arXiv subjects
Publications and source records attributed to S. Cebrat.
The standard Penna ageing model with sexual reproduction is enlarged by adding additional bit-strings for love: Marriage happens only if the male love strings are sufficiently different from the female ones. We simulate at what level of required difference the population dies out.
We have simulated the evolution of sexually reproducing populations composed of individuals represented by diploid genomes. A series of eight bits formed an allele occupying one of 128 loci of one haploid genome (chromosome). The environment required a specific activity of each locus, this being the sum of the activities of both alleles located at the corresponding loci on two chromosomes. This activity is represented by the number of bits set to zero. In a constant environment the best fitted individuals were homozygous with alleles' activities corresponding to half of the environment requirement for a locus (in diploid genome two alleles at corresponding loci produced a proper activity). Changing the environment under a relatively low recombination rate promotes generation of more polymorphic alleles. In the heterozygous loci, alleles of different activities complement each other fulfilling the environment requirements. Nevertheless, the genetic pool of populations evolves in the direction of a very restricted number of complementing haplotypes and a fast changing environment kills the population. If simulations start with all loci heterozygous, they stay heterozygous for a long time.
Computer simulations of the Penna ageing model suggest that already a small fraction of births with enhanced number of new mutations can negatively influence the whole population.
To counterbalance the views presented here by Suzana Moss de Oliveira, we explain here the truth: How men are oppressed by Mother Nature, who may have made an error inventing us, and by living women, who could get rid of most of us. Why do women live longer than us? Why is the Y chromosome for men so small? What are the dangers of marital fidelity? In an appendix we mention the demographic challenges of the future with many old and few young people.
We discovered a dynamic phase transition induced by sexual reproduction. The dynamics is a pure Darwinian rule with both fundamental ingredients to drive evolution: 1) random mutations and crossings which act in the sense of increasing the entropy (or diversity); and 2) selection which acts in the opposite sense by limiting the entropy explosion. Selection wins this competition if mutations performed at birth are few enough. By slowly increasing the average number m of mutations, however, the population suddenly undergoes a mutational degradation precisely at a transition point mc. Above this point, the "bad" alleles spread over the genetic pool of the population, overcoming the selection pressure. Individuals become selectively alike, and evolution stops. Only below this point, m < mc, evolutionary life is possible. The finite-size-scaling behaviour of this transition is exhibited for large enough "chromosome" lengths L. One important and surprising observation is the L-independence of the transition curves, for large L. They are also independent on the population size. Another is that mc is near unity, i.e. life cannot be stable with much more than one mutation per diploid genome, independent of the chromosome length, in agreement with reality. One possible consequence is that an eventual evolutionary jump towards larger L enabling the storage of more genetic information would demand an improved DNA copying machinery in order to keep the same total number of mutations per offspring.
In simulations of sexual reproduction with diploid individuals, we introduce that female haploid gametes recognize one specific allele of the genomes as a marker of the male haploid gametes. They fuse to zygotes preferrably with male gametes having a different marker than their own. This gamete recognition enhances the advantage of complementary bit-strings in the simulated diploid individuals, at low recombination rates. Thus with rare recombinations the bit-string evolve to be complementary; with recombination rate above about 0.1 instead they evolve under Darwinian purification selection, with few bits mutated.
The population in the sexual Penna ageing model is first separated into several reproductively isolated groups. Then, after equilibration, sexual mixing between the groups is allowed. We study the changes in the population size due to this mixing and interpret them through a counterplay of purifying selection and of haplotype complementarity.
We show, that the specific distribution of gene's length, which is observed in natural genomes, might be a result of a growth process, in which a single length scale $L(t)$ develops that grows with time as $t^{1/3}$. This length scale could be associated with the length of the longest gene in an evolving genome. The growth kinetics of the genes resembles the one observed in physical systems with conserved ordered parameter. We show, that in genome this conservation is guaranteed by compositional compensation along DNA strands of the purine-like trends introduced by genes. The presented mathematical model is the modified Bak-Sneppen model of critical self-organization applied to the one-dimensional system of $N$ spins. The spins take discrete values, which represent gene's length.
We have analyzed the relations between the mutational pressure, recombination and selection pressure in the bit-string model with sexual reproduction. For specific sets of these parameters we have found three phase transitions with one phase where populations can survive. In this phase, recombination enhances the survival probability. Even if recombination is associated, to some extent, with additional mutations it could be advantageous to reproduction, indicating that the frequencies of recombinations and recombination-associated mutations can self-organize in Nature. Partitioning the diploid genome into pairs of chromosomes independently assorted during gamete production enables recombinations between groups of genes without the risk of mutations and is also advantageous for the strategy of sexual reproduction.
We have analysed the possibility of scaling the sexual Penna ageing model. Assuming that the number of genes expressed before the reproduction age grows linearly with the genome size and that the mutation rate per genome and generation is constant, we have found that the fraction of defective genes expressed before the minimum reproduction age drops with the genome size, while the number of defective genes eliminated by the genetic death grows with genome size. Thus, the evolutionary costs decrease with enlarging the genome. After rescaling the time scale according to the mutational clock, age distributions of populations do not depend on the genome size. Nevertheless, enlarging the genome increases the reproduction potential of populations.
... By additionally considering a two-mutation model for carcinogenesis and indefinite proliferation by the activation of telomerase, we demonstrate that the risk of dying doe to cancer can outweigh the positive effect of longer telomeres on the longevity.
We have simulated demographic changes in the human population using the Penna microscopic model, based on the simple Monte Carlo method. The results of simulations have shown that during a few generations changes in the genetic pool of a population are negligible, while improving the methods of compensation of genetic defects or genetically determined proneness to many disorders drastically affects the average life span of organisms. Age distribution and mortality of the simulated populations correspond very well to real demographic data available from different countries. Basing on the comparison of structures of real human populations and the results of simulations it is possible to predict changes in the age structure of populations in the future.
The coding sequence in DNA molecule is considered as a message to be transferred to receiver, the proteins, through a noisy information channel and each nucleotide is assigned a respective information weight. With the help of the nucleotide substitution matrix we estimated the lower bound of the amount of information carried out by nucleotides which is not subject of mutations. We used the calculated weights to reconstruct k-oligomers of genes from the Borrelia burgdorferi genome. We showed, that to this aim there is sufficient a simple rule, that the number of bits of the carried information cannot exceed some threshold value. The method introduced by us is general and applies to every genome.
We have found that the effective survival time of amino acids in organisms follows a power law with respect to frequency of their occurrence in genes. We have used mutation data matrix PAM1 PET91 to calculate selection pressure on each kind of amino acid. The results have been compared to MPM1 matrix (Mutation Probability Matrix) representing the pure mutational pressure in the Borrelia burgdorferi genome.The results are universal in the sense that the survival time of amino acids calculated from the higher order PAMk matrices (k>1) follows the same power law as in the case of PAM1 matrices.
We have analyzed DNA sequences of known genes from 16 yeast chromosomes (Saccharomyces cerevisiae) in terms of oligonucleotides. We have noticed that the relative abundances of oligonucleotide usage in the genome follow a long-tail Levy-like distribution. We have observed that long genes often use strongly over-represented and under-represented nucleotides, whereas it was not the case for the short genes (shorter than 300 nucleotides) under consideration. If selection on the extremely over-represented/under-represented oligonucleotides was strong, long genes would be more affected by spontaneous mutations than short ones.
The concept of random deaths in a computational model for population dynamics is critically examined. We claim that it is just an artifact, albeit useful, of computational models to limit the size of the populations and has no biological foundation. Alternative implementations of random deaths strategies are discussed and compared.