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You are here: Home / Teams / Regulation of Genome Architecture and Dynamics of Splicing (ReGArDS) - D. Auboeuf and C. Bourgeois / Publications / Endothelial, epithelial, and fibroblast cells exhibit specific splicing programs independently of their tissue of origin.

Endothelial, epithelial, and fibroblast cells exhibit specific splicing programs independently of their tissue of origin.

Pierre Mallinjoud, Jean-Philippe Villemin, Hussein Mortada, Micaela Polay Espinoza, Francois-Olivier Desmet, Samaan Samaan, Emilie Chautard, Leon-Charles Tranchevent, and Didier Auboeuf (2014)

Genome Res, 24(3):511-21.

Alternative splicing is the main mechanism of increasing the proteome diversity coded by a limited number of genes. It is well established that different tissues or organs express different splicing variants. However, organs are composed of common major cell types, including fibroblasts, epithelial, and endothelial cells. By analyzing large-scale data sets generated by The ENCODE Project Consortium and after extensive RT-PCR validation, we demonstrate that each of the three major cell types expresses a specific splicing program independently of its organ origin. Furthermore, by analyzing splicing factor expression across samples, publicly available splicing factor binding site data sets (CLIP-seq), and exon array data sets after splicing factor depletion, we identified several splicing factors, including ESRP1 and 2, MBNL1, NOVA1, PTBP1, and RBFOX2, that contribute to establishing these cell type-specific splicing programs. All of the analyzed data sets are freely available in a user-friendly web interface named FasterDB, which describes all known splicing variants of human and mouse genes and their splicing patterns across several dozens of normal and cancer cells as well as across tissues. Information regarding splicing factors that potentially contribute to individual exon regulation is also provided via a dedicated CLIP-seq and exon array data visualization interface. To the best of our knowledge, FasterDB is the first database integrating such a variety of large-scale data sets to enable functional genomics analyses at exon-level resolution.

 
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