Classical epistasis analysis can determine the order of function of genes in pathways using morphological, biochemical and other phenotypes. It requires knowledge of the pathway's phenotypic output and a variety of experimental expertise and so is unsuitable for genome-scale analysis. Here we used microarray profiles of mutants as phenotypes for epistasis analysis. Considering genes that regulate activity of protein kinase A in Dictyostelium, we identified known and unknown epistatic relationships and reconstructed a genetic network with microarray phenotypes alone. This work shows that microarray data can provide a uniform, quantitative tool for large-scale genetic network analysis.
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We thank V. Lundblad for discussions and for critical reading of the manuscript, R. Guerra for help with statistical analysis and for discussions and E. Holloway for assistance with data deposition. This work was supported by a grant from the National Institute of Child Health and Human Development. N.V.D. and E.O.B. are supported in part by training fellowships from the W.M. Keck Foundation of the Gulf Coast Consortia through the Keck Center for Computational and Structural Biology. J.D., P.J. and B.Z. are supported in part by the Slovene Ministry of Education, Science and Sports.
The authors declare no competing financial interests.
Transcriptional profiling to test whether pufA is epistatic to yakA. (PDF 2049 kb)
Transcriptional profiling to test whether pkaC is epistatic to pufA. (PDF 1847 kb)
Transcriptional profiling to test whether pkaR is epistatic to regA. (PDF 564 kb)
Pathway construction. RNA samples from developing acaA− and acaA− pkaCO/E cells were analyzed. (PDF 12 kb)
Additional genetic relationships between pkaC and pufA. (PDF 1105 kb)
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Van Driessche, N., Demsar, J., Booth, E. et al. Epistasis analysis with global transcriptional phenotypes. Nat Genet 37, 471–477 (2005) doi:10.1038/ng1545
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