Year: 2015
Type: article
Abstract: Genetic interaction screens have been applied with great success in several organisms to study gene function and the genetic architecture of the cell. However, most studies have been performed under optimal growth conditions even though many functional interactions are known to occur under specific cellular conditions. In this study, we have performed a large-scale genetic interaction analysis in Saccharomyces cerevisiae involving approximately 49 × 1,200 double mutants in the presence of five different stress conditions, including osmotic, oxidative and cell wall-altering stresses. This resulted in the generation of a differential E-MAP (or dE-MAP) comprising over 250,000 measurements of conditional interactions. We found an extensive number of conditional genetic interactions that recapitulate known stress-specific functional associations. Furthermore, we have also uncovered previously unrecognized roles involving the phosphatase regulator Bud14, the histone methylation complex COMPASS and membrane trafficking complexes in modulating the cell wall integrity pathway. Finally, the osmotic stress differential genetic interactions showed enrichment for genes coding for proteins with conditional changes in phosphorylation but not for genes with conditional changes in gene expression. This suggests that conditional genetic interactions are a powerful tool to dissect the functional importance of the different response mechanisms of the cell.
Source: Molecular Systems Biology
Institutions: Universidad Complutense de Madrid, Instituto Ramón y Cajal de Investigación Sanitaria, University of California, San Francisco, Peking University, Center for Life Sciences, Princeton University, European Bioinformatics Institute, University of Aveiro, Howard Hughes Medical Institute, QB3, Gladstone Institutes
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $7,990
Awards: Genetic Analysis of the Nucleosome and RNA Polymerase II: A Systems Approach, G1868574430, G2528919290, G37385316, Comparative Analysis of Genetic Interaction Networks, Protein Recognition in Signal Transduction, G5951746209, Physical and Genetic Interaction Landscape of the Tyrosine Kinome, UCSF-Bay Area Center for AIDS Research, Integrating computation and genetics to quantify specificity in protein networks
OpenAlex ID: W2104872953