DNA metabarcoding of forensic mycological samples

Abstract Background DNA metabarcoding and massive parallel sequencing are valuable molecular tools for the characterization of environmental samples. In forensic sciences, the analysis of the sample’s fungal population can be highly informative for the estimation of post-mortem interval, the ascertainment of deposition time, the identification of the cause of death, or the location of buried corpses. Unfortunately, metabarcoding data analysis often requires strong bioinformatic capabilities that are not widely available in forensic laboratories. Results The present paper describes the adoption of a user-friendly cloud-based application for the identification of fungi in typical forensic samples. The samples have also been analyzed through the QIIME pipeline, obtaining a relevant data concordance on top genus classification results (88%). Conclusions The availability of a user-friendly application that can be run without command line activities will increase the popularity of metabarcoding fungal analysis in forensic samples.