Genetic covariances promote climatic adaptation in Australian Drosophila*

Evolutionary potential for adaptation hinges upon the orientation of genetic variation for traits under selection, captured by the additive genetic variance-covariance matrix (G), as well as the evolutionary stability of G. Yet studies that assess both the stability of G and its alignment with selection are extraordinarily rare. We evaluated the stability of G in three Drosophila melanogaster populations that have adapted to local climatic conditions along a latitudinal cline. We estimated population- and sex-specific G matrices for wing size and three climatic stress-resistance traits that diverge adaptively along the cline. To determine how G affects evolutionary potential within these populations, we used simulations to quantify how well G aligns with the direction of trait divergence along the cline (as a proxy for the direction of local selection) and how genetic covariances between traits and sexes influence this alignment. We found that G was stable across the cline, showing no significant divergence overall, or in sex-specific subcomponents, among populations. G also aligned well with the direction of clinal divergence, with genetic covariances strongly elevating evolutionary potential for adaptation to climatic extremes. These results suggest that genetic covariances between both traits and sexes should significantly boost evolutionary responses to environmental change.     

Antagonistic pleiotropy can promote adaptation to patchy environments*

How do gene variants with opposing effects on fitness in juvenile and adult insects perform in different ecological settings? Marden et al. used alleles of two antagonistic genes involved in metabolism and oxygen sensing in the Glanville fritillary butterfly as a model to demonstrate how these genes can antagonistically affect larval development and the adaptation of adults to different landscapes. This paper provides a case study for understanding how antagonistic pleiotropy can contribute to species adaption in patchy environments.     

A synaptic model for spatial frequency adaptation

A model for visual adaptation to spatial grating is developed based on the assumption that inhibitory synapses within the visual system may be temporarily modified as a function of recent usage. Specifically, it is hypothesized that inhibitory synaptic weights are altered as a function of the correlation between recent presynaptic and postsynaptic activity. When such modifiable synapses are incorporated into a simple neural network model having the spatial filtering properties of the human visual system, two coupled equations are obtained which may be solved analytically. The model accounts for experimental data on adaptation to sinusoidal gratings, square wave gratings, single bars, and tilted gratings. The relationship of the model to single and multiple channel models of the human visual system is discussed.     

Sexual selection fails to promote adaptation to a new environment

Selection can be divided into sexual and nonsexual components. Some work finds that a component of sexual selection, adaptive female selection for good genes, can promote nonsexual fitness. Less studied is the benefit from sexual selection in toto, that is, when intra- and intersexual selection are both present and able to affect females directly and indirectly. Here an upper bound for the net benefit of sexual selection is estimated for Drosophila melanogaster. Replicate populations were allowed to adapt to low-grade thermal stress, with or with out the operation of sexual selection. Because proteins and lipids are highly sensitive to temperature, low-grade thermal stress will select broadly across the genome for alternative alleles. Such broad, directional selection for thermal tolerance should increase the measurable benefits of sexual selection far beyond that available under stabilizing selection. Sexual selection was removed by enforced monogamy without mate choice and retained by enforced polyandry (four males per female). After 36 generations of thermal stress exposure, there was substantial adaptation to the new environment (the net reproductive rate increased six standard deviations relative to thermal controls). However, sexual selection did not affect the rate of adaptation. Therefore, adaptive female selection for thermal tolerance either was insignificant or negated by other aspects of sexual selection, for example, male-induced female harm, which has been shown to diminish under monogamy. This experiment employed two parameters that reduced the opportunity for divergence in such harm: a truncated intersexual interaction period and strong directional selection for thermal tolerance. No divergence in male-induced harm was observed.     

Travelling waves of resistance in a bi-trophic pest adaptation model

We consider a reaction-diffusion system for spatial spread of pest resistance to host plant resistance genes which is based on the Lotka-Volterra predator-prey equations, with logistic growth of the resource level and a diffusion term added to account for spatial spread of the pest. The model is phenotype specific, in which a pest subpopulation's fitness comes down to a balance between its resource assimilation rate and its respiration rate. We derive an expression for the rate of spatial spread of the resistant pest types from an initial point source, and discuss its relevance for adaptive pest resistance management strategies. Using results for an analogous single-species reaction-diffusion model in heterogeneous media, we consider the likely impact of pest-susceptible plant refugia on the speed of the travelling wave of resistant pests, and simultaneously the expected trade-off, in terms of crop yield decrease, when refugia are included. We also explore the possibility that resistance breaking by the pest population is not an inevitable phenomenon, particularly when refugia of the appropriate size are used.     

Contribution of cerebellar sensorimotor adaptation to hippocampal spatial memory

Complementing its primary role in motor control, cerebellar learning has also a bottom-up influence on cognitive functions, where high-level representations build up from elementary sensorimotor memories. In this paper we examine the cerebellar contribution to both procedural and declarative components of spatial cognition. To do so, we model a functional interplay between the cerebellum and the hippocampal formation during goal-oriented navigation. We reinterpret and complete existing genetic behavioural observations by means of quantitative accounts that cross-link synaptic plasticity mechanisms, single cell and population coding properties, and behavioural responses. In contrast to earlier hypotheses positing only a purely procedural impact of cerebellar adaptation deficits, our results suggest a cerebellar involvement in high-level aspects of behaviour. In particular, we propose that cerebellar learning mechanisms may influence hippocampal place fields, by contributing to the path integration process. Our simulations predict differences in place-cell discharge properties between normal mice and L7-PKCI mutant mice lacking long-term depression at cerebellar parallel fibre-Purkinje cell synapses. On the behavioural level, these results suggest that, by influencing the accuracy of hippocampal spatial codes, cerebellar deficits may impact the exploration-exploitation balance during spatial navigation.     

Eco-evolutionary metapopulation dynamics and the spatial scale of adaptation

We construct a model that combines extinction-colonization dynamics with the dynamics of local adaptation in a network of habitat patches of dissimilar qualities. We derive a deterministic approximation for the stochastic model that allows the calculation of patch-specific incidences of occupancy and levels of adaptation at steady state. Depending on (i) the strength of local selection, (ii) the amount of genetic variance, (iii) the demographic cost of maladaptation, (iv) the spatial scale of gene flow, and (v) the amount of habitat heterogeneity, the model predicts adaptation at different spatial scales. Local adaptation is predicted when there is much genetic variance and strong selection, while network-level adaptation occurs when the demographic cost of maladaptation is low. For little genetic variance and high cost of maladaptation, the model predicts network-level habitat specialization in species with long-range migration but an intermediate scale of adaptation (mosaic specialization) in species with short-range migration. In fragmented landscapes, the evolutionary dynamics of adaptation may both decrease and enhance metapopulation viability in comparison with no evolution. The model can be applied to real patch networks with given sizes, qualities, and spatial positions of habitat patches.     

Response and adaptation of different methanotrophic bacteria to low methane mixing ratios

Described genera of methanotrophic bacteria are present in most upland soils, but it is not known whether these are sufficiently oligotrophic to oxidize methane at its trace atmospheric mixing ratio of 1.75 ppmv. Members of the genera Methylocystis, Methylosinus, Methylocaldum and Methylobacter were isolated from different upland soils and compared with type strains for growth and activity under low methane mixing ratios. The specific affinity (a0s) varied by about one order of magnitude among different methanotrophs. It was highest in some Methylocystis spp., suggesting that these were the most oligotrophic. In direct tests, the threshold mixing ratio of methane required by most methanotrophs for growth ranged from 100 to greater than 1000 ppmv. However, two Methylocystis strains grew at only 10-100 ppmv of methane and one oxidized atmospheric methane for >3 months with little or no decline in the absolute rate. The results show that some cultivated methanotrophic bacteria are much more oligotrophic than others, and may contribute to atmospheric methane oxidation in soils. However, it is likely that these need additional energy sources for long-term survival, and that uncultivated groups of methanotrophic bacteria are primarily responsible for the process in soils possessing high methane oxidation rates.     

The spatial scale of local adaptation in a stochastic environment

The distribution of phenotypes in space will be a compromise between adaptive plasticity and local adaptation increasing the fit of phenotypes to local conditions and gene flow reducing that fit. Theoretical models on the evolution of quantitative characters on spatially explicit landscapes have only considered scenarios where optimum trait values change as deterministic functions of space. Here, these models are extended to include stochastic spatially autocorrelated aspects to the environment, and consequently the optimal phenotype. Under these conditions, the regression of phenotype on the environmental variable becomes steeper as the spatial scale on which populations are sampled becomes larger. Under certain deterministic models – such as linear clines – the regression is constant. The way in which the regression changes with spatial scale is informative about the degree of phenotypic plasticity, the relative scale of effective gene flow and the environmental dependency of selection. Connections to temporal models are discussed.     

The effect of spatial structure on adaptation in Escherichia coli

Populations of organisms are generally organized in a given spatial structure. However, the vast majority of population genetic studies are based on populations in which every individual competes globally. Here we use experimental evolution in Escherichia coli to directly test a recently made prediction that spatial structure slows down adaptation and that this cost increases with the mutation rate. This was studied by comparing populations of different mutation rates adapting to a liquid (unstructured) medium with populations that evolved in a Petri dish on solid (structured) medium. We find that mutators adapt faster to both environments and that adaptation is slower if there is spatial structure. We observed no significant difference in the cost of structure between mutator and wild-type populations, which suggests that clonal interference is intense in both genetic backgrounds.     

Reduction of species coexistence through mixing in a spatial competition model

Many ecological systems exhibit self-organized spatial patterns due to local interactions. Such patterns can promote species diversity and therefore serve as an important mechanism for biodiversity maintenance. Previous work has shown that when species interactions occurred at local spatial scales, species diversity was greatest when robust mosaic spatial patterns formed. Also, intransitive interactions led to the emergence of spiral patterns, frequently resulting in multispecies coexistence. In some instances, intransitive interactions reduced species diversity as the consequence of competitive hierarchies. Here, we extend and broaden this line of investigation and examine the role of global competition along a continuum ranging from spatial mosaics to spiral patterns. While previous models have predicted that species diversity is reduced when interactions occur over larger spatial scales, our model considers the effects of various levels of mixing on species diversity, in the context of various network structures as measured by the covariance of row and column sums of the competition matrix. First, we compare local competition (unmixed system) versus global competition (mixed systems) and show that greater species diversity is maintained under a positive covariance. Second, we show that under various levels of mixing, species diversity declines more rapidly under a negative covariance. Lastly, we demonstrate that time to extinction in our model occurs much more rapidly under a negative covariance.     

Selective methylation changes on the Bacillus subtilis chemotaxis receptor McpB promote adaptation

The Bacillus subtilis McpB is a class III chemotaxis receptor, from which methanol is released in response to all stimuli. McpB has four putative methylation sites based upon the Escherichia coli consensus sequence. To explore the nature of methanol release from a class III receptor, all combinations of putative methylation sites Gln(371), Gln(595), Glu(630), and Glu(637) were substituted with aspartate, a conservative substitution that effectively eliminates methylation. McpB((Q371D,E630D,E637D)) in a Delta(mcpA mcpB tlpA tlpB)101::cat mcpC4::erm background failed to release methanol in response to either the addition or removal of the McpB-mediated attractant asparagine. In the same background, McpB((E630D,E637D)) produced methanol only upon asparagine addition, whereas McpB((Q371D,E630D)) produced methanol only upon asparagine removal. Thus methanol release from McpB was selective. Mutants unable to methylate site 637 but able to methylate site 630 had high prestimulus biases and were incapable of adapting to asparagine addition. Mutants unable to methylate site 630 but able to methylate site 637 had low prestimulus biases and were impaired in adaptation to asparagine removal. We propose that selective methylation of these two sites represents a method of adaptation novel from E. coli and present a model in which a charged residue rests between them. The placement of this charge would allow for opposing electrostatic effects (and hence opposing receptor conformational changes). We propose that CheC, a protein not found in enteric systems, has a role in regulating this selective methylation.     

Limited dispersal and local adaptation promote allopatric speciation in a biodiversity hotspot

Recently diverged or diverging populations can offer unobstructed insights into early barriers to gene flow during the initial stages of speciation. The current study utilised a novel insect system (order Mantophasmatodea) to shed light on the early drivers of speciation. The members of this group have limited dispersal abilities, small allopatric distributions and strong habitat associations in the Cape Floristic Region biodiversity hotspot in South Africa. Sister taxa from the diverse family Austrophasmatidae were chosen as focal species (Karoophasma biedouwense, K. botterkloofense). Population genetics and Generalized Dissimilarity Modelling (GDM) were used to characterise spatial patterns of genetic variation and evaluate the contribution of environmental factors to population divergence and speciation. Extensive sampling confirmed the suspected allopatry of these taxa. However, hybrids were identified in a narrow region occurring between the species' distributions. Strong population structure was found over short geographic distances; particularly in K. biedouwense in which geographic distance accounted for 32% of genetic variation over a scale of 50 km (r = .56, p < .001). GDM explained 42%–78% of the deviance in observed genetic dissimilarities. Geographic distance was consistently indicated to be important for between species and within population differentiation, suggesting that limited dispersal ability may be an important neutral driver of divergence. Temperature, altitude, precipitation and vegetation were also indicated as important factors, suggesting the possible role of adaptation to local environmental conditions for species divergence. The discovery of the hybrid-zone, and the multiple allopatric species pairs in Austrophasmatidae support the idea that this could be a promising group to further our understanding of speciation modes.     

Phenotypic and transgenerational plasticity promote local adaptation to sun and shade environments

Adaptive plasticity is expected to be important when the grain of environmental variation is encompassed in offspring dispersal distance. We investigated patterns of local adaptation, selection and plasticity in an association of plant morphology with fine-scale habitat shifts from oak canopy understory to adjacent grassland habitat in Claytonia perfoliata. Populations from beneath the canopy of oak trees were >90 % broad leaved and large seeded, while plants from adjacent grassland habitat were >90 % linear-leaved and small seeded. In a 2-year study, we used reciprocal transplants and phenotypic selection analysis to investigate local adaptation, selection, plasticity and maternal effects in this trait-environment association. Transgenerational effects were studied by planting offspring of inbred maternal families grown in both environments across the same environments in the second year. Reciprocal transplants revealed local adaptation to habitat type: broad-leaved forms had higher fitness in oak understory and linear-leaved plants had higher fitness in open grassland habitat. Phenotypic selection analyses indicated selection for narrower leaves and lower SLA in open habitat, and selection for broad leaves and intermediate values of SLA in understory. Both plant morphs exhibited plastic responses in traits in the same direction as selection on traits (narrower leaves and lower SLA in open habitat) suggesting that plasticity is adaptive. We detected an adaptive transgenerational effect in which maternal environment influenced offspring fitness; offspring of grassland-reared plants had higher fitness than understory-reared plants when grown in grassland. We did not detect costs of plasticity, but did find a positive association between leaf shape plasticity and fitness in linear-leaved plants in grassland habitat. Together, these findings indicate that fixed differences in trait values corresponding to selection across habitat contribute to local adaptation, but that plasticity and maternal environmental effects may be favored through promotion of survival across heterogeneous environments.     

The role of motor learning in spatial adaptation near a tool

Some visual-tactile (bimodal) cells have visual receptive fields (vRFs) that overlap and extend moderately beyond the skin of the hand. Neurophysiological evidence suggests, however, that a vRF will grow to encompass a hand-held tool following active tool use but not after passive holding. Why does active tool use, and not passive holding, lead to spatial adaptation near a tool? We asked whether spatial adaptation could be the result of motor or visual experience with the tool, and we distinguished between these alternatives by isolating motor from visual experience with the tool. Participants learned to use a novel, weighted tool. The active training group received both motor and visual experience with the tool, the passive training group received visual experience with the tool, but no motor experience, and finally, a no-training control group received neither visual nor motor experience using the tool. After training, we used a cueing paradigm to measure how quickly participants detected targets, varying whether the tool was placed near or far from the target display. Only the active training group detected targets more quickly when the tool was placed near, rather than far, from the target display. This effect of tool location was not present for either the passive-training or control groups. These results suggest that motor learning influences how visual space around the tool is represented.     

Signal processing through a generalized module of adaptation and spatial sensing

Signal transduction in many cellular processes is accompanied by the feature of adaptation, which allows certain key signalling components to respond to temporal and/or spatial variation of external signals, independent of the absolute value of the signal. We extend and formulate a more general module which accounts for robust temporal adaptation and spatial response. In this setting, we examine various aspects of spatial and temporal signalling, as well as the signalling consequences and restrictions imposed by virtue of adaptation. This module is able to exhibit a variety of behaviour in response to temporal, spatial and spatio-temporal inputs. We carefully examine the roles of various parameters in this module and how they affect signal processing and propagation. Overall, we demonstrate how a simple module can account for a range downstream responses to a variety of input signals, and how elucidating the downstream response of many cellular components in systems with such adaptive signalling can be consequently very non-trivial.