Data - Biases in the metabarcoding of plant pathogens

We investigated and analysed the causes of differences between next-generation sequencing metabarcoding approaches and traditional DNA cloning in the detection and quantification of recognized species of rust fungi from environmental samples.

The data support this article: Makiola A, Dickie IA, Holdaway RJ, Wood JR, Orwin KH, Lee CK, Glare TR. 2018. Biases in the metabarcoding of plant pathogens using rust fungi as a model system. MicrobiologyOpen.

The resources (data files) represent the raw sequence data for analysis supporting this manuscript. Leaf samples from 30 sites were collected and analysed using Illumina MiSeq (folder ‘Illumina’), Ion Torrent PGM (file ‘IonTorrent.fastq’), cloning followed by Sanger sequencing (file ‘CloningSanger.fna’). The ‘barcodes.csv’ file contains the barcode names and the corresponding sites.

Data and Resources

IlluminaZIP
Illumina MiSeq data - zipped folder
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IonTorrent_fastq.zipZIP
Ion Torrent PGM data (file ‘IonTorrent.fastq’ - zipped)
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CloningSanger.fnaFNA
Sanger sequencing data
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barcodes.csvCSV
CSV file containing the barcode names and the corresponding sites.
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Additional Info

Field	Value
Theme
Author	Makiola, Andreas & Dickie, Ian A. & Holdaway, Robert J. & Wood, Jamie R. & Orwin, Kate H. & Lee, C.K. & Glare, T.R.
Maintainer	Ian Dickie
Maintainer Email	Ian Dickie
Source
Source Created	Unknown
Source Modified	Unknown
Language	English
Spatial
Source Identifier