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High-throughput identification of transcription start sites, conserved promoter motifs and predicted regulons

Nature Biotechnology volume 25, pages 584–592 (2007)Cite this article

Abstract

Using 62 probe-level datasets obtained with a custom-designed Caulobacter crescentus microarray chip, we identify transcriptional start sites of 769 genes, 53 of which are transcribed from multiple start sites. Transcriptional start sites are identified by analyzing probe signal cross-correlation matrices created from probe pairs tiled every 5 bp upstream of the genes. Signals from probes binding the same message are correlated. The contribution of each promoter for genes transcribed from multiple promoters is identified. Knowing the transcription start site enables targeted searching for regulatory-protein binding motifs in the promoter regions of genes with similar expression patterns. We identified 27 motifs, 17 of which share no similarity to the characterized motifs of other C. crescentus transcriptional regulators. Using these motifs, we predict coregulated genes. We verified novel promoter motifs that regulate stress-response genes, including those responding to uranium challenge, a stress-response sigma factor and a stress-response noncoding RNA.

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Figure 1: Transcriptional start-site identification.
Figure 2: Genes with multiple start sites.
Figure 3: Motifs identified from cell cycle dataset.
Figure 4: Motifs identified from heavy metal stress response data.
Figure 5: Comparison of motif searching with and without transcriptional start sites.
Figure 6: CauloHI1 Affymetrix microarray design.

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Acknowledgements

We thank Esteban Toro for comments on the manuscript and Michael Laub and Michael Mittman for assistance in designing the CauloHI1 chip. This work was supported by National Institute of Health (NIH) grants GM32506 (L.S.) and 5R24GM73011-2 (H.H.M., L.S.), Department of Energy Office of Science grant DE-FG02-01ER63219 (H.H.M., L.S.), NIH training grant T32 HG00044 (P.T.M.) and Damon Runyon Cancer Research Foundation Fellowship DRG-1880-05 (N.J.H.). P.H. was funded by the DOE Genomes to Life program under the auspices of the University of California, Lawrence Berkeley National Laboratory, Contract no. DE-AC02-05CH11231. H.L. was supported by a Stanford Graduate Fellowship.

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Authors and Affiliations

  1. Department of Physics, Stanford University, Varian Physics, 382 Via Pueblo Mall, Stanford, 94305, California, USA

    Patrick T McGrath

  2. Department of Developmental Biology, Stanford University, B300 Beckman Center, 279 Campus Drive, Stanford, 94305, California, USA

    Patrick T McGrath, Li Zhang, Antonio A Iniesta, Meng How Tan, Nathan J Hillson, Lucy Shapiro & Harley H McAdams

  3. Department of Computer Science, Stanford University, Gates Building, Stanford, 94305, California, USA

    Honglak Lee

  4. Department of Applied Physics, Stanford University, 316 Via Pueblo Mall, Stanford, California 94305, USA.,

    Li Zhang

  5. Lewis-Sigler Institute for Integrative Genomics, Princeton University, L206 Carl C. Icahn Laboratory, Princeton, 08544, New Jersey, USA

    Alison K Hottes

  6. Center for Environmental Biotechnology, Lawrence Berkeley National Laboratory, 1 Cyclotron Road Mail 70A3317, Berkeley, 94720, California, USA

    Ping Hu

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Correspondence to Harley H McAdams.

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Supplementary information

Supplementary Fig. 1

Correlation Tables for dnaN (CC0156) and clpX (CC1961) (PDF 239 kb)

Supplementary Fig. 2

Correlation tables for CC2510 (PDF 19 kb)

Supplementary Fig. 3

Cluster diagram of co-expressed genes in cell cycle microarray experiments (PDF 43 kb)

Supplementary Fig. 4

Cluster diagram of coexpressed genes from heavy metal response data (PDF 33 kb)

Supplementary Fig. 5

cc_2 promoter site (PDF 11 kb)

Supplementary Fig. 6

cc_3 is a FixK binding site (PDF 13 kb)

Supplementary Fig. 7

cc_7 is a SigU binding site (PDF 15 kb)

Supplementary Fig. 8

m_5 in the CC1891 promoter (PDF 14 kb)

Supplementary Fig. 9

Motif cc_5 is the RNAP sigma 54 binding motif (PDF 12 kb)

Supplementary Table 1

Motif Summary (PDF 13 kb)

Supplementary Methods (PDF 152 kb)

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McGrath, P., Lee, H., Zhang, L. et al. High-throughput identification of transcription start sites, conserved promoter motifs and predicted regulons. Nat Biotechnol 25, 584–592 (2007). https://doi.org/10.1038/nbt1294

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