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A Gene Coexpression Network for Global Discovery of Conserved Genetic Modules Joshua M. Stuart, Eran Segal, Daphne Koller, Stuart K. Kim Presented by Carri-Lyn Mead Investigating Gene Function ► Genome sequences for Human, Fly, Worm, Yeast ► DNA Microarrays Coregulated genes Functionally related genes Correlated expression patterns ► Cross species comparison of gene expression To measure evolutionarily conserved coexpression on a genome-wide scale, create a gene coexpression network Step 1: Find Meta-genes ► 6307 ► 6591 Total Meta-genes human ► 5180 worm ► 5802 fly ► 2434 yeast Step 2: Identify Meta-genes with correlated coexpression 3182 DNA Microarrays 1202 human 979 worm 155 fly 643 yeast Step 2: Identify Meta-genes with correlated coexpression Pearson correlation of gene pairs 2. Rank genes by Pearson correlation 3. Generate P –value of rank configuration 4. P < 0.05 cutoff indicates coexpression 5. Link coexpressed meta-genes 1. Gene Coexpression Network Result: ► Network of 3416 metagenes ► Connected by 22,163 expression interactions 3-D Terrain Map Component 5 ► Strongly enriched for meta-genes involved in cell cycle processes ► Contains 241 meta-genes 110 previously known to be involved in cell cycle 131 not previously known to be involved in cell cycle Testing Significance of Results 1. 2. 3. Rule out random pairs of meta-genes having significant coexpression interactions Ensure broad and diverse microarray data Test network stability with added noise Verify Results ► Experimentally functions validate predicted gene Select 5 meta-genes MEG1503 (snRNP protein involved in splicing) MEG342 (nucleoporin-interaction component) MEG4513 (novel protein, unknown function) MEG1192 (novel protein, unknown function) MEG1146 (novel protein, unknown function) Further Analyses ► Single Species Networks vs Multi-species Network Further Analyses ► Accuracy related to more data in Multispecies networks? Conservation of Genetic Modules Conclusions ► Gene coexpression networks can be used as a powerful tool for generating hypotheses about genes whose functions are unknown. ► Gene coexpression networks can be used to describe the evolution of genetic interactions. ► Multi-species networks perform better than single species networks overall. Discussion Topics ► What other model organisms would be useful to expand the multi-species network? ► Would the multi-species network be as useful for species that are more closely related? ► Gene orthology is based on protein sequence similarity. Does sequence conservation equate to conserved function? ► Are 12 clusters of meta-genes sufficient to hypothesize function for 3416 metagenes? ► How can gene function for genes without known orthologs be investigated?