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Updated: Aug 28, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
More than one way to SNP a scat? The implementation of a microhaplotype SNP panel for non-invasive fecal samples
Ariana L Cerreta1, Jennifer R Adams2, Kathleen Petersen1
1Idaho Cooperative Fish and Wildlife Research Unit, Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID 83844, USA.
Abstract:
Biologists use long-term monitoring of wildlife populations to investigate how populations change over time or in relation to extrinsic pressures. Recently, amplicon-based sequencing approaches with high-quality samples have been used to study or monitor wildlife populations in lieu of traditional microsatellite methodologies. However, the application of these techniques with lower-quality DNA sources has had mixed results and risks the loss of interoperability between microsatellites and genomic data in long-term datasets. We sought to optimize a microhaplotype panel for use with non-invasively collected wolf fecal samples, maintaining the ability to identify and match individuals across two datasets and draw familial inferences. We conducted 16 experiments to investigate pre-treatment of sample extracts, PCR1 cleaning methods, combining PCR2 with normalization using "Nate's Plates", and incubating normalization plates overnight. Additionally, we developed a quantitative PCR (qPCR) assay to quantify wolf nuclear DNA in fecal samples. We quantified 2283 fecal sample extractions on qPCR assays and ultimately genotyped 790 unique fecal samples. We retained 472 unique samples within our final dataset with an average capture rate per individual of 1.63. Finally, we successfully reconnected the two datasets by matching 66 individuals identified through scat sampling with harvest tissue genotypes. We found that noninvasive samples should have a minimum concentration of 0.2 ng/uL accompanied by efforts to reduce primer artifacts. As next generation sequencing technologies become increasingly applied in wildlife populations including using low-quality samples as we have demonstrated, special care will be required to maintain interoperability across datasets.
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