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Predicting evolutionary predictability.

Catherine R Linnen1

  • 1Department of Biology, University of Kentucky, Lexington, Kentucky.

Molecular Ecology
|June 13, 2018
PubMed
Summary

Evolutionary predictability is quantified by studying genomic changes in butterflies adapting to new host plants. While genomic shifts show some predictability, the degree varies by comparison type, scale, and genomic location.

Keywords:
adaptationconvergent evolutionecological genomicsevolutionary repeatabilityhost shiftplant-insect interactions

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Area of Science:

  • Evolutionary Biology
  • Genomics
  • Ecology

Background:

  • Phenotypic and genetic convergence suggest evolution is predictable, but quantifying this predictability across different levels remains challenging.
  • Studies quantifying evolutionary predictability often focus on specific examples rather than broad patterns.

Discussion:

  • Chaturvedi et al. quantify the predictability of genomewide genetic changes accompanying host shifts in the Melissa blue butterfly (Lycaeides melissa) adapting to alfalfa.
  • Predictability was assessed by comparing genomic loci associated with host use in natural populations and laboratory experiments.
  • The study examines predictability in two contexts: overlap in host-associated loci among independently colonizing populations and overlap between natural and experimental host-associated loci.

Key Insights:

  • Genomic changes during host shifts in Lycaeides melissa are somewhat predictable.
  • The degree of predictability is influenced by the comparison method (natural vs. experimental populations), type of convergence, geographic scale, and genomic location (autosomes vs. sex chromosomes).

Outlook:

  • This research contributes to a growing dataset suggesting that the balance of stochastic and deterministic factors in evolutionary responses to new environments can be variable, yet potentially predictable.
  • Further research is needed to explore the variability and predictability of genomewide evolutionary responses across diverse systems.