Dependence of regulatory activity on positions relative to gene structure

<p><b>Copyright information:</b></p><p>Taken from "Identification of tissue-specific cis-regulatory modules based on interactions between transcription factors"</p><p>http://www.biomedcentral.com/1471-2105/8/437</p><p>BMC Bioinformatics 2007;8():437-437.</p><p>Published online 9 Nov 2007</p><p>PMCID:PMC2194798.</p><p></p> We calculated the probability for each position containing a CRM. The reference positions (origins in the x-axis) are transcription start sites, the respective start sites of introns and transcription end sites in three regions, respectively. The pink curve in the left panel is from random sequences which were generated with the same nucleic acids compositions and 1order transition probabilities, respectively, as those of the all promoter sequences in the human genome

Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

<div><p>Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.</p></div

Experimental validations for <i>CSNK2A1</i> and <i>MAPK9</i>.

<p>A human proteome microarray, comprised of 17,000 individually purified human proteins in full-length, was used to perform phosphorylation reactions with CKII (CSNK2A1) and JNK2 (MAPK9) in the presence or absence of their predicted scaffold proteins, ATF2 and PIN1. Phosphorylation signals were detected by exposure of the human proteome microarrays to X-ray film. Positive hits in red boxes were identified by visual inspection.</p

Characterization of scaffold proteins.

<p>(<i>A</i>) Enriched GO terms for scaffold proteins. (<i>B</i>) Enriched protein domains defined by Pfam in scaffold proteins. The GO and Pfam terms are sorted increasingly from left to right by p-value. (<i>C</i>) Distribution of protein lengths. (<i>D</i>) Distribution of evolutionary conservation.</p

Scaffold proteins are widespread in signaling networks.

<p>(<i>A</i>) PPI distance of KSR pairs and all human protein pairs. The PPI distance of a protein pair is defined as the shortest distance of the two proteins in PPI network. KSR pairs are significantly enriched in PPI distance = 2. In fact, 24.9% of KSR pairs have PPI distance of 2, while only 2.7% of all human protein pairs have the same PPI distance. (<i>B</i>) Network motifs in which one protein interacts with a series of proteins and these proteins form a cascade via KSRs. These network motifs are enriched, suggesting that scaffold proteins are widespread in signaling pathways.</p

Strategy to predict scaffold proteins.

<p>For each potential scaffold protein, we corrected the effect of interaction degree of the protein and the length of associated pathways. We utilized the randomized PPI to assess the significance of a predicted scaffold protein. The random PPI keep the same PPI degree for each protein by randomly selecting two PPI pairs and changing their partners.</p

Specificity of scaffold proteins and pathways.

<p>(<i>A</i>) Number of pathways related to scaffold proteins. 408 pathways (67.4%) are found to be associated with only one scaffold protein. (<i>B</i>) Number of scaffold proteins related to pathways. Specifically, 83 scaffold proteins are associated with only one pathways, while 28 scaffold proteins are related to >10 pathways.</p

In (A), the user could type a gene name and obtain a view of gene expressions and crm profiles

In (B), the user could type a TF name and obtain a view of co-regulations. In (C), the user could select a tissue name and obtain a view of gene expressions, crm detections and TF interactions.<p><b>Copyright information:</b></p><p>Taken from "TiGER: A database for tissue-specific gene expression and regulation"</p><p>http://www.biomedcentral.com/1471-2105/9/271</p><p>BMC Bioinformatics 2008;9():271-271.</p><p>Published online 9 Jun 2008</p><p>PMCID:PMC2438328.</p><p></p

Dynamics of Regulatory Networks in the Developing Mouse Retina

<div><p>Understanding gene regulation is crucial to dissect the molecular basis of human development and disease. Previous studies on transcription regulatory networks often focused on their static properties. Here we used retinal development as a model system to investigate the dynamics of regulatory networks that are comprised of transcription factors, microRNAs and other protein-coding genes. We found that the active sub-networks are topologically different at early and late stages of retinal development. At early stages, the active sub-networks tend to be highly connected, while at late stages, the active sub-networks are more organized in modular structures. Interestingly, network motif usage at early and late stages is also distinct. For example, network motifs containing reciprocal feedback regulatory relationships between two regulators are overrepresented in early developmental stages. Additionally, our analysis of regulatory network dynamics revealed a natural turning point at which the regulatory network undergoes drastic topological changes. Taken together, this work demonstrates that adding a dynamic dimension to network analysis can provide new insights into retinal development, and we suggest the same approach would likely be useful for the analysis of other developing tissues.</p> </div

Clinicopathological Characteristics and Prognosis for Survival after Enucleation of Uveal Melanoma in Chinese Patients: Long-term Follow-up

<p><i>Purpose</i>: To summarize the clinicopathological characteristics and prognosis of uveal melanoma (UM) after enucleation in Chinese patients.</p> <p><i>Methods</i>: Between 2003 and 2012, a series of 171 patients with UM received enucleation at the Eye & ENT Hospital of Fudan University in Shanghai. Patient clinical information was collected. Pathological examination and BAP1 staining of the enucleated eyes were conducted. Univariate and multivariate Cox proportional hazard regressions were conducted to determine the risk factors, and the survival rates were calculated and compared.</p> <p><i>Results</i>: The study included 83 (49%) men and 88 (51%) women, with a mean age of 48.6 years. The mean largest basal tumor diameter and mean largest tumor thickness were 11.8 and 8.6 mm, respectively. Ciliary body involvement was observed in 19 tumors (11%). Spindle and nonspindle patterns were observed in 100 (58%) and 71 eyes (42%), respectively. Extrascleral extension was observed in three eyes (2%). BAP1 staining was negative in 34% (53/156) of all tumors and 53% (19/36) of the cases with melanoma-related metastasis.</p> <p>The mean follow-up period was 63.4 months for all patients with the exception of 11 patients, who were excluded because they were lost during follow-up. A large basal tumor diameter, ciliary body involvement, nonspindle cell type, extrascleral extension, and negative BAP1 staining were associated with a worse prognosis. The survival curves significantly differed between the BAP1-negative and BAP1-positive groups (<i>P</i> = 0.004). According to Kaplan–Meier analysis, the 5- and 10-year metastasis-free survival rates were 80% and 70%, respectively.</p> <p><i>Conclusions</i>: A large basal tumor diameter, ciliary body involvement, nonspindle cell type, extrascleral extension, and negative BAP1 staining may be risk factors for the prediction of the UM prognosis. A younger age at diagnosis and a similar prognosis between genders may be unique features in Asian patients compared to the Caucasian population.</p