Equipped with his five senses, man explores the universe around him and calls the adventure Science. ~Edwin Powell Hubble, The Nature of Science, 1954
Welcome to Quantitative Biology at Stanford! Here you will find information pertaining to Stanford biology labs with diverse research interests whose common thread is a quantitative approach toward biological questions. From the single molecule level up to an entire ecosystem, our research methods are grounded in the physical and mathematical sciences to understand the world around us.
If you're interested in joining one of our labs or if you'd like further information, please don't hesitate to contact the lab directly.
Genome-wide scans for adaptive evolution of gene expression
Despite a great deal of work in this area, only a handful of cases of adaptive gene expression evolution have been discovered – each by a painstaking candidate gene approach. The Fraser lab recently developed the first method that systematically scans genome-wide data to identify genes whose expression levels are under positive selection. They are currently extending this method in a variety of ways, and applying it to a wide range of species, including yeast, insects, plants, mice, and humans. Fraser et al 2010a; Fraser et al 2010b.
Direct observation of kinesin head-to-microtubule binding
The motor protein kinesin transports cargos across cells by walking hand-over-hand along microtubule tracks and using ATP as fuel. The Block lab recently probed the mechanochemical cycle of kinesin using a novel single-molecule optical trapping assay (Figure 1A) in which a polystyrene bead was attached to one of the kinesin heads through a piece of DNA. The trapped bead was used to exert piconewton forces on the kinesin head and monitor its position to nanometer precision. As the kinesin molecule stepped along the microtubule, the labeled head adopted different orientations (Figure 1C, 1E) and was observed to remain unbound from the microtubule while its partner head waited for ATP to bind. Guydosh and Block, Nature 2009.
Every mutation, at every site, at any given time
Adaptation 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. The Petrov lab investigated a showpiece case for rapid adaptation, the evolution of pesticide resistance in the classical genetic organism Drosophila melanogaster. Their 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. They 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. They 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. Karasov, Messer, and Petrov, Plos Genetics 2010.