New smut-specific primers for the ITS barcoding of Ustilaginomycotina

Kruse, Julia and Choi, Young-Joon and Thines, Marco (2017) New smut-specific primers for the ITS barcoding of Ustilaginomycotina. Mycological Progress, 16 (3). pp. 213-221. ISSN 1617-416X


The smut fungi (Ustilaginomycotina) are a highly diverse group, containing about 115 genera and 1700 species, most of which are biotrophic plant pathogens. As for other fungal groups, the ITS rDNA region is widely used to determine smut fungi at species level due to its high discriminatory power and for phylogenetic reconstructions within genera. So far, two primer sets, ITS1/ITS4 and M-ITS1/ITS4, were generally used to amplify smut fungi, but these often co-amplify host plants or contaminant fungi and do not yield satisfactory amplification for a variety of smut fungi. In the present study, based on a selection of genera that include more than 90% of the species of smut fungi (more than half of the genera of smut fungi), three new primers, smITS-F, smITS-R1 and smITSR2, situated in the SSU or LSU region, were designed to avoid the amplification of host plants and to extend the coverage of PCR amplification for as many smut genera as possible.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Current - USQ Other
Faculty/School / Institute/Centre: Current - USQ Other
Date Deposited: 26 Nov 2019 06:19
Last Modified: 03 Jan 2020 01:33
Uncontrolled Keywords: Barcoding locus; Basidiomycota; Diversity; DNA-extraction methods; Smut-specific primers
Fields of Research (2008): 06 Biological Sciences > 0605 Microbiology > 060505 Mycology
06 Biological Sciences > 0601 Biochemistry and Cell Biology > 060102 Bioinformatics
Fields of Research (2020): 31 BIOLOGICAL SCIENCES > 3107 Microbiology > 310705 Mycology
31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310299 Bioinformatics and computational biology not elsewhere classified
Identification Number or DOI: doi:10.1007%2Fs11557-016-1265-x

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