Terminal cellular differentiation is often coupled with a halt in proliferation and permanent exit from the cell cycle. A loss of coordination between these processes can lead to aberrant tissue development and tumorigenesis. Despite its importance, little is known about how cell cycle exit and terminal differentiation are coordinated. One hypothesis, supported by studies in cell culture, mice and insects, suggests that the extracellular signals that trigger differentiation also control the expression of key cell cycle regulators. However, the identities of these regulators and the genetic regulatory networks linking extracellular differentiation signals with cell cycle genes remain largely unknown. To identify the gene regulatory networks linking terminal differentiation with cell cycle exit in vivo, this collaborative pilot project between Dr. Edgar at FHCRC and Dr. Song at NMSU proposes to combine a novel systems biology approach through discrete dynamic system models with high throughput temporal gene expression and reverse genetics studies in the successful model organism, Drosophila melanogaster. These models will allow one to predict genetic networks that connect extracellular signals with the cell cycle machinery. The models will be tested and explored by experiments in vivo. This project has three specific aims:
Aim 1. To advance the methodology and software to generate discrete dynamic system models from genomewide temporal gene expression. Microarray data from Drosophila wings will be used.
Aim 2. To test the modeling approach by genetic perturbations in silico and comparing the predicted changes in gene expression to the changes experimentally observed in vivo.
Aim 3. To use the modeling approach to predict new genetic regulatory networks converging on cell cycle control during differentiation, and experimentally explore and validate the predicted networks in vivo. Importantly, the aims are highly iterative and will lead to a close integration and cooperation between the in vivo experiments at FHCRC and in silico modeling at NMSU. These investigations will ultimately provide information about how developmental signals interface with the cell cycle to ensure cell cycle exit upon terminal differentiation. In addition, a powerful and widely applicable computational approach to elucidating gene regulatory networks will be developed.
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