Assessment of the relationship between genome information and sociality across mammal species

Sociogenomics studies the dynamic relationships between genomes and social traits. The relationship between the genome and sociality has gained interest in recent years, providing empirical evidence of this relationship in different animal species. However, despite the growing number of sociogenomic studies and data availability, it is still not clear which statistical regularities between genomic and social traits provide informative clues on the underlying patterns and mechanism that provide coherence between the large number of components that define a sociogenomic system. Also, there is still unclear whether trait quantifications can be done beyond single species findings. Here, we studied the abundance of genome components, and the number of gene products involved in biological processes associated with social behaviors. We found that the abundance of protein-coding genes, one of the nine genome components studied, significantly differs between social mammals and solitary species. We also found that, compared with solitary species, social species presented a statistically significant increase in the number of gene products associated with all five studied biological processes. The evaluation of a conceptual map of the hypothesized relationships among sociality and genome architecture via a structural equation model revealed a coherent causal relationship among the considered variables, which was similar in shape for social and solitary mammals but with differences in the coefficients of the causal paths. The results also revealed a significant relationship between the latent variables representing i) genome components and the epigenetic control system and ii) genome components and gene products in the considered biological processes for both social and solitary specified models, as well as a third significant relationship between the latent variables representing the epigenetic control system and life history traits in the model specified with social species data. This work aims to build a new bridge to improve our comprehension of the evolution of social life in mammals by integrating information from multiple genome components, functional genomics and a multivariate model, providing a causal framework related to genomics and social behaviors.