Mammalian Annotation Database for improved annotation and functional classification of Omics datasets from less...

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Next-generation sequencing enables gene expression studies in non-model organisms.
• Incomplete genome annotation hinders downstream RNA sequencing data analysis.
• Accurate functional annotation is crucial for interpreting gene expression data.

Purpose of the Study:

• To develop a tool for providing homologous gene information for non-model mammalian species.
• To improve the accuracy of functional annotation in RNA sequencing studies.
• To facilitate gene ID assignment between different annotation databases.

Main Methods:

• Developed the Mammalian Annotation Database (MAdb) tool.
• Implemented a three-step species assignment process: gene symbol matching, Ensembl Compara orthologs, and BLAST comparisons.
• Created the AnnOverlappeR tool for reliable National Center for Biotechnology Information (NCBI) and Ensembl gene ID assignment.

Main Results:

• MAdb successfully provided homologous gene information for selected mammalian species.
• Tested on pig RNA-seq data, MAdb improved overrepresentation analysis results using assigned human homologous genes.
• Gene lists translated to human IDs yielded consistent functional annotation regardless of starting NCBI or Ensembl IDs.

Conclusions:

• MAdb enhances functional annotation for RNA sequencing data in non-model organisms.
• The tool improves data analysis by providing reliable homologous gene information.
• MAdb is accessible via web interface and Galaxy application for broader use.