Paul Hohenlohe
Paul Hohenlohe
Professor, Director, Bioinformatics and Computational Biology Graduate Program
LSS 256
果冻传媒麻豆社
875 Perimeter MS 3051
Moscow, Idaho 83844-3051
Our research focuses on the genomic architecture of evolving populations, developing sophisticated theory and analytical tools to harness the power of modern DNA sequencing technology. We address basic questions of evolutionary biology as well as applications to conservation and cancer biology.
I earned my B.A. in Biology from Williams College and moved to Alaska for a year, where I worked for The Wilderness Society and taught at the University of Alaska. Following my graduate work, conducted at Friday Harbor Laboratories of the University of Washington, I worked for several years as a conservation biologist and Regional Interagency Malacologist (slug and snail expert) for the federal Northwest Forest Plan. I conducted postdoctoral work in quantitative genetics and evolutionary genomics with Steve Arnold at Oregon State University and Bill Cresko at the University of Oregon.
- Genomic architecture of evolution
The genetic basis of complex, multivariate phenotypes depends on the distribution and interactions of many loci across the genome. Evolutionary forces shape this genomic architecture of phenotypic variation, and genomic architecture in turn constrains and bends the responses to natural selection and the trajectories of diversification. Modern sequencing technology now allows us to take an empirical genome-scale view of evolution in a myriad of species. - Our research addresses a range of related questions:
What is the genomic architecture of multivariate phenotypes in natural populations? How do interactions between population structure, gene flow, and divergent natural selection shape genomic architecture to facilitate rapid evolution? How many directions in phenotypic space are available to evolution? How wrong are the traditional quantitative genetic assumptions about the structure of continuous phenotypic variation, and what is a better model? - Cancer as an evolutionary process
The cell lineages in a developing tumor form a highly heterogeneous, evolving population, and prognosis and treatment options depend on this evolutionary process. We are seeking to combine evolutionary genomic theory and high-throughput sequencing to understand evolution in cancer at the genomic scale. - Conservation genomics
Evolutionary genomic approaches have powerful applications to conservation of species and ecosystems. We are collaborating with a number of researchers to develop large sets of genetic markers, assess phylogeographic structure, detect hybridization and introgression, and estimate patterns of genetic variation in natural populations.