[en] Despite an increasing number of interactomic datasets already available for model organisms and humans, many aspects remain contradictory, debatable or unclear due to the lack of complete high-quality networks. It has, for instance, been proposed that macromolecule connectivity in interactome maps reflects functional importance, functional relatedness, pleiotropy, implication in diseases, and other important biological characteristics. The most notorious example of such relationships concerns so-called essential genes believed to correspond to highly connected hubs that are critical to network integrity. Such claims have led to debate in the literature because connectivity could also be explained by bias and uneven coverage of the interactome space.
To provide fresh insight into these questions, we produced a new, systematic interactome map for S. cerevisiae, organism for which a plethora of systematic interactomic and functional data is available. This alternative view of the interactome network was generated by modifying our screening pipeline based on our empirically-controlled framework. Using a new high-quality ORFeome collection and a new assay version, we systematically performed three replicate yeast-two hybrid screens. This produced a map of 1,200 protein-protein interactions, which, while of similar size as previously published interactome
maps, covers the entire proteome without bias. These interactions were subsequently successfully validated using an orthogonal protein complementation assay based on a split Gaussia princeps luciferase. The latest analyses of this new map and progress towards generating a first Yeast Reference Interactome map will be presented.
Research Center/Unit :
Center for Cancer System Biology
Disciplines :
Genetics & genetic processes
Author, co-author :
Desbuleux, Alice ; Université de Liège - ULiège > Form. doct. sc. (bioch., biol. mol. cel., bioinf. - paysage)
Language :
English
Title :
Towards a yeast reference interactome
Publication date :
March 2015
Event name :
Cold Spring Harbor Laboratory Meeting : Systems biology : networks