Inferring direct regulatory targets from expression and genome location analyses: a comparison of transcription factor deletion and overexpression.
BACKGROUND
Effects 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.


RESULTS
The 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.


CONCLUSIONS
Most 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.
Tang
Lin
L
Biophysics and Biophysical Chemistry, Johns Hopkins School of Medicine, Baltimore, MD, USA. ltang@aviaradx.com
Liu
Xiao
X
Clarke
Neil D
ND
D015079:2-Isopropylmalate Synthase / Q000235:genetics / Q000378:metabolism; D001483:Base Sequence; D047369:Chromatin Immunoprecipitation / Q000379:methods; D019295:Computational Biology / Q000379:methods; D004268:DNA-Binding Proteins / Q000235:genetics / Q000378:metabolism*; D015966:Gene Expression Regulation, Fungal / Q000235:genetics*; D016681:Genome, Fungal / Q000235:genetics*; D009154:Mutation / Q000235:genetics; D011485:Protein Binding; D050436:Regulatory Elements, Transcriptional / Q000235:genetics; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics / Q000378:metabolism*; D015534:Trans-Activators / Q000235:genetics / Q000378:metabolism*; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
D004268:DNA-Binding Proteins; C063667:LEU3 protein, S cerevisiae; D029701:Saccharomyces cerevisiae Proteins; D015534:Trans-Activators; D014157:Transcription Factors; D015079:2-Isopropylmalate Synthase