Deciphering the plant splicing code: experimental and computational approaches for predicting alternative splicing...

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Alternative splicing (AS) of pre-mRNAs in multicellular eukaryotes enhances proteome diversity and gene expression regulation.
• In flowering plants, AS affects up to 48% of intron-containing genes, but its full extent remains largely uncharacterized.
• High-throughput RNA-Seq technologies are generating vast plant sequence data, necessitating advanced computational tools for AS analysis.

Purpose of the Study:

• To review computational tools for predicting and visualizing transcriptome-wide AS in plants using short-read data.
• To highlight the limitations of current AS prediction and visualization tools in plants.
• To discuss the current state of research on splicing regulatory elements (SREs) in plants and emerging tools for their identification.

Main Methods:

• Review of existing literature on AS in plants.
• Analysis of comparative studies between plant and animal AS events.
• Discussion of computational and experimental tools for SRE identification.

Main Results:

• Significant differences exist in prevalent AS event types between plants and animals, indicating distinct exon-intron recognition mechanisms.
• Few studies have focused on identifying cis-acting SREs regulating AS in plants, unlike in animals.
• Computational prediction of SREs, followed by experimental validation, is a promising approach for plant AS research.

Conclusions:

• Accurate prediction and visualization of AS in plants require further development of computational tools.
• Identifying plant-specific SREs is crucial for understanding plant gene regulation and deciphering the plant splicing code.
• Future research combining computational and experimental approaches will elucidate plant-specific AS mechanisms.