Deep transcriptomics reveals cell-specific isoforms of pan-neuronal genes.

Area of Science:

• Neuroscience
• Molecular Biology
• Genomics

Background:

• Profiling alternative splicing in single neurons is difficult due to low RNA capture efficiency and sensitivity.
• Splicing patterns and regulation in neurons are less understood compared to gene expression.
• The C. elegans model offers unique advantages for deep neuron-specific transcriptome analysis.

Purpose of the Study:

• To generate high-confidence global splicing maps across diverse neuron types in C. elegans.
• To identify cell-specific splice variants and potential regulatory factors controlling neuronal splicing.
• To develop a platform for visualizing spatial transcriptomic splicing patterns at single-neuron resolution.

Main Methods:

• Leveraged biological replicates from the CeNGEN consortium for robust analysis.
• Developed a novel algorithm to identify cell-specific expression patterns and isoforms.
• Performed in vivo genetic interrogation of identified splicing regulatory factors.

Main Results:

• Discovered pan-neuronal genes with cell-specific splice variants.
• Observed abundant differential intron retention across different neuron types.
• Identified three splicing factors critical for controlling splicing in single neurons.

Conclusions:

• Established comprehensive splicing maps in C. elegans neurons, even for low-expression genes.
• Uncovered novel mechanisms of neuronal splicing regulation.
• Provided a user-friendly platform for spatial transcriptomic visualization of splicing patterns.