title: Detection of eQTL modules mediated by activity levels of transcription factors.
abstract: BACKGROUND
  Studies of gene expression quantitative trait loci (eQTL) in different organisms have shown the existence of eQTL hot spots: each being a small segment of DNA sequence that harbors the eQTL of a large number of genes. Two questions of great interest about eQTL hot spots arise: (1) which gene within the hot spot is responsible for the linkages, i.e. which gene is the quantitative trait gene (QTG)? (2) How does a QTG affect the expression levels of many genes linked to it? Answers to the first question can be offered by available biological evidence or by statistical methods. The second question is harder to address. One simple situation is that the QTG encodes a transcription factor (TF), which regulates the expression of genes linked to it. However, previous results have shown that TFs are not overrepresented in the eQTL hot spots. In this article, we consider the scenario that the propagation of genetic perturbation from a QTG to other linked genes is mediated by the TF activity. We develop a procedure to detect the eQTL modules (eQTL hot spots together with linked genes) that are compatible with this scenario.
  
  
  RESULTS
  We first detect 27 eQTL modules from a yeast eQTL data, and estimate TF activity profiles using the method of Yu and Li (2005). Then likelihood ratio tests (LRTs) are conducted to find 760 relationships supporting the scenario of TF activity mediation: (DNA polymorphism --> cis-linked gene --> TF activity --> downstream linked gene). They are organized into 4 eQTL modules: an amino acid synthesis module featuring a cis-linked gene LEU2 and the mediating TF Leu3; a pheromone response module featuring a cis-linked gene GPA1 and the mediating TF Ste12; an energy-source control module featuring two cis-linked genes, GSY2 and HAP1, and the mediating TF Hap1; a mitotic exit module featuring four cis-linked genes, AMN1, CSH1, DEM1 and TOS1, and the mediating TF complex Ace2/Swi5. Gene Ontology is utilized to reveal interesting functional groups of the downstream genes in each module.
  
  
  BACKGROUND
  Our methods are implemented in an R package: eqtl.TF, which includes source codes and relevant data. It can be freely downloaded at http://www.stat.ucla.edu/~sunwei/software.htm.
  
  
  BACKGROUND
  http://www.stat.ucla.edu/~sunwei/yeast_eQTL_TF/supplementary.pdf.
authors.affiliation: Department of Statistics, University of California at Los Angeles, Los Angeles, California, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Sun
authors.forename: Tianwei
authors.initials: T
authors.lastname: Yu
authors.forename: Ker-Chau
authors.initials: KC
authors.lastname: Li
mesh_terms: D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D008969:Molecular Sequence Data; D040641:Quantitative Trait Loci / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D014157:Transcription Factors / Q000235:genetics*; D015533:Transcriptional Activation / Q000235:genetics*
chemical_list: D014157:Transcription Factors