Abstract
BackgroundA key problem in systems biology is the determination of the regulatory mechanism corresponding to a phenotype. An empirical approach in this regard is to compare the expression profiles of cells under two conditions or tissues from two phenotypes and to unravel the underlying transcriptional regulation. We have proposed the method BASE to statistically infer the effective regulatory factors that are responsible for the gene expression differentiation with the help from the binding data between factors and genes. Usually the protein-DNA binding data are obtained by ChIP-seq experiments, which could be costly and are condition-specific.ResultsHere we report a definition of binding strength based on a probability model. Using this condition-free definition, the BASE method needs only the frequencies of cis-motifs in regulatory regions, thereby the inferences can be carried out in silico. The directional regulation can be inferred by considering down- and up-regulation separately. We showed the effectiveness of the approach by one case study. In the study of the effects of polyunsaturated fatty acids (PUFA), namely, docosahexaenoic (DHA) and eicosapentaenoic (EPA) diets on mouse small intestine cells, the inferences of regulations are consistent with those reported in the literature, including PPARα and NFκB, respectively corresponding to enhanced adipogenesis and reduced inflammation. Moreover, we discovered enhanced RORA regulation of circadian rhythm, and reduced ETS1 regulation of angiogenesis.ConclusionsWith the probabilistic definition of cis-trans binding affinity, the BASE method could obtain the significances of TF regulation changes corresponding to a gene expression differentiation profile between treatment and control samples. The landscape of the inferred cis-trans regulations is helpful for revealing the underlying molecular mechanisms. Particularly we reported a more comprehensive regulation induced by EPA&DHA diet.
Highlights
A key problem in systems biology is the determination of the regulatory mechanism corresponding to a phenotype
The modified Binding association with sorted expressions (BASE) reversely infers the effective regulators from gene expression profile
We demonstrate how the modified BASE works by one expression data set, which was from the study of the the effects of EPA&DHA diets in mouse small intestinal epithelial cells
Summary
A key problem in systems biology is the determination of the regulatory mechanism corresponding to a phenotype. The central dogma is the core model of molecular biology According to this dogma, in a cell DNA is transcribed into RNA, and the coding RNA is translated into various kinds of proteins with specific biological. When certain transcription factor(s) bind onto the specific short sequence motifs in the upstream promoter regions of a DNA segment, they can recruit polymerase. A “cis” motif could be represented by a joint multinomial distribution, each component of which corresponds to a DNA position in the short sequence. Such a probabilistic model can be transformed into a position weight matrices (PWM). The data of chromatin accessibility is condition-specific too
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