Dr. Samuel Yeaman

My research program focuses on using evolutionary models to understand genomic data, and uses genomic data to understand the process of evolution. I am broadly interested in understanding how and why different kinds of adaptations evolve in response to similar evolutionary challenges. This fundamental research question has important implications to any process involving evolutionary change and understanding the genomic basis of this change. I often collaborate with researchers working on applied problems in medicine and agriculture.

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Natural environments are highly variable and biological constraints often prevent a single individual from performing best in all conditions. Specialization through genetic adaptation to the local environment provides one way to cope with a heterogeneous environment, and has been observed in a wide range of species, from lodgepole pine to threespine stickleback.

My research aims to understand how organisms adapt to both spatially and temporally heterogeneous environments and how this process shapes the genetic and genomic architecture of complex traits. I use a combination of population genetic theory and individual-based simulations to formulate hypotheses, and seek to test these hypotheses using comparative genomics and studies of genomic variation in natural populations. Understanding how evolution shapes the genomic basis of complex traits has important implications for medicine, personalized genomics, and predicting the response of natural populations to climate change.

Specific Research Projects:

• Genome rearrangements and the evolution of clustered architectures in threespine stickleback (through de novo assembly of outgroup species)
• Comparative genomics of clustered architectures in Eukaryotes
• Genomic signatures of adaptation: disentangling signatures of selection from background variation
• Comparative genomics of local adaptation to climate in lodgepole pine and interior spruce

I am very interested in a range of related problems, including:

• The mapping of genotype to phenotype and genetic modularity and redundancy
• Comparative genomics of adaptation and convergent vs. divergent responses to similar ecological challenges
• Visualization of complex patterns in high-dimensionality genomic data
• Maintenance of genetic variation within populations
• Cultural evolution and the maintenance of misinformation