Diploidy and the selective advantage for sexual reproduction in unicellular organisms.
This article develops mathematical models describing the evolutionary dynamics of both asexually and sexually reproducing populations of diploid unicellular organisms. The asexual and sexual life cycles are based on the asexual and sexual life cycles in Saccharomyces cerevisiae, Baker's yeast, which normally reproduces by asexual budding, but switches to sexual reproduction when stressed. The mathematical models consider three reproduction pathways: (1) Asexual reproduction, (2) self-fertilization, and (3) sexual reproduction. We also consider two forms of genome organization. In the first case, we assume that the genome consists of two multi-gene chromosomes, whereas in the second case, we consider the opposite extreme and assume that each gene defines a separate chromosome, which we call the multi-chromosome genome. These two cases are considered to explore the role that recombination has on the mutation-selection balance and the selective advantage of the various reproduction strategies. We assume that the purpose of diploidy is to provide redundancy, so that damage to a gene may be repaired using the other, presumably undamaged copy (a process known as homologous recombination repair). As a result, we assume that the fitness of the organism only depends on the number of homologous gene pairs that contain at least one functional copy of a given gene. If the organism has at least one functional copy of every gene in the genome, we assume a fitness of 1. In general, if the organism has l homologous pairs that lack a functional copy of the given gene, then the fitness of the organism is kappa(l). The kappa(l) are assumed to be monotonically decreasing, so that kappa(0) = 1 > kappa(1) > kappa(2) > cdots, three dots, centered > kappa(infinity) = 0. For nearly all of the reproduction strategies we consider, we find, in the limit of large N, that the mean fitness at mutation-selection balance is max{2e(-mu) - 1,0} where N is the number of genes in the haploid set of the genome, epsilon is the probability that a given DNA template strand of a given gene produces a mutated daughter during replication, and mu = Nepsilon. The only exception is the sexual reproduction pathway for the multi-chromosomed genome. Assuming a multiplicative fitness landscape where kappa(l) = alpha(l) for alpha in (0, 1), this strategy is found to have a mean fitness that exceeds the mean fitness of all the other strategies. Furthermore, while other reproduction strategies experience a total loss of viability due to the steady accumulation of deleterious mutations once mu exceeds [Formula: see text] no such transition occurs in the sexual pathway. Indeed, in the limit as alpha --> 1 for the multiplicative landscape, we can show that the mean fitness for the sexual pathway with the multi-chromosomed genome converges to e(-2mu), which is always positive. We explicitly allow for mitotic recombination in this study, which, in contrast to previous studies using different models, does not have any advantage over other asexual reproduction strategies. The results of this article provide a basis for understanding the selective advantage of the specific meiotic pathway that is employed by sexually reproducing organisms. The results of this article also suggest an explanation for why unicellular organisms such as Saccharomyces cerevisiae (Baker's yeast) switch to a sexual mode of reproduction when stressed. While the results of this article are based on modeling mutation-propagation in unicellular organisms, they nevertheless suggest that, in more complex organisms with significantly larger genomes, sex is necessary to prevent the loss of viability of a population due to genetic drift. Finally, and perhaps most importantly, the results of this article demonstrate a selective advantage for sexual reproduction with fewer and much less restrictive assumptions than those of previous studies.
Kleiman
Maya
M
Department of Chemistry, Ben-Gurion University of the Negev, Be'er-Sheva, Israel.
Tannenbaum
Emmanuel
E
D000465:Algorithms; D005075:Biological Evolution; D002875:Chromosomes / Q000235:genetics; D003198:Computer Simulation; D004171:Diploidy; D005796:Genes / Q000235:genetics; D040961:Genetic Drift; D056084:Genetic Fitness / Q000235:genetics; D016678:Genome / Q000235:genetics; D018095:Germ-Line Mutation / Q000235:genetics; D006238:Haploidy; D007178:Inbreeding; D008957:Models, Genetic; D011995:Recombination, Genetic / Q000235:genetics; D012098:Reproduction / Q000235:genetics; D012100:Reproduction, Asexual / Q000235:genetics; D012441:Saccharomyces cerevisiae / Q000235:genetics; D012641:Selection, Genetic / Q000235:genetics*; D013269:Stochastic Processes