Beckman Institute Special Seminar

In this talk she will discuss a new Boolean computational model which shows that we are actually able to capture the system-level genomic information controlling dynamic gene expression during developmental process. Over the past decade, the Davidson lab has generated, based on extensive experimental evidence, a model for the gene regulatory network (GRN) which drives early development in sea urchin embryos. To test the regulatory properties of these network models, we have developed a Boolean computational tool which progressively computes gene expression in time and space based on regulatory interactions, initial inputs and embryonic geometry. Incorporating all regulatory genes and interactions contained in the sea urchin GRN models into a Boolean model resulted in the computation of gene expression patterns which, with a few exceptions, closely matched the gene expression patterns observed in the sea urchin embryo. Furthermore, perturbation of the Boolean model accurately predicted the outcome of experimental perturbation. The Boolean model thus demonstrates that GRN models are in principle sufficient to explain progressive regulatory gene expression during development and contributes to the formalization of regulatory processes. This approach will be applicable to a wide range of developmental processes and to synthetic and evolutionary studies of developmental processes at the genome level.