Thursday, July 29, 2010

James Cai is a new Assistant Professor at Texas A&M!

We are very happy to announce that James Cai, a postdoctoral fellow in the lab, has accepted an offer for a tenure-track Assistant Professor position at Texas A&M University, Department of Veterinary Integrative Biosciences. He will be moving in September and is already starting to build a computational genomics laboratory there. (See the ad for a postdoctoral position in James's new lab.) His group will focus on computational research in population genomics and molecular evolution, applying population genetic theory to modern biological data and developing statistical tests and computational tools to investigate evolutionary processes shaping genome variability patterns within and between species. James joined our lab in 2006 after the completion of his Ph.D. at the University of Hong Kong. Viola Luo, James's wife pictured above, moved from Hong Kong to the Bay Area and joined James at Stanford in 2007, where she started her career in regulatory affairs of clinical trials at Stanford Cancer Center. In our lab, James focused on understanding how positive selection shapes patterns of polymorphism in the human genome and published a key paper that showed for the first time that positive selection is indeed pervasive in the human genome and does leave the expected signatures in the patterns of polymorphism. See the description of this research in Stanford Daily. James was also interested how the timing of the gene's entry into the genome (gene age) interacts with the gene's importance to the functioning of the organism and the way natural selection shapes its evolution. He published a series of papers on this topic as well. Finally, James is famous for creating a set of Matlab based toolkits for population genetics and molecular evolution. We are all extremely proud of James and wish him the best of luck in his brilliant young career!

Tuesday, July 13, 2010

Every mutation, at every site, at any given time

imageAdaptation in eukaryotes is often assumed to be limited by the waiting time for adaptive mutations. This is because effective population sizes are believed to be relatively small, typically on the order of only a few million reproducing individuals or less. It should therefore take hundreds or even thousands of generations until a particular new mutation emerges. However, several striking examples of rapid adaptation appear inconsistent with this view. In a paper just published by PloS Genetics, we (co-first authors Talia Karasov and Philipp Messer, and Dmitri) investigate a showpiece case for rapid adaptation, the evolution of pesticide resistance in the classical genetic organism Drosophila melanogaster. Our analysis reveals distinct population genetic signatures of this adaptation that can only be explained if the number of reproducing flies is, in fact, more than 100-fold larger than commonly believed. We argue that the old estimates, based on standing levels of neutral genetic variation, are misleading in the case of rapid adaptation because levels of standing variation are strongly affected by infrequent population crashes or adaptations taking place in the vicinity of neutral sites. We suggest that much of the time adaptation in Drosophila takes place in populations that are much larger that a billion meaning that every single-step mutation at every site exists in the population at every given time. This means that soft sweeps should be very common and that complex, multi-step adaptations should fix all at once without intermediate fixations of single-step mutations. We also argue that adaptation should be not mutation-limited in all species with population sizes that exceed a billion (roughly the inverse of mutation rate per site), which is the case for many insects and most marine invertebrates. Nick Barton wrote a great perspective article and the work was also highlighted in Nature Review Genetics and Faculty of 1000. It is currently in the top 10 most viewed articles on Faculty of 1000 and in PLoS Genetics.