Skip to main content
Dryad logo

Data from: Comparative transcriptomic analysis of the mechanisms underpinning ageing and fecundity in social insects

Citation

Korb, Judith et al. (2021), Data from: Comparative transcriptomic analysis of the mechanisms underpinning ageing and fecundity in social insects, Dryad, Dataset, https://doi.org/10.5061/dryad.66t1g1k1b

Abstract

Exceptional longevity of social insect queens despite their lifelong high fecundity remains poorly understood in ageing biology. To gain insights into the mechanisms that might underlie ageing in social insects, we compared gene expression patterns between young and old castes (both queens and workers) across different lineages of social insects (two termite, two bee and two ant species). After global analyses, we paid particular attention to genes of the insulin/insulin-like growth factor 1 signalling (IIS)/target of rapamycin (TOR)/juvenile hormone (JH) network, which is well known to regulate lifespan and the trade-off between reproduction and somatic maintenance in solitary insects. Our results reveal a major role of the downstream components and target genes of this network (e.g. JH signalling, vitellogenins, major royal jelly proteins and immune genes) in affecting ageing and the caste-specific physiology of social insects, but an apparently lesser role of the upstream IIS/TOR signalling components. Together with a growing appreciation of the importance of such downstream targets, this leads us to propose the TI–J–LiFe (TOR/IIS–JH–Lifespan and Fecundity) network as a conceptual framework for understanding the mechanisms of ageing and fecundity in social insects and beyond.

This article is part of the theme issue ‘Ageing and sociality: why, when and how does sociality change ageing patterns?’.

Methods

Methods are in detail provided in the main manuscript and in the supplementary text of the study. 

Usage Notes

For any questions on the supplementary archives provided on DRYAD, please contact Karen Meusemann (mail@karen-meusemann.de).

Funding

Deutsche Forschungsgemeinschaft, Award: BE6684/1-1, FE1333/6-1, FE1333/6-2, FO298/19-1, FO298/19-2, HE1623/37, KO1895/16-1, KO1895/19-1, KO1895/20-1, KO1895/20-2, LI3051/3-1, NE1969/4-1, PA632/9 -1, PA632/9-2

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Award: 310030E-164207 and 31003A_182262

Novartis Stiftung für Medizinisch-Biologische Forschung, Award: 19B149

Novartis Stiftung für Medizinisch-Biologische Forschung, Award: 19B149