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Social insects have provided some of the clearest insights into the origins and evolution of collective behaviour. Over 20 years ago, Maynard Smith and Szathmáry defined the most complex form of insect social behaviour—superorganismality—among the eight major transitions in evolution that explain the emergence of biological complexity. However, the mechanistic processes underlying the transition from solitary life to superorganismal living in insects remain rather elusive. An overlooked question is whether this major transition arose via incremental or step-wise modes of evolution. We suggest that examination of the molecular processes underpinning different levels of social complexity represented across the major transition from solitary to complex sociality can help address this question. We present a framework for using molecular data to assess to what extent the mechanistic processes that take place in the major transition to complex sociality and superorganismality involve nonlinear (implying step-wise evolution) or linear (implying incremental evolution) changes in the underlying molecular mechanisms. We assess the evidence for these two modes using data from social insects and discuss how this framework can be used to test the generality of molecular patterns and processes across other major transitions. This article is part of a discussion meeting issue ‘Collective behaviour through time’. 

Abstract The evolution of eusociality requires that individuals forgo some or all their own reproduction to assist the reproduction of others in their group, such as a primary egg-laying queen. A major open question is how genes and genetic pathways sculpt the evolution of eusociality, especially in rudimentary forms of sociality—those with smaller cooperative nests when compared with species such as honeybees that possess large societies. We lack comprehensive comparative studies examining shared patterns and processes across multiple social lineages. Here we examine the mechanisms of molecular convergence across two lineages of bees and wasps exhibiting such rudimentary societies. These societies consist of few individuals and their life histories range from facultative to obligately social. Using six species across four independent origins of sociality, we conduct a comparative meta-analysis of publicly available transcriptomes. Standard methods detected little similarity in patterns of differential gene expression in brain transcriptomes among reproductive and non-reproductive individuals across species. By contrast, both supervised machine learning and consensus co-expression network approaches uncovered sets of genes with conserved expression patterns among reproductive and non-reproductive phenotypes across species. These sets overlap substantially, and may comprise a shared genetic “toolkit” for sociality across the distantly related taxa of bees and wasps and independently evolved lineages of sociality. We also found many lineage-specific genes and co-expression modules associated with social phenotypes and possible signatures of shared life-history traits. These results reveal how taxon-specific molecular mechanisms complement a core toolkit of molecular processes in sculpting traits related to the evolution of eusociality. 

Identifying the genetic basis of behavior has remained a challenge for biologists. A major obstacle to this goal is the difficulty of examining gene function in an ecologically relevant context. New tools such as CRISPR/Cas9, which alter the germline of an organism, have taken center stage in functional genomics in non-model organisms. However, germline modifications of this nature cannot be ethically implemented in the wild as a part of field experiments. This impediment is more than technical. Gene function is intimately tied to the environment in which the gene is expressed, especially for behavior. Most lab-based studies fail to recapitulate an organism's ecological niche, thus most published functional genomics studies of gene-behavior relationships may provide an incomplete or even inaccurate assessment of gene function. In this review, we highlight RNA interference as an especially effective experimental method to deepen our understanding of the interplay between genes, behavior, and the environment. We highlight the utility of RNAi for researchers investigating behavioral genetics, noting unique attributes of RNAi including transience of effect and the feasibility of releasing treated animals into the wild, that make it especially useful for studying the function of behavior-related genes. Furthermore, we provide guidelines for planning and executing an RNAi experiment to study behavior, including challenges to consider. We urge behavioral ecologists and functional genomicists to adopt a more fully integrated approach which we call "ethological genomics". We advocate this approach, utilizing tools such as RNAi, to study gene-behavior relationships in their natural context, arguing that such studies can provide a deeper understanding of how genes can influence behavior, as well as ecological aspects beyond the organism that houses them.