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From morphology to molecular biology: can we use sequence data to identify fungal endophytes?

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Abstract

Isolation followed by morphological identification was the traditional basis of all earlier endophyte studies. However, the use of molecular phylogenetics has become increasingly common in the identification of fungal endophytes, and during the period of 2007–2010 there were approximately 200 publications that reported data obtained using this approach. This new methodology involves using sequence data from isolates or whole DNA from plant substrates, which are amplified using fungus- specific primers. The data obtained are compared with sequences downloaded from public databases such as GenBank and then used to construct phylogenetic trees. The major problem with this approach is that much of the sequence data in these databases has been shown to be from isolates that were incorrectly named. In some species, as much as 86% of the sequences available are not from the organism whose name has been applied to the sequence in question. The use of these GenBank sequences to identify endophytic isolates by sequence similarity simply perpetuates the problem of wrong species identification, and any lists of endophytes established by such methods are likely to be highly erroneous. It is recommended that comparisons of sequence data be made using sequences from type species, and if such sequences are not available, then the data must be treated with caution.

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Acknowledgements

The research reported herein was supported by the TRF/BIOTEC Special Program for Biodiversity Research and Training grant BRT R253012 and the Royal Golden Jubilee Ph.D. Program of the National Research Council of Thailand. The Global Research Network for Fungal Biology and King Saud University are also thanked for supporting this research.

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Authors and Affiliations

  1. School of Science, Mae Fah Luang University, Thasud, Chiang Rai, 57100, Thailand

    Thida Win Ko Ko & Kevin D. Hyde

  2. Mushroom Research Foundation, 128 Moo 3, Bahn Pha Deng, T. Pa Pae, A. Mae Taeng, Chiang Mai, 50150, Thailand

    Thida Win Ko Ko

  3. Department of Biological Sciences, University of Arkansas, Fayetteville, AR, 72701, USA

    Steven L. Stephenson

  4. College of Science, Botany and Microbiology Department, King Saud University, P.O. Box: 2455, Riyadh, 1145, Saudi Arabia

    Ali H. Bahkali & Kevin D. Hyde

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  1. Thida Win Ko Ko
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Correspondence to Thida Win Ko Ko.

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Ko Ko, T.W., Stephenson, S.L., Bahkali, A.H. et al. From morphology to molecular biology: can we use sequence data to identify fungal endophytes?. Fungal Diversity 50, 113–120 (2011). https://doi.org/10.1007/s13225-011-0130-0

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