Koala Genome Survey: An Open Data Resource to Improve Conservation Planning

Genes (Basel). 2023 Feb 22;14(3):546. doi: 10.3390/genes14030546.

Abstract

Genome sequencing is a powerful tool that can inform the management of threatened species. Koalas (Phascolarctos cinereus) are a globally recognized species that captured the hearts and minds of the world during the 2019/2020 Australian megafires. In 2022, koalas were listed as 'Endangered' in Queensland, New South Wales, and the Australian Capital Territory. Populations have declined because of various threats such as land clearing, habitat fragmentation, and disease, all of which are exacerbated by climate change. Here, we present the Koala Genome Survey, an open data resource that was developed after the Australian megafires. A systematic review conducted in 2020 demonstrated that our understanding of genomic diversity within koala populations was scant, with only a handful of SNP studies conducted. Interrogating data showed that only 6 of 49 New South Wales areas of regional koala significance had meaningful genome-wide data, with only 7 locations in Queensland with SNP data and 4 locations in Victoria. In 2021, we launched the Koala Genome Survey to generate resequenced genomes across the Australian east coast. We have publicly released 430 koala genomes (average coverage: 32.25X, range: 11.3-66.8X) on the Amazon Web Services Open Data platform to accelerate research that can inform current and future conservation planning.

Keywords: adaptive potential; conservation management; genomics; technological advancements.

Publication types

  • Systematic Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Australia
  • Endangered Species
  • Genomics
  • Phascolarctidae* / genetics

Grants and funding

The Koala Genome Survey was funded by the NSW Government and the Australian Government’s Bushfire Recovery for Wildlife and their Habitats program (GA2000526). Further support was provided by The University of Sydney, Amazon Web Services Open Data Sets, Ramaciotti Centre for Genomics, and Illumina.