlies the evolution of mutational robustness. However, the role of selection in the evolution of robustness is still under debate. Computer simulations of the dynamics and evolution of gene regulatory networks have shown that selection for any gene activity pattern that is steady and self-sustaining is sufficient to promote the evolution of mutational robustness. Here, I generalize this scenario using a computational model to show that selection for different aspects of a gene activity phenotype increases mutational robustness. Mutational robustness evolves even when selection favours properties that conflict with the stationarity of a gene activity pattern. The results that I present support an important role for stabilizing selection in the evolution of robustness in gene regulatory networks.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Selection for distinct gene expression properties favours the evolution of mutational robustness in gene regulatory networks

Espinosa‐Soto

2016

J of Evolutionary Biology

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“…Mating is not only restricted by genetic similarity but also by spatial proximity, so that an individual can only choose as mating partner those inside a circular neighborhood of radius S centered on its spatial location, called the mating neighborhood. We note that a number of other effects, such as demographic stochasticity [29], population expansions [27,30], costs of reproduction [31], and migration rates between subpopulations [32] In order to avoid clustering we implement the dynamics in a slightly different way [22] (see also section V): the initial population is randomly placed in the L × L area. Each one of the M individuals has a chance of reproducing but there is a probability Q that it will not do so, accounting for the fact that not all individuals in the present generation will be first parents of the next.…”

Section: Spatial Model With Finite Genomesmentioning

confidence: 99%

Speciation in the Derrida–Higgs model with finite genomes and spatial populations

Aguiar

Marcus²

2017

J. Phys. A: Math. Theor.

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The speciation model proposed by Derrida and Higgs demonstrated that a sexually reproducing population can split into different species in the absence of natural selection or any type of geographic isolation, provided that mating is assortative and the number of genes involved in the process is infinite. Here we revisit this model and simulate it for finite genomes, focusing on the question of how many genes it actually takes to trigger neutral sympatric speciation. We find that, for typical parameters used in the original model, it takes of the order of 10 5 genes. We compare the results with a similar spatially explicit model where about 100 genes suffice for speciation. We show that when the number of genes is small the species that emerge are strongly segregated in space. For larger number of genes, on the other hand, the spatial structure of the population is less important and the species distribution overlap considerably. 1 arXiv:1606.06559v2 [q-bio.PE] 5 Jan 2017 I. INTRODUCTION Speciation requires the evolution of reproductive isolation between initially compatible individuals [1]. One of the most accepted mechanisms for the development of reproductive barriers is the geographic isolation of the populations, which can be complete (allopatry) or partial (parapatry) [2, 3]. In both cases the reduction of gene flow between individuals inhabiting different regions facilitates the fixation of local adaptations. These, in turn, may lead to pre-zygotic or post-zygotic mating incompatibilities and can eventually develop into full reproductive isolation.Sympatric speciation, where new species arise from a population inhabiting a single geographic region, has been highly debated [4,5] and its occurrence in nature is documented in only a few cases [2,6]. Mathematical models have shown that sympatric speciation is theoretically possible [7][8][9][10][11][12] and the model by Dieckmann and Doebeli [13], in particular, attracted a lot of attention. In their model, speciation results from the interplay between strong competition for resources and the way resources are distributed. It was shown that, under appropriate conditions, the population will evolve in such a way as to consume the most abundant type of resource, but it will arrive at the corresponding 'optimal' phenotype in a minimum of the fitness landscape, causing it to split in two. The resulting system of two subpopulations with different phenotypes would then be at a fitness maximum. For sexually reproducing individuals the evolution of reproductive barriers between the two nearly split populations would need a further ingredient, assortative mating. This is tendency of individuals to mate with others that are similar to themselves and prevents the mixing of the two subpopulations. In the model assortative mating was shown to evolve naturally because only then the fitness maximum could be achieved. In spite of its theoretical plausibility, this and other models have been criticized for their supposedly unrealistic assumptions [14][15][16][17].More surprisin...

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“…Recently, a gene regulatory network (GRN) model first proposed by Wagner (1994Wagner ( , 1996 has emerged as a popular computational approach to study recombination in a network context (Azevedo et al, 2006;MacCarthy and Bergman, 2007;Lohaus et al, 2010;Le Cunff and Pakdaman, 2014). One novel feature in Wagner's GRN model is that it introduces selection for phenotypic stability, performed as a separate layer of truncation selection in addition to selection for a particular optimal phenotype.…”

Section: Introductionmentioning

confidence: 99%

Recombination Is Surprisingly Constructive for Artificial Gene Regulatory Networks in the Context of Selection for Developmental Stability

Wang

Lan

Weinreich

et al. 2015

07/20/2015-07/24/2015

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Recombination is ubiquitous in multicellular plants, animals and even fungi. Many studies have shown that recombination can generate a great amount of genetic innovations, but it is also believed to damage well-adapted lineages, causing debates over how organisms cope with such disruptions. Using an established model of artificial gene regulatory networks, here we show that recombination may not be as destructive as expected. Provided only that there is selection for developmental stability, recombination can establish and maintain lineages with reliably better phenotypes compared to asexual reproduction. Contrary to expectation, this does not appear to be a simple side effect of higher levels of variation. A simple model of the underlying dynamics demonstrates a surprisingly high robustness in these lineages against the disruption caused by recombination. Contrary to expectation, lineages subject to recombination are less likely to produce offspring suffering truncation selection for instability than asexual lineages subject to simple mutation. These findings indicate the fundamental differences between recombination and high mutation rates, which has important implications for understanding both biological innovation and hierarchically structured models of machine learning.

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Reproduction cost reduces demographic stochasticity and enhances inter-individual compatibility

Cited by 8 publications

References 60 publications

Selection for distinct gene expression properties favours the evolution of mutational robustness in gene regulatory networks

Selection for distinct gene expression properties favours the evolution of mutational robustness in gene regulatory networks

Speciation in the Derrida–Higgs model with finite genomes and spatial populations

Recombination Is Surprisingly Constructive for Artificial Gene Regulatory Networks in the Context of Selection for Developmental Stability

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