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Harnessing the power of multi-omics data for predicting climate change response.

Kara K S LaytonIan R Bradbury
Published in: The Journal of animal ecology (2021)
Predicting how species will respond to future climate change is of central importance in the midst of the global biodiversity crisis, and recent work has demonstrated the utility of population genomics for improving these predictions. Here, we suggest a broadening of the approach to include other types of genomic variants that play an important role in adaptation, like structural (e.g. copy number variants) and epigenetic variants (e.g. DNA methylation). These data could provide additional power for forecasting response, especially in weakly structured or panmictic species. Incorporating structural and epigenetic variation into estimates of climate change vulnerability, or maladaptation, may not only improve prediction power but also provide insight into the molecular mechanisms underpinning species' response to climate change.
Keyphrases
  • climate change
  • copy number
  • dna methylation
  • mitochondrial dna
  • genome wide
  • gene expression
  • human health
  • big data
  • electronic health record
  • single cell
  • public health
  • machine learning