Биологическая и социальная фазы макроэволюции: сходства и различия эволюционных принципов и механизмов
The article is devoted to the supernatural punishment hypothesis elaborated by Dominic D.P.Johnson, Professor at the Oxford University, and a possibility of applying this hypothesis to Political Science. The essence of the hypothesis is that religion and belief in gods improve human cooperation and form a basis for altruistic behavior. Johnson views people’s ability to believe in the “supernatural agent” who is watching them and who will surely punish them for their sins as the evolutionary meaning of religion. The author provides a detailed analysis of Johnson’s concept and demonstrates its unequivocal scientific importance, but at the same time he pinpoints its weaknesses such as data interpretation and adequacy of using the terms “religion”, “altruism” and “group cooperation”. The author proposes several alternative explanations of the evolutionary meaning of religion and considers it from the meme theory perspective. According to his conclusion, if altruistic behavior is indeed natural to human beings at the biological level, then an institution of religion can be viewed as its higher form, but not its cause. In order to make both positions in this scientific debate clear, the author invites metaphors of symbiosis and parasitism for describing relationships between a human being and a belief in a supernatural agent (religion). Johnson’s hypothesis deserves close attention and scrutiny as an argument in favor of the “symbiosis” metaphor. However, one must use it with caution, admit its limitations and avoid oversimplification of a highly complicated model of the human sociality that inevitably includes religious consciousness.
It is shown that competition in the economy by purchasing various forms, it contributes to the evolutionary development of society. An analogy with the competition and the struggle for existence of Charles Darwin.
Many RNA molecules possess complicated secondary structure critical to their function. Mutations in double-helical regions of RNA may disrupt Watson-Crick (WC) interactions causing structure destabilization or even complete loss of function. Such disruption can be compensated by another mutation restoring base pairing, as has been shown for mRNA, rRNA and tRNA. Here, we investigate the evolutionof intrinsic transcription terminators between closely related strains of Bacillus cereus. While the terminator structure is maintained by strong natural selection, as evidenced by the low frequency of disrupting mutations, we observe multiple instances of pairs of disrupting-compensating mutations in RNA structure stems. Such two-step switches between different WC pairs occur very fast, consistent with the low fitness conferred by the intermediate non-WC variant. Still, they are not instantaneous, and probably involve transient fixation of the intermediate variant. The GU wobble pair is the most frequent intermediate, and remains fixed longer than other intermediates, consistent with its less disruptive effect on the RNA structure. Double switches involving non-GU intermediates are more frequent at the ends of RNA stems, probably because they are associated with smaller fitness loss. Together, these results show that the fitness landscape of bacterial transcription terminators is rather rugged, but that the fitness valleys associated with unpaired stem nucleotides are rather shallow, facilitating evolution.
We investigate the dynamics of a molecular evolution model related to the mutator gene phenomenon. Here mutation in one gene drastically changes the properties of the whole genome. We investigated the Crow-Kimura version of the model, which can be mapped into a Hamilton-Jacobi equation. For the symmetric fitness landscape, we calculated the dynamics of the maximum of the total population distribution. We found two phases in the dynamics: a simple one when the maximum of distribution moves along a characteristics, and more involved one when the maximum jumps to another characteristic at some turnout point T.