A new Genotyping-in-thousands by sequencing (GT-seq) assay for polar bears (Ursus maritimus): development, validation, and applications

Abstract

Traditional wildlife monitoring approaches are often time-consuming and expensive, and fail to partner with and benefit Indigenous communities. This is particularly relevant for polar bears (Ursus maritimus), which lack contemporary range-wide data on population dynamics, are facing large-scale habitat declines due to climate change, and are of socioeconomic and cultural importance to northern communities. Genetic monitoring using non-invasive samples (e.g. scat) can provide a complement or alternative to traditional methods, but requires novel genetic techniques that are optimized for degraded DNA. Thus, my second data chapter focused on developing, optimizing, and validating a Genotyping-in-Thousands by sequencing (GT-seq) panel of 324 single nucleotide polymorphisms for degraded polar bear DNA. My work demonstrated successful genotyping (>50% loci) for a range of DNA sources, including 62.9% of non-invasively collected scat samples determined to contain polar bear DNA, and that GT-seq data can be reliably used to discern individuals, identify sex, assess relatedness, and resolve population structure in Canadian polar bears. To further expand our understanding of polar bear population dynamics and explore the power of GT-seq, I used this new GT-seq assay in my third data chapter to test for male-biased dispersal in four Canadian polar bear subpopulations and whether this increases with population density. My genetic clustering results indicated some fine-scale genetic structure in females from low-density areas, consistent with male-biased dispersal. In contrast, spatial autocorrelation analyses did not reveal spatial patterns consistent with male-biased dispersal, although were likely limited by poor sampling resolution and geographic scale of sampling. My work confirms that GT-seq provides comparable information and resolution to traditional methods of monitoring, but enables greater cost-efficiency and the use of degraded (e.g. non-invasive) samples. Importantly, I demonstrate the power of GT-seq for sex-biased dispersal evaluation and provide the first of such applications. Overall, I conclude that GT-seq in tandem with community-based monitoring programs may improve temporal monitoring of polar bear populations and Arctic ecosystems, actively provide socioeconomic benefits to northern communities, and serve as a model for inclusive, non-invasive wildlife monitoring worldwide.