The molecular basis of socially mediated phenotypic plasticity in a eusocial paper wasp

Benjamin A Taylor,Alessandro Cini,Max Reuter,Seirian Sumner,Christopher D R Wyatt

doi:10.1038/s41467-021-21095-6

Benjamin A Taylor, Alessandro Cini + Show 3 more

Open Access

https://doi.org/10.1038/s41467-021-21095-6

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Abstract

Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes. Analyses of the molecular foundations of phenotypic plasticity are challenging, however, especially in the case of complex social phenotypes. Here we apply a machine learning approach to tackle this challenge by analyzing individual-level gene expression profiles of Polistes dominula paper wasps following the loss of a queen. We find that caste-associated gene expression profiles respond strongly to queen loss, and that this change is partly explained by attributes such as age but occurs even in individuals that appear phenotypically unaffected. These results demonstrate that large changes in gene expression may occur in the absence of outwardly detectable phenotypic changes, resulting here in a socially mediated de-differentiation of individuals at the transcriptomic level but not at the levels of ovarian development or behavior.

Highlights

Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes
Much research in behavioral and evolutionary ecology is based on the implicit assumption that phenotypic traits can be modeled as though they directly reflect gene expression patterns, and that evolutionary trajectories can be studied while remaining agnostic with regard to the underlying molecular mechanisms[1,2,3]
Support vector machines (SVMs) have become a key tool in the early identification of phenotypically indistinguishable cancer subtypes[30,31,32] and their potential value has recently been demonstrated in animal behavior studies: Chakravarty et al.[33], for example, recently showed that an SVM trained using accelerometer data can reliably classify the behaviors of wild Kalahari meerkats

Summary

Introduction

Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes. The European paper wasp Polistes dominula (Christ 1791) is a model organism often used in studies of social insect behavior[22,23] and, more recently, for analyses of caste gene expression[24,25,26] In this species, removing the established queen from a single-foundress colony induces a queen succession process in which one (or very few) workers transition to a queen phenotype, with age playing a key role in predicting which individual will do so[27,28]: almost invariably, the new queen is one of the oldest individuals, and there is little conflict over succession[19,29]. Given their ability to detect subtle changes in patterns of high-dimensional data, SVMs should be ideally suited to quantify gene expression variation across the spectrum between differentiated worker and queen roles

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