Project 12.3

Eusocial insects distribute colony tasks among individuals, leading to a division of labor (DOL), driven by genetic and environmental factors. Recent research suggests that epigenetic factors may play a role in worker behavior and caste differentiation. In my project, we will explore how different epigenetic mechanisms such as histone modifications and miRNAs might influence gene expression, aiming to reveal the mechanisms behind DOL and task allocation.

Eusocial insect societies exhibit variability in structure and task allocation, with individuals assuming different “jobs” according to colony need. Ant colonies often exhibit a division of labor (DOL)/privilege between a queen (or queens) that takes on the majority of the reproductive capacity and the worker caste that focuses on tasks like foraging or brood care. DOL and worker behavior is linked to gene expression and is modulated by a range of factors including age, nutrition, experience, and hormone regulation.

Recent studies have sought to explore the molecular underpinnings of division of labor in social insects on an epigenetic scale. These studies link behavior and gene expression to RNA modifications, DNA methylation, non-coding RNA expression, and histone modifications. For instance, inhibition of histone acetyltransferases (HATs), accompanied by manipulation of colony demographics, has been shown to prolong foraging behavior in major C. floridanus ants (Simola et al., 2016) and to impair the ability of foragers to transition to brood-caring behavior in T. longispinosus (Kohlmeier et al., 2023). Additionally, differential expression of small RNAs has been observed across different life stages and tissues in various ant species. Preliminary data from our group suggest that microRNA expression patterns in the brains of foragers and brood carers may vary.

In my project, we aim to further investigate how epigenetic factors, such as histone modification patterns and miRNAs, regulate gene expression in the context of DOL. We will use Cut&Tag and RNA-seq data to establish a connection between behavior, gene expression, and regulatory mechanisms. We will also functionally characterize genes and investigate gene regulatory networks implicated in DOL via RNAi.