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Phylogenomic history of enigmatic pygmy perches: implications for biogeography, taxonomy and conservation.

Sean J BuckleyFabricius M C B DomingosCatherine R M AttardChris J BrauerJonathan Sandoval-CastilloRyan LodgePeter J UnmackLuciano B Beheregaray
Published in: Royal Society open science (2018)
Pygmy perches (Percichthyidae) are a group of poorly dispersing freshwater fishes that have a puzzling biogeographic disjunction across southern Australia. Current understanding of pygmy perch phylogenetic relationships suggests past east-west migrations across a vast expanse of now arid habitat in central southern Australia, a region lacking contemporary rivers. Pygmy perches also represent a threatened group with confusing taxonomy and potentially cryptic species diversity. Here, we present the first study of the evolutionary history of pygmy perches based on genome-wide information. Data from 13 991 ddRAD loci and a concatenated sequence of 1 075 734 bp were generated for all currently described and potentially cryptic species. Phylogenetic relationships, biogeographic history and cryptic diversification were inferred using a framework that combines phylogenomics, species delimitation and estimation of divergence times. The genome-wide phylogeny clarified the biogeographic history of pygmy perches, demonstrating multiple east-west events of divergence within the group across the Australian continent. These results also resolved discordance between nuclear and mitochondrial data from a previous study. In addition, we propose three cryptic species within a southwestern species complex. The finding of potentially new species demonstrates that pygmy perches may be even more susceptible to ecological and demographic threats than previously thought. Our results have substantial implications for improving conservation legislation of pygmy perch lineages, especially in southwestern Western Australia.
Keyphrases
  • genome wide
  • dna methylation
  • climate change
  • genetic diversity
  • healthcare
  • oxidative stress
  • electronic health record
  • risk assessment
  • machine learning
  • human health
  • health information
  • social media