A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans. Export

@article{Lee+Marcotte:NG08, abstract = {The fundamental aim of genetics is to understand how an organism's phenotype is determined by its genotype, and implicit in this is predicting how changes in DNA sequence alter phenotypes. A single network covering all the genes of an organism might guide such predictions down to the level of individual cells and tissues. To validate this approach, we computationally generated a network covering most C. elegans genes and tested its predictive capacity. Connectivity within this network predicts essentiality, identifying this relationship as an evolutionarily conserved biological principle. Critically, the network makes tissue-specific predictions-we accurately identify genes for most systematically assayed loss-of-function phenotypes, which span diverse cellular and developmental processes. Using the network, we identify 16 genes whose inactivation suppresses defects in the retinoblastoma tumor suppressor pathway, and we successfully predict that the dystrophin complex modulates EGF signaling. We conclude that an analogous network for human genes might be similarly predictive and thus facilitate identification of disease genes and rational therapeutic targets.}, author = {Lee, Insuk and Lehner, Ben and Crombie, Catriona and Wong, Wendy and Fraser, Andrew G. and Marcotte, Edward M.}, citeulike-article-id = {2311321}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/ng.2007.70}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/ng.2007.70}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/18223650}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=18223650}, citeulike-linkout-4 = {http://www.wormbase.org/db/misc/paper?name=WBPaper00031465}, day = {27}, doi = {10.1038/ng.2007.70}, issn = {1546-1718}, journal = {Nature genetics}, month = {February}, number = {2}, pages = {181--188}, posted-at = {2009-02-02 07:29:17}, priority = {2}, publisher = {Nature Publishing Group}, title = {A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans.}, url = {http://dx.doi.org/10.1038/ng.2007.70}, volume = {40}, year = {2008} }

TY - JOUR ID - Lee+Marcotte:NG08 L3 - citeulike-article-id:2311321 N2 - The fundamental aim of genetics is to understand how an organism's phenotype is determined by its genotype, and implicit in this is predicting how changes in DNA sequence alter phenotypes. A single network covering all the genes of an organism might guide such predictions down to the level of individual cells and tissues. To validate this approach, we computationally generated a network covering most C. elegans genes and tested its predictive capacity. Connectivity within this network predicts essentiality, identifying this relationship as an evolutionarily conserved biological principle. Critically, the network makes tissue-specific predictions-we accurately identify genes for most systematically assayed loss-of-function phenotypes, which span diverse cellular and developmental processes. Using the network, we identify 16 genes whose inactivation suppresses defects in the retinoblastoma tumor suppressor pathway, and we successfully predict that the dystrophin complex modulates EGF signaling. We conclude that an analogous network for human genes might be similarly predictive and thus facilitate identification of disease genes and rational therapeutic targets. IS - 2 JF - Nature genetics SN - 1546-1718 EP - 188 TI - A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans. PB - Nature Publishing Group VL - 40 SP - 181 AU - Lee, Insuk AU - Lehner, Ben AU - Crombie, Catriona AU - Wong, Wendy AU - Fraser, Andrew AU - Marcotte, Edward PY - 2008/02/27/ UR - http://dx.doi.org/10.1038/ng.2007.70 ER -