Abstract
Plant pathogens such as rust fungi (Pucciniales) are of global economic and ecological importance. This means there is a critical need to reliably and cost‐effectively detect, identify, and monitor these fungi at large scales. We investigated and analyzed the causes of differences between next‐generation sequencing (NGS) metabarcoding approaches and traditional DNA cloning in the detection and quantification of recognized species of rust fungi from environmental samples. We found significant differences between observed and expected numbers of shared rust fungal operational taxonomic units (OTUs) among different methods. However, there was no significant difference in relative abundance of OTUs that all methods were capable of detecting. Differences among the methods were mainly driven by the method's ability to detect specific OTUs, likely caused by mismatches with the NGS metabarcoding primers to some Puccinia species. Furthermore, detection ability did not seem to be influenced by differences in sequence lengths among methods, the most appropriate bioinformatic pipeline used for each method, or the ability to detect rare species. Our findings are important to future metabarcoding studies, because they highlight the main sources of difference among methods, and rule out several mechanisms that could drive these differences. Furthermore, strong congruity among three fundamentally different and independent methods demonstrates the promising potential of NGS metabarcoding for tracking important taxa such as rust fungi from within larger NGS metabarcoding communities. Our results support the use of NGS metabarcoding for the large‐scale detection and quantification of rust fungi, but not for confirming the absence of species.
Highlights
Plant pathogens are a critical threat to global food security (Bebber & Gurr, 2015), the conservation of natural ecosystems, and the future resilience and sustainability of ecosystem services (Bever, Mangan, & Alexander, 2015)
This study demonstrates that next‐generation sequencing (NGS) metabarcoding is an effective technique for large‐scale detection of rust fungus plant pathogens, but that taxonomic biases due to primer selection are a potential limitation
To the best of our knowledge, this is the first study with a real‐world application and comparison of cloning and NGS meta‐ barcoding to survey Pucciniales
Summary
Plant pathogens are a critical threat to global food security (Bebber & Gurr, 2015), the conservation of natural ecosystems, and the future resilience and sustainability of ecosystem services (Bever, Mangan, & Alexander, 2015). Two limitations that frequently arise in NGS metabarcoding studies are the ability to quantify the abundances of different taxa (Deiner et al, 2017; Elbrecht & Leese, 2015), and the introduction of false positives/negatives by PCR amplification, library prepara‐ tion, and sequencing (Coissac, Riaz, & Puillandre, 2012) We address these two possible limitations of NGS metabarcoding using the group of rust fungi as a model system. For the NGS metabarcoding approach, we use two fundamentally different sequencing technologies (Illumina MiSeq and Ion Torrent PGM) and fungal NGS metabarcoding primers to de‐ tect rust fungi from within a larger fungal community. We hypothesize that differences among methods are due to: 1. differences in sequence lengths among methods 2. differences in the most appropriate bioinformatic pipelines for each method 3. taxonomic biases of the methods 4. different abilities of methods to detect rare species
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