Co-expression Gene Networks and Machine-learning Algorithms Unveil a Core Genetic Toolkit for Reproductive Division of Labour in Rudimentary Insect Societies

Gene regulation supporting sociality shared across lineages and variation in complexity

Across evolutionary lineages, insects vary in social complexity, from those that exhibit extended parental care to those with elaborate divisions of labor. Here, we synthesize the sociogenomic resources from hundreds of species to describe common gene regulatory mechanisms in insects that regulate social organization across phylogeny and levels of social complexity. Different social phenotypes expressed by insects can be linked to the organization of co-expressing gene networks and features of the epigenetic landscape. Insect sociality also stems from processes like the emergence of parental care and the decoupling of ancestral genetic programs. One underexplored avenue is how variation in a group's social environment affects the gene expression of individuals. Additionally, an experimental reduction of gene expression would demonstrate how the activity of specific genes contributes to insect social phenotypes. While tissue specificity provides greater localization of the gene expression underlying social complexity, emerging transcriptomic analysis of insect brains at the cellular level provides even greater resolution to understand the molecular basis of social insect evolution.

Genomic signatures of eusocial evolution in insects

The genomes of eusocial insects allow the production and regulation of highly distinct phenotypes, largely independent of genotype. Although rare, eusociality has evolved convergently in at least three insect orders (Hymenoptera, Blattodea and Coleoptera). Despite such disparate origins, eusocial phenotypes show remarkable similarity, exhibiting long-lived reproductives and short-lived sterile workers and soldiers. In this article, we review current knowledge on genomic signatures of eusocial evolution. We confirm that especially an increased regulatory complexity and the adaptive evolution of chemical communication are common to several origins of eusociality. Furthermore, colony life itself can shape genomes of divergent taxa in a similar manner. Future research should be geared towards generating more high-quality genomic resources, especially in hitherto understudied clades, such as ambrosia beetles and termites. The application of more sophisticated tools such as machine learning techniques may allow the detection of more subtle convergent genomic footprints of eusociality.