Toward a comprehensive profiling of alternative splicing proteoform structures, interactions and functions.

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• The human genome encodes ~20,000 genes, but mRNA splicing generates over 100,000 transcripts.
• High-throughput technologies like single-cell and long-read sequencing are rapidly expanding transcriptomic data.
• The functional consequences of alternative splicing on proteome diversity are not fully understood.

Purpose of the Study:

• To review current methods for assessing alternative splicing's role in proteome diversification.
• To discuss the application of artificial intelligence (AI) in analyzing alternative splicing.
• To explore the potential and challenges of AI in identifying and characterizing alternative splicing proteoforms.

Main Methods:

• Literature review of alternative splicing research.
• Analysis of high-throughput sequencing data trends.
• Discussion of AI methodologies for transcriptomic and proteomic analysis.

Main Results:

• Alternative splicing significantly increases proteome complexity beyond gene count.
• AI offers promising avenues for identifying and characterizing novel proteoforms.
• Systematic assessment of splicing's functional impact remains a challenge.

Conclusions:

• Understanding alternative splicing is crucial for comprehending proteome function.
• AI is a key technology for advancing research in alternative splicing and proteogenomics.
• Further development is needed to fully leverage AI for characterizing splicing variations and their functional roles.