Detecting signatures of balancing selection to identify targets of anti-parasite immunity.

Parasite antigen genes might evolve under frequency-dependent immune selection. The distinctive patterns of polymorphism that result can be detected using population genetic methods that test for signatures of balancing selection, allowing genes encoding important targets of immunity to be identified. Analyses can be complicated by population structures, histories and features of a parasite's genome. However, new sequencing technologies facilitate scans of polymorphism throughout parasite genomes to identify the most exceptional gene specific signatures. We focus on malaria parasites to illustrate challenges and opportunities for detecting targets of frequency-dependent immune selection to discover new potential vaccine candidates

Frequency-Dependent Selection at Rough Expanding Fronts

Microbial colonies are experimental model systems for studying the colonization of new territory by biological species through range expansion. We study a generalization of the two-species Eden model, which incorporates local frequency-dependent selection, in order to analyze how social interactions between two species influence surface roughness of growing microbial colonies. The model includes several classical scenarios from game theory. We then concentrate on an expanding public goods game, where either cooperators or defectors take over the front depending on the system parameters. We analyze in detail the critical behavior of the nonequilibrium phase transition between global cooperation and defection and thereby identify a new universality class of phase transitions dealing with absorbing states. At the transition, the number of boundaries separating sectors decays with a novel power law in time and their superdiffusive motion crosses over from Eden scaling to a nearly ballistic regime. In parallel, the width of the front initially obeys Eden roughening and, at later times, passes over to selective roughening.Comment: 11 pages, 10 figure

How to Measure Group Selection in Real-world Populations

Multilevel selection and the evolution of cooperation are fundamental to the formation of higher-level organisation and the evolution of biocomplexity, but such notions are controversial and poorly understood in natural populations. The theoretic principles of group selection are well developed in idealised models where a population is neatly divided into multiple semi-isolated sub-populations. But since such models can be explained by individual selection given the localised frequency-dependent effects involved, some argue that the group selection concepts offered are, even in the idealised case, redundant and that in natural conditions where groups are not well-defined that a group selection framework is entirely inapplicable. This does not necessarily mean, however, that a natural population is not subject to some interesting localised frequency-dependent effects – but how could we formally quantify this under realistic conditions? Here we focus on the presence of a Simpson’s Paradox where, although the local proportion of cooperators decreases at all locations, the global proportion of cooperators increases. We illustrate this principle in a simple individual-based model of bacterial biofilm growth and discuss various complicating factors in moving from theory to practice of measuring group selection

Novel Floating General Element Simulators Using CBTA

In this study, a novel floating frequency dependent negative resistor (FDNR), floating inductor, floating capacitor and floating resistor simulator circuit employing two CBTAs and three passive components is proposed. The presented circuit can realize floating FDNR, inductor, capacitor or resistor depending on the passive component selection. Since the passive elements are all grounded, this circuit is suitable for fully integrated circuit design. The circuit does not require any component matching conditions, and it has a good sensitivity performance with respect to tracking errors. Moreover, the proposed FDNR, inductance, capacitor and resistor simulator can be tuned electronically by changing the biasing current of the CBTA or can be controlled through the grounded resistor or capacitor. The high-order frequency dependent element simulator circuit is also presented. Depending on the passive component selection, it realizes high-order floating circuit defining as V(s) = snAI(s) or V(s) = s-nBI(s). The proposed floating FDNR simulator circuit and floating high-order frequency dependent element simulator circuit are demonstrated by using PSPICE simulation for 0.25 μm, level 7, TSMC CMOS technology parameters

Frequency-dependent selection predicts patterns of radiations and biodiversity

Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking niche-filling processes, whereas constant rates have been attributed to non-adaptive processes such as sexual selection, mutation, and dispersal. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the speciation rate is driven by frequency dependent selection. We used a frequency-dependent and DNA sequence-based model of populations and genetic-distance-based speciation, in the absence of adaptation to ecological niches. We tested the frequency-dependent selection mechanism using cichlid fish and Darwin's finches, two classic model systems for which speciation rates and richness data exist. Using negative frequency dependent selection, our model both predicts the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, the speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity are driven by larger incipient species abundance (and consequent lower extinction rates) with frequency-dependent selection. These results demonstrate that mutations, genetic-distance-based speciation, sexual and frequency-dependent selection are sufficient not only for promoting rapid proliferation of new species, but also for maintaining the high diversity observed in natural systems

Morphological and population genomic evidence that human faces have evolved to signal individual identity.

Facial recognition plays a key role in human interactions, and there has been great interest in understanding the evolution of human abilities for individual recognition and tracking social relationships. Individual recognition requires sufficient cognitive abilities and phenotypic diversity within a population for discrimination to be possible. Despite the importance of facial recognition in humans, the evolution of facial identity has received little attention. Here we demonstrate that faces evolved to signal individual identity under negative frequency-dependent selection. Faces show elevated phenotypic variation and lower between-trait correlations compared with other traits. Regions surrounding face-associated single nucleotide polymorphisms show elevated diversity consistent with frequency-dependent selection. Genetic variation maintained by identity signalling tends to be shared across populations and, for some loci, predates the origin of Homo sapiens. Studies of human social evolution tend to emphasize cognitive adaptations, but we show that social evolution has shaped patterns of human phenotypic and genetic diversity as well

Symmetric competition as a general model for single-species adaptive dynamics

Adaptive dynamics is a widely used framework for modeling long-term evolution of continuous phenotypes. It is based on invasion fitness functions, which determine selection gradients and the canonical equation of adaptive dynamics. Even though the derivation of the adaptive dynamics from a given invasion fitness function is general and model-independent, the derivation of the invasion fitness function itself requires specification of an underlying ecological model. Therefore, evolutionary insights gained from adaptive dynamics models are generally model-dependent. Logistic models for symmetric, frequency-dependent competition are widely used in this context. Such models have the property that the selection gradients derived from them are gradients of scalar functions, which reflects a certain gradient property of the corresponding invasion fitness function. We show that any adaptive dynamics model that is based on an invasion fitness functions with this gradient property can be transformed into a generalized symmetric competition model. This provides a precise delineation of the generality of results derived from competition models. Roughly speaking, to understand the adaptive dynamics of the class of models satisfying a certain gradient condition, one only needs a complete understanding of the adaptive dynamics of symmetric, frequency-dependent competition. We show how this result can be applied to number of basic issues in evolutionary theory.Comment: 26 pages, 1 figur