Department of Ecology & Evolution
The University of Chicago
1103 E. 57th St., EBC 305A
Chicago, IL 60637
Phone: (773) 702-5948
Fax: (773) 702-9740
We are interested in the genetics of adaptation to seasonal light environments. Quantitative and population genetic approaches in Arabidopsis thaliana are used to dissect local and regional phenotypic variation. What genes and what alleles explain differential survival (germination/elongation) and reproduction (flowering time) in the field? Are these new variants or new combinations of existing polymorphisms?
We have revealed extensive genetic variation in world wide collections for seedling elongation (Nature Genetics 2001) and flowering time (Genetics 2005) under unique light environments and determined quantitative trait loci (QTL) responsible for this variation (Genetics 2002,2004). The next questions are what are the genes underlying these QTL and what are the functional allelic differences? How have the patterns of variation at these loci been shaped by natural selection? Can we find evidence for local adaptation and determine the ecological environmental differences driving selection?
A second focus is on the development of genomics methods to enable comprehensive studies of natural variation. Tools such as whole genome oligo-nucleotide tiling arrays are being used for very high resolution studies of polymorphism (Genome Research, 2003 Genetics 2004, PNAS 2005, Plant Phys 2005), mapping and haplotype analysis. These arrays which interrogate nearly every base of the A. thaliana genome, can reveal natural variation in gene expression and alternative splicing to identify candidate genes for QTL and their downstream responses. Natural variation in invivo DNA binding sites, via whole genome chromatin immuno-precipitation, can also reveal rapid evolution in cis regulation. We have also revealed natural variation in methylation by differential enzyme digestion followed by tiling array hybridization. Together these studies will reveal the functional genomic responses and highlight candidate genes underlying adaptive phenotypic variation.