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PLoS One. 2012;7(12):e52092. doi: 10.1371/journal.pone.0052092. Epub 2012 Dec 18.

DNA barcoding for identification of 'Candidatus Phytoplasmas' using a fragment of the elongation factor Tu gene.

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  • 1Department of Agroecology, AU Science and Technology, Aarhus University, Slagelse, Denmark.



Phytoplasmas are bacterial phytopathogens responsible for significant losses in agricultural production worldwide. Several molecular markers are available for identification of groups or strains of phytoplasmas. However, they often cannot be used for identification of phytoplasmas from different groups simultaneously or are too long for routine diagnostics. DNA barcoding recently emerged as a convenient tool for species identification. Here, the development of a universal DNA barcode based on the elongation factor Tu (tuf) gene for phytoplasma identification is reported.


We designed a new set of primers and amplified a 420-444 bp fragment of tuf from all 91 phytoplasmas strains tested (16S rRNA groups -I through -VII, -IX through -XII, -XV, and -XX). Comparison of NJ trees constructed from the tuf barcode and a 1.2 kbp fragment of the 16S ribosomal gene revealed that the tuf tree is highly congruent with the 16S rRNA tree and had higher inter- and intra- group sequence divergence. Mean K2P inter-/intra- group divergences of the tuf barcode did not overlap and had approximately one order of magnitude difference for most groups, suggesting the presence of a DNA barcoding gap. The use of the tuf barcode allowed separation of main ribosomal groups and most of their subgroups. Phytoplasma tuf barcodes were deposited in the NCBI GenBank and Q-bank databases.


This study demonstrates that DNA barcoding principles can be applied for identification of phytoplasmas. Our findings suggest that the tuf barcode performs as well or better than a 1.2 kbp fragment of the 16S rRNA gene and thus provides an easy procedure for phytoplasma identification. The obtained sequences were used to create a publicly available reference database that can be used by plant health services and researchers for online phytoplasma identification.

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