Molecular population genetics and evolution (Drosophila and Arabidopsis)
I have had a longstanding interest in molecular population genetics, and have contributed over the years to the development of methods for analyzing DNA sequence polymorphism and evolutionary data, particularly with respect to detecting the action of natural selection. Although our work has historically focused on Drosophila, we have shifted our attention in recent years to Arabidopsis thaliana and its bacterial pathogens (in collaboration with Joy Bergelson's lab). Plant resistance to bacterial disease and bacterial pathenogenicity is an immensely powerful system for investigating both the ecological and evolutionary contexts of molecular adaptation, and holds the promise of uniting the two. In collaboration with Magnus Nordborg (http://walnut.usc.edu/) and Justin Borevitz, we have completed genome-wide assessments of genetic polymorphism, have assembled at 250K SNP chip, and have genotyped hundreds of isolines derived from natural populations. We have validated genome-wide association mapping in Arabidopsis to discover disease resistance polymorphism, and intend to do the same with common bacterial pathogens. We are also carrying out metagenomic surveys of the bacterial pathogen community infecting Arabidopsis.
Ever since our early studies of sequence variation and evolution in Drosophila, including noncoding regions, we have been interested in the contribution of gene regulation to adaptation. Drawing on extensive molecular analysis of the Drosophila even-skipped stripe two enhancer (eS2E) -- arguably the best characterized of any eukaryotic cis-regulatory sequence -- and a rich knowledge of the segmentation process in embryogenesis, Dr. Michael Ludwig (UC) and I have embarked on a research program to functionally dissect the evolution of this enhancer. Our approach has been to exploit transformation technology and the extensive molecular genetic arsenal available for the fly to quantitatively investigate evolved differences in eS2E performance. We are currently investigating features of the eS2E structural architecture that might contribute to functional robustness in enhancer performance, and the evolution of these features. We are also investigating developmental canalization of the segmentation process and the ability of the system to evolve in the face of this canalization. Finally, with the availability of a dozen Drosophila genome sequences, and genome-wide polymorphism data, we are functionally characterizing polymorphic and fixed differences in transcription factor binding sites with the goal of developing novel statistical methods to evaluate mechanisms of selection acting on binding site evolution.
Egg size variation
We are using several techniques to visualize the way that different selective pressures on egg size affect the spatial patterning of early segmentation genes in developing Drosophila embryos. We have used artificial selection to generate replicate large and small egg lines. Using in situ hybridization, we triple stained these embryos for mRNA of giant (gt), and even-skipped (eve), with Sytox green as a nuclear stain. We used some innovative software called PointCloudToolbox (http://bdtnp.lbl.gov/Fly-Net/bioimaging.jsp?w=software) to compare the eve stripe patterns between the divergently selected lines, as well as number of nuclei at the periphery for mitotic cycle 14 embryos. This manuscript is online early in the journal Evolution (DOI:10.1111/j.1558-5646.2010.01088.x). We have also generated replicate Drosophila lines (from the same base population as the selected lines) with evolved differences in egg size as a result of reducing the temperature in which they were raised. Analysis of these lines is ongoing. We derived inbred sublines from the artificially selected populations and extracted RNA from ovaries dissected from these females. We plan to use resequencing techniques to compare expression between the divergently selected lines and we are currently surveying these inbred sublines for eve stripe border position.
Drosophila Transcriptional Enhancers Evolution