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Epistasis analysis with global transcriptional phenotypes

Nature Genetics volume 37, pages 471–477 (2005)Cite this article

Abstract

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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Figure 1: Transcriptional profiling to test whether pufA is epistatic to yakA.
Figure 2: Transcriptional profiling to test whether pkaC is epistatic to pufA.
Figure 3: Transcriptional profiling to test whether pkaR is epistatic to regA.
Figure 4: Pathway construction.
Figure 5: Additional genetic relationships between pkaC and pufA.

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Acknowledgements

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.

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Authors and Affiliations

  1. Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, 77030, Texas, USA

    Nancy Van Driessche, Ezgi O Booth, Paul Hill, Adam Kuspa & Gad Shaulsky

  2. Graduate Program in Developmental Biology, Baylor College of Medicine, One Baylor Plaza, Houston, 77030, Texas, USA

    Nancy Van Driessche, Adam Kuspa & Gad Shaulsky

  3. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia

    Janez Demsar, Peter Juvan & Blaz Zupan

  4. Graduate Program in Structural Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, 77030, Texas, USA

    Ezgi O Booth & Gad Shaulsky

  5. Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, 77030, Texas, USA

    Adam Kuspa

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Correspondence to Gad Shaulsky.

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Supplementary information

Supplementary Fig. 1

Transcriptional profiling to test whether pufA is epistatic to yakA. (PDF 2049 kb)

Supplementary Fig. 2

Transcriptional profiling to test whether pkaC is epistatic to pufA. (PDF 1847 kb)

Supplementary Fig. 3

Transcriptional profiling to test whether pkaR is epistatic to regA. (PDF 564 kb)

Supplementary Fig. 4

Pathway construction. RNA samples from developing acaA− and acaA− pkaCO/E cells were analyzed. (PDF 12 kb)

Supplementary Fig. 5

Additional genetic relationships between pkaC and pufA. (PDF 1105 kb)

Supplementary Note (PDF 216 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). https://doi.org/10.1038/ng1545

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