1. DNA metabarcoding of forensic mycological samples
- Author
-
Anna Anselmo, Giovanni Vanni Frajese, Marina Baldi, Teresa Rinaldi, Andrea Berti, S. Giampaoli, Arnold Liao, Daniel Brami, Kevin Charles Miranda, Filippo Barni, and Elisabetta De Vittori
- Subjects
Medicine (General) ,0303 health sciences ,Health (social science) ,Massive parallel sequencing ,Sample (material) ,Fungi ,Data analysis ,K1-7720 ,Computational biology ,Biology ,NGS, Fungi, Data analysis, Metabarcoding, Forensic science ,Pathology and Forensic Medicine ,Forensic science ,Fungal population ,03 medical and health sciences ,Law in general. Comparative and uniform law. Jurisprudence ,R5-920 ,0302 clinical medicine ,NGS ,Metabarcoding ,Identification (biology) ,030216 legal & forensic medicine ,Law ,030304 developmental biology - Abstract
BackgroundDNA 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.ResultsThe 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%).ConclusionsThe 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.
- Published
- 2021
- Full Text
- View/download PDF