Hohenlohe Lab

University of Idaho
Nerita versicolor


Home


Lab members


Research


Publications


Courses


Software


Contact


Research in the Hohenlohe Lab addresses basic questions in evolutionary genetics and genomics from both theoretical and empirical perspectives, and also applies genomic tools to conservation of threatened species.

RADseq

Restriction-site Associated DNA sequencing (RADseq) is a powerful tool for using next-generation sequencing to scan across the genomes of scores to hundreds of individuals from natural populations.  The lab is involved both in using this technique to generate data, and in developing statistical and analytical tools for RADseq data.  Members of the lab are applying RADseq in collaborative projects involving threespine stickleback, cutthroat trout, disease-vector mosquitoes, wolves, Channel Island foxes, oak-wilt fungi, anoles, and cane toads.  The goals of these projects range from determining basic demographic features, like population size and phylogeography, to estimating patterns of genetic diversity, detecting selection and mapping behavioral and morphological traits.

F_ST plot

Experimental population genomics

The explosion of population genomic data from non-model organisms, made possible by techniques like RADseq, has outstripped our understanding of genomic evolution and our ability to make sense of the data.  To bridge this gap, we are combining experimental evolution in yeast with next-generation sequencing.  Here we can control population sizes, migration rates, strengths of selection, recombination rates, and amount and structure of standing genetic variation in replicated experiments, and observe the results of evolution at the genomic sequence level.  The goal is to improve our powers of inference about natural populations from population genomic data.

yeast plate

Conservation Genomics

Evolutionary genomic approaches have powerful applications to conservation of species and ecosystems.  We are collaborating with a number of researchers to improve techniques for developing large sets of genetic markers, assess phylogeographic structure, detect hybridization and introgression, and estimate patterns of genetic variation in natural populations. 

In addition, we are collaborating on a genomic study of the evolution and epidemiology of Tasmanian devil facial tumor disease, a unique transmissible cancer, that poses a serious threat of extinction for this iconic species.  Our goal is to use RADseq and other genomic techniques to identify genetic variation in devil populations associated with disease progression, so that devil populations could potentially be managed using genomic techniques to reduce spread of the disease.

Thamnophis elegans

Evolutionary theory

Members of the lab are involved in several projects developing novel theory, analytical tools, or simulation approaches to understand evolutionary processes.  For example, we are studying the relationship between genetic regulatory networks and the structure of variation in complex multivariate phenotypes (i.e. the M and G matrices of quantitative genetics).  The long-term goal of this work is to link models of network evolution to specific regulatory networks in yeast, where we can empirically test the model predictions.  Second, we have developed a novel method for estimating the dimensionality of evolution that is widely applicable to mate choice and reproductive isolation, local adaptation, host-parasite coevolution, and other scenarios.

Curvature of phenotypic space



Collaborators

Fred Allendorf, University of Montana

Chris Funk, Colorado State University

Rodrigo Hamede, University of Tasmania

Menna Jones, University of Tasmania

Gordon Luikart, University of Montana

Hamish McCallum, Griffith University

Elizabeth Murchison, Cambridge University

Andrew Storfer, Washington State University

Barry Williams, Michigan State University

Center for Evolution and Cancer, University of California San Francisco


For research support, thanks to:


NSF    BEACON Center for the Study of Evolution in Action  
 NIH   Idaho INBRE

IBEST


© 2011 Paul Hohenlohe
Document made with Nvu