Population genetics of New Zealand fur seals (Arctocephalus forsteri): Genomic tools for research and management
|dc.contributor.author||Stovall, William Russell|
|dc.identifier.citation||Stovall, W. R. (2016). Population genetics of New Zealand fur seals (Arctocephalus forsteri): Genomic tools for research and management (Thesis, Master of Science). University of Otago. Retrieved from http://hdl.handle.net/10523/6762||en|
|dc.description.abstract||New Zealand fur seals (NZFS, Arctocephalus forsteri) are a relatively common feature on the rocky coasts of Southern Australia and New Zealand’s North, South, and subantarctic Islands. Several previous studies (e.g. Lento et al. 1997, Wynen 2001, Robertson and Gemmell 2005) have endeavoured to describe the population structure of NZFS, and have been unable to resolve distinct genetic differentiation among breeding colonies. However, it was unclear whether this could be attributed to an absence of structure in the species, or simply to a lack of discriminatory power provided by the molecular markers available at the time. In this study, we utilised a large and highly variable dataset of single nucleotide polymorphisms (SNPs) to thoroughly investigate population genetic trends, and to identify and describe new sources of genetic variation. We incorporated a total of 253 NZFS samples (167 from eight breeding colonies, 86 from fisheries bycatch) into our analyses. Adhering to the sequencing preparation protocol Genotyping-by-sequencing (GBS, Elshire et al. 2011), we digested DNA samples with the restriction enzyme Pst1. This effectively resulted in a reduction of genomic complexity, allowing for efficient identification of sites of variation at cut site loci. Post-sequencing bioinformatics processing (Stacks, Catchen et al. 2011) was implemented to produce a catalogue of 473,338 monomorphic and polymorphic loci for further analyses. We present a novel approach for the discovery and statistical validation of male-specific (Y-chromosome) loci in GBS datasets. Using a sex-specific locus threshold (SSLT) and a significant sex-assignment threshold (SSAT), we identified male-specific loci (monomorphic and polymorphic) within our dataset. We then screened for those loci within individuals of unknown sex in our bycatch sample group, and assigned sex to those individuals in silico. A significant bias toward males with the bycatch sample group was identified across all regions (68.6% – 80.2%, p < 0.001), which is consistent with previous observations on the species’ foraging behaviour. In addition, we developed a small panel of sex-specific PCR primers that can be used to ascertain the sex of unknown individuals in future studies. We employed a robust dataset of 22,192 neutral SNPs to investigate variation within and between NZFS subpopulations. While our conclusions were consistent with previous observations of relatively low population differentiation (0.65% – 0.85% variation explained by regional differences), we identified distinct similarities among West Coast colonies and Southern East Coast colonies. Northern East Coast colonies appear to be sites of genetic confluence, though further research will be required to verify these signatures. A weak, but significant (p = 0.01) isolation-by-distance pattern was identified among the eight breeding colonies studied, indicating a degree of previously overlooked, fine-scale population structure in this species. Using a new toolkit to examine genetic variation in NZFS, we demonstrate two major applications of SNP data (molecular sexing and population genetics), both of which can be applied in conservation and management practices. Next-generation markers discovered through GBS show great potential for future research on NZFS and other non-model species.|
|dc.publisher||University of Otago|
|dc.rights||All items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.|
|dc.title||Population genetics of New Zealand fur seals (Arctocephalus forsteri): Genomic tools for research and management|
|thesis.degree.name||Master of Science|
|thesis.degree.grantor||University of Otago|
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