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Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

BACKGROUND: 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 ne...

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Autores principales: Casey, Fergal, Krogan, Nevan, Shields, Denis C, Cagney, Gerard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176491/
https://www.ncbi.nlm.nih.gov/pubmed/21859460
http://dx.doi.org/10.1186/1752-0509-5-133
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author Casey, Fergal
Krogan, Nevan
Shields, Denis C
Cagney, Gerard
author_facet Casey, Fergal
Krogan, Nevan
Shields, Denis C
Cagney, Gerard
author_sort Casey, Fergal
collection PubMed
description BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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.
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spelling pubmed-31764912011-09-21 Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs Casey, Fergal Krogan, Nevan Shields, Denis C Cagney, Gerard BMC Syst Biol Research Article BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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. BioMed Central 2011-08-22 /pmc/articles/PMC3176491/ /pubmed/21859460 http://dx.doi.org/10.1186/1752-0509-5-133 Text en Copyright ©2011 Casey et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Casey, Fergal
Krogan, Nevan
Shields, Denis C
Cagney, Gerard
Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs
title Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs
title_full Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs
title_fullStr Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs
title_full_unstemmed Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs
title_short Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs
title_sort distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176491/
https://www.ncbi.nlm.nih.gov/pubmed/21859460
http://dx.doi.org/10.1186/1752-0509-5-133
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