Computational modeling of evolutionary learning processes in the brain

The evolutionary selection circuits model of learning has been specified algorithmically. The basic structural components of the selection circuits model are enzymatic neurons, that is, neurons whose firing behavior is controlled by membrane-bound macromolecules called excitases. Learning involves changes in the excitase contents of neurons through a process of variation and selection. In this paper we report on the behavior of a basic version of the learning algorithm which has been developed through extensive interactive experiments with the model. This algorithm is effective in that it enables single neurons or networks of neurons to learn simple pattern classification tasks in a number of time steps which appears experimentally to be a linear function of problem size, as measured by the number of patterns of presynaptic input. The experimental behavior of the algorithm establishes that evolutionary mechanisms of learning are competent to serve as major mechanisms of neuronal adaptation. As an example, we show how the evolutionary learning algorithm can contribute to adaptive motor control processes in which the learning system develops the ability to reach a target in the presence of randomly imposed disturbances.     

Sequential behavior and stability properties of enzymatic neuron networks

The cycle structure of enzymatic neural networks may be characterized in terms of number of cycles exhibited, size of cycle state sets and cycle lengths. Simulation experiments show that the stability properties of these networks have some unusual features which are not exhibited by networks of two-state switching elements or by randomly constructed ecosystem models. The behavioral and structural stability of these systems decreases with their structural complexity, as measured by the number of components. The behavioral and structural stability of enzymatic neural networks also decreases with structural complexity, as measured by the number of excitase types, but only up to the middle level of excitases per neuron. This is the point of highest potential responsiveness of the system to environmental stimuli. Beyond this point the behavioral and structural stability increase. This is due to the fact that the number of possible states increases up to this point and decreases beyond it. The number of possible states, not the number of components, serves as the useful measure of complexity in these types of systems. The selection circuits learning algorithm has been used to evolve networks whose cycle structures have desired features.     

Gene Network Polymorphism Is the Raw Material of Natural Selection: The Selfish Gene Network Hypothesis

Population genetics, the mathematical theory of modern evolutionary biology, defines evolution as the alteration of the frequency of distinct gene variants (alleles) differing in fitness over the time. The major problem with this view is that in gene and protein sequences we can find little evidence concerning the molecular basis of phenotypic variance, especially those that would confer adaptive benefit to the bearers. Some novel data, however, suggest that a large amount of genetic variation exists in the regulatory region of genes within populations. In addition, comparison of homologous DNA sequences of various species shows that evolution appears to depend more strongly on gene expression than on the genes themselves. Furthermore, it has been demonstrated in several systems that genes form functional networks, whose products exhibit interrelated expression profiles. Finally, it has been found that regulatory circuits of development behave as evolutionary units. These data demonstrate that our view of evolution calls for a new synthesis. In this article I propose a novel concept, termed the selfish gene network hypothesis, which is based on an overall consideration of the above findings. The major statements of this hypothesis are as follows. (1) Instead of individual genes, gene networks (GNs) are responsible for the determination of traits and behaviors. (2) The primary source of microevolution is the intraspecific polymorphism in GNs and not the allelic variation in either the coding or the regulatory sequences of individual genes. (3) GN polymorphism is generated by the variation in the regulatory regions of the component genes and not by the variance in their coding sequences. (4) Evolution proceeds through continuous restructuring of the composition of GNs rather than fixing of specific alleles or GN variants.     

Selection on an antimicrobial peptide defensin in ants

Ants live in crowded nests with interacting individuals, which makes them particularly prone to infectious diseases. The question is, how do ants cope with the increased risk of pathogen transmission due to sociality? We have studied the molecular evolution of defensin, a gene encoding an antimicrobial protein, in ants. Defensin sequences from several ant species were analyzed with maximum likelihood models of codon substitution to infer selection. Positive selection was detected in the mature region of defensin, whereas the signal and pro regions seem to be evolving neutrally. We also found a significantly higher rate of nonsynonymous substitutions in some phylogenetic lineages, as well as dN/dS >1, suggesting varying selection pressures in different lineages. Earlier studies on the molecular evolution of insect antimicrobial peptide genes have focused on termites and dipteran species, and detected positive selection only in duplicated termicin genes in termites. These findings, together with our present results, provide an indication that the immune systems of social insects (ants and termites) and dipteran insects may have responded differently to the selection pressure caused by microbial pathogens.     

Sphingosine-1-Phosphate Metabolism and Intestinal Tumorigenesis: Lipid Signaling Strikes Again

Superficially similar traits in phylogenetically unrelated species often result from adaptation to common selection pressures. Examples of convergent evolution are known at the levels of whole organisms, organ systems, gene networks and specific proteins. The phenotypic properties of living things, on the other hand, are determined in large part by complex networks of interacting proteins. Here we present a mathematical model of the network of proteins that controls DNA synthesis and cell division in the alpha-proteobacterium, Caulobacter crescentus. By comparing the protein regulatory circuits for cell reproduction in Caulobacter with that in budding yeast (Saccharomyces cerevisiae), we suggest that convergent evolution may have created similar molecular reaction networks in order to accomplish the same purpose of coordinating DNA synthesis to cell division. Although the genes and proteins involved in cell cycle regulation in prokaryotes and eukaryotes are very different and (apparently) phylogenetically unrelated, they seem to be wired together in similar regulatory networks, which coordinate cell cycle events by identical dynamical principles.     

Identification of genes with fast-evolving regions in microbial genomes

Complete sequences of multiple strains of the same microbial species provide an invaluable source for studying the evolutionary dynamics between orthologous genes over a relatively short time scale. Usually the intensity of the selection pressure is inferred from a comparison between the nonsynonymous substitution rate and the synonymous substitution rate. In this paper, we propose an alternative method for detecting genes with one or more fast-evolving regions from pairwise comparisons of orthologous genes. Our method looks for regions with overrepresented nonsynonymous mutations along the alignment, and requires a higher nonsynonymous evolution rate in those regions than the neutral evolution rate. It identifies gene targets under intensive selection pressure that are not detected from the conventional rate comparison analysis. For those identified genes with known annotations, most of them have a clear role in processes such as bacterial defense and host–pathogen interactions. Gene sets reported from our method provide a measure of the phenotypic divergence between two closely related genomes.     

Selection on coding regions determined Hox7 genes evolution

The important role of Hox genes in determining the regionalization of the body plan of the vertebrates makes them invaluable candidates for evolutionary analyses regarding functional and morphological innovation. Gene duplication and gene loss led to a variable number of Hox genes in different vertebrate lineages. The evolutionary forces determining the conservation or loss of Hox genes are poorly understood. In this study, we show that variable selective pressures acted on Hox7 genes in different evolutionary lineages, with episodes of positive selection occurring after gene duplications. Tests for functional divergence in paralogs detected significant differentiation in a region known to modulate HOX7 protein activity. Our results show that both positive and negative selection on coding regions are influencing Hox7 genes evolution.     

Non-mental aspects of encephalisation: The forebrain as a playground of mammalian evolution

Neo-darwinian theory holds that changes in mammalian and avian body morphology follow behavioral adaptation. The problem then is to explain how random mutations can result in a sufficiently rapid reorganization of the most complex biological system —common sense would predict that the CNS is the slowest to evolve. This paper attempts a parsimonious explanation which predicts that the accumulation of genetic variation is most likely in CNS systems ranking high in the functional hierarchy of the brain, and that thetop-ranking systems are the preferred initial targets after increased selective pressure. They thus serve as a matrix for subsequent canalized selection which leads to a comparatively rapid, top-to-bottom reorganization of the CNS, providing a neuronal framework for the evolution of body morphology.     

The evolution of concerted evolution

Concerted evolution is a consequence of processes that convert copies of a gene in a multigene family into the same copy. Here we ask whether this homogenization may be adaptive. Analysis of a modifier of homogenization reveals (1) that the trait is most likely to spread if interactions between deleterious mutations are not strongly synergistic; (2) that selection on the modifier is of the order of the mutation rate, hence the modifier is most likely to be favoured by selection when the species has a large effective population size and/or if the modifier affects many genes simultaneously; and (3) that linkage between the genes in the family, and between these genes and the modifier, makes invasion of the modifier easier, suggesting that selection may favour multigene families being in clustered arrays. It follows from the first conclusion that genes for which mutations may often be dominant or semi-dominant should undergo concerted evolution more commonly than others. By analysis of the mouse knockout database, we show that mutations affecting growth-related genes are more commonly associated with dominant lethality than expected by chance. We predict then that selection will favour homogenization of such genes, and possibly others that are significantly dosage dependent, more often than it favours homogenization in other genes. The first condition is almost the opposite of that required for the maintenance of sexual reproduction according to the mutation-deterministic theory. The analysis here therefore suggests that sexual organisms can simultaneously minimize both the effects of deleterious, strongly synergistically, interacting mutations and those that interact either weakly synergistically, multiplicatively, or antagonistically, assuming the latter class belong to a multicopy gene family. Recombination and an absence of homogenization are efficient in purging deleterious mutations in the former class, homogenization and an absence of recombination are efficient at minimizing the costs imposed by the latter classes.     

Sexual selection and the adaptive evolution of mammalian ejaculate proteins

An elevated rate of substitution characterizes the molecular evolution of reproductive proteins from a wide range of taxa. Although the selective pressures explaining this rapid evolution are yet to be resolved, recent evidence implicates sexual selection as a potentially important explanatory factor. To investigate this hypothesis, we sought evidence of a high rate of adaptive gene evolution linked to postcopulatory sexual selection in muroid rodents, a model vertebrate group displaying a broad range of mating systems. Specifically, we sequenced 7 genes from diverse rodents that are expressed in the testes, prostate, or seminal vesicles, products of which have the potential to act in sperm competition. We inferred positive Darwinian selection in these genes by estimation of the ratio of nonsynonymous (d(N), amino acid changing) to synonymous (d(S), amino acid retaining) substitution rates (omega = d(N)/d(S)). Next, we tested whether variation in this ratio among lineages could be attributed to interspecific variation in mating systems, as inferred from the variation in these rodents' relative testis sizes (RTS). Four of the 7 genes examined (Prm1, Sva, Acrv1, and Svs2, but not Svp2, Msmb, or Spink3) exhibit unambiguous evidence of positive selection. One of these, the seminal vesicle-derived protein Svs2, also shows some evidence for a concentration of positive selection in those lineages in which sperm competition is common. However, this was not a general trend among all the rodent genes we examined. Using the same methods, we then reanalyzed previously published data on 2 primate genes, SEMG1 and SEMG2. Although SEMG2 also shows evidence of positive selection concentrated in lineages subject to high levels of sperm competition, no such trend was found for SEMG1. Overall, despite a high rate of positive selection being a feature of many ejaculate proteins, these results indicate that the action of sexual selection potentially responsible for elevated evolutionary rates may be difficult to detect on a gene-by-gene basis. Although the extreme diversity of reproductive phenotypes exhibited in nature attests to the power of sexual selection, the extent to which this force predominates in driving the rapid molecular evolution of reproductive genes therefore remains to be determined.     

A Critique of R.D. Alexander's Views on Group Selection

Group selection is increasingly being viewed as an important force in human evolution. This paper examines the views of R.D. Alexander, one of the most influential thinkers about human behavior from an evolutionary perspective, on the subject of group selection. Alexander's general conception of evolution is based on the gene-centered approach of G.C. Williams, but he has also emphasized a potential role for group selection in the evolution of individual genomes and in human evolution. Alexander's views are internally inconsistent and underestimate the importance of group selection. Specific themes that Alexander has developed in his account of human evolution are important but are best understood within the framework of multilevel selection theory. From this perspective, Alexander's views on moral systems are not the radical departure from conventional views that he claims, but remain radical in another way more compatible with conventional views.     

Retroelements: tools for sex chromosome evolution

Many eukaryotic taxa inherit a heteromorphic sex chromosome pair. It is a generally accepted hypothesis that the sex chromosome pair is derived from a pair of homologous autosomes that has developed after the occurrence of a sex differentiator in an evolutionary process into two structurally and functionally different partners. In most of the analyzed systems the occurrence of the dominant sex differentiator is paralleled by the suppression of recombination within and close by that region. The recombinational isolation can spread in an evolutionary selection process from neighboring regions finally over the whole chromosome. Suppression of recombination strongly biases the distribution of retrotransposons in the genome. Our results and that from others indicate that the major force driving the evolution of Y chromosomes are retrotransposons, remodeling euchromatic chromosome structures into heterochromatic ones. In our model, intact or already eroded retrotransposons become trapped due to their inherent transposition mechanisms in non-recombining regions. The massive accumulation of retrotransposons interferes strongly with the activity of genes. We hypothesize that Y chromosome degeneration is a stepwise evolutionary process: (1) Massive accumulation of retrotransposons occurs in the non-recombining regions. (2) Heterochromatic nucleation centers are formed as a consequence of genomic defense against invasive parasitic elements; the established nucleation centers become epigenetically inherited. (3) Spreading of heterochromatin from the nucleation centers into flanking regions induces in an adaptive process gene silencing of neighbored genes that could either be still intact or in an already eroded condition, e.g., showing point mutations, deletions, insertions; the retroelements should be subjects to the same forces of deterioration as the genes themselves. (4) Constitutive silenced genes are not committed to the same genetic selection pressure as active genes and therefore more exposed to the decay process. (5) Gene dosage balance is reestablished by the parallel evolution of dosage compensation mechanisms. The evolving secondary sex chromosomes, neo-X and neo-Y, of Drosophila miranda are revealed to be a unique and potent model system to catch the evolutionary Y deterioration process in progress.     

The neutral theory of molecular evolution: a review of recent evidence

In sharp contrast to the Darwinian theory of evolution by natural selection, the neutral theory claims that the overwhelming majority of evolutionary changes at the molecular level are caused by random fixation (due to random sampling drift in finite populations) of selectively neutral (i.e., selectively equivalent) mutants under continued inputs of mutations. The theory also asserts that most of the genetic variability within species at the molecular level (such as protein and DNA polymorphism) are selectively neutral or very nearly neutral and that they are maintained in the species by the balance between mutational input and random extinction. The neutral theory is based on simple assumptions, enabling us to develop mathematical theories based on population genetics to treat molecular evolution and variation in quantitative terms. The theory can be tested against actual observations. Neo-Darwinians continue to criticize the neutral theory, but evidence for it has accumulated over the last two decades. The recent outpouring of DNA sequence data has greatly strengthened the theory. In this paper, I review some recent observations that strongly support the neutral theory. They include such topics as pseudoglobin genes of the mouse, alpha A-crystallin genes of the blind mole rat, genes of influenza A virus and nuclear vs. mitochondrial genes of fruit flies. I also discuss such topics as the evolution of deviant coding systems in Mycoplasma, the origin of life and the unified understanding of molecular and phenotypic evolution. I conclude that since the origin of life on Earth, neutral evolutionary changes have predominated over Darwinian evolutionary changes, at least in number.     

The relation between multilocus population genetics and social evolution theory

Evolution at multiple gene positions is complicated. Direct selection on one gene disturbs the evolutionary dynamics of associated genes. Recent years have seen the development of a multilocus methodology for modeling evolution at arbitrary numbers of gene positions with arbitrary dominance and epistatic relations, mode of inheritance, genetic linkage, and recombination. We show that the approach is conceptually analogous to social evolutionary methodology, which focuses on selection acting on associated individuals. In doing so, we (1) make explicit the links between the multilocus methodology and the foundations of social evolution theory, namely, Price's theorem and Hamilton's rule; (2) relate the multilocus approach to levels-of-selection and neighbor-modulated-fitness approaches in social evolution; (3) highlight the equivalence between genetical hitchhiking and kin selection; (4) demonstrate that the multilocus methodology allows for social evolutionary analyses involving coevolution of multiple traits and genetical associations between nonrelatives, including individuals of different species; (5) show that this methodology helps solve problems of dynamic sufficiency in social evolution theory; (6) form links between invasion criteria in multilocus systems and Hamilton's rule of kin selection; (7) illustrate the generality and exactness of Hamilton's rule, which has previously been described as an approximate, heuristic result.     

Concerted evolution of sea anemone neurotoxin genes is revealed through analysis of the Nematostella vectensis genome

Gene families, which encode toxins, are found in many poisonous animals, yet there is limited understanding of their evolution at the nucleotide level. The release of the genome draft sequence for the sea anemone Nematostella vectensis enabled a comprehensive study of a gene family whose neurotoxin products affect voltage-gated sodium channels. All gene family members are clustered in a highly repetitive approximately 30-kb genomic region and encode a single toxin, Nv1. These genes exhibit extreme conservation at the nucleotide level which cannot be explained by purifying selection. This conservation greatly differs from the toxin gene families of other animals (e.g., snakes, scorpions, and cone snails), whose evolution was driven by diversifying selection, thereby generating a high degree of genetic diversity. The low nucleotide diversity at the Nv1 genes is reminiscent of that reported for DNA encoding ribosomal RNA (rDNA) and 2 hsp70 genes from Drosophila, which have evolved via concerted evolution. This evolutionary pattern was experimentally demonstrated in yeast rDNA and was shown to involve unequal crossing-over. Through sequence analysis of toxin genes from multiple N. vectensis populations and 2 other anemone species, Anemonia viridis and Actinia equina, we observed that the toxin genes for each sea anemone species are more similar to one another than to those of other species, suggesting they evolved by manner of concerted evolution. Furthermore, in 2 of the species (A. viridis and A. equina) we found genes that evolved under diversifying selection, suggesting that concerted evolution and accelerated evolution may occur simultaneously.     

Morphological interpretation of darwinism

The development of evolutionary theory requires the resolution of the problem of relationships between random and regular processes in historical development of biological systems. According to the theory of natural selection, ecological factors play a leading role in evolution. Variations are nondirectional, unpredictable, and provide chaotic diversity of variants, only some of which are potentially useful. However, based on random processes, new variants that are useful for organisms and remain adaptive significance in various ecological situations are infrequent. At the same time, morphology demonstrates certain evolutionary patterns. The morphological approach takes into account the role in evolution of structural features of organism and social systems and evolutionary significance of “constructive technologies,” which distinguish morphological interpretation of evolutionary processes. The constructive and evolutionary patterns revealed in biological systems provide the basis for morphological interpretation of the principle of natural selection: both natural and artificial selection is interaction between social systems (populations, ecosystems, biogeocoenoses) and organisms composing them.     

Purifying and directional selection in overlapping prokaryotic genes

In overlapping genes, the same DNA sequence codes for two proteins using different reading frames. Analysis of overlapping genes can help in understanding the mode of evolution of a coding region from noncoding DNA. We identified 71 pairs of convergent genes, with overlapping 3' ends longer than 15 nucleotides, that are conserved in at least two prokaryotic genomes. Among the overlap regions, we observed a statistically significant bias towards the 123:132 phase (i.e. the second codon base in one gene facing the degenerate third position in the second gene). This phase ensures the least mutual constraint on nonconservative amino acid replacements in both overlapping coding sequences. The excess of this phase is compatible with directional (positive) selection acting on the overlapping coding regions. This could be a general evolutionary mode for genes emerging from noncoding sequences, in which the protein sequence has not been subject to selection.     

Are There Laws of Genome Evolution?

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.