My research uses a combination of population genetics and quantitative analyses of big data (genomic, physiological, and environmental) to understand effects of human- and natural-caused disturbances on ecological and evolutionary processes. I work on diverse taxonomic groups, including birds, large and small mammals, lizards, and insect pollinators (bees). Read more below and see my publications.

I combined population genetics and quantitative analyses of big data (genomic, physiological, and environmental) to understand organismal responses and evolutionary adaptations to natural- and human-caused disturbances. I used RNAseq data in deer mice to understand the importance of developmental stage in determining the phenotypic response to environmental stressors (Schweizer et al., 2023), and developed a DNA capture array to study genetic adaptation to high-altitude and spatial patterns of gene flow along elevational clines. These data are also being used in other studies to study selection to high-altitude, including from a developmental perspective (Velotta, Robertson, Schweizer, et al. 2020) and during pregnancy (Wilsterman, Moore, Schweizer, et al., In Press).

Yellowstone National Park Gibbon wolf pack standing on snow. Photo by Doug Smith.

For my PhD, I aimed to uncover and characterize genetic mechanisms of adaptive variation. Wild canids are an excellent system in which to study how wide-ranging organisms adapt to their environment since they are found throughout the world and have diverse morphological, physiological, and behavioral adaptations. Additionally, novel genomic resources have been developed for many canid species and the well-annotated dog genome is available.

Using SNP data and individual-level measurements of 12 environmental variables, I identified six ecotypes: West Forest, Boreal Forest, Arctic, High Arctic, British Columbia, and Atlantic Forest. I found consistent signals of selection on genes related to morphology, coat coloration, metabolism, vision and hearing. My findings showed that local adaptation can occur despite gene flow in a highly mobile species and can be detected through a genomic scan with a moderate number of SNPs. These patterns of local adaptation revealed by SNP genotyping likely reflect high fidelity to natal habitats of dispersing wolves, strong ecological divergence among habitats, and moderate levels of linkage in the wolf genome.

A white wolf from the interior of British Columbia. Photo by Marco Musiani.

As a continuation of the above study, I designed a targeted capture of 1040 genes, including all exons and flanking regions, as well as 5000 1 kilobase non-genic neutral regions and re-sequenced these regions in 107 wolves. Using tests that infer selection, I identified potentially functional variants related to local adaptation. By integrating these data with results from my first chapter, I demonstrated that combining data from genome wide SNP genotyping arrays with large-scale re-sequencing and environmental data provide a powerful approach to discern candidate functional variants in natural populations.

The above results were published in two first-author papers in early 2016 in Molecular Ecology.

 In many species, natural pigment variation is controlled by the Agouti- Mc1r pathway and many melanistic phenotypes are caused by a mutation in that pathway. Melanism in the gray wolf is caused by a mutation in the K locus. A previous study suggested that the melanistic K^B allele (a dominantly-inherited 3bp deletion) was introduced into the genome of North American wolves from the domestic dog via interbreeding, and then underwent positive selection.

Gray (agouti) and black (melanistic) wolves from the Druid Peak pack of Yellowstone National Park. Photo by Dan Stahler/NPS.

I designed a custom capture array to re-sequence five megabases surrounding the K locus core deletion in a larger sample of North American wolves from multiple areas to assess patterns of nucleotide and haplotype diversity, population-specific decay in linkage disequilibrium, and hierarchical patterns of genetic divergence among populations. We found that the North American wolf K^B haplotypes are monophyletic, suggesting that a single adaptive introgression from dogs to wolves most likely occurred in the Northwest Territories or Yukon. We also used a new analytical approach to date the origin of the K^B allele in Yukon wolves to between 1,598 and 7,248 years ago, suggesting that introgression with early Native American dogs was the source. Using population genetic simulations, we showed that the K locus is undergoing natural selection in four wolf populations, and that Yellowstone wolves are experiencing balancing selection that could be a result of selection for enhanced immunity in response to distemper. These results were published in Molecular Biology and Evolution. 

Through a collaboration with Dr. John Novembre and his group at the University of Chicago, we used data from a multi-generation Yellowstone pedigree to calculate wolf-specific mutation and recombination rates. These sequences provided a definitive estimate of mutation rate in wild wolves, a value that is the essential parameter in determining the evolutionary rate of genes and how selection alters the genome. This work was published in Molecular Biology and Evolution.