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Functional maps of protein complexes from quantitative genetic interaction data.

Bandyopadhyay S, Kelley R, Krogan NJ, Ideker T - PLoS Comput. Biol. (2008)

Bottom Line: Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits.Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism.These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function.

View Article: PubMed Central - PubMed

Affiliation: Program in Bioinformatics, University of California San Diego, La Jolla, California, United States of America.

ABSTRACT
Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function.

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Related in: MedlinePlus

Global map of protein complexes involved in yeast chromosome biology.Each node represents a predicted multimeric protein complex, while each link represents a significantly alleviating or aggravating bundle of genetic interactions between complexes, indicative of an inter-complex functional relationship. Node colors indicate enrichment for alleviating or aggravating genetic interactions among members of the same complex. Node sizes are proportional to the number of proteins in the complex. When known, nodes are labeled with the common name of the complex. For complexes that are newly identified by our study and thus unnamed, the constituent proteins are listed. For clarity, the co-chaperone prefoldin complex (PFD1, PAC10, YKE2, GIM3, GIM4, GIM5, BUD27) and the 25 links associated with it have been removed.
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pcbi-1000065-g002: Global map of protein complexes involved in yeast chromosome biology.Each node represents a predicted multimeric protein complex, while each link represents a significantly alleviating or aggravating bundle of genetic interactions between complexes, indicative of an inter-complex functional relationship. Node colors indicate enrichment for alleviating or aggravating genetic interactions among members of the same complex. Node sizes are proportional to the number of proteins in the complex. When known, nodes are labeled with the common name of the complex. For complexes that are newly identified by our study and thus unnamed, the constituent proteins are listed. For clarity, the co-chaperone prefoldin complex (PFD1, PAC10, YKE2, GIM3, GIM4, GIM5, BUD27) and the 25 links associated with it have been removed.

Mentions: Applying this method, we identified 91 distinct modules with an average size of 4.1 proteins per module. Figure 2 gives an overview of a subset of the identified modules and inter-module links. Complete results are catalogued at http://www.cellcircuits.org/Bandyopadhyay2008/html/. Overall, these results suggest ten novel complexes not recorded in either the small-scale or high-throughput MIPS compendium, covering 23 proteins in total. The results also identify 84 new subunits of known complexes (Dataset S1). Through permutation testing, 19 versus 9 of the identified modules could be categorized as enriched for alleviating or aggravating genetic interactions, respectively. A total of 313 significant genetic relationships were identified between modules, 94 versus 219 of which were enriched for alleviating or aggravating interactions.


Functional maps of protein complexes from quantitative genetic interaction data.

Bandyopadhyay S, Kelley R, Krogan NJ, Ideker T - PLoS Comput. Biol. (2008)

Global map of protein complexes involved in yeast chromosome biology.Each node represents a predicted multimeric protein complex, while each link represents a significantly alleviating or aggravating bundle of genetic interactions between complexes, indicative of an inter-complex functional relationship. Node colors indicate enrichment for alleviating or aggravating genetic interactions among members of the same complex. Node sizes are proportional to the number of proteins in the complex. When known, nodes are labeled with the common name of the complex. For complexes that are newly identified by our study and thus unnamed, the constituent proteins are listed. For clarity, the co-chaperone prefoldin complex (PFD1, PAC10, YKE2, GIM3, GIM4, GIM5, BUD27) and the 25 links associated with it have been removed.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2289880&req=5

pcbi-1000065-g002: Global map of protein complexes involved in yeast chromosome biology.Each node represents a predicted multimeric protein complex, while each link represents a significantly alleviating or aggravating bundle of genetic interactions between complexes, indicative of an inter-complex functional relationship. Node colors indicate enrichment for alleviating or aggravating genetic interactions among members of the same complex. Node sizes are proportional to the number of proteins in the complex. When known, nodes are labeled with the common name of the complex. For complexes that are newly identified by our study and thus unnamed, the constituent proteins are listed. For clarity, the co-chaperone prefoldin complex (PFD1, PAC10, YKE2, GIM3, GIM4, GIM5, BUD27) and the 25 links associated with it have been removed.
Mentions: Applying this method, we identified 91 distinct modules with an average size of 4.1 proteins per module. Figure 2 gives an overview of a subset of the identified modules and inter-module links. Complete results are catalogued at http://www.cellcircuits.org/Bandyopadhyay2008/html/. Overall, these results suggest ten novel complexes not recorded in either the small-scale or high-throughput MIPS compendium, covering 23 proteins in total. The results also identify 84 new subunits of known complexes (Dataset S1). Through permutation testing, 19 versus 9 of the identified modules could be categorized as enriched for alleviating or aggravating genetic interactions, respectively. A total of 313 significant genetic relationships were identified between modules, 94 versus 219 of which were enriched for alleviating or aggravating interactions.

Bottom Line: Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits.Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism.These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function.

View Article: PubMed Central - PubMed

Affiliation: Program in Bioinformatics, University of California San Diego, La Jolla, California, United States of America.

ABSTRACT
Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function.

Show MeSH
Related in: MedlinePlus