Combining biological networks to predict genetic interactions
- Sharyl L. Wong*,
- Lan V. Zhang*,
- Amy H. Y. Tong†,
- Zhijian Li†,
- Debra S. Goldberg*,
- Oliver D. King*,
- Guillaume Lesage‡,
- Marc Vidal§,
- Brenda Andrews†,
- Howard Bussey‡,
- Charles Boone†, and
- Frederick P. Roth*,¶
- *Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, MA 02115; †Banting and Best Department of Medical Research and Department of Medical Genetics and Microbiology, University of Toronto, Toronto, ON, Canada M5G 1L6; ‡Department of Biology, McGill University, Montreal, QC, Canada H3A 1B1; and §Dana–Farber Cancer Institute and Department of Genetics, Harvard Medical School, Smith 858, 1 Jimmy Fund Way, Boston, MA 02115
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Communicated by Nancy Kleckner, Harvard University, Cambridge, MA, September 15, 2004 (received for review June 4, 2004)
Abstract
Genetic interactions define overlapping functions and compensatory pathways. In particular, synthetic sick or lethal (SSL) genetic interactions are important for understanding how an organism tolerates random mutation, i.e., genetic robustness. Comprehensive identification of SSL relationships remains far from complete in any organism, because mapping these networks is highly labor intensive. The ability to predict SSL interactions, however, could efficiently guide further SSL discovery. Toward this end, we predicted pairs of SSL genes in Saccharomyces cerevisiae by using probabilistic decision trees to integrate multiple types of data, including localization, mRNA expression, physical interaction, protein function, and characteristics of network topology. Experimental evidence demonstrated the reliability of this strategy, which, when extended to human SSL interactions, may prove valuable in discovering drug targets for cancer therapy and in identifying genes responsible for multigenic diseases.
Footnotes
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↵ ¶ To whom correspondence should be addressed. E-mail: fritz_roth{at}hms.harvard.edu.
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Author contributions: S.L.W., L.V.Z., O.D.K., V.M., and F.R. designed research; S.L.W. performed research; S.L.W., L.V.Z., A.H.Y.T., Z.L., D.S.G., G.L., B.A., H.B., C.B., and F.R. contributed new reagents or analytic tools; S.L.W. and F.R. analyzed data; S.L.W. wrote the paper.
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Abbreviations: SSL, synthetic sick or lethal; SGA, synthetic genetic array; MIPS, Munich Information Center for Protein Sequences.
- Copyright © 2004, The National Academy of Sciences
