Title
Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs.
Abstract
Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks.We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter.We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.
Year
DOI
Venue
2011
10.1186/1752-0509-5-133
BMC systems biology
Keywords
Field
DocType
bioinformatics,systems biology,algorithms
Protein–protein interaction,Network motif,Gene,Biology,Epistasis,Metabolic pathway,Systems biology,Motif (music),Interaction network,Bioinformatics
Journal
Volume
Issue
ISSN
5
1
1752-0509
Citations 
PageRank 
References 
0
0.34
4
Authors
4
Name
Order
Citations
PageRank
Fergal P. Casey116818.37
Nevan Krogan2404.49
Denis C. Shields315820.92
Gerard Cagney411619.58