SFMetaDB: a comprehensive annotation of mouse RNA splicing factor RNA-Seq datasets

• Published in: Database : the journal of biological databases and curation Vol. 2017
• Main Authors: Li, Jin, Tseng, Ching-San, Federico, Antonio, Ivankovic, Franjo, Huang, Yi-Shuian, Ciccodicola, Alfredo, Swanson, Maurice S, Yu, Peng
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 2017
• Subjects: Database Update
• ISSN: 1758-0463; 1758-0463
• DOI: 10.1093/database/bax071

Although the number of RNA-Seq datasets deposited publicly has increased over the past few years, incomplete annotation of the associated metadata limits their potential use. Because of the importance of RNA splicing in diseases and biological processes, we constructed a database called SFMetaDB by curating datasets related with RNA splicing factors. Our effort focused on the RNA-Seq datasets in which splicing factors were knocked-down, knocked-out or over-expressed, leading to 75 datasets corresponding to 56 splicing factors. These datasets can be used in differential alternative splicing analysis for the identification of the potential targets of these splicing factors and other functional studies. Surprisingly, only ∼15% of all the splicing factors have been studied by loss- or gain-of-function experiments using RNA-Seq. In particular, splicing factors with domains from a few dominant Pfam domain families have not been studied. This suggests a significant gap that needs to be addressed to fully elucidate the splicing regulatory landscape. Indeed, there are already mouse models available for ∼20 of the unstudied splicing factors, and it can be a fruitful research direction to study these splicing factors in vitro and in vivo using RNA-Seq.
Database URL:http://sfmetadb.ece.tamu.edu/