Meeting Abstract

66.5  Friday, Jan. 6  Applying Seed Networks to Genomic Data in an EvoDevo Context: A New Analysis Tool SERB, J.M.*; ZHANG, X.; WEST GREENLEE, M.H.; Iowa State Univ. serb@iastate.edu

Large-scale genomic expression studies have not yielded the expected insight into genetic networks that control complex processes of development. These anticipated discoveries have not been limited by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful way. We present a strategy that applies a user-determined seed-network of gene relationships under an evolutionary comparative framework. Our approach results in a list of candidate genes for further study and the expansion of the network of interest. Based on the evolutionary conservation of gene relationships, we test the hypothesis that a seed network derived from studies of retinal cell determination in the fly, Drosophila melanogaster, will be an effective way to identify novel candidate genes for their role in mouse retinal development. Our results demonstrate that the seed-network approach is an effective tool for querying datasets and provides a context to generate hypotheses. We identified 46 genes that correlated with the seed-network members. While the majority of these candidates have been previously linked to the developing brain (54%) and the developing retina (33%), our study is the first to link these candidates with specific members of the retinal determination pathway. Five of six candidate genes were validated by spatial and temporal protein expression experiments in the mouse retina. Future implementation of this strategy will be useful to determine the extent of network conservation, not just gene conservation, among species and will facilitate the use of prior biological knowledge to develop rational, systems-based hypotheses in EvoDevo.