L04-shaw_wiley_2010

L04-shaw_wiley_2010 - Shaw K L 8 Wiley C(2010 The genelic...

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Unformatted text preview: Shaw, K. L. 8. Wiley, C. (2010) The genelic basis of behavior. In: Evolutionary Behavioral Ecology (eds, Weslneai, D.F & Fox, C.W.), Ch. 5:71-89. 5 KERRY L SHAW AND CHRIS WJLEY ehavioral ecologists are interested in behaviors expressed under particular ecological condiw " tions and the evolutionary causes and consequences : of such behavioral strategies. Evolution of behav- _-1 ior can occur only when there is a change in allele : frequencies. It therefore follows that there can be " no behavioral evolution without a genetic basis to _ behavioral variation. Thus the study of behavioral genetics is essential to our understanding of behav- ioral ecology and evolution because it informs us _ about the genetic and environmental contribu- tions to variation in individual behaviorai traits, and further may provide explanatory power for understanding major concepts in behavioral ecol- ogy. Recent advancements in molecular tools for studying genes have revolutionized the study of behavioral ecology; among a host of other uses, genetic tools have allowed us to infer paternity of offspring, indirectly assess dispersal patterns, and examine phylogenic relationships between taxa. Although these varied applications of genetic tools have had a profound impact on the study of hehav~ iotal ecology, this chapter will deal specifically with the insight that can be gained from more specific knowledge of the genetic basis of the actual behav- iors being studied. The idea that behavioral traits can have a strong genetic basis may be less intuitive than for other traits, such as morphological characters. This is perhaps illustrated most famously by the “nature- nurture” debate, in which “nurture” advocates Tl The Genetic Basis of Behavior espoused the view that human behavior is largely the effect of development, learning, and social environment (see Philosophical Psychology, 21[3], 2008) for a recent treatment of this debate). It is now realized that all phenotypes, including behav- iors, are affected by both genes and environment. That behaviors have a genetic basis, at least par- tially, is vital to our expanded appreciation of the importance of natural selection in generating bio- diversity le.g., through sexual or kin selection]. Many intricate and complex behaviors that serve as an endless source of fascination ,to the student of animal behavior defy easy comprehension as to how genes contribute to their existence (e.g., socile behavior in honey bees or sexual signaling in birds}. However, evidence is beginning to accumulate that even the most complex of behaviors can have genetic bases that can be dissected and understood both in terms of development and evolution. The study of behavioral genetics has a lengthy history (Greenspan 2008) and the importance of genetic insights to theories of behavioral evolution {e.g., Hamilton 1964) cannot be overemphasized. Yet, few genetic studies of specific traim are currently integrated into our understanding of the behavioral ecology of an organism, perhaps because optimal- ity models often omit explicit descriptions of the genetic basis of behavior, or because the study of behavioral genetics often has been undertaken in model laboratory organisms {Moore SC Boalte 1994; Boake et a1. 2002). For many years, simple 72 Foundations genetic assumptions (whether implicit or explicit) underlying behavioral “strategies” have been com- monplace in studies of behavioral ecology, and Studies of the selective forces that influence these behaviors have proceeded largely in ignorance of the underlying genetics. By and large, the approach termed the phenotypic gambit (Grafen 1984), in which simple genetic assumptions are made, have been successful in predicting conditions under which alternative strategies produce higher fimess payoffs. Although this simplification can be justi- fied in some traditional approaches to behavioral ecology, we can also see a steady increase in known instances in which these simplifications are likely misleading (e.g., Hadfield et al. 2,007). Furthermore, making simplified genetic assumptions greatly con- strains the scope of behavioral ecology and evolu- tion. This chapter attempts to provide examples of more complex questions of interest to behavioral ecologists that require details of, for example, the genetic origins of behavioral diversity or the evolu- tionary genetic processes underlying the fate of new behavioral genetic variation. Simple assumptions about the genetic inheritance of such behavioral variation would be counterproductive. Fortunately, the approaches used to study the evolution of other phenotypes can be readily applied to the genetics of behavior, using techniques that are increasingly tractable in natural populations. Like- wise, population and quantitative genetic models of behavioral trait evolution depend upon, and are improved by, knowledge of the genetic basis of behav- ioral variation (Moore 8:: Boake 1994). The aims of this chapter are to (1) discuss how genetic approaches to the study of behavior, particularly when knowledge of the underlying genes is lacking, can give us deeper insight into behavioral ecology and evolution and (2) discuss what might be possible in the study of behav— ioral ecology and evolution if we knew the actual genes underlying behavioral variation. Throughout, the focus is on the study of behavioral trait evolution rather than fhe employment of molecular methods for the study of behavioral processes. To launch a clear and meaningful discussion of the genetic basis of behavior, we must first clarify two classes of questions asked in die area of behav- ioral genetics. The first question asks, what is the genetic basis of the fully functional behavior (includ- ing those structures and molecular processes that combine to produce the behavioral output)? The second question, although fundamentally related to the first, represents an evolutionary perspective by asking, what is the genetic basis of behavioral variation? The scope of the latter question does not require knowledge of all genes that contribute to the structural development and expression of a behavior, but focuses on the underlying genetics cur- rently contributing to variation in a behavior. The content of this chapter largely deals with this second question, the genetic basis of behavioral variation, because this is of primary interest to behavioral ecologists studying the fitness of organisms in con- temporary or past populations. However, when considering the evolutionary origins of a behavior, the genetics of behavior and the genetics of behav- ioral variation are closely related because any of the genes contributing to the development and expres- sion of a behavior may vary in a given population and thereby contribute to behavioral variation. GENETICS OF BEHAVIOR WITHOUT THE GENES There are many reasons that motivate investiga- tions of the genetic basis of behavioral differences. Even in compelling behavioral systems in which lit- tle is known about the genome, we can gain imporw tant insights into questions of interest to behavioral ecologists, given some ability to perform husbandry or observe or construct pedigrees. Below, we dis- cuss a number of interesting and important ques- tions that may be addressed without knowledge of the Specific genes underlying a behavior. Our choice of examples is not exhaustive, but rather represents an introduction to some of the important roles that behavioral genetics can play in furthering Our understanding of behavioral ecology. Causes of Behavioral Variation Nongene‘tic Causes As discussed previously, the causes of behavioral variation are profoundly important because only variation in behavior due to variation in genes can evolve. However, the presence of behavioral varia- tion does not guarantee that there is a genetic basis to that variation. For example, hormones transferred to the egg or fetus during gestation may influence the neural development of the offspring, thereby influencing behavior through uongenetic means. In addition to such maternal effects, many behaviors have a strong propensity for cultural transmission The Genetic Basis of Behavior via learning from parents, other relatives, or nonre- ; 13th individuals. Finally, behavioral variation may be induced by an underlying variability in the physi- ‘ cal environment. Phenotypic plasticity, variation ‘ due to each of these differences in environment, is _ widespread and sometimes dramatic (see chapter 6). 7 Such is the case in many social hymenoptera in ‘ which different individuals perform different tasks _'such as nursing, foraging, and defense of the nest (Seeley 1 995), roles that are sometimes accompanied -‘ by considerable differences in morphology (e.g., as . - in the big-headed ant, Pbeidole megacepbala). This array of variable developmental outcomes, known as polyethism (behavioral variation) or more gener- ally polyphenism (phenotypes in general), is due not to genetic variation but to variation in developmen- tal or behavioral environment. Another conspicuous example of polyphenism appears in certain amphib— ians (Relyea 2004) in which apparently genetically identical individuals can develop into different " trophic morphs with distinctive morphologies and ' dietary behaviors. Behavioral phenotypes, like other ' phenotypes, are products of genes and environment, both of which can cause behavioral variation (Mac- kay 5c Anholt 2007). - Determining a Genetic Basis to Behavioral Variation The important goal of documenting a genetic basis to behavioral differences among popula— tions or species, thereby ruling out environmental differences as causes of the variation, is often first achieved through a “common garden” study, in which behavioral variants are reared in an identical environment. Behavioral differences that persist, or “breed true,” suggest a genetically heritable basis to the variation. For example, in a study by Sim- mons (2004),-comrnon garden breeding was con- ducted for several generations with the oceanic field cricket, Teleogryllus oceanicus,_ultimately showing that song differences among populations are due (at least partially) to genetic differences. Common garden experiments are not restricted to species amenable to laboratory Study. For example, even in Wild birds, cross-fostering chicks bemeen nests of closely related species has proven a useful tool for testing the genetic basis of behaviors ranging from mate preferences (Smeher et al. 2007) to foraging patterns (Slagsvold 5C Wiebe 2007). When trait variation exists within a single popu- lation, common garden studies are of limited utility 13 and further study must determine the degree to which variation is due to genes Versus environment. This is typically carried out by comparing the pbe— notypes of relatives to that of nonkin, something that is achievable when pedigrees are known. in such instances, a first goal is to determine whether the behavioral variation we see is based on alterna- tive alleles at a single locus (the realm of population genetics) or small contributions from variation at many loci (quantitative genetics). These alternatives have been studied using two very different research approaches in genetics (Greenspan 2004) that date back to the origins of the field of genetics itself. Although the research legacies of both approaches continue today, the consequences to modeling out- comes in behavioral evolution are significant (see below). If segregating variation within a family or population suggests polygenic control (i.e., varia— tion due to the contributions of many genes), a more formal treatment to estimate heritability can be undertaken to quantitatively attribute portions of phenotypic variance to genes and environment (Freeman Sc Heron 2004). Examples demonstrating heritability in behavioral variation have been pub- lished for a diversity of behaviors, from dispersal behavior (e.g., ballooning in spiders: Bonte 8: Lens 2007; migratory behavior in birds: Pulido 2007), to male signaling (e.g., cricket song: Sinmions 2004). Genetic Architecture of Behavioral Variation Genetic architecture refers to features characterizingr the relationship between genotype and phenotypic variation, such as the number of loei involved in trait variation, the number of alleles per loans, the allelic interactions both within and between loci, the amount an allele contributes to the phenotypic variation, the degree of pleiotropy (i.e., how many phenotypes a given gene can affect), as well as the: heritability of the trait. Below we discuss some of the ways in which an understanding of the genetic architecture of behavioral variation can yield insight into the evolutionary potential of the behavior. Single Genes versus Complex Genetic Architectures When an evolutionarily optimal endpoint lies out- side standing variation in a trait, we expect a popu— lation to move more slowly toward that optimum when potential variation is controlled by a single 74 Foundations locus than When variation is due to many genes. Under these conditions, traits with the potential for polygenic variation should evolve more quickly because there are more sources of new mutation. Conversely, traits determined by single genes may evolve more rapidly toward an adaptive optimum when the optimum is within standing variation in the trait. This is because favorable alleles are less likely to be concealed by variation at other loci, and thus can sweep to fixation more quickly. An understanding of the genetic architecture underly- ing phenotypic variation is therefore important for our understanding of the evolutionary potential of populations. A phenomenal example of this was reported recently in the oceanic field cricket mentioned above. The distribution of this species includes northern coastal Australia and many of the Pacific islands, extending more recently across the Hawai- ian archipelago. In Hawaii, I oceanicus is now in contact with the acoustic parasitoid tachinid fly, Ormt'a ocbracea, itself a recent invader from North America. Homing in on the song of male crickets, female 0. ocbmcea locate and larviposit on or near the host cricket. Larvae burrow into and eventually kill the cricket. On the island of Kauai, in fewer than 20 generations, a wing mutation rendering males mute, and thus well protected from the para- sitoid, swept to near fixation showing just how rap- idly a population can evolve under strong selective pressures (Zuk et al. 2006). Different methods have been developed to ana- lyze predictions of trait evolution when phenotypic variation is due to allelic variation at single or mul- tiple loci (Greenspan 2.004). Single-locus evolution is considerably easier to predict because models focus on genotypes and allele hequency change due to particular evolutionary forces and can be studied as deviations from the Hardy-Weinberg equilibrium. With complex genetic underpinnings to behavioral variation comes more complex mod- eling in which phenotypic changes are predicted, often in the absence of known genotypes. Classic quantitative genetic predictions of behavioral evo— [ution have been built around the "breeder’s” equa- tion (so-called due to its origin in the agricultural world), R = 1238, where R is the response to selec- tion, bl is the heritability of the trait and S is the selection differential on the trait (Freeman 65 Her- ron 2004; box 5.1). This model has been extremely useful because it offers a quantitative prediction of how much a population will respond as a function in traits to those within an epistatic network, are of two measurable features (heritability and selec- tion intensity), and is most effective when pheno- typic variation is due to many genes with. simple, additive effects. However, there are many different ways in which multiple genes can contribute to a phenotype that do not conform to simple, additive, quantita- tive generic models, and these may further compli- cate an estimation of evolutionary potential. One example is a threshold trait, in which quantitative variation at multiple loci may be phenotypically visible only when a certain quantity in expression is reached (Pulido 2007). Alternatively, complex genetic architectures may arise through epistatic interactions (in which one gene modifies the expres- sion of another) between the genes involved. Genes that operate within an epistatic network may be coadapted to function with other genes in the net- work, and expression in terms of timing and quan- tity of gene product will combine to produce a complex behavioral phenotype. Evolution of such phenorypes must proceed by mutual adjustments of multiple genetic factors. The evolution of all genes, from those contributing to additive variation further complicated if these genes have pleiotropic . effects on other aspects of fitness. The genes for- ager and period, known to have pleiotropic effects in Drosopbifa melanogaster, are discussed in a later section. Such complex genetic architectures can be the source of extensive constraint on behavioral evolution. Yet despite this importance of genetic architecture to trait evolution, our current under- standing of the genotype-phenotype relationship of quantitative traits is extremely limited, particu— larly in natural populations. What is clear is that the simplified views of both single gene control and additive quantitative genetics are frequently inap- ptopriate in the world of behavioral genetics. The diversity of genetic architectures of behav- ioral variation is illustrated nicely through the example of the genetics of animal migration. Within many species of winged insects there is variation in migratory behavior (Roff 6: Fairbairn 2007). in polymorphic populations, some individuals of a species undertake migratory flight, whereas oth- ers are sedentary. In some species, nonmigratory individuals are behaviorally, physiologically: and morphologically unable to fly because they lack fully developed wings and wing muscles to power flight. The genetic basis of this polymorphism difr fers in different insect species—both single gene BOX 5.1 A Brief Introduction to Quantitative Genetics )ason B. Wolfand Allen I. Moore Quantitative genetics provides a statistical description of the various influences on mea- surable traits (Falconer 5c Mackay 1996). We typically consider metric or quantitative (continuous) traits, but there can be exceptions. In behavior, most traits, or at least most influences on traits, are continuously distributed. Moreover; researchers that study behav- ior typically adopt a phenotypic approach, making quantitative genetics the most com- mon way to address how behavior is influenced by inheritance. In addition to its utility in providing a framework for understanding sources of trait variation, quantitative generics also provides a means of understanding phenotypic evolution, including factors such as the rate of, and constraints on, adaptive evolution. Thus, while” approaches such as opti- mality and game theory are useful for predicting expected outcomes of evolution, quanti- tative genetics provides insights into evolutionary processes and factors that limit optimal evolution or the attainment of an optimum. Using quantitative genetics to understand trait evolution involves defining the various factors that can influence a trait, and then to statistically partition the effects of these influ— ences. Influences can be very general or very specific. This is best expreSsed with linear equations. We begin with the most basic equation in quantitative genetics, which partitions the expression of a trait (2, which is the phenotypic value, or the trait value you measure on an individual) into a genetic (g, which reflects all of the genetic influences contributing to a trait) and an environmental component (2, the environmental deviation, which includes all of the environmental contributions influencing the expres...
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