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When, why and how does sociality and sex affect ageing and life history evolution in termites?

Subject Area Evolution, Anthropology
Term since 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 493354423
 
Social insects are promising nascent models to gain insights into life history evolution and especially ageing. Within a colony of termites, ants or honeybees, different individuals have different life histories despite sharing the same genetic background. Furthermore, queens have apparently overcome the almost universal life history trade-off between fecundity and longevity. They are among the most fertile and most long-lived insects with reproduction even increasing lifespan. In a recent project, we studied why and how sociality changes the fecundity/longevity trade-off and ageing in termites by using modelling and gene expression approaches, respectively. While we are close to providing answers to the why question, our proximate approach about the mechanisms was strongly affected by COVID-19. We aimed to generate transcriptomes of young and old queens and workers of termite species and one representative of the termites’ sister taxon, the woodroaches, covering the whole termite phylogeny with different degrees of sociality. Yet, COVID-19 restrictions limited sampling of species, which necessitated concentration mainly on species of low social complexity. Within the framework of this new proposal, we want to supplement the missing species to make full use of our available data sets and answer the question how the mechanisms underlying the fecundity/longevity trade-off and ageing change with degree of sociality (Objective 1). We want to complement this objective by adding the effect of sex on ageing, which has been largely ignored in social insect studies so far. Thus, in Objective 2, we aim to study sex-specific ageing in termite reproductives by addressing the question when, why, and how does sex-specific ageing occur. To answer our questions, we will also make use of novel machine learning approaches, which facilitate pattern detection across species. Our project will provide new insights into fundamental questions of life history evolution and mechanisms underlying a long lifespan.
DFG Programme Research Grants
 
 

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