ArticleBMC genomics2006
Inferring direct regulatory targets from expression and genome location analyses: a comparison of transcription factor deletion and overexpression.
Article in BMC genomics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- When HSFs bring the heat-mapping the transcriptional circuitries of HSF-type regulators inmSphere · 2025Review
- Yeast response and tolerance to benzoic acid involves the Gcn4- and Stp1-regulated multidrug/multixenobiotic resistance transporter Tpo1.Applied microbiology and biotechnology · 2017Article
- Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae.Bulletin of mathematical biology · 2015Article
- Analysis of Candida albicans mutants defective in the Cdk8 module of mediator reveal links between metabolism and biofilm formation.PLoS genetics · 2014Article
- Amino acid homeostasis and chronological longevity in Saccharomyces cerevisiae.Sub-cellular biochemistry · 2012Review
- Uga3 and Uga35/Dal81 transcription factors regulate UGA4 transcription in response to gamma-aminobutyric acid and leucine.Eukaryotic cell · 2010Article
- Characterizing regulatory path motifs in integrated networks using perturbational data.Genome biology · 2010Article
- Autophagy and amino acid homeostasis are required for chronological longevity in Saccharomyces cerevisiae.Aging cell · 2009Article
- Identification of the Candida albicans Cap1p regulon.Eukaryotic cell · 2009Article
- Genomewide location analysis of Candida albicans Upc2p, a regulator of sterol metabolism and azole drug resistance.Eukaryotic cell · 2008Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundEffects on gene expression due to environmental or genetic changes can be easily measured using microarrays. However, indirect effects on expression can be substantial. The indirect effects of a perturbation need to be distinguished from the direct effects if we are to understand the structure and behavior of regulatory networks.
resultsThe most direct way to perturb a transcriptional network is to alter transcription factor activity. Here, for the first time, we compare expression changes and genomic binding in a simple regulon under conditions of both low and high transcription factor activity. Specifically, we assessed the effects on expression and binding due to deletion of the yeast LEU3 transcription factor gene and effects due to elevation of Leu3 activity. Leu3 activity was elevated through overexpression and the introduction of a mutation that renders the protein constitutively active. Genes that are bound and/or regulated by Leu3 under one or both conditions were characterized in terms of their functional annotations and their predicted potential to be bound by Leu3. We also assessed the evolutionary conservation of the predicted binding potential using a novel alignment-independent method. Both perturbations yield genes that are likely to be direct targets of Leu3, including most of the classically defined targets. Additional direct targets are identified by each of the methods. However, experimental and computational criteria suggest that most genes whose expression is affected by the Leu3 genotype are unlikely to be regulated by binding of the protein.
conclusionMost genes that are differentially expressed by Leu3 are not direct targets despite the exceptional simplicity of the regulon, and the unusually direct nature of the perturbations investigated. These conclusions are reached through computational analyses that support and extend chromatin immunoprecipitation data on the identities of direct targets. These results have implications for the interpretation of expression experiments, especially in cases for which chromatin immunoprecipitation data are unavailable, incomplete, or ambiguous.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.