PT  - JOURNAL ARTICLE
AU  - Jin Li
AU  - Ching-San Tseng
AU  - Antonio Federico
AU  - Franjo Ivankovic
AU  - Yi-Shuian Huang
AU  - Alfredo Ciccodicola
AU  - Maurice S. Swanson
AU  - Peng Yu
TI  - SFMetaDB: A Comprehensive Annotation of Mouse RNA Splicing Factor RNA-Seq Datasets
AID  - 10.1101/177931
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 177931
4099  - http://biorxiv.org/content/early/2017/08/18/177931.short
4100  - http://biorxiv.org/content/early/2017/08/18/177931.full
AB  - 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/