Molecular Biology ReportsMolecular BiologyPeer-reviewed journal article
Development of an STR panel for a non-native population of an endangered species
Erin HilliD, Adrian M. T. LinacreiD, Simon D. Toop, Nicholas P. MurphyiD, Jan M. StrugnelliD
Abstract
The establishment of non-native populations of threatened and legally protected species can have many implications for the areas where these species have been introduced. Non-native populations of threatened species have the potential to be exploited and therefore the subject of legal protection, while conversely, if they have become invasive in their introduced range, there is the likelihood that population control will be carried out to reduce abundance and negative impacts associated with introduced species. From both a legal and invasive species monitoring standpoint, it is important to know how many individuals are present. Short tandem repeats (STRs) were developed for the hog deer, an endangered species that was introduced following European settlement to Victoria, Australia using Illumina MiSeq sequencing technology. These markers were combined with previous STRs characterised for hog deer to create a 29-plex identification system. A total of 224 samples were genotyped across the population in Victoria, and further analyses of null allele frequencies, deviation from Hardy-Weinberg equilibrium, and the removal of monomorphic or low amplifying markers resulted in a final marker panel of 17 loci. Despite low values for number of alleles at each locus (2-4), probability of identity showed sufficient discrimination power, with an average probability of identity at 9.46 x 10-7, and a probability of sibling identity of 7.67 x 10-4 across all sites. These findings show that it is feasible to create an informative DNA profiling system that can distinguish between individuals for applications in both wildlife forensic and population control research.
- organism: non-human primate
- assay: DNA methylation
- research focus: cell type annotation
- approach: statistical model
- Citations
- 2
- FWCI
- 0.28
- Field percentile
- top 47%
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