Beyond the Blueprint

Choosing mates amidst competition is ubiquitous among animals, but the logistics of how such choice evolved is less straightforward: because male song type is largely determined by genetics, female mating behavior is under the influence of male genes. In other words, the females’ decision-making behaviors evolved based on the genetic composition of the entire social group. Such indirect genetic effects (IGEs), also called associative effects or extended phenotypes, are common and have profound implications for evolution. Beyond learning and behavior in social species, IGEs affect how organisms develop, how productive plants are, and whether individuals are attacked by predators, herbivores, and disease.

In some sense, examples of IGEs are intuitively obvious. No individual exists in a vacuum, isolated from the influences of others it encounters. Yet for decades, many prominent evolutionary theories assumed that all of the genetic influences on an individual’s phenotype came from genes within itself. What the field needs now is a clear framework that recognizes IGEs as additional factors in a population’s evolution, allowing for more-accurate predictions about how biological systems will change in the future. The genetic makeup of an individual not only influences phenotypes of individuals in its own species, but can have far-reaching effects on organisms at different trophic levels within its food web, impacting the dynamics of entire ecosystems. The role of commensal microbes in human health is a prime example of how IGEs can transcend species boundaries.

How IGEs affect evolutionary dynamics remains very much an open question. Recent theoretical strides in this area show how IGEs can greatly accelerate evolutionary change and hint at their hitherto unsuspected roles in such varied phenomena as animal mating rituals, the development of human agricultural systems, species range shifts in response to climate change, and even altruism. The influences of IGEs on diverse evolutionary processes are undoubtedly more complicated than most models can capture, and biologists must think creatively about new phenomena that IGEs may drive.

The social network

House cricket© VITALII/ISTOCKPHOTO.COMExamples of IGEs in social learning and behavior, such as cricket mating song preferences, are common. For example, contests between male red deer (Cervus elaphus) determine the population’s dominance hierarchy, such that the fitness of one male affects the outcome of contests with his opponents. Male dancing fiddler crabs (Uca terpsichores) build shelters that differ in quality, some of which provide better protection than others. Shelter quality determines which males are selected by female fiddler crabs, and the fitness of the female is in turn affected by the quality of the shelter, which is partly under the control of the male’s genes.

As a highly social species, humans are no exception. More than 50 years ago, Albert Bandura of Stanford University and his colleagues conducted the now-famous Bobo doll experiment, in which they exposed 3- to 6-year-old children to three different scenarios: an adult peacefully playing with toys while ignoring a weighted, inflatable toy called Bobo (that returns to a standing position after being disturbed); an adult yelling and striking the doll; or no adult present at all. When the children were given the choice of toys, they tended to mimic the actions of the adult they had observed: those who had seen an adult aggressively playing with the doll did the same, but played quietly with the other toys.² Because behavioral traits such as aggressiveness are partially determined by genetics, this experiment suggested that the phenotypes of adults, and, in part, their genes, are a factor shaping the social choices made by children.

Recent research has also shown that when species interact, IGEs can have far-reaching effects. Last year, we published an article about two goldenrod species (Solidago altissima and S. gigantea) whose genomes affected not only neighboring plants, but also associated pollinators, and even the rate at which nutrients in dropped leaves are recycled through the ecosystem.³ We grew genetically identical individuals of each goldenrod species with neighbors of the same or different genetic identity to examine how unique combinations of plants fared. As expected, some clones were more productive than others—both in terms of above- and belowground biomass growth—and the more productive clones received more visits from pollinators. More surprisingly, clones predictably affected the productivity and chemical composition of their neighbors. For example, the neighbors of a particularly productive S. gigantea clone always devoted more resources to belowground biomass, a shift that was accompanied by higher levels of the complex polymer lignin. Increased lignin production by the plants neighboring the productive S. gigantea clone, in turn, made the neighbors’ leaf litter less attractive to microbial decomposers, such that it look longer for those nutrients to be cycled. The effects on pollinators were less clear: focal plants had more pollinators when grown next to particular genotypes, but a subsequent analysis indicated that it wasn’t simply due to plants producing more biomass. It’s possible that differences in the timing of floral displays between neighbors influenced visitation.

Also last year, Darren Rebar and Rafael Rodríguez of the University of Wisconsin–Milwaukee found additional evidence to support the idea that IGEs could have impacts across an ecosystem. They explored the interactions of treehoppers (Enchenopa binotata) and the nannyberry tree (Viburnum lentago), which serves as the insects’ host plant and primary environment.⁴ On the population level, as evolution acts on the plants’ genes, the treehoppers’ environment changes. And because each plant is genetically different—yielding larger or smaller leaves that provide better or worse hiding places for the arthropods, for example—a different mix of plants may select for different traits in their associated arthropod community.

By assuming that the genetic component of a particular trait is con­fined to your genes and only yours, scientists overlooked another important input: the genes of your neighbors.

For this experiment, the researchers raised a random sample of treehoppers on several clones of V. lentago and found that different clonal lines had varying effects on the arthropods’ traits related to mating and reproduction. Once again, the influence of the plants’ genomes on the treehoppers may seem obvious in retrospect, but this study provides some of the most direct evidence to date that IGEs operate between trophic levels of an ecosystem. This also reinforces the notion that IGEs are ubiquitous in natural systems, but are not always recognized as such. Moreover, this example illustrates an important consequence of IGEs: when an organism’s environment has a genetic component, that environment itself can evolve.

A changing landscape

SHARED GENETIC EFFECTS: Pollinators, such as this honeybee on a thyme flower, are under the influence not just of their own genomes, but the genes of their host plants as well. The genetic underpinnings of a plant’s nectar productivity, for example, could affect an insect’s physiology and behavior.© GREGORY DUBUS/ISTOCKPHOTO.COMOne ecosystem in which IGEs undoubtedly have a major influence is the human gut. Researchers are developing microbes as tools to combat obesity, for example, and some are already used in skin-care products and for the treatment of Clostridium difficile infections. In each case, researchers are exploiting IGEs, targeting the genetic composition of the gut microbial community to effect a phenotypic change in the patient.

Recently, perturbations in the gut microbiome have been linked to cardiovascular disease, the leading cause of death worldwide. Red meat contains a molecule called carnitine that, when broken down by gut microbes, becomes trimethylamine-N-oxide (TMAO), a compound that causes plaque to build up and clog arteries. In April 2013, Stanley Hazen of the Cleveland Clinic and his colleagues enlisted omnivorous and vegan human volunteers to eat red meat and then tested differences in the activity of their gut microbes. The gut microbes of vegans didn’t break down carnitine into TMAO as fast as the bacterial community of meat eaters, suggesting that the function of the gut microbiome has evolved in response to host diet.⁵ These changes to the gut bacterial community have, in turn, affected people’s ability to digest certain foods, with implications for their health, such as susceptibility to heart disease.

We should not be surprised if future research continues to affirm the relationship between the genetic contents of our commensal bacterial communities and our own health. (See “The Body’s Ecosystem,” The Scientist, August 2014.) Indeed, humans have long recognized that altering the microbial composition of the gut may be beneficial. The idea of using fecal material to treat digestive issues dates as far back as the 4th century, when ancient Chinese practitioners created soups that included fecal material from healthy individuals for those suffering from digestive problems. Modern methods in fecal bacteriotherapy are more sophisticated in how the material is transferred, but the basic principle is the same. Use of these procedures in recalcitrant cases of C. difficile infection is approved as a treatment and has already produced positive outcomes for patients: Els van Nood of the University of Amsterdam, along with a group of other researchers, showed in 2013 that fecal transplants could be more effective at treating C. difficile than the antibiotic vancomycin.⁶

IGEs also may play a role in the migration of species to different geographic ranges as the Earth’s climate continues to change. In a paper published earlier this year, we showed that plants typically found at high elevations grow better when near other high-elevation individuals of the same species, harboring different high-elevation-adapted genotypes. The same was not true of low-elevation plants, which do not perform better in the presence of other low-elevation varieties.⁷ Mathematical models published earlier this year by one of us (Schweitzer) confirmed this by showing that plant-soil interactions—through which plants alter bacterial and fungal soil communities with subsequent impacts on plant fitness—can lead to soil properties that favor some individuals over others, thereby selecting for different plant and microbial traits over time.⁸

In addition, the feedback that can occur as a consequence of IGEs may affect the rate and direction of evolution, possibly speeding the process of local adaptation to novel environmental conditions. (See “Seeds of Hopelessness,” The Scientist, August 2014.) Global climate change is causing significant shifts in environmental conditions worldwide by altering temperature and precipitation patterns and fragmenting once-intact habitats. These changing environments are a hotbed for IGEs; we just have to know where to look and how to detect them.

Remodeling evolution

IT TAKES A VILLAGE: Indirect genetic effects (IGEs) are ubiquitous in all ecosystems. Animals that feed or live on other species, for example, are under the influence of that species’ genes. And looking closely at any ecosystem will reveal hundreds more IGEs, which are overlooked by the majority of evolutionary models. It’s time for researchers to consider all the genes in an environment when exploring the evolution of a single species, rather than simply the genome of the focal organism.
See full infographic: JPG | PDF© LINDSAY HOLLADAYWhen it comes to modeling IGEs to explore their influence on evolution, scientists must develop a framework that is both conceptual—drawing from examples across scientific fields to develop a cohesive theory of how IGEs influence genetic change—and mathematical, allowing researchers to make precise, testable predictions. Although the idea that social interactions could accelerate evolution dates back to 1915, interest in the evolutionary importance of IGEs surged in the late 1950s, and some four decades later, scientists finally began writing mathematical models to formalize these predictions. In particular, papers from Allen Moore, then based at the University of Kentucky, and Jason Wolf, first at Kentucky and later at Indiana University, developed evolutionary models that incorporated IGEs and quantified how these affected rates of evolution. Moore and Wolf showed that for certain traits, such as behaviors that involve reciprocal responses like escalating aggression between individuals, IGEs can greatly accelerate the rate of evolutionary change.^9,10 Because traits in a focal individual are also part of the “environment” for an interacting individual, when the focal individual’s traits change, so does the environment for an interacting individual—and vice versa. When traits of the focal and interacting individuals both change in the same direction, a positive feedback loop forms that accelerates evolutionary change.

Evolutionary models that incorporate IGEs have developed to the point that they can inform how some societies have developed egalitarian or altruistic tendencies over time. Most animal populations are composed of genetically diverse organisms, some weaker and some stronger, resulting in the adoption of rigid dominance hierarchies. But this is not a universal structure of animal societies. Diverse species, from invertebrates to humans, have complex social structures in which individuals make sacrifices for the good of the group, or for the good of others.

When an organism’s environment has a genetic component, that environment itself can evolve.

According to mathematical models, the answer may involve genetically determined, group-level aversion to inequity that counteracts the tendency of strong individuals to demand tribute from the weak. Sergey Gavrilets of the University of Tennessee, Knoxville, modeled such a system in which the evolution of “helping” behavior was an emergent property of the model.¹¹ In this model, a group of imagined organisms of the same species interact and are ranked from strongest to weakest. When an individual finds a resource, a competitor may demand that resource, and the finder must then decide whether to give in or resist. Gavrilets’s model assumes that there are significant risks associated with losing a contest for possession of the resource, suggesting that the weaker individual will often give in. But the distribution of resources throughout a large group affects every individual in that group, not just a bully and its victims. If the demanding individual has more resources, and is therefore likely to be stronger than the resisting individual, it can be beneficial for an observer to intercede on behalf of the resisting individual, provided that the risk of injury or other costs are not prohibitive. In other words, in Gavrilets’s model, the selfish impulse turns out to be an individual-level aversion to inequality—a desire that no one else be stronger than oneself. Such behavior represents an IGE through which the ultimate share of resources in a population depends on the simultaneous expression of genes in many interacting individuals.

Gavrilets’s model indicates that helping behavior can evolve in just 1,000 generations, a very short time span in the history of human culture, and can ensure a more equitable, although not perfectly even, distribution of resources even in the presence of oppressive individuals. Moreover, because the tendency of an individual to participate in a conflict is genetically determined, these “escalation thresholds” can evolve over time.

Such helping is one of many examples of behavior that could be described as moral decisions, a topic that has attracted the attention of scholars for millennia. Some of the most convincing work on the evolution of morality suggests that it is not only the intelligence of humans that promotes moral behavior, but the demands of social groups in which humans find themselves embedded—the expectation to behave a certain way and to follow certain rules. If this is indeed the case, many of these social demands likely evolved due to impacts of IGEs. Whether we study crickets, microbes, plants, or humans, IGEs are important components of many biological systems and key drivers of evolution of all life. 

Mark A. Genung is a postdoctoral researcher in the lab of Joseph K. Bailey, who is an associate professor of ecology and evolutionary biology at the University of Tennessee, Knoxville. Jennifer A. Schweitzer is also an associate professor in the department.

References

1. N.W. Bailey, M. Zuk, “Field crickets change mating preferences using remembered social information,” Biol Lett, 5:449-51, 2009.
2. A. Bandura et al., “Transmission of aggression through imitation of aggressive models,” J Abnorm Soc Psych, 63:575-82, 1961.
3. M.A. Genung et al., “The afterlife of interspecific indirect genetic effects: genotype interactions alter litter quality with consequences for decomposition and nutrient dynamics,” PLOS ONE, 8:e53718, 2013.
4. D. Rebar, R.L. Rodríguez, “Trees to treehoppers: genetic variation in host plants contributes to variation in the mating signals of a plant-feeding insect,” Ecol Lett, 17:203-10, 2014.
5. R.A. Koeth et al., “Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis,” Nat Med, 19:576-85, 2013.
6. E. van Nood et al., “Duodenal infusion of donor feces for recurrent Clostridium difficile,” New Engl J Med, 368:407-15, 2013.
7. J.K. Bailey et al., “Indirect genetic effects: an evolutionary mechanism linking feedbacks, genotypic diversity and coadaptation in a climate change context,” Func Ecol, 28:87-95, 2014.
8. J.A. Schweitzer et al., “Are there evolutionary consequences of plant-soil feedbacks along gradients?” Func Ecol, 28:55-64, 2014.
9. A.J. Moore et al., “Interacting phenotypes and the evolutionary process. 1. Direct and indirect genetic effects of social interactions,” Evolution, 51:1352-62, 1997.
10. J.B. Wolf et al., “Evolutionary consequences of indirect genetic effects,” Trends Ecol Evol, 13:64-69, 1998.
11. S. Gavrilets, “On the evolutionary origins of the egalitarian syndrome,” PNAS, 109:14069-74, 2012.