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Systematic interpretation of genetic interactions using protein networks


Genetic interaction analysis,in which two mutations have a combined effect not exhibited by either mutation alone, is a powerful and widespread tool for establishing functional linkages between genes. In the yeast Saccharomyces cerevisiae, ongoing screens have generated >4,800 such genetic interaction data. We demonstrate that by combining these data with information on protein-protein, prote in-DNA or metabolic networks, it is possible to uncover physical mechanisms behind many of the observed genetic effects. Using a probabilistic model, we found that 1,922 genetic interactions are significantly associated with either between- or within-pathway explanations encoded in the physical networks, covering 40% of known genetic interactions. These models predict new functions for 343 proteins and suggest that between-pathway explanations are better than within-pathway explanations at interpreting genetic interactions identified in systematic screens. This study provides a road map for how genetic and physical interactions can be integrated to reveal pathway organization and function.

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Figure 1: Method overview.
Figure 2: Between-pathway explanations for genetic interactions.
Figure 3: Within-pathway explanations for genetic interactions.
Figure 4: Genetic interaction prediction schemes.
Figure 5: Success rate of genetic interaction prediction versus the stringency of prediction.

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We thank Jonathan Wang, Owen Ozier and Gopal Ramachandran for preliminary investigations and Vineet Bafna, Ben Raphael and Vikas Bansal for insightful commentary. Craig Mak, Silpa Suthram and Taylor Sittler provided helpful reviews of the text. Funding was provided by the National Institute of General Medical Sciences (GM070743-01) and the National Science Foundation (NSF 0425926).

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Correspondence to Trey Ideker.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Direct overlaps between genetic and physical interactions, while statistically significant, are limited in systematic data and probably biased. (PDF 192 kb)

Supplementary Fig. 2

Influence of beta on result set. (PDF 179 kb)

Supplementary Fig. 3

Estimated prediction accuracy for naive and pathway-based within-pathway genetic predictions. (PDF 188 kb)

Supplementary Table 1

Compounds excluded from the physical interaction network (not used to connect two proteins in a metabolic interaction). (PDF 19 kb)

Supplementary Table 2

The members of pathways identified in various searches. (PDF 68 kb)

Supplementary Table 3

The log-odds score associated with each network model identified in various searches. (PDF 62 kb)

Supplementary Table 4

Results from reduced searches. (PDF 28 kb)

Supplementary Table 5

Functional enrichment. (PDF 23 kb)

Supplementary Table 6

GO annotation predictions made with pathways obtained from various searches. (PDF 112 kb)

Supplementary Table 7

Basis of annotation predictions. (PDF 21 kb)

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Kelley, R., Ideker, T. Systematic interpretation of genetic interactions using protein networks. Nat Biotechnol 23, 561–566 (2005).

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