Genetics in the Honey Bee: Achievements and Prospects toward the Functional Analysis of Molecular and Neural Mechanisms Underlying Social Behaviors

Abstract

The European honey bee is a model organism for studying social behaviors. Comprehensive analyses focusing on the differential expression profiles of genes between the brains of nurse bees and foragers, or in the mushroom bodies—the brain structure related to learning and memory, and multimodal sensory integration—has identified candidate genes related to honey bee behaviors. Despite accumulating knowledge on the expression profiles of genes related to honey bee behaviors, it remains unclear whether these genes actually regulate social behaviors in the honey bee, in part because of the scarcity of genetic manipulation methods available for application to the honey bee. In this review, we describe the genetic methods applied to studies of the honey bee, ranging from classical forward genetics to recently developed gene modification methods using transposon and CRISPR/Cas9. We then discuss future functional analyses using these genetic methods targeting genes identified by the preceding research. Because no particular genes or neurons unique to social insects have been found yet, further exploration of candidate genes/neurons correlated with sociality through comprehensive analyses of mushroom bodies in the aculeate species can provide intriguing targets for functional analyses, as well as insight into the molecular and neural bases underlying social behaviors.

Analysis of Synaptic Microcircuits in the Mushroom Bodies of the Honeybee

“…The crucial part, however, will be genetic manipulation experiments using knockdown or knockout techniques such as RNA interference or CRISPR/Cas9 gene editing. Although CRISPR/Cas9 and related approaches have recently emerged as a promising tool, including for the honeybee [67,[121][122][123], candidate genes involved in adult neuronal plasticity most probably play equally important roles during development, and knockout of these genes, if not compensated by other genes, will lead to early death or severe developmental defects. Furthermore, the CRISPR/Cas9 technique is difficult to apply and is time-consuming in the honeybee, mainly due to the reproductive biology and social lifestyle of honeybee colonies [67].…”

“…More recent characterizations of KCs according to molecular criteria and gene expression profiles suggest additional subpopulations within the group of class I KCs [63][64][65][66][67].…”

Distributed physiology and the molecular basis of social life in eusocial insects

“…This can be contrasted with exocrine glands, for which the transcriptome can be expected to more closely approximate the instantaneous secretory function of the tissue due to rapid transcriptomic turnover 16,95 . We expect that integrated neuroscientific approaches involving the single-cell profiling of social insect brain tissue along with live-imaging and reverse genetic approaches will be required to reach nuanced claims about the neurophysiology of individual behavior 88,146 . However it is a second layer of organization above individual neurobiological mechanisms, through interactions among nestmates, by which colony collective behavior arises 54,55,69 .…”

“…First, the epigenetic plasticity of eusocial insect workers situates them as tractable models to disentangle genetic and environmental influences on behavior 88,163 . 29,120,146,155,164 .…”

Fungus-Growing Ants: Models for the Integrative Analysis of Cognition and Brain Evolution

“…Correlations between behavioral capabilities and tissue volume have been viewed critically (Herculano-Houzel et al, 2006Rowe, 2007, 2013;Chittka and Niven, 2009;Godfrey and Gronenberg, 2019;Wartel et al, 2019), although in principle quantify brain investment. Functionally specialized brain compartments may develop allometrically (disproportionate scaling) through differential cell and tissue-type trajectories (Barton and Harvey, 2000;Hager et al, 2012), circuitry (Guzowski et al, 2005), neuron structure and function (Quiroga et al, 2005), and genetics (Hibar et al, 2015;Kohno and Kubo, 2019). These patterns provide fine-grain traits for evolutionary analyses.…”