Applying emerging genetic methods to wild model systems

• Main Author: Blåhed, Ida-Maria
• Format: Doctoral or Postdoctoral Thesis
• Language: Swedish; English
• Published: 2019
• Subjects: Genetics (medical genetics to be 30107 and agricultural genetics to be 40402); Ecology; Alces alces; Rangifer tarandus
• Online Access: https://pub.epsilon.slu.se/16173/; https://pub.epsilon.slu.se/16173/7/blahed_im_190524.pdf

Genetic material is an invaluable source of information for assessments of wild populations. By using information derived from genetic markers, individuals can be identified and tracked over time, enabling studies of a wide range of behavioral, ecological, and evolutionary processes. At the population level, estimations of the distribution of genetic variation increase our knowledge about a wide range of population processes and can reveal barriers to gene flow, information that is important to integrate in both conservation- and management plans. This thesis presents new methods for individual- and population based assessments of deer (Cervidae), with a focus on moose (Alces alces). Molecular markers, SNPs (single nucleotide polymorphisms), were developed using two different approaches. First, crossspecies amplification was explored between cattle and the five deer species occurring in Sweden; moose, roe deer (Capreolus capreolus), red deer (Cervus elaphus), fallow deer (Dama dama) and reindeer (Rangifer tarandus). Next, a reduced representation sequencing approach was chosen for de-novo SNP discovery in moose, with the main purpose of finding markers suitable for individual identification. As a result, a moose SNP panel including 86 autosomal, five sex-specific- and five species diagnostic SNPs was developed. Both approaches resulted in SNPs useful for both individual- and population level applications. SNP genotyping was subsequently applied for assessments of the Swedish moose population by conducting a non-invasive capture-mark-recapture study and to explore spatio-temporal genetic patterns in a population of seasonally migratory moose. These studies show that non-invasive SNP genotyping is useful for estimations of population size and sex-ratio, while also producing information about population structure and genetic variation. Furthermore, by combining genetic- and movement data over time, temporal spatial genetic structures were detected. These temporal structures elucidate different components of moose behavior, such as fidelity to seasonal ranges, which to some extent is maintained between generations. Consequently, the genetic information retrieved in this thesis clearly illustrate the potential of SNP genotyping for assessments of population- and behavioral processes in deer, including non-invasive monitoring.