Genetic team composition and level of selection in the evolution of cooperation

In cooperative multiagent systems, agents interac to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules ("geneti- cally homogeneous teams") and select behavior at the team level ("team-level selection"). Here we extend current approaches to include four combinations of genetic team composition and level of selection. We compare the performance of genetically homo- geneous teams evolved with individual-level selection, genetically homogeneous teams evolved with team-level selection, genetically heterogeneous teams evolved with individual-level selection, and genetically heterogeneous teams evolved with team-level selection. We use a simulated foraging task to show that the optimal combination depends on the amount of cooperation required by the task. Accordingly, we distinguish between three types of cooperative tasks and suggest guidelines for the optimal choice of genetic team composition and level of selection

The evolution of personality in patients with mild cognitive impairment.

Aims: To describe personality traits and their changes in mild cognitive impairment (MCI) and control subjects. Methods: Sixty-three MCI and 90 control subjects were asked to describe their current personality traits by the Structured Interview for the Five-Factor Model (SIFFM). For each subject, a close relative retrospectively assessed these descriptions both as to the previous and current personality traits, using the Revised NEO Personality Inventory, Form R (NEO-PI-R). Results: Self-assessed MCI subjects reported significantly lower scores in the openness dimension than control subjects [F(1, 150) = 9.84, p = 0.002, ηp(2) = 0.06]. In current observer ratings, MCI subjects had higher scores on neuroticism [F(1, 137) = 7.55, p = 0.007, ηp(2) = 0.05] and lower ones on extraversion [F(1, 137) = 6.40, p = 0.013, ηp(2) = 0.04], openness [F(1, 137) = 9.93, p = 0.002, ηp(2) = 0.07], agreeableness [F(1, 137) = 10.18, p = 0.002, ηp(2) = 0.07] and conscientiousness [F(1, 137) = 25.96, p < 0.001, ηp(2) = 0.16]. Previous personality traits discriminated the groups as previous openness [odds ratio (OR) = 0.97, 95% confidence interval (CI) = 0.95-0.99, p = 0.014] and conscientiousness (OR = 0.96, 95% CI 0.94-0.98, p = 0.001) were negatively related to MCI group membership. In MCI subjects, conscientiousness [F(1, 137) = 19.20, p < 0.001, ηp(2) = 0.12] and extraversion [F(1, 137) = 22.27, p < 0.001, ηp(2) = 0.14] decreased between previous and current evaluations and neuroticism increased [F(1, 137) = 22.23, p < 0.001, ηp(2) = 0.14], whereas no significant change was found in control subjects. Conclusions: MCI subjects undergo significant personality changes. Thus, personality assessment may aid the early detection of dementia. © 2013 S. Karger AG, Basel.

What kind of relationships between the evolution of pain, beliefs and bio-psycho-social complexity after a locomotor traumatism?

Introduction: Pain and beliefs have an influence on the patient's course in rehabilitation, pain causes fears and fears influence pain perception. The aim of this study is to understand pain and beliefs evolutions during rehabilitation taking into account of bio-psycho-social complexity.Patients and methods: 631 consecutive patients admitted in rehabilitation after a musculoskeletal traumatism were included and assessed at admission and at discharge. Pain was measured by VAS (Visual Analogical Scale), bio-psycho-social complexity by Intermed scale, and beliefs by judgement on Lickert scales. Four kinds of beliefs were evaluated: fear of a severe origin of pain, fear of movement, fear of pain and feeling of distress (loss of control). The association between the changes in pain and beliefs during the hospitalization was assessed by linear regressions.Results: After adjustment for gender, age, education and native language, patients with a decrease in pain during rehabilitation have higher probability of decreasing their fears. For the distress feeling, this relationship is weaker among bio-psycho-socially complex patients (odds-ratio 1.22 for each decreasing of 10mm/100 VAS) than among non-complex patients (OR 1.47). Patients with a pain decrease of 30% or more during hospitalization have higher probability of seeing their fears decrease, this relationship being stronger in complex patient for fear of a severe origin of pain.Discussion: The relationships between evolution of pain and beliefs move in the same direction. The higher a patient feels pain, the less they could be able to modify their dysfunctional beliefs. When the pain diminishes of 30% or more, the probability to challenge the beliefs is increased. The prognostic with regard to feeling of distress and fear of a severe origin of pain, is worse among bio-psycho-socially complex patients.

Evidence for the evolution of multiple genomes in arbuscular mycorrhizal fungi.

Ancient asexuals directly contradict the evolutionary theories that explain why organisms should evolve a sexual life history. The mutualistic, arbuscular mycorrhizal fungi are thought to have been asexual for approximately 400 million years. In the absence of sex, highly divergent descendants of formerly allelic nucleotide sequences are thought to evolve in a genome. In mycorrhizal fungi, where individual offspring receive hundreds of nuclei from the parent, it has been hypothesized that a population of genetically different nuclei should evolve within one individual. Here we use DNA-DNA fluorescent in situ hybridization to show that genetically different nuclei co-exist in individual arbuscular mycorrhizal fungi. We also show that the population genetics techniques used in other organisms are unsuitable for detecting recombination because the assumptions and underlying processes do not fit the fungal genomic structure shown here. Instead we used a phylogenetic approach to show that the within-individual genetic variation that occurs in arbuscular mycorrhizal fungi probably evolved through accumulation of mutations in an essentially clonal genome, with some infrequent recombination events. We conclude that mycorrhizal fungi have evolved to be multi-genomic.

Predicting the evolution of Kaposi sarcoma, in the highly active antiretroviral therapy era.

BACKGROUND: The outcome of Kaposi sarcoma varies. While many patients do well on highly active antiretroviral therapy, others have progressive disease and need chemotherapy. In order to predict which patients are at risk of unfavorable evolution, we established a prognostic score. METHOD: The survival analysis (Kaplan-Meier method; Cox proportional hazards models) of 144 patients with Kaposi sarcoma prospectively included in the Swiss HIV Cohort Study, from January 1996 to December 2004, was conducted. OUTCOME ANALYZED: use of chemotherapy or death. VARIABLES ANALYZED: demographics, tumor staging [T0 or T1 (16)], CD4 cell counts and HIV-1 RNA concentration, human herpesvirus 8 (HHV8) DNA in plasma and serological titers to latent and lytic antigens. RESULTS: Of 144 patients, 54 needed chemotherapy or died. In the univariate analysis, tumor stage T1, CD4 cell count below 200 cells/microl, positive HHV8 DNA and absence of antibodies against the HHV8 lytic antigen at the time of diagnosis were significantly associated with a bad outcome.Using multivariate analysis, the following variables were associated with an increased risk of unfavorable outcome: T1 [hazard ratio (HR) 5.22; 95% confidence interval (CI) 2.97-9.18], CD4 cell count below 200 cells/microl (HR 2.33; 95% CI 1.22-4.45) and positive HHV8 DNA (HR 2.14; 95% CI 1.79-2.85).We created a score with these variables ranging from 0 to 4: T1 stage counted for two points, CD4 cell count below 200 cells/microl for one point, and positive HHV8 viral load for one point. Each point increase was associated with a HR of 2.26 (95% CI 1.79-2.85). CONCLUSION: In the multivariate analysis, staging (T1), CD4 cell count (<200 cells/microl), positive HHV8 DNA in plasma, at the time of diagnosis, predict evolution towards death or the need of chemotherapy.

The evolution of helping and harming on graphs: the return of the inclusive fitness effect.

Evolutionary graph theory has been proposed as providing new fundamental rules for the evolution of co-operation and altruism. But how do these results relate to those of inclusive fitness theory? Here, we carry out a retrospective analysis of the models for the evolution of helping on graphs of Ohtsuki et al. [Nature (2006) 441, 502] and Ohtsuki & Nowak [Proc. R. Soc. Lond. Ser. B Biol. Sci (2006) 273, 2249]. We show that it is possible to translate evolutionary graph theory models into classical kin selection models without disturbing at all the mathematics describing the net effect of selection on helping. Model analysis further demonstrates that costly helping evolves on graphs through limited dispersal and overlapping generations. These two factors are well known to promote relatedness between interacting individuals in spatially structured populations. By allowing more than one individual to live at each node of the graph and by allowing interactions to vary with the distance between nodes, our inclusive fitness model allows us to consider a wider range of biological scenarios leading to the evolution of both helping and harming behaviours on graphs.

The evolution of gene expression levels in mammalian organs.

Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

The evolution of punishment through reputation.

Punishment of non-cooperators has been observed to promote cooperation. Such punishment is an evolutionary puzzle because it is costly to the punisher while beneficial to others, for example, through increased social cohesion. Recent studies have concluded that punishing strategies usually pay less than some non-punishing strategies. These findings suggest that punishment could not have directly evolved to promote cooperation. However, while it is well established that reputation plays a key role in human cooperation, the simple threat from a reputation of being a punisher may not have been sufficiently explored yet in order to explain the evolution of costly punishment. Here, we first show analytically that punishment can lead to long-term benefits if it influences one's reputation and thereby makes the punisher more likely to receive help in future interactions. Then, in computer simulations, we incorporate up to 40 more complex strategies that use different kinds of reputations (e.g. from generous actions), or strategies that not only include punitive behaviours directed towards defectors but also towards cooperators for example. Our findings demonstrate that punishment can directly evolve through a simple reputation system. We conclude that reputation is crucial for the evolution of punishment by making a punisher more likely to receive help in future interactions, and that experiments investigating the beneficial effects of punishment in humans should include reputation as an explicit feature.

The interplay between relatedness and horizontal gene transfer drives the evolution of plasmid-carried public goods.

Plasmids carry a wide range of genes that are often involved in bacterial social behaviour. The question of why such genes are frequently mobile has received increasing attention. Here, we use an explicit population genetic approach to model the evolution of plasmid-borne bacterial public goods production. Our findings highlight the importance of both transmission and relatedness as factors driving the evolution of plasmid-borne public goods production. We partition the effects of plasmid transfer of social traits into those of infectivity and the effect of increased relatedness. Our results demonstrate that, owing to its effect on relatedness, plasmid mobility increases the invasion and stability of public goods, in a way not seen in individually beneficial traits. In addition, we show that plasmid transfer increases relatedness when public goods production is rare but this effect declines when production is common, with both scenarios leading to an increase in the frequency of plasmid-borne public goods. Plasmids remain important vectors for the spread of social genes involved in bacterial virulence thus an understanding of their dynamics is highly relevant from a public health perspective.

A quantitative test of Hamilton's rule for the evolution of altruism.

The evolution of altruism is a fundamental and enduring puzzle in biology. In a seminal paper Hamilton showed that altruism can be selected for when rb - c > 0, where c is the fitness cost to the altruist, b is the fitness benefit to the beneficiary, and r is their genetic relatedness. While many studies have provided qualitative support for Hamilton's rule, quantitative tests have not yet been possible due to the difficulty of quantifying the costs and benefits of helping acts. Here we use a simulated system of foraging robots to experimentally manipulate the costs and benefits of helping and determine the conditions under which altruism evolves. By conducting experimental evolution over hundreds of generations of selection in populations with different c/b ratios, we show that Hamilton's rule always accurately predicts the minimum relatedness necessary for altruism to evolve. This high accuracy is remarkable given the presence of pleiotropic and epistatic effects as well as mutations with strong effects on behavior and fitness (effects not directly taken into account in Hamilton's original 1964 rule). In addition to providing the first quantitative test of Hamilton's rule in a system with a complex mapping between genotype and phenotype, these experiments demonstrate the wide applicability of kin selection theory.

Non-random autosome segregation: a stepping stone for the evolution of sex chromosome complexes?

A new study in Caenorhabditis elegans shows that homologous autosomes segregate non-randomly with the sex chromosome in the heterogametic sex. Segregation occurs according to size, small autosomes segregating with, and large autosomes segregating away from the X-chromosome. Such sex-biased transmission of autosomes could facilitate the spread of sexually antagonistic alleles whose effects favor the fitness of one sex at the expense of the other. This may provide a first step toward the evolution of new sex determination systems.