Open Collections

Description

Abstract

Studies in ecology, evolution, and conservation often rely on non-invasive samples, making it challenging to generate large amounts of high-quality genetic data for many elusive and at-risk species. We developed and optimized a Genotyping-in-Thousands by sequencing (GT-seq) panel using non-invasive samples to inform the management of invasive Sitka black-tailed deer (Odocoileus hemionus sitkensis) in Haida Gwaii (Canada). We validated our panel using paired high-quality tissue and non-invasive fecal and hair samples to simultaneously distinguish individuals, identify sex and reconstruct kinship among deer sampled across the archipelago, then provided a proof-of-concept application using field-collected feces on SGang Gwaay, an island of high ecological and cultural value. Genotyping success across 244 loci was high (90.3%) and comparable to that of high-quality tissue samples genotyped using restriction-site associated DNA sequencing (92.4%), while genotyping discordance between paired high-quality tissue and non-invasive samples was low (0.50%). The panel will be used to inform future invasive species operations (culls or eradications) in Haida Gwaii by providing individual and population information to inform management. More broadly, our GT-seq workflow that includes quality control analyses for targeted SNP selection and a modified protocol may be of wider utility for other studies and systems where non-invasive genetic sampling is employed.

Genotyping-in-Thousands by sequencing (GT-seq) following Campbell et al. (2015) Molecular Ecology Resources as modified in Schmidt et al. (2020) Molecular Ecology Resources and the associated work.

gtseq244_nis_genepop.txt: genepop file of genotypic data at 244 SNPs collected with GT-seq for non-invasive (fecal and hair) samples.

gtseq244_tissue_genepop.txt: genepop file of genotypic data at 244 SNPs collected with GT-seq for paired tissue samples.

radseq244_final.vcf: vcf file of genotypic data at 244 SNPs collected with RAD-seq for tissue samples.

metadata.csv: text file containing individual metadata for all samples used including sample identifiers, location, year, and sample type.