Sample identification and pedigree reconstruction in Wolverine (Gulo gulo) using SNP genotyping of non-invasive samples

• Published in: Conservation Genetics Resources
• Main Authors: Ekblom, Robert, Aronsson, Malin, Elsner-Gearing, Franziska, Johansson, Malin, Fountain, Toby, Persson, Jens
• Format: Article in Journal/Newspaper
• Language: English
• Published: Uppsala universitet, Evolutionsbiologi 2021
• Subjects: Wolverine; Conservation; Single nucleotide polymorphisms; Population genetics; Relatedness; Pedigree; Genetics; Genetik; Gulo gulo
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-468631; https://doi.org/10.1007/s12686-021-01208-5

For conservation genetic studies using non-invasively collected samples, genome-wide data may be hard to acquire. Until now, such studies have instead mostly relied on analyses of traditional genetic markers such as microsatellites (SSRs). Recently, high throughput genotyping of single nucleotide polymorphisms (SNPs) has become available, expanding the use of genomic methods to include non-model species of conservation concern. We have developed a 96-marker SNP array for use in applied conservation monitoring of the Scandinavian wolverine (Gulo gulo) population. By genotyping more than a thousand non-invasively collected samples, we were able to obtain precise estimates of different types of genotyping errors and sample dropout rates. The SNP panel significantly outperforms the SSR markers (and DBY intron markers for sexing) both in terms of precision in genotyping, sex assignment and individual identification, as well as in the proportion of samples successfully genotyped. Furthermore, SNP genotyping offers a simplified laboratory and analysis pipeline with fewer samples needed to be repeatedly genotyped in order to obtain reliable consensus data. In addition, we utilised a unique opportunity to successfully demonstrate the application of SNP genotype data for reconstructing pedigrees in wild populations, by validating the method with samples from wild individuals with known relatedness. By offering a simplified workflow with improved performance, we anticipate this methodology will facilitate the use of non-invasive samples to improve genetic management of many different types of populations that have previously been challenging to survey.