The functional landscape of mouse gene expression. Export

@article{citeulike:479056, abstract = {BACKGROUND: Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. RESULTS: We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. CONCLUSIONS: We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.}, address = {Banting and Best Department of Medical Research, University of Toronto, 1 King's College Circle, Toronto, ON M5S 1A8, Canada. wendy.zhang@utoronto.ca}, author = {Zhang, W. and Morris, Q. D. and Chang, R. and Shai, O. and Bakowski, M. A. and Mitsakakis, N. and Mohammad, N. and Robinson, M. D. and Zirngibl, R. and Somogyi, E. and Laurin, N. and Eftekharpour, E. and Sat, E. and Grigull, J. and Pan, Q. and Peng, W. T. and Krogan, N. and Greenblatt, J. and Fehlings, M. and van der Kooy, D. and Aubin, J. and Bruneau, B. G. and Rossant, J. and Blencowe, B. J. and Frey, B. J. and Hughes, T. R.}, citeulike-article-id = {479056}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/jbiol16}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/15588312}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=15588312}, doi = {10.1186/jbiol16}, issn = {1475-4924}, journal = {J Biol}, keywords = {expression, gene}, number = {5}, posted-at = {2007-09-21 03:50:35}, priority = {2}, title = {The functional landscape of mouse gene expression.}, url = {http://dx.doi.org/10.1186/jbiol16}, volume = {3}, year = {2004} }

TY - JOUR ID - citeulike:479056 L3 - citeulike-article-id:479056 N2 - BACKGROUND: Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. RESULTS: We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. CONCLUSIONS: We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics. IS - 5 JF - J Biol SN - 1475-4924 AD - Banting and Best Department of Medical Research, University of Toronto, 1 King's College Circle, Toronto, ON M5S 1A8, Canada. wendy.zhang@utoronto.ca TI - The functional landscape of mouse gene expression. VL - 3 KW - expression KW - gene AU - Zhang, W AU - Morris, QD AU - Chang, R AU - Shai, O AU - Bakowski, MA AU - Mitsakakis, N AU - Mohammad, N AU - Robinson, MD AU - Zirngibl, R AU - Somogyi, E AU - Laurin, N AU - Eftekharpour, E AU - Sat, E AU - Grigull, J AU - Pan, Q AU - Peng, WT AU - Krogan, N AU - Greenblatt, J AU - Fehlings, M AU - van der Kooy, D AU - Aubin, J AU - Bruneau, BG AU - Rossant, J AU - Blencowe, BJ AU - Frey, BJ AU - Hughes, TR PY - 2004/// UR - http://dx.doi.org/10.1186/jbiol16 ER -