Altruism and antagonistic pleiotropy in Penna ageing model

Cebrat, S.; Stauffer, Dietrich

doi:10.1016/j.thbio.2004.09.002

Cited by 7 publications

(2 citation statements)

References 12 publications

(11 reference statements)

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“…An analytic solution is also available (Coe and Mao, 2003). The model has been successfull in reproducing the senescence of the pacific salmon , and has been modified to account for the antagonistic pleiotropy mechanism (Sousa and de Oliveira, 2001;Cebrat and Stauffer, 2005) and spatial distributions on a lattice (Makowiec, 2000). Speciation in age structured populations has also been of interest, and in specific sympatric speciation (Sousa, 2000;LuzBurgoa et al, 2003) and parapatric speciation (Schwammle et al, 2006), in some cases including sexual reproduction, diploid and even triploid organisms (de Oliveira, 2004;Sousa et al, 2003).…”

Section: Computational Modelling For Biological Agingmentioning

confidence: 99%

Evolution of the rate of biological aging using a phenotype based computational model

Kittas

2010

Journal of Theoretical Biology

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.Evolution of the rate of biological aging using a phenotype based computational model Aristotelis KittasTo cite this version: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Evolution of the rate of biological aging using a phenotype based computational model Aristotelis KittasDepartment of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece AbstractIn this work I introduce a simple model to study how natural selection acts upon aging, which focuses on the viability of each individual. It is able to reproduce the Gompertz law of mortality and can make predictions about the relation between the level of mutation rates (beneficial/deleterious/neutral), age at reproductive maturity and the degree of biological aging. With no mutations, a population with low age at reproductive maturity R stabilizes at higher density values, while with mutations it reaches its maximum density, because even for large pre-reproductive periods each individual evolves to survive to maturity. Species with very short pre-reproductive periods can only tolerate a small number of detrimental mutations. The probabilities of detrimental (P d ) or beneficial (P b ) mutations are demonstrated to greatly affect the process. High absolute values produce peaks in the viability of the population over time. Mutations combined with low selection pressure move the system towards weaker phenotypes. For low values in the ratio P d /P b , the speed at which aging occurs is almost independent of R, while higher values favor significantly species with high R. The value of R is critical to whether the population survives or dies out. The aging rate is controlled by P d and P b and the amount the viability of each individual is modified, with neutral mutations allowing the system more "room" to evolve. The process of aging in this simple model is revealed to be fairly complex, yielding a rich variety of results.

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Section: Computational Modelling For Biological Agingmentioning

confidence: 99%

Evolution of the rate of biological aging using a phenotype based computational model

Kittas

2010

Journal of Theoretical Biology

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“…In fact, the Penna model does not assume the Medawar hypothesis but the results of simulations using this model support the Medawar hypothesis. Moreover, the Penna model could be very useful in describing many phenomena connected with the evolution of biological populations, like altruism [13], menopause [14], the role of the immunological system [15], of mother care [16], even the evolution of sex chromosomes [17]. There are two main versions of the model, haploid and diploid.…”

Section: Description Of the Standard Penna Modelmentioning

confidence: 99%

Evolution of the age-structured populations and demography

Laszkiewicz

Biecek

Bonkowska

et al. 2009

Series on Advances in Mathematics for Applied Sciences

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We describe the simulation method of modeling the population evolution using Monte Carlo based on the Penna model. Individuals in the populations are represented by their diploid genomes. Genes expressed after the minimum reproduction age are under a weaker selection pressure and accumulate more mutations than those expressed before the minimum reproduction age. The generated gradient of defective genes determines the ageing of individuals and age-structured populations are very similar to the natural, sexually reproducing populations. The genetic structure of a population depends on the way how the random death affects the population. The improvement of the medical care and healthier life styles are responsible for the increasing of the life expectancy of humans during the last century. Introducing a noise into the relations between the genotype, phenotype, and environment, it is possible to simulate some other effects, like the role of immunological systems and a mother care. One of the most interesting results was the evolution of sex chromosomes. Placing the male sex determinants on one chromosome of a pair of sex chromosomes is enough to condemn it for shrinking if the population is panmictic (random-mating is assumed). If males are indispensable for taking care of their offspring and have to be faithful to their females, the male sex chromosome does not shrink.

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Evolution of tag-mediated altruistic behavior in one-shot encounters on large-scale complex networks

Hadzibeganovic

Lima

Stauffer

2012

Computer Physics Communications

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Altruism and antagonistic pleiotropy in Penna ageing model

Abstract: The Penna ageing model is based on mutation accumulation theory. We show that it also allows for self-organization of antagonistic pleiotropy which helps at young age at the expense of old age. This can be interpreted as emergence of altruism.

Cited by 7 publications

References 12 publications

Evolution of the rate of biological aging using a phenotype based computational model

Evolution of the rate of biological aging using a phenotype based computational model

Evolution of the age-structured populations and demography

Evolution of tag-mediated altruistic behavior in one-shot encounters on large-scale complex networks

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