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Genome-wide SNP data reveal improved evidence for Antarctic glacial refugia and dispersal of terrestrial invertebrates.

Angela McGaughranAleks TeraudsPeter ConveyCeridwen I Fraser
Published in: Molecular ecology (2019)
Antarctica is isolated, surrounded by the Southern Ocean and has experienced extreme environmental conditions for millions of years, including during recent Pleistocene glacial maxima. How Antarctic terrestrial species might have survived these glaciations has been a topic of intense interest, yet many questions remain unanswered, particularly for Antarctica's invertebrate fauna. We examine whether genetic data from a widespread group of terrestrial invertebrates, springtails (Collembola, Isotomidae) of the genus Cryptopygus, show evidence for long-term survival in glacial refugia along the Antarctic Peninsula. We use genome-wide SNP analyses (via genotyping-by-sequencing, GBS) and mitochondrial data to examine population diversity and differentiation across more than 20 sites spanning >950 km on the Peninsula, and from islands both close to the Peninsula and up to ~1,900 km away. Population structure analysis indicates the presence of strong local clusters of diversity, and we infer that patterns represent a complex interplay of isolation in local refugia coupled with occasional successful long-distance dispersal events. We identified wind and degree days as significant environmental drivers of genetic diversity, with windier and warmer sites hosting higher diversity. Thus, we infer that refugial areas along the Antarctic Peninsula have allowed populations of indigenous springtails to survive in situ throughout glacial periods. Despite the difficulties of dispersal in cold, desiccating conditions, Cryptopygus springtails on the Peninsula appear to have achieved multiple long-distance colonization events, most likely through wind-related dispersal events.
Keyphrases
  • genome wide
  • genetic diversity
  • dna methylation
  • electronic health record
  • copy number
  • big data
  • gene expression
  • single cell
  • climate change
  • data analysis
  • risk assessment
  • artificial intelligence