Login / Signup

Phylogeographic analysis of shrubby beardtongues reveals range expansions during the Last Glacial Maximum and implicates the Klamath Mountains as a hotspot for hybridization.

Benjamin W StoneAndrea D Wolfe
Published in: Molecular ecology (2021)
Quaternary glacial cycles often altered species' geographic distributions, which in turn altered the geographic structure of species' genetic diversity. In many cases, glacial expansion forced species in temperate climates to contract their ranges and reside in small pockets of suitable habitat (refugia), where they were likely to interact closely with other species, setting the stage for potential gene exchange. These introgression events, in turn, would have degraded species boundaries, making the inference of phylogenetic relationships challenging. Using high-throughput sequence data, we employed a combination of species distribution models and hybridization tests to assess the effect of glaciation on the geographic distributions, phylogenetic relationships, and patterns of gene flow of five species of Penstemon subgenus Dasanthera, long-lived shrubby angiosperms distributed throughout the Pacific Northwest of North America. Surprisingly, we found that rather than reducing their ranges to small refugia, most Penstemon subgenus Dasanthera species experienced increased suitable habitat during the Last Glacial Maximum relative to the present day. We also found substantial evidence for gene exchange between species, with the bulk of introgression events occurring in or near the Klamath Mountains of southwestern Oregon and northwestern California. Subsequently, our phylogenetic inference reveals blurred taxonomic boundaries in the Klamath Mountains, where introgression is most prevalent. Our results question the classical paradigm of temperate species' responses to glaciation and highlight the importance of contextualizing phylogenetic inference with species' histories of introgression.
Keyphrases
  • genetic diversity
  • high throughput
  • gene expression
  • risk assessment
  • deep learning
  • amino acid
  • human health
  • living cells