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Published VersionCC BY V4.0, Open Access
Journal article
Fresh is best: Accurate SNP genotyping from koala scats
Ecology and Evolution, Vol.8(6), pp.3139-3151
2018
PMCID: PMC5869377
PMID: 29607013
Appears in UniSC Supported Open Access Outputs
Abstract
Maintaining genetic diversity is a crucial component in conserving threatened species. For the iconic Australian koala, there is little genetic information on wild populations that is not either skewed by biased sampling methods (e.g., sampling effort skewed toward urban areas) or of limited usefulness due to low numbers of microsatellites used. The ability to genotype DNA extracted from koala scats using next-generation sequencing technology will not only help resolve location sample bias but also improve the accuracy and scope of genetic analyses (e.g., neutral vs. adaptive genetic diversity, inbreeding, and effective population size). Here, we present the successful SNP genotyping (1272 SNP loci) of koala DNA extracted from scat, using a proprietary DArTseqâ„¢ protocol. We compare genotype results from two-day- old scat DNA and 14-day- old scat DNA to a blood DNA template, to test accuracy of scat genotyping. We find that DNA from fresher scat results in fewer loci with missing information than DNA from older scat; however, 14-day- old scat can still provide useful genetic information, depending on the research question. We also find that a subset of 209 conserved loci can accurately identify individual koalas, even from older scat samples. In addition, we find that DNA sequences identified from scat samples through the DArTseqâ„¢ process can provide genetic identification of koala diet species, bacterial and viral pathogens, and parasitic organisms.
Details
- Title
- Fresh is best: Accurate SNP genotyping from koala scats
- Authors
- Anthony J Schultz (Corresponding Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and EngineeringRomane H Cristescu (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and EngineeringBethan Littleford-Colquhoun (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and EngineeringDamian Jaccoud (Author) - University of CanberraCeline H Frere (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
- Publication details
- Ecology and Evolution, Vol.8(6), pp.3139-3151
- Publisher
- John Wiley & Sons Ltd.
- Date published
- 2018
- DOI
- 10.1002/ece3.3765
- ISSN
- 2045-7758; 2045-7758
- PMID
- 29607013; PMC5869377
- Copyright note
- Copyright © 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Organisation Unit
- School of Science and Engineering - Legacy; GeneCology Research Centre - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99451278402621
- Output Type
- Journal article
- Research Statement
- false
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Ecology
- Evolutionary Biology