A framework for studying behavioral evolution by reconstructing ancestral repertoires

Abstract

Although extensive behavioral changes often exist between closely related animal species, our understanding of the genetic basis underlying the evolution of behavior has remained limited. Here, we propose a new framework to study behavioral evolution by computational estimation of ancestral behavioral repertoires. We measured the behaviors of individuals from six species of fruit flies using unsupervised techniques and identified suites of stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the suites of behaviors exhibited by ancestral species, as well as the intra- and inter-species behavioral covariances. We found that much of intraspecific behavioral variation is explained by differences between individuals in the status of their behavioral hidden states, what might be called their "mood." Lastly, we propose a method to identify groups of behaviors that appear to have evolved together, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the genetic basis of behavioral evolution.

Measuring the repertoire of age-related behavioral changes in Drosophila melanogaster

“…While the complexity of the behavioral repertoire remains unchanged, the complexity of how the animals traverse through this space over time might still show significant deviations. Prior investigations into the complexity of fly behavioral sequences have shown that these dynamics of transitions between stereotyped behaviors exhibit long time scales and hierarchical organization [18,24]. A hypothesis for aging-related behavioral change is that the structure of the behavioral repertoire becomes less complex with age [25,26], and with the detailed measurements of behavior described here, we can test this idea, potentially gaining insight into changes occurring to the internal programs that may generate these patterns.…”

“…The results of this calculation for each individual animal are shown in Figure 4B as a function of age. While there is significant scatter in the data (likely due to variance in the internal activity state of the flies [18,24]), when we compute a smoothed average of the data, a clearer portrait emerges. Specifically, we observe that these curves are reminiscent of the sexual dimorphism we observed in the inter-group eigenvector projections in Figure 3.…”

“…While the data plotted in Figure 2 displays how flies' mean behavioral profile alters with age, there also exist significant variance and co-variance within sex and age groups [18][19][20]. Thus, we need to isolate the variance in our data that is associated with changing age, rather than from inter-age-group variability.…”

Variation and variability inDrosophilagrooming behavior

“…A recent investigation of unstimulated behaviors in different Drosophila species detected differences in spontaneous grooming between species and among individuals within a species (31). Using similar methods, they accurately assigned individuals into species categories and assessed variability among individuals.…”

“…Genetic factors have been implicated in spontaneous (i.e., unstimulated) grooming behavior in Drosophila melanogaster (36) and in other drosophilid species (31). Our results demonstrate that this is true for dust-induced grooming as well.…”