Choosing appropriate genetic markers and analytical methods for testing landscape genetic hypotheses

Landscape genetics and phylogeography both examine population‐level microevolutionary processes, such as population structure and gene flow, in the context of environmental and geographic variation. They differ in terms of the spatial and temporal scales they typically investigate, meaning that different genetic markers and analytical methods are better suited for testing the different hypotheses typically posed by each discipline. In a recent comment, Bohonak & Vandergast (2011) argue that I overlooked the value of mtDNA for landscape genetics in an article I published last year in Molecular Ecology (Wang 2010) and that a gap between landscape genetics and phylogeography, which I outlined, does not exist. Here, I clarify several points in my original article and summarize the commonly held viewpoint that different genetic markers are appropriate for drawing inferences at different temporal scales.     

Bias in Behaviour Genetics: An Ecological Perspective

Research in behaviour genetics uncovers causes of behaviour at the population level. For inferences about individuals we also need to know how genes and the environment affect phenotypes. Behaviour genetics fosters a biased view of individual behaviour since it identifies the environment with psychosocial factors and disregards ecology.     

Optimality and evolutionary genetics: complementary procedures for evolutionary analysis in behavioural ecology

The concepts and tools of optimality and game theory are a major component of research in behavioural ecology. In contrast, the theory and practice of evolutionary, ecological, population and quantitative genetics have made less of an impact on those studying the evolution of animal behaviour. A more complete understanding of the evolution of behaviour can be achieved by pursuing research that combines optimality and genetics, thereby overcoming some of the limitations inherent in a single approach.     

Genetic contributions to behavioural diversity at the gene-environment interface

Recent work on behavioural variation within and between species has furthered our understanding of the genetic architecture of behavioural traits, the identities of relevant genes and the ways in which genetic variants affect neuronal circuits to modify behaviour. Here we review our understanding of the genetics of natural behavioural variation in non-human animals and highlight the implications of these findings for human genetics. We suggest that gene-environment interactions are central to natural genetic variation in behaviour and that genes affecting neuromodulatory pathways and sensory processing are preferred sites of naturally occurring mutations.     

The behaviour and ecology of the zebrafish, Danio rerio

The zebrafish Danio rerio, is an important model organism in developmental genetics, neurophysiology and biomedicine, but little is known about its natural ecology and behaviour. It is a small, shoaling cyprinid, native to the flood-plains of the Indian subcontinent, where it is found in shallow, slow-flowing waters. Zebrafish are group spawners and egg scatterers, although females are choosy with respect to sites for oviposition and males defend territories around such sites. Laboratory studies of zebrafish behaviour have encompassed shoaling, foraging, reproduction, sensory perception and learning. These studies are reviewed in relation to the suitability of the zebrafish as a model for studies on cognition and learning, development, behavioural and evolutionary ecology, and behavioural genetics.     

Human behavioural genetics of cognitive abilities and disabilities

Although neither the genome nor the environment can be manipulated in research on human behaviour, some of the new tools of molecular genetics can be brought to bear on human behavioural disorders (e.g. cognitive disabilities) and quantitative traits (e.g. cognitive abilities). The inability to manipulate the human genome experimentally has had the positive effect of focusing attention on naturally occuring genetic variation responsible for behavioural differences among individuals in all their complex multifactorial splendour. Genes in such complex multiple-gene systems are called quantitative trait loci (QTLs), which merge the two worlds of genetic research, quantitative genetics and molecular genetics. Although most genetic research on complex human behaviour has focused on severe mental disorders, cognitive abilities and disabilities may be even more immediately relevant to neuroscience. For example, verbal ability and spatial ability are two of the most heritable cognitive abilities, and reading disability is the first behavioural disability for which replicated QTL linkage has been found. The purpose of this essay is to provide an overview of the genetics of cognitive abilities and disabilities as an example of the impending merger of quantitative genetics and molecular genetics in QTL analysis of complex traits.     

Dynamics of a neural system with a multiscale architecture

The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales-neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are 'slaved' to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested.     

Science and society: applications of behavioural genetics: outpacing the science?

Human behavioural genetics is an established research discipline of the genomic age, and applications for behavioural genetic information are most likely to emerge in areas such as criminal justice, education, employment and insurance. However, behavioural genetic research into personality traits and antisocial behaviour poses several risks; for example, tentative or preliminary research findings might be misused in legal and commercial settings. Scientific caution, public and media education, expert consultation and confidentiality protection are essential for the responsible use of behavioural genetics.     

Quantitative genetics of behavioural reaction norms: genetic correlations between personality and behavioural plasticity vary across stickleback populations

Behavioural ecologists have proposed various evolutionary mechanisms as to why different personality types coexist. Our ability to understand the evolutionary trajectories of personality traits requires insights from the quantitative genetics of behavioural reaction norms. We assayed > 1000 pedigreed stickleback for initial exploration behaviour of a novel environment, and subsequent changes in exploration over a few hours, representing their capacity to adjust their behaviour to changes in perceived novelty and risk. We found heritable variation in both the average level of exploration and behavioural plasticity, and population differences in the sign of the genetic correlation between these two reaction norm components. The phenotypic correlation was not a good indicator of the genetic correlation, implying that quantitative genetics are necessary to appropriately evaluate evolutionary hypotheses in cases such as these. Our findings therefore have important implications for future studies concerning the evolution of personality and plasticity.     

Plant genetics shapes inquiline community structure across spatial scales

Recent research in community genetics has examined the effects of intraspecific genetic variation on species diversity in local communities. However, communities can be structured by a combination of both local and regional processes and to date, few community genetics studies have examined whether the effects of instraspecific genetic variation are consistent across levels of diversity. In this study, we ask whether host-plant genetic variation structures communities of arthropod inquilines within distinct habitat patches – rosette leaf galls on tall goldenrod ( Solidago altissima ). We found that genetic variation determined inquiline diversity at both local and regional spatial scales, but that trophic-level responses varied independently of one another. This result suggests that herbivores and predators likely respond to heritable plant traits at different spatial scales. Together, our results show that incorporating spatial scale is essential for predicting the effects of genetically variable traits on different trophic levels and levels of diversity within the communities that depend on host plants.     

Spatial correlations at different spatial scales are themselves highly correlated in isolation by distance processes

Although many properties of spatial autocorrelation statistics are well characterized, virtually nothing is known about possible correlations among values at different spatial scales, which ultimately would influence how inferences about spatial genetics are made at multiple spatial scales. This article reports the results of stochastic space-time simulations of isolation by distance processes, having a very wide range of amounts of dispersal for plants or animals, and analyses of the correlations among Moran's I-statistics for different mutually exclusive distance classes. In general, the stochastic correlations are extremely large (>0.90); however, the correlations bear a complex relationship with level of dispersal, spatial scale and spatial lag between distance classes. The correlations are so large that any existing or conceived statistical method that employs more than one distance class (or spatial scale) should not ignore them. This result also suggests that gains in statistical power via increasing sample size are limited, and that increasing numbers of assayed loci generally should be preferred. To the extent that sampling error for real data sets can be treated as white noise, it should be possible to account for stochastic correlations in formulating more precise statistical methods. Further, while the current results are for isolation by distance processes, they provide some guidance for some more complex stochastic space-time processes of landscape genetics. Moreover, the results hold for several popular measures other than Moran's I. In addition, in the results, the signal to noise ratios strongly decreased with distance, which also has several implications for optimal statistical methods using correlations at multiple spatial scales.     

Greenbeards in yeast: an undergraduate laboratory exercise to teach the genetics of cooperation

Recent years have seen a dramatic increase in our understanding of the social behaviour of microbes. Here, we take advantage of these developments to present an undergraduate laboratory exercise that uses the cooperative flocculating behaviour of yeast (Saccharomyces sp.) to introduce the concept of inclusive fitness and teach the genetics of cooperation. Students generate their own data using co-cultures of various yeast strains and perform statistical analyses to test whether kin selection or greenbeard effects determine the cooperative flocculating behaviour. The lab has run successfully for two consecutive years in a second year course with some 1, 200 students per year at the University of Toronto, Canada. We discuss the benefits of using microbes to teach social evolution, describe the set-up and learning outcomes of the laboratory exercise, and then outline possible extension and variants of the lab. In addition to providing students with the opportunity to use a model organism to study social behaviour, students are also taught common laboratory skills, such as replica plating and sterile techniques. Ultimately, while the genetics of cooperation has traditionally been taught through computer simulations and evolutionary games, this exercise demonstrates a way to experimentally introduce the topic.     

Population genetics strategies to characterize long-distance dispersal of insects

Population genetics strategies offer an alternative and powerful approach for obtaining information about long-distance movement, and have been widely used for examining patterns and magnitude of insect dispersal over geographic and temporal scales. Such strategies are based on the principle that genetic divergence between local populations reflects the interplay between genetic drift and gene flow, and thus can function as an indicator of dispersal capacity. Relatively new approaches for inferring population history are widely applicable for documenting introduction routes of invasive or quarantine species. These approaches are based on genetic variability calculated from changes in gene frequency of subpopulations, measured using molecular genetic markers. Inferences from population genetics can supplement and corroborate conventional observational approaches for characterizing insect dispersal and have provided important clues to many questions raised in the field of behavior and ecology of insects. Here, we summarize our work on the boll weevil as a case study to illustrate the kinds of information on dispersal capacity and dispersal patterns that can be obtained from population genetics techniques that would be difficult or impossible to acquire in other ways. Then we provide examples of how the molecular markers and population genetics tools have been applied to answer immediate questions of relevance to eradication program managers. Though the latter are idiosyncratic to this particular pest, they demonstrate the kinds and range of problems that can be addressed in other systems through application of population genetics strategies.     

Extending eco-evolutionary theory with oligomorphic dynamics

Understanding the interplay between ecological processes and the evolutionary dynamics of quantitative traits in natural systems remains a major challenge. Two main theoretical frameworks are used to address this question, adaptive dynamics and quantitative genetics, both of which have strengths and limitations and are often used by distinct research communities to address different questions. In order to make progress, new theoretical developments are needed that integrate these approaches and strengthen the link to empirical data. Here, we discuss a novel theoretical framework that bridges the gap between quantitative genetics and adaptive dynamics approaches. ‘Oligomorphic dynamics’ can be used to analyse eco-evolutionary dynamics across different time scales and extends quantitative genetics theory to account for multimodal trait distributions, the dynamical nature of genetic variance, the potential for disruptive selection due to ecological feedbacks, and the non-normal or skewed trait distributions encountered in nature. Oligomorphic dynamics explicitly takes into account the effect of environmental feedback, such as frequency- and density-dependent selection, on the dynamics of multi-modal trait distributions and we argue it has the potential to facilitate a much tighter integration between eco-evolutionary theory and empirical data.     

The Role of Nature and Nurture for Individual Differences in Primary Emotional Systems: Evidence from a Twin Study

The present study investigated for the first time the relative importance of genetics and environment on individual differences in primary emotionality as measured with the Affective Neuroscience Personality Scales (ANPS) by means of a twin-sibling study design. In N = 795 participants (n = 303 monozygotic twins, n = 172 dizygotic twins and n = 267 non-twin full siblings), moderate to strong influences of genetics on individual differences in these emotional systems are observed. Lowest heritability estimates are presented for the SEEKING system (33%) and highest for the PLAY system (69%). Further, multivariate genetic modeling was applied to the data showing that associations among the six ANPS scales were influences by both, a genetic as well as an environmental overlap between them. In sum, the study underlines the usefulness of the ANPS for biologically oriented personality psychology research.     

The population genetics of a solitary oligolectic sweat bee, Lasioglossum (Sphecodogastra) oenotherae (Hymenoptera: Halictidae)

Strong evidence exists for global declines in pollinator populations. Data on the population genetics of solitary bees, especially diet specialists, are generally lacking. We studied the population genetics of the oligolectic bee Lasioglossum oenotherae, a specialist on the pollen of evening primrose (Onagraceae), by genotyping 455 females from 15 populations across the bee's North American range at six hyper-variable microsatellite loci. We found significant levels of genetic differentiation between populations, even at small geographic scales, as well as significant patterns of isolation by distance. However, using multilocus genotype assignment tests, we detected 11 first-generation migrants indicating that L. oenotherae's sub-populations are experiencing ongoing gene flow. Southern populations of L. oenotherae were significantly more likely to deviate from Hardy-Weinberg equilibrium and from genotypic equilibrium, suggesting regional differences in gene flow and/or drift and inbreeding. Short-term N(e) estimated using temporal changes in allele frequencies in several populations ranged from approximately 223 to 960. We discuss our findings in terms of the conservation genetics of specialist pollinators, a group of considerable ecological importance.     

Rearing jewel wasps Mormoniella vitripennis (Walker) and their use in teaching biology

Jewel wasps are parasitic on the pupae of house-flies and blow-flies. They are easy and cheap to rear in a teaching laboratory, in large numbers, and little time is needed for the maintenance of a culture. They are especially useful in genetics and in the observation of animal behaviour. The teacher can arrange for students to see feeding, courtship, and egg-laying, for example, many times and at times chosen by the observer.     

Experimental evidence that adult antipredator behaviour is heritable and not influenced by behavioural copying in a wild bird

Knowledge of the relative importance of genetics and behavioural copying is crucial to appraise the evolvability of behavioural consistencies. Yet, genetic and non-genetic factors are often deeply intertwined, and experiments are required to address this issue. We investigated the sources of variation of adult antipredator behaviour in the Alpine swift (Apus melba) by making use of long-term behavioural observations on parents and cross-fostered offspring. By applying an 'animal model' approach to observational data, we show that antipredator behaviour of adult Alpine swifts was significantly repeatable over lifetime (r = 0.273) and heritable (h(2) = 0.146). Regression models also show that antipredator behaviours differed between colonies and sexes (females were more tame), and varied with the hour and year of capture. By applying a parent-offspring regression approach to 59 offspring that were exchanged as eggs or hatchlings between pairs of nests, we demonstrate that offspring behaved like their biological parents rather than like their foster parents when they were adults themselves. Those findings provide strong evidence that antipredator behaviour of adult Alpine swifts is shaped by genetics and/or pre-hatching maternal effects taking place at conception but not by behavioural copying.     

Do landscape processes predict phylogeographic patterns in the wood frog?

Understanding factors that influence population connectivity and the spatial distribution of genetic variation is a major goal in molecular ecology. Improvements in the availability of high-resolution geographic data have made it increasingly possible to quantify the effects of landscape features on dispersal and genetic structure. However, most studies examining such landscape effects have been conducted at very fine (e.g. landscape genetics) or broad (e.g. phylogeography) spatial scales. Thus, the extent to which processes operating at fine spatial scales are linked to patterns at larger scales remains unclear. Here, we test whether factors impacting wood frog dispersal at fine spatial scales are correlated with genetic structure at regional scales. Using recently developed methods borrowed from electrical circuit theory, we generated landscape resistance matrices among wood frog populations in eastern North America based on slope, a wetness index, land cover and absolute barriers to wood frog dispersal. We then determined whether these matrices are correlated with genetic structure based on six microsatellite markers and whether such correlations outperform a landscape-free model of isolation by resistance. We observed significant genetic structure at regional spatial scales. However, topography and landscape variables associated with the intervening habitat between sites provide little explanation for patterns of genetic structure. Instead, absolute dispersal barriers appear to be the best predictor of regional genetic structure in this species. Our results suggest that landscape variables that influence dispersal, microhabitat selection and population structure at fine spatial scales do not necessarily explain patterns of genetic structure at broader scales.     

A microcomputer method for recording and analysing behavioural elements

The trend in ethology, psychopharmacology and behaviour genetics is to get increasingly higher resolution of the behaviour of animals, since it increases the sensitivity of the tests used. Consequently the higher resolution requires an increased data-logging efficiency, and a decreased time-investment for data handling. In this paper a method for inexpensive microcomputers is presented, which enables an individual experimenter to obtain frequency, relative duration and its variance from as many behavioural elements as desired.