TY - JOUR
T1 - Large-Scale Genetic Perturbations Reveal Regulatory Networks and an Abundance of Gene-Specific Repressors
AU - Kemmeren, Patrick
AU - Sameith, Katrin
AU - van de Pasch, Loes A. L.
AU - Benschop, Joris J.
AU - Lenstra, Tineke L.
AU - Margaritis, Thanasis
AU - O'Duibhir, Eoghan
AU - Apweiler, Eva
AU - van Wageningen, Sake
AU - Ko, Cheuk W.
AU - van Heesch, Sebastiaan
AU - Kashani, Mehdi M.
AU - Ampatziadis-Michailidis, Giannis
AU - Brok, Mariel O.
AU - Brabers, Nathalie A. C. H.
AU - Miles, Anthony J.
AU - Bouwmeester, Diane
AU - van Hooff, Sander R.
AU - van Bakel, Harm
AU - Sluiters, Erik
AU - Bakker, Linda V.
AU - Snel, Berend
AU - Lijnzaad, Philip
AU - van Leenen, Dik
AU - Koerkamp, Marian J. A. Groot
AU - Holstege, Frank C. P.
PY - 2014/4/24
Y1 - 2014/4/24
N2 - 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.
AB - 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.
KW - SACCHAROMYCES-CEREVISIAE
KW - TRANSCRIPTION FACTORS
KW - EXPRESSION PROFILES
KW - EUKARYOTIC GENOME
KW - YEAST
KW - MECHANISMS
KW - PATHWAYS
KW - INTERACTOME
KW - CIRCUITRY
KW - TARGETS
U2 - 10.1016/j.cell.2014.02.054
DO - 10.1016/j.cell.2014.02.054
M3 - Article
SN - 0092-8674
VL - 157
SP - 740
EP - 752
JO - Cell
JF - Cell
IS - 3
ER -