Integrated analysis of a compendium of RNA-Seq datasets for splicing factors

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Public RNA-sequencing datasets are valuable resources for advancing transcriptome research.
• Alternative splicing plays a critical role in various biological processes and diseases.
• Systematic analysis of splicing factors is needed to understand their functions.

Purpose of the Study:

• To perform the first large-scale integrated analysis of RNA-sequencing data focusing on splicing factors.
• To systematically identify key splicing factors involved in specific diseases and biological processes.
• To leverage public data to generate hypotheses for experimental validation.

Main Methods:

• Integrated analysis of 1,321 mouse RNA-sequencing libraries (6.6 TB) from 75 studies.
• Experimental manipulation of 56 splicing factors.
• Computation of RNA splicing and gene expression signatures.
• Signature comparison analysis for identifying key factors.
• Neuronal morphology analysis and metabolic flux analysis.

Main Results:

• Identified key splicing factors associated with Rett syndrome and cold-induced thermogenesis.
• Demonstrated that cold-induced RNA-binding proteins can rescue neurite outgrowth defects in a model of Rett syndrome.
• Revealed the requirement of SRSF1 and PTBP1 for energy expenditure in adipocytes.

Conclusions:

• Large-scale integrated analysis of public RNA-Seq data is effective for identifying key biological regulators.
• Splicing factors play crucial roles in neurological disorders and metabolic processes.
• Public data resources are essential for generating novel research hypotheses.