Poster abstracts
Poster number 41 submitted by Wilberforce Ouma
Topological and statistical analyses of gene regulatory grids reveal unifying emergent properties
Wilberforce Zachary Ouma (Molecular Cellular and Developmental Biology Graduate Program), Mohammadmahdi R Yousefi (Department of Electrical and Computer Engineering, Ohio State University ), Erich Grotewold (Department of Molecular Genetics, Ohio State University )
Abstract:
Gene regulatory grids (GRGs) are static representations of gene regulatory networks (GRNs) encompassing all possible transcription factor (TF)-target gene interactions that provide a system-wide view of transcriptional gene regulation. To understand their architectural organization, transcriptional GRGs of Caenorhabditis elegans, Drosophila melanogaster, and Saccharomyces cerevisiae were constructed from experimental data and GRG emergent topological and statistical properties investigated. We examined the GRG degree connectivity by developing and implementing a formal statistical approach for fitting node degree to a power-law function. We observed that the out-degree, but neither the in- nor total-degree distribution, can be estimated by a power-law function. Unexpectedly, the exponent parameter of the power-law (alpha) was different for different organisms. In addition, the sampling of sub-grids of various sizes showed that exponents were generally invariant, thus providing us with a powerful tool to mathematically estimate the number of interactions that characterize the fully connected grids for these three organisms.
We hypothesized that a consequence of the scale-free property in cellular networks is faster signal propagation. To test this, we performed computational simulations to model the rate of signal propagation in GRGs and demonstrated that signals propagate faster in GRGs compared to their respective randomized grids. These observations support the hypothesis that network architecture and topology determines function, and that transcriptional GRGs have evolved to reduce the time taken for a signal to propagate throughout the grid.
Keywords: Gene regulatory grids , Network properties , Transcription