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Open Access Research article

Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions

Bo Li1, Weiguo Cao2, Jizhong Zhou3 and Feng Luo1*

Author Affiliations

1 School of Computing, Clemson University, Clemson, SC 29634, USA

2 Department of Genetics and Biochemistry, South Carolina Experiment Station, Clemson University, Clemson, SC 29634, USA

3 Institue for Environmental Genomics, University of Oklahoma, Norman, OK, USA

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BMC Systems Biology 2011, 5:73  doi:10.1186/1752-0509-5-73

Published: 17 May 2011

Abstract

Background

Synthetic lethal genetic interactions among proteins have been widely used to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions is still unclear.

Results

In this study, we demonstrated that yeast synthetic lethal genetic interactions can be explained by the genetic interactions between domains of those proteins. The domain genetic interactions rarely overlap with the domain physical interactions from iPfam database and provide a complementary view about domain relationships. Moreover, we found that domains in multidomain yeast proteins contribute to their genetic interactions differently. The domain genetic interactions help more precisely define the function related to the synthetic lethal genetic interactions, and then help understand how domains contribute to different functionalities of multidomain proteins. Using the probabilities of domain genetic interactions, we were able to predict novel yeast synthetic lethal genetic interactions. Furthermore, we had also identified novel compensatory pathways from the predicted synthetic lethal genetic interactions.

Conclusion

The identification of domain genetic interactions helps the understanding of originality of functional relationship in SLGIs at domain level. Our study significantly improved the understanding of yeast mulitdomain proteins, the synthetic lethal genetic interactions and the functional relationships between proteins and pathways.