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Adapting to climate with limited genetic diversity: Nucleotide, DNA methylation and microbiome variation among populations of the social spider Stegodyphus dumicola.

Anne AagaardShenglin LiuTom TregenzaMarie Braad LundAndreas SchrammKoen J F VerhoevenJesper BechsgaardTrine Bilde
Published in: Molecular ecology (2022)
Understanding the role of genetic and nongenetic variants in modulating phenotypes is central to our knowledge of adaptive responses to local conditions and environmental change, particularly in species with such low population genetic diversity that it is likely to limit their evolutionary potential. A first step towards uncovering the molecular mechanisms underlying population-specific responses to the environment is to carry out environmental association studies. We associated climatic variation with genetic, epigenetic and microbiome variation in populations of a social spider with extremely low standing genetic diversity. We identified genetic variants that are associated strongly with environmental variation, particularly with average temperature, a pattern consistent with local adaptation. Variation in DNA methylation in many genes was strongly correlated with a wide set of climate parameters, thereby revealing a different pattern of associations than that of genetic variants, which show strong correlations to a more restricted range of climate parameters. DNA methylation levels were largely independent of cis-genetic variation and of overall genetic population structure, suggesting that DNA methylation can work as an independent mechanism. Microbiome composition also correlated with environmental variation, but most strong associations were with precipitation-related climatic factors. Our results suggest a role for both genetic and nongenetic mechanisms in shaping phenotypic responses to local environments.
Keyphrases
  • genetic diversity
  • dna methylation
  • genome wide
  • copy number
  • gene expression
  • climate change
  • healthcare
  • human health
  • mental health
  • life cycle
  • risk assessment
  • transcription factor