ArticlePLoS biology2004
Similarities and differences in genome-wide expression data of six organisms.
Article in PLoS biology, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 152 papers, 2 of them syntheses that pooled it.
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Who cites it
152 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.PLoS computational biology · 2009Pooled it
- Meta-analysis and profiling of cardiac expression modules.Physiological genomics · 2008Pooled it
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92 more citing papers are in PubMed but not listed here.
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3 authors.
Funding
Abstract
Comparing genomic properties of different organisms is of fundamental importance in the study of biological and evolutionary principles. Although differences among organisms are often attributed to differential gene expression, genome-wide comparative analysis thus far has been based primarily on genomic sequence information. We present a comparative study of large datasets of expression profiles from six evolutionarily distant organisms: S. cerevisiae, C. elegans, E. coli, A. thaliana, D. melanogaster, and H. sapiens. We use genomic sequence information to connect these data and compare global and modular properties of the transcription programs. Linking genes whose expression profiles are similar, we find that for all organisms the connectivity distribution follows a power-law, highly connected genes tend to be essential and conserved, and the expression program is highly modular. We reveal the modular structure by decomposing each set of expression data into coexpressed modules. Functionally related sets of genes are frequently coexpressed in multiple organisms. Yet their relative importance to the transcription program and their regulatory relationships vary among organisms. Our results demonstrate the potential of combining sequence and expression data for improving functional gene annotation and expanding our understanding of how gene expression and diversity evolved.
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