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Revealing modular organization in the yeast transcriptional network

Nature Genetics volume 31, pages 370–377 (2002)Cite this article

Abstract

Standard clustering methods can classify genes successfully when applied to relatively small data sets, but have limited use in the analysis of large-scale expression data, mainly owing to their assignment of a gene to a single cluster. Here we propose an alternative method for the global analysis of genome-wide expression data. Our approach assigns genes to context-dependent and potentially overlapping 'transcription modules', thus overcoming the main limitations of traditional clustering methods. We use our method to elucidate regulatory properties of cellular pathways and to characterize cis-regulatory elements. By applying our algorithm systematically to all of the available expression data on Saccharomyces cerevisiae, we identify a comprehensive set of overlapping transcriptional modules. Our results provide functional predictions for numerous genes, identify relations between modules and present a global view on the transcriptional network.

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Figure 1: The recurrence signature method.
Figure 2: The recurrence criteria.
Figure 3: Co-regulation of TCA cycle genes.
Figure 4: Functional consistency of transcription modules.
Figure 5: Experimental verification of the involvement of Sda1 and Ltv1 in rRNA processing.
Figure 6: Correlation between the regulatory contexts of different modules.
Figure 7: Comparison between the signature approach and clustering using in silico expression data (Methods).

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Acknowledgements

We thank D.R. Kellogg for the sda2-1 strain; U. Alon, M. Dolev, E. Domany, A. Eldar, O. Gileadi, Y. Kafri, B.-Z. Shilo and S. Shnider for discussions and comments on the manuscript; G. Jona and O. Gileadi for experimental help. This work was supported by the US National Institutes of Health, the Israeli Science Ministry and the Benoziyo center. S.B. is a Koshland fellow. N.B. is the incumbent of the Soretta and Henry Shapiro career development chair.

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  1. Departments of Molecular Genetics and Physics of Complex Systems, Weizmann Institute of Science, Rehovot, 76100, Israel

    Jan Ihmels, Gilgi Friedlander, Sven Bergmann, Ofer Sarig, Yaniv Ziv & Naama Barkai

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  1. Jan Ihmels
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Correspondence to Naama Barkai.

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Ihmels, J., Friedlander, G., Bergmann, S. et al. Revealing modular organization in the yeast transcriptional network. Nat Genet 31, 370–377 (2002). https://doi.org/10.1038/ng941

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