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PRONAME: a user-friendly pipeline to process long-read nanopore metabarcoding data by generating high-quality
Benjamin Dubois1, Mathieu Delitte2, Salomé Lengrand2
1Bioengineering Unit, Life Sciences Department, Walloon Agricultural Research Centre, Gembloux, Belgium.
Frontiers in Bioinformatics
|January 6, 2025
Summary
PRONAME is a new bioinformatics pipeline for processing Nanopore metabarcoding data. It enhances sequence accuracy and taxonomic resolution, offering a robust tool for analyzing complex microbial communities.
Area of Science:
- Genomics
- Bioinformatics
- Microbial Ecology
Background:
- Metabarcoding studies taxonomic composition using DNA sequencing.
- Oxford Nanopore Technologies offer long-read sequencing but have higher error rates.
- Existing bioinformatics pipelines struggle with Nanopore data accuracy.
Purpose of the Study:
- To develop a user-friendly pipeline for processing Nanopore metabarcoding data.
- To improve sequence accuracy and taxonomic resolution for Nanopore sequencing.
- To provide a versatile tool for analyzing diverse microbial communities.
Main Methods:
- Developed PRONAME (PROcessing NAnopore MEtabarcoding data) pipeline.
- Integrated precompiled and custom databases for 16S rRNA and 23S rRNA operon sequences.
- Implemented Nanopore-specific quality filtering, clustering, and innovative error-correction strategies.
Main Results:
- PRONAME achieves high-quality duplex reads with improved sequence accuracy.
- Consensus sequences demonstrate at least 99.5% accuracy.
- The pipeline offers enhanced versatility for analyzing any domain of life.
Conclusions:
- PRONAME addresses the challenges of Nanopore long-read data processing.
- It provides high-precision consensus sequences, nearing Illumina accuracy.
- Leverages long-read benefits for robust genomic analysis of complex communities.
