Cosplicing network analysis of mammalian brain RNA-Seq data utilizing WGCNA and Mantel correlations

Area of Science:

• Genomics
• Systems Biology
• Neuroscience

Background:

• Gene isoform production is widespread, particularly in the mammalian brain.
• Gene expression coordination forms scale-free coexpression networks.
• Transcriptome-wide isoform production coordination remains less understood.

Purpose of the Study:

• To evaluate system-level properties of cosplicing in mammalian brain gene expression data.
• To compare cosplicing networks with traditional coexpression networks.
• To identify novel gene hubs and regulatory mechanisms within cosplicing networks.

Main Methods:

• Developed a novel network inference procedure using exon counts and exon inclusion rates.
• Constructed cosplicing and coexpression network matrices across mouse, macaque, and human brain data.
• Analyzed network properties, hub characteristics, and regulatory factor influences.

Main Results:

• Cosplicing networks are scale-free and distinct from coexpression networks.
• Identified novel cosplicing hubs enriched in neurobiological pathways, neuronal/glial markers, and autism spectrum disorder genes.
• Discovered distinct regulatory mechanisms for coexpression (transcription factors) and cosplicing (splicing factors).

Conclusions:

• Cosplicing represents a fundamental layer of gene regulation with unique network properties.
• Cosplicing hubs are critical for brain function and may offer insights into neurodevelopmental disorders.
• Network patterns of cosplicing are conserved across species, suggesting evolutionary importance.