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A Boolean gene regulatory model of heterosis and speciation

BACKGROUND: Modelling genetic phenomena affecting biological traits is important for the development of agriculture as it allows breeders to predict the potential of breeding for certain traits. One such phenomenon is heterosis or hybrid vigor: crossing individuals from genetically distinct populati...

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Autores principales: Emmrich, Peter Martin Ferdinand, Roberts, Hannah Elizabeth, Pancaldi, Vera
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349475/
https://www.ncbi.nlm.nih.gov/pubmed/25888139
http://dx.doi.org/10.1186/s12862-015-0298-0
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author Emmrich, Peter Martin Ferdinand
Roberts, Hannah Elizabeth
Pancaldi, Vera
author_facet Emmrich, Peter Martin Ferdinand
Roberts, Hannah Elizabeth
Pancaldi, Vera
author_sort Emmrich, Peter Martin Ferdinand
collection PubMed
description BACKGROUND: Modelling genetic phenomena affecting biological traits is important for the development of agriculture as it allows breeders to predict the potential of breeding for certain traits. One such phenomenon is heterosis or hybrid vigor: crossing individuals from genetically distinct populations often results in improvements in quantitative traits, such as growth rate, biomass production and stress resistance. Heterosis has become a very useful tool in global agriculture, but its genetic basis remains controversial and its effects hard to predict. We have taken a computational approach to studying heterosis, developing a simulation of evolution, independent reassortment of alleles and hybridization of Gene Regulatory Networks (GRNs) in a Boolean framework. These artificial regulatory networks exhibit topological properties that reflect those observed in biology, and fitness is measured as the ability of a network to respond to external inputs in a pre-defined way. RESULTS: Our model reproduced common experimental observations on heterosis using only biologically justified parameters, such as mutation rates. Hybrid vigor was observed and its extent was seen to increase as parental populations diverged, up until a point of sudden collapse of hybrid fitness. Thus, the model also describes a process akin to speciation due to genetic incompatibility of the separated populations. We also reproduce, for the first time in a model, the fact that hybrid vigor cannot easily be fixed by within a breeding line, currently an important limitation of the use of hybrid crops. The simulation allowed us to study the effects of three standard models for the genetic basis of heterosis: dominance, over-dominance, and epistasis. CONCLUSION: This study describes the most detailed simulation of heterosis using gene regulatory networks to date and reproduces several phenomena associated with heterosis for the first time in a model. The level of detail in our model allows us to suggest possible warning signs of the impending collapse of hybrid vigor in breeding. In addition, the simulation provides a framework that can be extended to study other aspects of heterosis and alternative evolutionary scenarios. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-015-0298-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-43494752015-03-05 A Boolean gene regulatory model of heterosis and speciation Emmrich, Peter Martin Ferdinand Roberts, Hannah Elizabeth Pancaldi, Vera BMC Evol Biol Research Article BACKGROUND: Modelling genetic phenomena affecting biological traits is important for the development of agriculture as it allows breeders to predict the potential of breeding for certain traits. One such phenomenon is heterosis or hybrid vigor: crossing individuals from genetically distinct populations often results in improvements in quantitative traits, such as growth rate, biomass production and stress resistance. Heterosis has become a very useful tool in global agriculture, but its genetic basis remains controversial and its effects hard to predict. We have taken a computational approach to studying heterosis, developing a simulation of evolution, independent reassortment of alleles and hybridization of Gene Regulatory Networks (GRNs) in a Boolean framework. These artificial regulatory networks exhibit topological properties that reflect those observed in biology, and fitness is measured as the ability of a network to respond to external inputs in a pre-defined way. RESULTS: Our model reproduced common experimental observations on heterosis using only biologically justified parameters, such as mutation rates. Hybrid vigor was observed and its extent was seen to increase as parental populations diverged, up until a point of sudden collapse of hybrid fitness. Thus, the model also describes a process akin to speciation due to genetic incompatibility of the separated populations. We also reproduce, for the first time in a model, the fact that hybrid vigor cannot easily be fixed by within a breeding line, currently an important limitation of the use of hybrid crops. The simulation allowed us to study the effects of three standard models for the genetic basis of heterosis: dominance, over-dominance, and epistasis. CONCLUSION: This study describes the most detailed simulation of heterosis using gene regulatory networks to date and reproduces several phenomena associated with heterosis for the first time in a model. The level of detail in our model allows us to suggest possible warning signs of the impending collapse of hybrid vigor in breeding. In addition, the simulation provides a framework that can be extended to study other aspects of heterosis and alternative evolutionary scenarios. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-015-0298-0) contains supplementary material, which is available to authorized users. BioMed Central 2015-02-24 /pmc/articles/PMC4349475/ /pubmed/25888139 http://dx.doi.org/10.1186/s12862-015-0298-0 Text en © Emmrich et al; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Emmrich, Peter Martin Ferdinand
Roberts, Hannah Elizabeth
Pancaldi, Vera
A Boolean gene regulatory model of heterosis and speciation
title A Boolean gene regulatory model of heterosis and speciation
title_full A Boolean gene regulatory model of heterosis and speciation
title_fullStr A Boolean gene regulatory model of heterosis and speciation
title_full_unstemmed A Boolean gene regulatory model of heterosis and speciation
title_short A Boolean gene regulatory model of heterosis and speciation
title_sort boolean gene regulatory model of heterosis and speciation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349475/
https://www.ncbi.nlm.nih.gov/pubmed/25888139
http://dx.doi.org/10.1186/s12862-015-0298-0
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