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Fresh is best: Accurate SNP genotyping from koala scats
Journal article   Open access   Peer reviewed

Fresh is best: Accurate SNP genotyping from koala scats

Anthony J Schultz, Romane H Cristescu, Bethan Littleford-Colquhoun, Damian Jaccoud and Celine H Frere
Ecology and Evolution, Vol.8(6), pp.3139-3151
2018
PMCID: PMC5869377
PMID: 29607013
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Fresh is best - Accurate SNP genotyping from koala scats564.95 kBDownloadView
Published VersionCC BY V4.0 Open Access
url
https://doi.org/10.1002/ece3.3765View
Published Version

Abstract

diet disease koala scat SNP Genotyping
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.

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Domestic collaboration
Web Of Science research areas
Ecology
Evolutionary Biology
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