One of the key questions in developmental biology is how cells acquire their identities. This is an important question in human development where stem cells divide and differentiate into skin, muscle, fat etc. It is equally central to plant development where most organs and cells are formed from stem cell populations known as meristems. Our laboratory addresses this question using a combination of genetics, molecular biology and genomics to identify and characterize the genes that regulate formation of the root in the plant model system, Arabidopsis thaliana. The choice of the root as a model was based on the simplicity of its organization and its stereotyped developmental program.

Our research program over the last few years has made important discoveries that help elucidate how cells in the root divide and acquire their identities. These discoveries originated with screens for mutants with roots that had altered cell division potential. Characterization of these mutants revealed alterations in cell division and cell identity leading to dramatic changes in the radial pattern of the root. We have isolated the genes mutated in these lines and found that several of them encode transcriptional regulators. One of these called SHORT-ROOT is made in the vascular cylinder of the root and then moves to the adjacent tissue where it activates the expression of a second transcription factor, SCARECROW. The SHORT-ROOT/SCARECROW pathway has been shown to play a central role in radial patterning as well as in specifying the stem cell niche known as the quiescent center.

We are also using a systems biology approach to understanding cell specification. Our goal is to identify the transcriptional networks responsible for specifying all of the cells in the root. As a first step we developed a method that combines cell sorting with microarray analysis to generate the global expression pattern for every cell type in the root. From this dataset we have identified all transcription factors that are expressed in a tissue-specific pattern. We are currently localizing these transcription factors and determining their immediate targets. In collaboration with members of the Systems Biology Group at Duke we are developing computational approaches to model these transcriptional networks.