title: Using evolutionary conserved modules in gene networks as a strategy to leverage high throughput gene expression queries.
abstract: BACKGROUND
  Large-scale gene expression studies have not yielded the expected insight into genetic networks that control complex processes. These anticipated discoveries have been limited not by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful way. Previous work suggests that using a pre-determined seed-network of gene relationships to query large-scale expression datasets is an effective way to generate candidate genes for further study and network expansion or enrichment. 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.
  
  
  RESULTS
  Our results demonstrate that a number of gene relationships regulating retinal cell differentiation in the fly are identifiable as pairwise correlations between genes from developing mouse retina. In addition, we demonstrate that our extracted seed-network of correlated mouse genes is an effective tool for querying datasets and provides a context to generate hypotheses. Our query identified 46 genes correlated with our extracted seed-network members. Approximately 54% of these candidates had been previously linked to the developing brain and 33% had been previously linked to the developing retina. Five of six candidate genes investigated further were validated by experiments examining spatial and temporal protein expression in the developing retina.
  
  
  CONCLUSIONS
  We present an effective strategy for pursuing a systems biology approach that utilizes an evolutionary comparative framework between two model organisms, fly and mouse. Future implementation of this strategy will be useful to determine the extent of network conservation, not just gene conservation, between species and will facilitate the use of prior biological knowledge to develop rational systems-based hypotheses.
authors.affiliation: Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, Iowa, United States of America. serb@iastate.edu
authors.forename: Jeanne M
authors.initials: JM
authors.lastname: Serb
authors.forename: Megan C
authors.initials: MC
authors.lastname: Orr
authors.forename: M Heather
authors.initials: MH
authors.lastname: West Greenlee
mesh_terms: D000465:Algorithms; D000818:Animals; D004331:Drosophila melanogaster / Q000235:genetics* / Q000378:metabolism; D019143:Evolution, Molecular; D015870:Gene Expression; D053263:Gene Regulatory Networks; D051379:Mice / Q000235:genetics* / Q000254:growth & development / Q000378:metabolism; D011506:Proteins / Q000235:genetics / Q000378:metabolism; D012160:Retina / Q000254:growth & development / Q000378:metabolism
chemical_list: D011506:Proteins
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