Evolutionary genomics of healthy ageing
in eusocial animals

With our research, we are asking:

  1. Why does extreme longevity evolve along with eusociality

  2. Which molecular mechanisms and biological pathways are involved in this repeated decoupling of the longevity/fecundity trade-off?

  3. What can we learn from these molecular mechanisms about ageing pathologies and lifespan in non-eusocial animals, such as humans?

My research: centres on understanding the molecular signatures that underlie the evolution of complex phenotypic traits in insects, such as developmental strategies (Fouks, Harrison, et al. iScience, 2023, feeding behaviour (Harrison et al. JEZ-B, 2018) and especially eusociality (Harrison et al. Nat Ecol Evol, 2018;).

Eusociality: The most advanced eusocial species, in which distinct, permanent castes exist within large, complex colonies (e.g. ants, honeybees, higher termites and naked mole-rats), can be considered superorganisms, the evolution of which represents one of the eight major transitions in evolution.

A fascinating aspect of most eusocial animals, relates to the extreme lifespans achieved by reproductive castes despite high reproductive output and limited signs of ageing, if any. This extreme longevity and reduced ageing in reproductive individuals has evolved multiple times along with eusociality in insects and mammals. We aim to understand this fascinating phenomenon in order to gain insights for ageing in non-eusocial animals.

To address these questions: we have been employing a combination of genomics (Harrison et al. Nat Ecol Evol, 2018), transcriptomics (Harrison et al. GBE, 2021; Seite, Harrison et al. Comms Biol 2022), epigenomics (Harrison et al. Open Biology, 2022), and mobilomics (Post et al. Mol Ecol 2023), on long-lived termite and ant queens, and have managed to discover several important anti-ageing mechanisms.

Currently: we are developing genomic and transcriptomic resources for cockroaches, termites, burying beetles and wood-boring weevils, which cover the full range of social complexity from solitary living, through parental care, alloparental care and superorganismality (see projects). Further more, we are working on machine learning tools that can identify key genomic features, with which social phenotypes and caste- and age-specific expression can be accurately predicted based on genome sequences alone.

Fig. 1 Evolution of chemical communication in termites

Fig. 2 Evolution of viviparity in insects

Fig. 3 Convergent co-expression network structures in long-lived ant and termite queens

Fig. 4 Convergent genomic footprints of eusociality

Fig. 5 Predicting eusociality based on genomic sequence features with a mulit-layer perceptron

Fig. 6 Social classification of genome sequences with a mulitlayer perceptron