RegNetwork: Regulatory Network Repository of Transcription Factor and microRNA Mediated Gene Regulations

About:

RegNetwork is a database of transcriptional and posttranscriptional regulatory networks in human and mouse. TF and miRNA are two major regulators controlling gene expression. RegNetwork collects the knowledge-based regulatory relationships, as well as some potentially regulatory relationships between the two regulators and targets. It provides a platform of depositing the known and predicted gene regulations in the transcriptional and posttranscriptional levels simultaneously. The knowledge-derived regulatory networks is expected to be greatly beneficial for identifying critical regulatory programs in various context-specific conditions.

Introduction to the Framework of Query:

The following Figure 1 illustrates the details of functionality for each button and option on 'Search' page.

Figure 1. The functionality of each entry on 'Search' page

Figure 1. The functionality of each entry on 'Search' page

RegNetwork allows the query by multiple entries at one time. The regulations underlying these searching proteins, genes and miRNAs will be identified. For example, given a co-expressed gene set identified by a siRNA treatment experiment (Lacaze P, Raza S, Sing G, Page D, Forster T, Storm P, Craigon M, Awad T, Ghazal P, Freeman TC. Combined genome-wide expression profiling and targeted RNA interference in primary mouse macrophages reveals perturbation of transcriptional networks associated with interferon signalling. BMC Genomics. 2009 Aug 10;10:372. doi: 10.1186/1471-2164-10-372), RegNetwork can identify the existing regulatory relationships among these genes.

Figure 2. The regulatory relationships extracted from RegNetwork for a group of differentially co-expressed genes in a siRNA treatment experiment.

Figure 2. The regulatory relationships extracted from RegNetwork for a group of differentially co-expressed genes in a siRNA treatment experiment.

In their original paper, the authors used six siRNAs targeted the six important immunological genes Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2 transcripts respectively in primary mouse macrophages. They profiled the genome-wide gene expressions and identified several co-expressed gene clusters. By RegNetwork, we can easily extract the existing regulatory relationships in each gene cluster respectively. Figure 2 illustrates some of the regulatory relationships in such a cluster (The third gene cluster in the original paper). Moreover, RegNetwork identifies the miRNA regulatory relationships with these genes simultaneously.

Compared to the original gene set, the regulatory wiring information directs further interesting analyses and experimental designs about the influences transmitted between these genes in response to the siRNA treatment. RegNetwork provides a resource for depositing the existing TF and miRNA mediated regulations, which are expected to benefit many regulatory researches and experimental designs.

Statistics:

As of 2015, the following table lists the contained regulations in RegNetwork, the statistics of the built regulatory networks of human and mouse.

Element Description Number
Human Mouse
Node All paired nodes included in the built regulatory network 23079 20738
Edge All regulatory relationships included in the built regulatory network 369277 323636
TF The documented TFs included in the built regulatory network 1456 1328
miRNA The miRNAs included in the built regulatory network 1904 1290
Gene The target genes included in the built regulatory network 19719 18120
TF-gene The 'TF-gene' regulations included in the built regulatory network 149841 94876
TF-TF The 'TF'-'TF gene' self-regulations included the built regulatory network 361 129
TF-miRNA The 'TF-miRNA gene' regulations included in the built regulatory network 21744 25574
miRNA-gene The 'miRNA-target gene' regulations included in the built regulatory network 171477 176512
miRNA-TF The 'miRNA-TF gene' regulations included in the built regulatory network 25854 26545