Abstract
Eukaryotic gene expression requires the coordinated activity of many macromolecular machines including transcription factors and RNA polymerase, the spliceosome, mRNA export factors, the nuclear pore, the ribosome and decay machineries. Yeast carrying mutations in genes encoding components of these machineries were examined using microarrays to measure changes in both pre-mRNA and mRNA levels. We used these measurements as a quantitative phenotype to ask how steps in the gene expression pathway are functionally connected. A multiclass support vector machine was trained to recognize the gene expression phenotypes caused by these mutations. In several cases, unexpected phenotype assignments by the computer revealed functional roles for specific factors at multiple steps in the gene expression pathway. The ability to resolve gene expression pathway phenotypes provides insight into how the major machineries of gene expression communicate with each other.
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Acknowledgements
We thank B. Noble for help with SVM analysis, S. Ruby, P. Silver, E. Hurt and L. Hicke for yeast strains, and A. Caroll and J. DeRisi for advice and assistance with microarrays. This work was primarily funded by grants to M.A. from the US National Institutes of Health (NIH) (GM040478), the Packard Foundation, and the W.M. Keck Foundation (to the University of California Santa Cruz RNA Center). The Howard Hughes Medical Institute Professors program supported Y.M.-G. Grants to G.H. from the NIH (GM060479), and the University of California Cancer Research Coordinating Committee supported this work as well, and T.-H.C. was supported by the NIH (GM48752) and the US National Science Foundation (MCB-9982726).
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Supplementary information
Supplementary Fig. 1
Comparison of microarray with QPCR. (PDF 83 kb)
Supplementary Fig. 2
Intron versus exon log ratios. (PDF 111 kb)
Supplementary Fig. 3
Ceg1 phenotype. (PDF 86 kb)
Supplementary Fig. 4
ROC plots for the SVM results. (PDF 63 kb)
Supplementary Table 1
Values for graph in Supplementary Figure 1. (PDF 47 kb)
Supplementary Table 2
Oligonucleotides used for QPCR analysis. (PDF 44 kb)
Supplementary Table 3
Intron accumulation index data for clustering. (TXT 193 kb)
Supplementary Table 4
Multiclass SVM scores. (XLS 33 kb)
Supplementary Table 5
Strain and experimental details. (XLS 32 kb)
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Burckin, T., Nagel, R., Mandel-Gutfreund, Y. et al. Exploring functional relationships between components of the gene expression machinery. Nat Struct Mol Biol 12, 175–182 (2005). https://doi.org/10.1038/nsmb891
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DOI: https://doi.org/10.1038/nsmb891
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