April 6-7, 2017 | Lincoln, Nebraska
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2017 NRIC speakers
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Dr. Philip Benfey
Duke University
Underground signaling networks
9:15 - 9:55 am, Thursday 6 April 2017
ABSTRACT:
To understand the progression from stem cells to differentiated tissues we are exploiting the simplifying aspects of root development. We have developed new experimental, analytical and imaging methods to identify networks functioning within different cell types and developmental stages of the root. We are particularly interested in a subnetwork that regulates a key asymmetric cell division of a stem cell and the regulatory networks that control differentiation of the stem cell’s progeny. These networks are partially dependent on cell-to-cell signaling through movement of transcription factors. To quantify dynamic aspects of these networks, we are employing light-sheet microscopy to image accumulation of their different components. To find additional signaling molecules we performed ribosome profiling and identified putative peptide ligands. We have also uncovered a clock-like process responsible for the positioning of lateral roots along the root primary axis. Two sets of genes were identified that oscillate in opposite phases at the root tip and are involved in the production of prebranch sites, locations of future lateral roots. A derivative of the carotenoid biosynthesis pathway appears to act as a new mobile signal regulating root architecture.
BIO:
Philip Benfey is an HHMI Investigator and the Paul Kramer Professor of Biology at Duke University. His research focuses on plant developmental genetics and genomics. He is a fellow of the American Association for the Advancement of Science and a member of the US National Academy of Sciences. Dr. Benfey received his Ph.D. from Harvard University and a DEUG (Diplome d'Etudes Universitaire Generale) from the University of Paris. He co-founded a spin-off company, GrassRoots Biotechnology, which was sold to a large multinational. He now leads a new company, Hi Fidelity Genetics, which applies sophisticated data analytics to plant breeding.