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Genetic variation within a stick-insect species associated with community-level traits.

Marion Sinclair-WatersLaura S ZamoranoZachariah GompertTom ParchmanVenera TyukmaevaDavid P HopkinsPatrik Nosil
Published in: Journal of evolutionary biology (2024)
Phenotypic variation within species can affect the ecological dynamics of populations and communities. Characterizing the genetic variation underlying such effects can help parse the roles of genetic evolution and plasticity in "eco-evolutionary dynamics" and inform how genetic variation may shape patterns of evolution. Here, we employ genome-wide association (GWA) methods in Timema cristinae stick insects and their co-occurring arthropod communities to identify genetic variation associated with community-level traits. Previous studies have shown that maladaptation (i.e., imperfect crypsis) of T. cristinae can reduce the abundance and species richness of other arthropods due to an increase in bird predation. Whether genetic variation that is independent of crypsis has similar effects is unknown and was tested here using genome-wide genotyping-by-sequencing data of stick insects, arthropod community information, and GWA mapping with Bayesian sparse linear mixed models. We find associations between genetic variation in stick insects and arthropod community traits. However, these associations disappear when host-plant traits are accounted for. We thus use path analysis to disentangle interrelationships among stick-insect genetic variation, host-plant traits, and community traits. This revealed that host-plant size has large effects on arthropod communities, while genetic variation in stick insects has a smaller, but still significant effect. Our findings demonstrate that (1) genetic variation in a species can be associated with community-level traits but that (2) interrelationships among multiple factors may need to be analyzed to disentangle whether such associations represent causal relationships. This work helps to build a framework for genomic studies of eco-evolutionary dynamics.
Keyphrases
  • genome wide
  • dna methylation
  • mental health
  • healthcare
  • copy number
  • genetic diversity
  • climate change
  • machine learning
  • social media
  • risk assessment
  • artificial intelligence
  • data analysis