A network biology approach to aging in yeast Export

@article{citeulike:4009344, abstract = {10.1073/pnas.0812551106 In this study, a reverse-engineering strategy was used to infer and analyze the structure and function of an aging and glucose repressed gene regulatory network in the budding yeast . The method uses transcriptional perturbations to model the functional interactions between genes as a system of first-order ordinary differential equations. The resulting network model correctly identified the known interactions of key regulators in a 10-gene network from the Snf1 signaling pathway, which is required for expression of glucose-repressed genes upon calorie restriction. The majority of interactions predicted by the network model were confirmed using promoter-reporter gene fusions in gene-deletion mutants and chromatin immunoprecipitation experiments, revealing a more complex network architecture than previously appreciated. The reverse-engineered network model also predicted an unexpected role for transcriptional regulation of the gene by hexose kinase enzyme/transcriptional repressor Hxk2, Mediator subunit Med8, and transcriptional repressor Mig1. These interactions were validated experimentally and used to design new experiments demonstrating Snf1 and its transcriptional regulators Hxk2 and Mig1 as modulators of chronological lifespan. This work demonstrates the value of using network inference methods to identify and characterize the regulators of complex phenotypes, such as aging.}, author = {Lorenz, David R. and Cantor, Charles R. and Collins, James J.}, citeulike-article-id = {4009344}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0812551106}, citeulike-linkout-1 = {http://www.pnas.org/content/106/4/1145.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/106/4/1145.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19164565}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19164565}, day = {27}, doi = {10.1073/pnas.0812551106}, journal = {Proceedings of the National Academy of Sciences}, keywords = {analysis, clip2, gene\_expression, network}, month = {January}, number = {4}, pages = {1145--1150}, posted-at = {2009-04-01 08:05:38}, priority = {2}, title = {A network biology approach to aging in yeast}, url = {http://dx.doi.org/10.1073/pnas.0812551106}, volume = {106}, year = {2009} }

TY - JOUR ID - citeulike:4009344 L3 - citeulike-article-id:4009344 N2 - 10.1073/pnas.0812551106 In this study, a reverse-engineering strategy was used to infer and analyze the structure and function of an aging and glucose repressed gene regulatory network in the budding yeast . The method uses transcriptional perturbations to model the functional interactions between genes as a system of first-order ordinary differential equations. The resulting network model correctly identified the known interactions of key regulators in a 10-gene network from the Snf1 signaling pathway, which is required for expression of glucose-repressed genes upon calorie restriction. The majority of interactions predicted by the network model were confirmed using promoter-reporter gene fusions in gene-deletion mutants and chromatin immunoprecipitation experiments, revealing a more complex network architecture than previously appreciated. The reverse-engineered network model also predicted an unexpected role for transcriptional regulation of the gene by hexose kinase enzyme/transcriptional repressor Hxk2, Mediator subunit Med8, and transcriptional repressor Mig1. These interactions were validated experimentally and used to design new experiments demonstrating Snf1 and its transcriptional regulators Hxk2 and Mig1 as modulators of chronological lifespan. This work demonstrates the value of using network inference methods to identify and characterize the regulators of complex phenotypes, such as aging. IS - 4 JF - Proceedings of the National Academy of Sciences EP - 1150 TI - A network biology approach to aging in yeast VL - 106 SP - 1145 KW - analysis KW - clip2 KW - gene_expression KW - network AU - Lorenz, David AU - Cantor, Charles AU - Collins, James PY - 2009/01/27/ UR - http://dx.doi.org/10.1073/pnas.0812551106 ER -