Darwinian purifying selection versus complementing strategy in Monte-Carlo simulations

Abstract

Intragenomic recombination (crossover) is a very important evolutionary mechanism. The crossover events are not evenly distributed along the natural chromosomes. Monte Carlo simulations revealed that frequency of recombinations decides about the strategy of chromosomes' and genomes' evolution. In large panmictic populations, under high recombination rate the Darwinian purifying selection operates keeping the fraction of defective genes at the relatively low level. In small populations and under low recombination rate the strategy of complementing haplotypes seems to be more advantageous. Switching between the two strategies has a character of phase transition -it depends on inbreeding coefficient and crossover rate. The critical recombination rate depends also on the size of chromosome. It is also possible, that in one genome some chromosomes could be under complementing while some other under purifying selection. Such situation stabilizes genome evolution and reproduction strategy. It seems that this phenomenon can be responsible for the positive correlation between kinship and fecundity, recently found in the Islander population. When large population is forced to enter the complementing strategy, the phenomenon of sympatric speciation is observed.3.

The Role of Haplotype Complementation and Purifying Selection in the Genome Evolution

“…If a female can choose a partner at distance no larger than P and she can locate her baby at distance no larger than O then the effective population size and inbreeding coefficient is determined by these two parameters: P and O, independently of the population size (dimensions of the lattice). Results of simulations ( Fig.9) suggest that under all other parameters fixed, C * value does not depend on population size [44] [46]. For increasing P and/or O, C * decreases and populations enter the purifying strategy at lower recombination rate (results not shown).…”

“…Under low and high recombination rate populations are larger while in the intermediate recombination rate they are smaller or could be even extinct. This effect is connected with higher zygotic death close to the critical recombination rate (Fig.7)[50] [46]. Zygotic death in this case means, that fusion of two gametes produces a dying offspring.…”

“…It has been noticed that the distribution of accepted recombination events in the genomes of simulated populations depends on parameters of simulations. If evolution is studied in small effective populations under relatively low recombination rate, the central parts of chromosomes start to form clusters of genes where recombinations have deleterious effect on reproduction potential [46]. Gametes which are produced by recombinations in these regions have lower chance to produce surviving zygotes.…”

“…If one considers the problem from the point of evolutionary costs, it seems to be more effective to avoid the recombination in some regions rather than to eliminate recombinants from the population. It has been shown in simulations that the distributions of recombination spots are under selection pressure and can evolve [46] [20]. To find this, simulations start with recombinations distributed evenly.…”

“…On the other hand the probability of mating between two individuals decreases with the distance. It is possible to follow (or almost directly observe) the evolution of individual genomes on lattice [44] [46]. Let assume that to each number from the range 1 to 2 24 a specific colour is ascribed and a 24 bits long fragment of a bitstring, representing one haplotype of a diploid genome is considered as a number in a binary numeral system.…”