DeleteomeTools: utilizing a compendium of yeast deletion strain transcriptomes to identify co-functional genes

Area of Science:

• * Molecular Biology
• * Systems Biology
• * Bioinformatics

Background:

• * Understanding gene function is crucial for deciphering biological complexity.
• * Yeast single-gene deletion mutant transcriptomes offer a rich resource for functional genomics.
• * Existing methods for inferring gene function may not capture all functional relationships.

Purpose of the Study:

• * To introduce DeleteomeTools, an R package for predicting gene function using the Deleteome compendium.
• * To identify functional relationships between genes based on transcriptomic signatures of deletion strains.
• * To experimentally validate a novel predicted gene function association.

Main Methods:

• * Developed an R package, DeleteomeTools, utilizing the Deleteome compendium.
• * Implemented functions to identify similarities in transcriptomic signatures of yeast deletion strains.
• * Performed systematic evaluation of the package's ability to predict Gene Ontology (GO) annotations.
• * Experimentally confirmed a predicted functional link.

Main Results:

• * DeleteomeTools successfully predicted functional relationships between genes.
• * A novel association between nucleoporin Nup170 and the Ctf18-RFC complex was predicted and experimentally validated.
• * The package accurately predicted a majority of GO:biological process annotations.
• * The method using differential expression signatures showed potential for discovering undetected functional links.

Conclusions:

• * DeleteomeTools is a valuable tool for predicting gene function and uncovering novel biological insights.
• * The identified link between nuclear pore complexes and DNA replication machinery expands our knowledge of cellular regulation.
• * The differential expression signature approach offers a unique strategy for functional genomics research.