CCPRD: A Novel Analytical Framework for the Comprehensive Proteomic Reference Database Construction of NonModel...

Area of Science:

• Proteomics
• Bioinformatics
• Genomics

Background:

• Efficient proteomic analyses rely on protein reference databases.
• Constructing comprehensive databases for nonmodel organisms is challenging.
• Existing methods often lack contamination control or increase computational burden.

Purpose of the Study:

• To propose a framework for creating customized comprehensive proteomic reference databases (CCPRD).
• To demonstrate the effectiveness of CCPRD using myxozoan proteomes.
• To improve proteomic analysis for nonmodel organisms.

Main Methods:

• Developed a framework using draft genomes and deep sequencing transcriptomes.
• Applied customized contamination removal procedures.
• Validated CCPRD against traditional frame-based methods and contaminated databases.

Main Results:

• CCPRD identified 35.2-50.7% more peptides and 35.8-43.8% more proteins than traditional methods.
• Achieved up to 84.6% reduction in database size.
• Maintained high completeness as shown by BUSCO analysis.
• Successfully identified and removed contaminations without overdecontamination.

Conclusions:

• CCPRD outperforms existing methods in peptide/protein identification, database size, and completeness.
• The framework is effective for nonmodel organisms, even without high-quality genomes.
• CCPRD offers a significant advancement for proteomic research.