Tissue-specific mouse mRNA isoform networks.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Alternative splicing generates multiple mRNA isoforms from single genes, leading to functional diversity.
• Current functional networks are primarily gene-level, limiting understanding of isoform-specific roles.
• Investigating mRNA isoform functions is critical for understanding gene regulation, disease, and environmental responses.

Purpose of the Study:

• To develop a computational method for predicting functional networks at the mRNA isoform level.
• To create tissue-specific functional networks (TENSION) to uncover isoform-specific biological roles.
• To provide a resource for exploring the functional landscape of alternative splicing.

Main Methods:

• Trained random forest models using tissue-specific RNA-seq datasets and sequence information.
• Utilized Gene Ontology, KEGG, BioCyc pathways, and protein-protein interactions to define functional relationships.
• Employed a leave-one-tissue-out cross-validation strategy and generated organism-level networks for mice.

Main Results:

• Generated 17 tissue-specific functional networks (TENSION) and one organism-level network for mice.
• Validated network predictions against existing methods, randomized data, updated annotations, and literature.
• Demonstrated the capability of TENSION networks to highlight tissue-specific functional distinctions among isoforms of the same gene.

Conclusions:

• The TENSION resource enables the study of mRNA isoform functions and their tissue-specific activities.
• This approach advances the understanding of alternative splicing's role in biological complexity.
• The developed methods and data provide a foundation for future isoform-centric functional genomics research.