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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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Aggravating complexes are more likely to contain essential genes.The percentage of complexes that contain at least one essential gene is shown, for various groups of complexes defined within small-scale complexes in MIPS (left three bars) or complexes identified in this study (right three bars). In MIPS, approximately 80% of “aggravating” complexes (see text) contain an essential gene, versus 20% for “alleviating” complexes. The trend is similar for the complexes reported in this study, with 55% versus 22% of aggravating versus alleviating complexes containing an essential gene. The list of all essential genes was taken from (http://www-sequence.stanford.edu/group/yeast_deletion_project/deletions3.html).
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pcbi-1000065-g004: Aggravating complexes are more likely to contain essential genes.The percentage of complexes that contain at least one essential gene is shown, for various groups of complexes defined within small-scale complexes in MIPS (left three bars) or complexes identified in this study (right three bars). In MIPS, approximately 80% of “aggravating” complexes (see text) contain an essential gene, versus 20% for “alleviating” complexes. The trend is similar for the complexes reported in this study, with 55% versus 22% of aggravating versus alleviating complexes containing an essential gene. The list of all essential genes was taken from (http://www-sequence.stanford.edu/group/yeast_deletion_project/deletions3.html).

Mentions: To test the hypothesis that essential genes are more likely in aggravating modules, we analyzed both MIPS small-scale complexes and our learned modules for the presence of essential genes (Figure 4). We found that 80% of aggravating MIPS complexes contained an essential gene, compared to only 20% of alleviating MIPS complexes (a four-fold increase). Similarly, of the aggravating modules determined by our approach, 55% contained an essential gene compared to only 21% of alleviating modules (a 2.6-fold increase). These results are not correlated with module size, as the median size of aggravating learned modules is less than the median size of alleviating learned modules. They suggest that, regardless of the technique for identifying complexes, those containing essential genes tend to be composed of primarily aggravating genetic interactions. Mechanistically, this might occur through a variety of means, including proteins with separate but functionally redundant roles in maintaining complex integrity, or subunit substitution by paralogous proteins.


Functional maps of protein complexes from quantitative genetic interaction data.

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

Aggravating complexes are more likely to contain essential genes.The percentage of complexes that contain at least one essential gene is shown, for various groups of complexes defined within small-scale complexes in MIPS (left three bars) or complexes identified in this study (right three bars). In MIPS, approximately 80% of “aggravating” complexes (see text) contain an essential gene, versus 20% for “alleviating” complexes. The trend is similar for the complexes reported in this study, with 55% versus 22% of aggravating versus alleviating complexes containing an essential gene. The list of all essential genes was taken from (http://www-sequence.stanford.edu/group/yeast_deletion_project/deletions3.html).
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1000065-g004: Aggravating complexes are more likely to contain essential genes.The percentage of complexes that contain at least one essential gene is shown, for various groups of complexes defined within small-scale complexes in MIPS (left three bars) or complexes identified in this study (right three bars). In MIPS, approximately 80% of “aggravating” complexes (see text) contain an essential gene, versus 20% for “alleviating” complexes. The trend is similar for the complexes reported in this study, with 55% versus 22% of aggravating versus alleviating complexes containing an essential gene. The list of all essential genes was taken from (http://www-sequence.stanford.edu/group/yeast_deletion_project/deletions3.html).
Mentions: To test the hypothesis that essential genes are more likely in aggravating modules, we analyzed both MIPS small-scale complexes and our learned modules for the presence of essential genes (Figure 4). We found that 80% of aggravating MIPS complexes contained an essential gene, compared to only 20% of alleviating MIPS complexes (a four-fold increase). Similarly, of the aggravating modules determined by our approach, 55% contained an essential gene compared to only 21% of alleviating modules (a 2.6-fold increase). These results are not correlated with module size, as the median size of aggravating learned modules is less than the median size of alleviating learned modules. They suggest that, regardless of the technique for identifying complexes, those containing essential genes tend to be composed of primarily aggravating genetic interactions. Mechanistically, this might occur through a variety of means, including proteins with separate but functionally redundant roles in maintaining complex integrity, or subunit substitution by paralogous proteins.

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