Towards integrative annotation of the cell-type specific gene functional and signaling map in vascular endothelial cells.
Vascular endothelial cells (VECs), which form the inner surface of blood vessels, play essential roles in many physiological and pathological processes. VECs are exposed to various micro-environmental stimuli delivered by the circulatory systems. Systematically deciphering the gene functions and signaling circuits in VECs responsive to the complex micro-environmental stimuli is one of the fundamental tasks in vascular biology. Currently, several databases aim at genome-widely annotating the gene functions and signaling circuits, but most of them take limited consideration on the cell-type specific information. And also, current annotations only provide the core genes involved in different signaling circuits, lacking the annotations on the peripheral signaling molecules or the signaling cross-talks. To quickly construct the genome-wide gene functional and signaling map in VECs, we developed a N[combining low line]etwork-based a[combining low line]n[combining low line]n[combining low line]o[combining low line]tating system (Nanno) by integrating cell-type specific gene expression profiles, genome-wide protein-protein interaction (PPI) networks, Gene Ontology (GO) annotations and microRNA (miRNA) target gene information. Using this system, we successfully re-annotated the genes involved in several essential cellular functions and also identified the signaling circuits under different stimuli in VECs in a cell-type specific manner. Many important genes, which are not included in GO annotations, can be recovered by Nanno. And several canonical signaling pathways and miRNAs are predicted to involve in the inflammatory and angiogenic signaling in VECs. The annotations suggest that there may exist cross-talks in cell cycle regulation between the two conditions.
Bioinformatics Division, Tsinghua National Laboratory for Information Science and Technology-TNLIST and Department of Automation, Tsinghua University, Beijing 100084, China. jgu@tsinghua.edu.cn
Jin
J
Gu
Shao
S
Li
D002478:Cells, Cultured; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D042783:Endothelial Cells / Q000378:metabolism*; D006801:Humans; D035683:MicroRNAs / Q000235:genetics; D058977:Molecular Sequence Annotation / Q000379:methods*; D012984:Software
D035683:MicroRNAs