ArticlemSystems
Reconstruction of a Global Transcriptional Regulatory Network for Control of Lipid Metabolism in Yeast by Using Chromatin Immunoprecipitation with Lambda Exonuclease Digestion.
Article in mSystems. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 35 citations in OpenAlex.
- The importance of regulated resource reallocation during dynamic environmental shifts in yeast.The EMBO journal · 2026Article
- Yeast-secreted compounds with antifungal activity-screening, genetic parts, biosynthetic pathways, and regulation.FEMS yeast research · 2025Review
- Regulated resource reallocation is transcriptionally hard wired into the yeast stress response.bioRxiv : the preprint server for biology · 2024Article
- Two ZnApplied and environmental microbiology · 2024Article
- ChEC-seq2: an improved chromatin endogenous cleavage sequencing method and bioinformatic analysis pipeline for mapping in vivo protein-DNA interactions.NAR genomics and bioinformatics · 2024Article
- New biomarkers underlying acetic acid tolerance in the probiotic yeast Saccharomyces cerevisiae var. boulardii.Applied microbiology and biotechnology · 2024Article
- FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi.PLoS computational biology · 2023Article
- ChEC-seq2: an improved Chromatin Endogenous Cleavage sequencing method and bioinformatic analysis pipeline for mappingbioRxiv : the preprint server for biology · 2023Article
- Key enzymes involved in the utilization of fatty acids byFrontiers in microbiology · 2023Review
- Article
- Transcriptional regulation of ergosterol biosynthesis genes in response to iron deficiency.Environmental microbiology · 2022Article
- Predicting which genes will respond to transcription factor perturbations.G3 (Bethesda, Md.) · 2022Article
- Inferring TF activities and activity regulators from gene expression data with constraints from TF perturbation data.Bioinformatics (Oxford, England) · 2021Article
- Article
- Rational gRNA design based on transcription factor binding data.Synthetic biology (Oxford, England) · 2021Article
- Regulation of Ergosterol Biosynthesis inGenes · 2020Review
- Motifs enable communication efficiency and fault-tolerance in transcriptional networks.Scientific reports · 2020Article
- Dual threshold optimization and network inference reveal convergent evidence from TF binding locations and TF perturbation responses.Genome research · 2020Article
- DNA variants affecting the expression of numerous genes in trans have diverse mechanisms of action and evolutionary histories.PLoS genetics · 2019Article
- Predictive models of eukaryotic transcriptional regulation reveals changes in transcription factor roles and promoter usage between metabolic conditions.Nucleic acids research · 2019Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To build transcription regulatory networks, transcription factor binding must be analyzed in cells grown under different conditions because their responses and targets differ depending on environmental conditions. We performed whole-genome analysis of the DNA binding of five Saccharomyces cerevisiae transcription factors involved in lipid metabolism, Ino2, Ino4, Hap1, Oaf1, and Pip2, in response to four different environmental conditions in chemostat cultures, which allowed us to keep the specific growth rate constant. Chromatin immunoprecipitation with lambda exonuclease digestion (ChIP-exo) enabled the detection of binding events at a high resolution. We discovered a large number of unidentified targets and thus expanded functions for each transcription factor (e.g., glutamate biosynthesis as a target of Oaf1 and Pip2). Moreover, condition-dependent binding of transcription factors in response to cell metabolic state (e.g., differential binding of Ino2 between fermentative and respiratory metabolic conditions) was clearly suggested. Combining the new binding data with previously published data from transcription factor deletion studies revealed the high complexity of the transcriptional regulatory network for lipid metabolism in yeast, which involves the combinatorial and complementary regulation by multiple transcription factors. We anticipate that our work will provide insights into transcription factor binding dynamics that will prove useful for the understanding of transcription regulatory networks.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.