Fig 1.
Strategy for development of in silico screening system using a transcription factors regulatory network.
(a) Schemes to identify candidate genes and signaling pathways involved in differentiation or pharmacological effects using transcriptome data. In the upper traditional scheme, up- and down-regulated genes are identified but the core signaling pathways remain still a black box. In the lower scheme established in this study, relationships among each gene were predicted using only comprehensive input data. (b) The requirements to develop the ISNA theory. (c) To estimate all TFs binding to each gene promoter, Sp (reflecting activator binding) and Sq values (reflecting repressor binding) were calculated using score matrixes. The top 4 binding sites were listed in a gene promoter and selected a most competitive TF to each binding site as a repressor. (d) The image of selection for regions of TF-bindable promoters and gene bodies from ChIP-Atlas data and binding sites of activators and repressors. (e) Learning Kd values in ISNA using a gradient descent method.
Fig 2.
(a) The condition for learning Kd values in ISNA. The same HUVEC RNA-seq data was used as the input and reference expression data. One or 10 values were used as input Kd values for all TFs. The values of “a” as a weighting factor for effects of Sp and Sq values on binding TFs were set to e or 10. (b) The schematic image of learning Kd values. (c) The mean and median TF concentration values in all TFs and the Kd value of ETS1 in learning Kd values in 20 steps.
Fig 3.
Identification of core TFs in endothelial to mesenchymal transition in HUVEC using ISNA.
(a) The condition for learning Kd values in ISNA and the table of the number and name of core TFs in which the Kd values were changed after learning. (b) The digraph was derived from derivative factors of the gradient descent method to visualize the relationships among core TFs at each promoter region. When the TFs had a larger number of edges with the entering direction to the TFs, the TFs were situated at a more center position. Left bar and color of TFs: the number of edges with the forward direction from the TFs. Width of edges: reflecting the size of derivative factors. (c) Heatmap of log2 fold change of rate of Kd values (values after analysis/initial values) for the core TFs in the TRN regulating the gene expression from control HUVEC to reference situation. When SMAD2/3 or ETS1 was selected, the Kd values were fixed in the analysis. (d) List of rates of Kd value in the TRN regulating the gene expression from control HUVEC to EndMT. (e) The digraph was derived from the rate of derivative factors of the gradient descent method (EndMT/control values) in activated or repressed TFs in EndMT to visualize the relationships among core TFs at each promoter region. (f) The schematic image of TRN and core ELK1 to induce EndMT in HUVEC.
Fig 4.
Identification of core TFs for differentiation into mesodermal cells in human and mouse ESC using ISNA.
Lists of rates of Kd value in the TRN regulating the gene expression from hESC (a) and mESC (b) to mesodermal cells. (c) The digraph was derived from the rate of derivative factors of the gradient descent method (mesodermal cells/hESC values) in repressed TFs in EndMT to visualize the relationships among core TFs at each promoter region. When the TFs had a larger number of edges with the entering direction to the TFs, the TFs were situated at a more center position. Left bar and color of TFs: the number of edges with the forward direction from the TFs. Width of edges: reflecting the size of derivative factors. (d) The schematic image of TRN and core TFs related to pluripotency to induce mesodermal cells in HUVEC.
Fig 5.
Identification of new specific core TF in uterine epithelial cells using ISNA.
(a) Lists of Kd value in the TRN regulating the gene expression in human endometrial epithelial cells. (b) The ratio of gene expression between the uterus and vagina or the uterus and oviduct in 4-week-old mice was listed using data examined with microarray. (c) The immunofluorescence images for HMGA2 or DLX5 (green) in the uterus, vagina, ampulla of oviduct, and isthmus of oviduct of 3-month-old OVX mice with oil or E2 treatment. Blue: the nuclei. White arrows: the uterine glands. Dash line: basement membrane. n = 3, biologically independent. (d) The table of expression for HMGA2 and DLX5 in the nuclei of the epithelium of female reproductive tracts in adult mice with or without E2. (e) The percentage of EdU-positive cells in the epithelium of organ-cultured uterus with or without E2 and HMGA2 inhibitor, Hoechst 33258. * : p ≤ 0.05. n = 5. (f) The schematic image of TRN and specific TFs in adult uterine epithelial cells.