Evolutionary Applications (Sep 2021)

Ageing European lobsters (Homarus gammarus) using DNA methylation of evolutionarily conserved ribosomal DNA

  • Eleanor A. Fairfield,
  • David S. Richardson,
  • Carly L. Daniels,
  • Christopher L. Butler,
  • Ewen Bell,
  • Martin I. Taylor

DOI
https://doi.org/10.1111/eva.13296
Journal volume & issue
Vol. 14, no. 9
pp. 2305 – 2318

Abstract

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Abstract Crustaceans are notoriously difficult to age because of their indeterminate growth and the moulting of their exoskeleton throughout life. The poor knowledge of population age structure in crustaceans therefore hampers accurate assessment of population dynamics and consequently sustainable fisheries management. Quantification of DNA methylation of the evolutionarily conserved ribosomal DNA (rDNA) may allow for age prediction across diverse species. However, the rDNA epigenetic clock remains to be tested in crustaceans, despite its potential to inform both ecological and evolutionary understanding, as well as conservation and management practices. Here, patterns of rDNA methylation with age were measured across 5154 bp of rDNA corresponding to 355 quality‐filtered loci in the economically important European lobster (Homarus gammarus). Across 0‐ to 51‐month‐old lobsters (n = 155), there was a significant linear relationship between age and percentage rDNA methylation in claw tissue at 60% of quality‐filtered loci (n = 214). An Elastic Net regression model using 46 loci allowed for the accurate and precise age estimation of individuals (R2 = 0.98; standard deviation = 1.6 months). Applying this ageing model to antennal DNA from wild lobsters of unknown age (n = 38) resulted in predicted ages that are concordant with estimates of minimum size at age in the wild (mean estimated age = 40.1 months; range 32.8–55.7 months). Overall, the rDNA epigenetic clock shows potential as a novel, nonlethal ageing technique for European lobsters. However, further validation is required across a wider range of known‐age individuals and tissue types before the model can be used in fisheries management.

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