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From promise to practice: pairing non-invasive sampling with genomics in conservation
Michael A Russello1, Matthew D Waterhouse1, Paul D Etter2
1Department of Biology, University of British Columbia , Kelowna, BC , Canada.
Conservation genomics using non-invasive hair samples is feasible for the American pika (Ochotona princeps). Genotyping-by-sequencing identified thousands of single nucleotide polymorphisms (SNPs), revealing genetic diversity linked to elevation.
Area of Science:
- Ecology
- Genetics
- Conservation Biology
Background:
- Conservation genomics relies on non-invasive sampling, but its compatibility with next-generation sequencing (NGS) is uncertain.
- The American pika (Ochotona princeps) is a climate-sensitive mammal, making it a key species for conservation studies.
Purpose of the Study:
- To assess the feasibility of genotyping-by-sequencing (GBS) using non-invasively collected hair samples for SNP identification and genotyping in the American pika.
- To explore the relationship between genetic diversity, elevation, and potential selection pressures in this species.
Main Methods:
- Utilized GBS on hair samples from eight sites across two elevational transects.
- Identified and genotyped high-confidence single nucleotide polymorphisms (SNPs) with low starting DNA amounts (as low as 1 ng).
- Analyzed outlier loci for divergent selection and correlated genome-wide gene diversity with elevation.
Main Results:
- Successfully identified and genotyped 3,803 high-confidence SNPs.
- Detected 55 outlier loci potentially under divergent selection.
- Found a significant positive correlation between genome-wide gene diversity and elevation, with low elevation sites showing heterozygote deficit indicative of inbreeding.
Conclusions:
- Non-invasive GBS is a viable method for conservation genomics in the American pika.
- Genetic diversity is influenced by elevation, suggesting adaptation to different climate conditions.
- Highlights critical considerations for non-invasive sampling in genomics, including field protocols, data quality control, and cost-effective analysis.
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