Development and validation of a GT-seq panel for genetic monitoring in a threatened species using minimally invasive sampling
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Abstract
Minimally invasive samples are often the best option for collecting genetic material from species of conservation concern, but they perform poorly in many genomic sequencing methods due to their tendency to yield low DNA quality and quantity. Genotyping-in-thousands by sequencing (GT-seq) is a powerful amplicon sequencing method that can genotype large numbers of variable-quality samples at a standardized set of single nucleotide polymorphism (SNP) loci. Here, we develop, optimize, and validate a GT-seq panel for the federally threatened northern Idaho ground squirrel (Urocitellus brunneus) to provide a standardized approach for future genetic monitoring and assessment of recovery goals using minimally invasive samples. The optimized panel consists of 224 neutral and 81 putatively adaptive SNPs. DNA collected from buccal swabs from 2016 to 2020 had 73% genotyping success, while samples collected from hair from 2002 to 2006 had little to no DNA remaining and did not genotype successfully. We evaluated our GT-seq panel by measuring genotype discordance rates compared to RADseq and whole-genome sequencing. GT-seq and other sequencing methods had similar population diversity and FST estimates, but GT-seq consistently called more heterozygotes than expected, resulting in negative FIS values at the population level. Genetic ancestry assignment was consistent when estimated with different sequencing methods and numbers of loci. Our GT-seq panel is an effective and efficient genotyping tool that will aid in the monitoring and recovery of this threatened species, and our results provide insights for applying GT-seq for minimally invasive DNA sampling techniques in other rare animals.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Development and validation of a GT-seq panel for genetic monitoring in a threatened species using minimally invasive sampling |
Series title | Ecology and Evolution |
DOI | 10.1002/ece3.11321 |
Volume | 14 |
Issue | 5 |
Year Published | 2024 |
Language | English |
Publisher | Wiley |
Contributing office(s) | Coop Res Unit Seattle |
Description | e11321, 13 p. |
Google Analytic Metrics | Metrics page |