Queens of eusocial species live extraordinarily long compared to their workers. So far, it has been argued that these lifespan divergences are readily explained by the classical evolutionary theory of ageing. As workers predominantly perform risky tasks, such as foraging and nest defense, and queens stay in the well-protected nests, selection against harmful genetic mutations expressed in old age should be weaker in workers than in queens due to caste differences in extrinsic mortality risk, and thus, lead to the evolution of longer queen and shorter worker lifespans. However, these arguments have not been supported by formal models. Here, we present a model for the evolution of caste-specific ageing in social insects, based on Williams' antagonistic pleiotropy theory of ageing. In individual-based simulations, we assume that mutations with antagonistic fitness effects can act within castes, that is, mutations in early life are accompanied by an antagonistic effect acting in later life, or between castes, where antagonistic effects emerge due to caste antagonism or indirect genetic effects between castes. In monogynous social insect species with sterile workers, large lifespan divergences between castes evolved under all different scenarios of antagonistic effects, but regardless of the degree of caste-specific extrinsic mortality. Mutations with antagonistic fitness effects within castes reduced lifespans of both castes, while mutations with between-caste antagonistic effects decreased worker lifespans more than queen lifespans, and consequently increased lifespan divergences. Our results challenge the central explanatory role of extrinsic mortality for caste-specific ageing in eusocial organisms and suggest that antagonistic pleiotropy affects castes differently due to reproductive monopolization by queens, hence, reproductive division of labor. Finally, these findings provide new insights into the evolution of tissue-specific ageing in multicellular organisms in general.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190452 | PMC |
http://dx.doi.org/10.1002/evl3.230 | DOI Listing |
The dynamics of virulence evolution in vector-borne plant pathogens can be complex. Here, we use individual-based, quantitative-genetic simulations to investigate how virulence evolution depends on genetic trade-offs and population structure. Although quite generic, the model is inspired by the ecology of the plant-pathogenic bacterium , and we use it to gain insights into possible modes of virulence evolution in that group.
View Article and Find Full Text PDFInt J Mol Sci
November 2024
Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27705, USA.
Physical activity (PA) is a modifiable factor in mitigating/preventing Alzheimer's disease (AD). It is crucial to identify the conditions under which PA's effects on AD risk would be beneficial. This study aims to gain insights into pleiotropic predisposition to AD and PA within and across sexes and environmental effects.
View Article and Find Full Text PDFCells
November 2024
CNRS, INSERM, iBV, Université Côte d'Azur, 06107 Nice, France.
P16Ink4a is a well-established marker of senescence. Although P16Ink4a is expressed in endothelial cells, little is known about its function in these cells. Using isolated liver endothelial cells with silencing or overexpression of P16Ink4a, we show here that dependent on P16Ink4a levels, different pathways and functions are affected.
View Article and Find Full Text PDFEvol Lett
December 2024
Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, United States.
bioRxiv
October 2024
Department of Biology, Stanford University, Stanford, CA, USA.
Life-history trade-offs are an inherent feature of organismal biology that evolutionary theory posits play a key role in patterns of divergence within and between species. Efforts to quantify trade-offs are largely confined to phenotypic measurements and the identification of negative genetic-correlations among fitness-relevant traits. Here, we use time-series genomic data collected during experimental evolution in large, genetically diverse populations of to directly measure the manifestation of trade-offs in response to temporally fluctuating selection pressures on ecological timescales.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!