MycorrhizaTracer: A BIOINFORMATIC PIPELINE FOR FUNGI AND PLANT CLASSIFICATION OF SANGER DNA SEQUENCES
Processing Sanger DNA sequences remains a routine yet technically demanding step in many biodiversity and ecological studies, particularly when barcoding large numbers of environmental samples. Manual inspection and editing of trace files, DNA sequence alignment, and classification using taxonomic reference databases is time-consuming, inconsistent, and prone to error. These challenges are compounded in studies involving degraded samples, in-house DNA sequencing, under-described taxa, or when investigators have limited access to computational tools. We present MycorrhizaTracer, an open-source, fully automated pipeline for processing and taxonomically classifying large batches of Sanger sequencing chromatograms. We have optimized it for fungal and plant taxa, but it is adaptable across the tree of life. The pipeline performs quality trimming, consensus generation from bidirectional reads, taxonomic classification via BLAST, clustering, optional salvaging of low-quality sequences, and functional annotation of fungal taxa. Designed for scalability and ease of use, MycorrhizaTracer can process thousands of DNA chromatograms in a matter of hours without the need for an HPC. Accuracy and ecological relevance are ensured by features such as gene region-specific taxonomic filtering and sequence-based clustering of unclassified reads. By streamlining trace-to-taxon workflows, MycorrhizaTracer reduces the burden of manual curation, supports reproducibility, and enables efficient recovery of biodiversity data from Sanger sequences - particularly in field-based or resource-limited research contexts.