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A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples
A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples
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A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples
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A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples
A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples

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A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples
A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples
Journal Article

A novel metabarcoding approach to investigate Fusarium species composition in soil and plant samples

2019
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Overview
The genus Fusarium contains more than 300 species, most of which are plant pathogens. Appropriate molecular tools for accurately and rapidly describing temporal and spatial shifts in Fusarium communities would be useful for the development of control strategies. Here, we present a new Fusarium-specific primer pair targeting the translation elongation factor 1-α (EF1α) gene with amplicons of ~430 bp, suitable for MiSeq metabarcoding sequencing. Mock Fusarium communities were used to evaluate its resolution and to optimize read filtering and downstream analyses. The use of the DADA2 pipeline coupled with operational taxonomic unit (OTU) picking at 98% similarity cut-off significantly increased the accuracy of read filtering. Building a phylogenetic tree using a manually curated database as a reference allowed taxonomic assignment at the species or species-complex level. This methodology was tested on soil and maize residue samples collected from crop fields. Up to 18 Fusarium OTUs, belonging to 17 species and 8 species complexes, were obtained, with F. oxysporum being the most abundant species in soil samples, while F. graminearum and F. avenaceum were the most abundant in maize residues. We demonstrated the high performance of this workflow which could be further used for profiling Fusarium species composition and dynamics during the cultivation cycle.