Transcriptional Regulatory Networks in Saccharomyces cerevisiae

Lee, Tong Ihn; Rinaldi, Nicola J.; Robert, François; Odom, Duncan T.; Bar-Joseph, Ziv; Gerber, Georg K.; Hannett, Nancy M.; Harbison, Christopher T.; Thompson, Craig M.; Simon, Itamar; Zeitlinger, Julia; Jennings, Ezra G.; Murray, Heather L.; Gordon, D. Benjamin; Ren, Bing; Wyrick, John J.; Tagne, Jean-Bosco; Volkert, Thomas L.; Fraenkel, Ernest; Gifford, David K.; Young, Richard A.

doi:10.1126/science.1075090

Cited by 2,956Gene Regulatory Network AnalysisFungal and yeast genetics researchBioinformatics and Genomic Networks

Transcriptional Regulatory Networks in Saccharomyces cerevisiae

Lee, Tong Ihn, Rinaldi, Nicola J., Robert, François, Odom, Duncan T., Bar-Joseph, Ziv, Gerber, Georg K., Hannett, Nancy M., Harbison, Christopher T. +13 more·2002·Science

DOI 10.1126/science.1075090

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Abstract

We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.

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TF motifs present in regulatory peaks correlated with RFX3 gene expression included STAT2 and IRF1 as well as FOSB and SPI1 (PU.1), which were differentially upregulated at gene expression level in IGPs.
“We determined TF motifs present in the regulatory peaks that correlated with RFX3 gene expression (i.e. linked peaks analysis) 63 and identified those of STAT2 and IRF1 (further supporting an IRF1-specific response) as well as FOSB and SPI1 (or PU.1), which were differentially upregulated at the gene expression level in IGPs”
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Authors: Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., Hannett, N. M., Harbison, C. T., Thompson, C. M., Simon, I., Zeitlinger, J., Jennings, E. G., Murray, H. L., Gordon, D. B., Ren, B., Wyrick, J. J., Tagne, J.-B., Volkert, T. L., Fraenkel, E., Gifford, D. K., & Young, R. A.
Affiliations: Whitehead Institute for Biomedical Research (US)
Whitehead Institute for Biomedical Research, Nine Cambridge Center, Cambridge, MA 02142, USA.
MIT Laboratory of Computer Science, 200 Technology Square, Cambridge, MA 02139, USA.
Massachusetts Institute of Technology (US)
Corresponding author: Lee, Tong Ihn
Rinaldi, Nicola J.
Thompson, Craig M.
Ren, Bing
Wyrick, John J.
Young, Richard A.
ORCID: Lee, Tong Ihn
Rinaldi, Nicola J.
Odom, Duncan T.
Gerber, Georg K.
Simon, Itamar
Zeitlinger, Julia
Gordon, D. Benjamin
Ren, Bing
Wyrick, John J.
Tagne, Jean-Bosco
Fraenkel, Ernest
Gifford, David K.
Young, Richard A.
Venue: Science
Publisher: American Association for the Advancement of Science (AAAS)
Published: 2002-10-25
Volume: 298
Issue: 5594
Pages: 799-804
ISSN: 0036-8075 (ISSN-L)
1095-9203
DOI: 10.1126/science.1075090
OpenAlex: W2126602684
Cited by: 2,956
References: 3
Citations by year: 2026: 28 · 2025: 33 · 2024: 33 · 2023: 35 · 2022: 48 · 2021: 53 · 2020: 45 · 2019: 62 · 2018: 55 · 2017: 54 · 2016: 62 · 2015: 73 · 2014: 94 · 2013: 113 · 2012: 138
FWCI: 79.79
Type: journal article
Language: en
Open access: closed
Locations: Science (publishedVersion)
PubMed (publishedVersion)
CaltechAUTHORS (California Institute of Technology) (submittedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords: transcriptional regulatory networks, Saccharomyces cerevisiae, transcription factors, network motifs, network assembly, eukaryotic gene regulation
MeSH terms: Algorithms, Cell Cycle, DNA, Fungal, Genes, Fungal, Models, Genetic, Promoter Regions, Genetic, Protein Binding, Saccharomyces cerevisiae, Transcription Factors, Transcription, Genetic, Gene Expression Regulation, Fungal, Genome, Fungal, Computational Biology, Gene Expression Profiling, Feedback, Physiological, Saccharomyces cerevisiae Proteins

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Transcriptional Regulatory Networks in Saccharomyces cerevisiae

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