Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks

Beryl M Jones,Troy J Comi,Saurabh Sinha,Tim Gernat,Tobias Jagla,Gene E Robinson,Martin Middendorf,Amy C Cash-Ahmed,Charles Blatti,Sriram Chandrasekaran,Benjamin Er Rubin,Syed S Husain,Shounak Bhogale,Vikyath D Rao

doi:10.7554/elife.62850

Abstract

Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless honey bee (Apis mellifera) colonies, where individuals engage in both reproductive and non-reproductive behaviors. Using high-throughput behavioral tracking, we discovered these colonies contain a continuum of phenotypes, with some individuals specialized for either egg-laying or foraging and 'generalists' that perform both. Brain gene expression and chromatin accessibility profiles were correlated with behavioral variation, with generalists intermediate in behavior and molecular profiles. Models of brain GRNs constructed for individuals revealed that transcription factor (TF) activity was highly predictive of behavior, and behavior-associated regulatory regions had more TF motifs. These results provide new insights into the important role played by brain GRN plasticity in the regulation of behavior, with implications for social evolution.

Highlights

Understanding the genomic regulatory architecture of phenotypic plasticity is necessary to achieve comprehensive knowledge of the mechanisms and evolution of complex traits
We used automatic behavioral tracking and genomics to uncover the role of brain gene regulatory network (GRN) activity in the extensive behavioral variation observed in colonies of laying worker honey bees
We discovered that continuous phenotypic variation is associated with continuous variation in both brain gene expression and brain chromatin accessibility, and that transcription factor (TF) activity is predictive of behavioral phenotype at the individual level

Summary

Introduction

Understanding the genomic regulatory architecture of phenotypic plasticity is necessary to achieve comprehensive knowledge of the mechanisms and evolution of complex traits. While a growing body of knowledge exists on specific regulatory mechanisms involved in developmental plasticity, less is known about the regulation of behavioral plasticity. Behavioral plasticity is of special interest and presents unique challenges, as behavioral traits derive from the integrated actions of genetic, transcriptomic, and neuronal networks (Sinha et al, 2020)

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