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

Additional Info

Field Value
Authors Makiola, Andreas
Dickie, Ian A.
Holdaway, Robert J.
Wood, Jamie R.
Orwin, Kate H.
Lee, C.K.
Glare, T.R.
Maintainer Ian Dickie
Last Updated November 20, 2018, 10:48 (NZDT)
Created November 20, 2018, 10:12 (NZDT)
Publisher Landcare Research NZ Ltd
Publication Year 2018
Start Date 2014
End Date 2015
DOI https://doi.org/10.25898/KK41-CY40