EnTAP: Bringing faster and smarter functional annotation to non-model eukaryotic transcriptomes.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• De novo assembled transcriptomes in non-model eukaryotes often suffer from fragmentation, leading to inflated transcript estimates and poor functional annotation rates.
• Accurate functional gene annotation is crucial for understanding gene function, especially in organisms with limited genomic resources.

Purpose of the Study:

• To develop an accurate, fast, and flexible software package for functional gene annotation of de novo assembled eukaryotic transcriptomes.
• To address challenges associated with transcript fragmentation and improve annotation rates for protein-coding transcripts in non-model organisms.

Main Methods:

• EnTAP (Eukaryotic Non-Model Transcriptome Annotation Pipeline) filters transcripts based on expression and frame selection.
• Leverages open-source tools for functional annotation, including similarity searches across five repositories, protein domain assignment, orthologous gene family assessment, and Gene Ontology (GO) term assignment.
• Integrates multiple databases and uses weighted metrics (similarity score, taxonomic relationship, informativeness) for optimal annotation assignment.

Main Results:

• EnTAP effectively reduces transcript fragmentation and improves annotation rates for protein-coding transcripts.
• The pipeline provides fast similarity searches, domain assignment, ortholog identification, and GO term assignment.
• EnTAP offers optional filters for contaminant removal, pathway identification, and preparation for enrichment analysis.

Conclusions:

• EnTAP is an efficient, user-friendly pipeline for comprehensive functional gene annotation in non-model eukaryotes.
• The software significantly improves the speed and accuracy of transcriptome annotation, particularly for organisms with limited genomic data.
• EnTAP facilitates the generation of extensive functional information, aiding research in understudied eukaryotic species.