Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors.
Patrick Kemmeren, Katrin Sameith, Loes A L van de Pasch, Joris J Benschop, Tineke L Lenstra, Thanasis Margaritis, Eoghan O'Duibhir, Eva Apweiler, Sake van Wageningen, Cheuk W Ko, Sebastiaan van Heesch, Mehdi M Kashani, Giannis Ampatziadis-Michailidis, Mariel O Brok, Nathalie A C H Brabers, Anthony J Miles, Diane Bouwmeester, Sander R van Hooff, Harm van Bakel, Erik Sluiters, Linda V Bakker, Berend Snel, Philip Lijnzaad, Dik van Leenen, Marian J A Groot Koerkamp, Frank C P Holstege
To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system.
YeastPhenome.org is running in beta version.
The data are available for download, but, as of today, we cannot guarantee lack of errors or code bugs introduced during processing.
This warning will be removed after all cross-checks and validations have been completed.
In the meantime, please, be careful when using the data.