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

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Publicly available RNA-Seq datasets are increasing, but incomplete metadata hinders their utility.
• RNA splicing is crucial for biological processes and disease development.
• Splicing factors play a key role in regulating RNA splicing.

Purpose of the Study:

• To curate and organize RNA-Seq datasets related to RNA splicing factors.
• To create a comprehensive database (SFMetaDB) for studying splicing factor function.
• To identify gaps in the current research landscape of splicing factors.

Main Methods:

• Curated RNA-Seq datasets focusing on loss- or gain-of-function experiments for splicing factors.
• Collected 75 datasets covering 56 distinct splicing factors.
• Developed the SFMetaDB database, accessible at http://sfmetadb.ece.tamu.edu/.

Main Results:

• SFMetaDB contains 75 RNA-Seq datasets for 56 splicing factors, enabling differential alternative splicing analysis.
• Surprisingly, only approximately 15% of all splicing factors have been investigated using loss- or gain-of-function RNA-Seq studies.
• Splicing factors belonging to certain dominant Pfam domain families remain largely unstudied.

Conclusions:

• A significant research gap exists in understanding the function of many splicing factors.
• Further investigation using RNA-Seq, particularly in vitro and in vivo, is warranted for unstudied splicing factors.
• Existing mouse models for unstudied splicing factors present opportunities for future research.