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Genomics of cold adaptations in the Antarctic notothenioid fish radiation.

Iliana BistaJonathan M D WoodThomas DesvignesShane A McCarthyMichael MatschinerZemin NingAlan TraceyJames TorranceYing SimsWilliam ChowMichelle SmithKaren OliverLeanne HaggertyWalter SalzburgerJohn H PostlethwaitKerstin HoweMelody Susan ClarkHarry William DetrichC-H Christina ChengEric Alexander MiskaRichard Durbin
Published in: Nature communications (2023)
Numerous novel adaptations characterise the radiation of notothenioids, the dominant fish group in the freezing seas of the Southern Ocean. To improve understanding of the evolution of this iconic fish group, here we generate and analyse new genome assemblies for 24 species covering all major subgroups of the radiation, including five long-read assemblies. We present a new estimate for the onset of the radiation at 10.7 million years ago, based on a time-calibrated phylogeny derived from genome-wide sequence data. We identify a two-fold variation in genome size, driven by expansion of multiple transposable element families, and use the long-read data to reconstruct two evolutionarily important, highly repetitive gene family loci. First, we present the most complete reconstruction to date of the antifreeze glycoprotein gene family, whose emergence enabled survival in sub-zero temperatures, showing the expansion of the antifreeze gene locus from the ancestral to the derived state. Second, we trace the loss of haemoglobin genes in icefishes, the only vertebrates lacking functional haemoglobins, through complete reconstruction of the two haemoglobin gene clusters across notothenioid families. Both the haemoglobin and antifreeze genomic loci are characterised by multiple transposon expansions that may have driven the evolutionary history of these genes.
Keyphrases
  • genome wide
  • copy number
  • dna methylation
  • radiation induced
  • single molecule
  • electronic health record
  • heavy metals
  • gene expression
  • single cell
  • high intensity
  • risk assessment
  • big data
  • data analysis
  • genetic diversity