MIST: a Multilocus Identification System for Trichoderma.

Applied and Environmental Microbiology
Kai DouChulong Zhang

Abstract

Due to the rapid expansion in microbial taxonomy, precise identification of common industrially and agriculturally relevant fungi such as Trichoderma species is challenging. In this study, we introduce the online multilocus identification system (MIST) for automated detection of 349 Trichoderma species based on a set of three DNA barcodes. MIST is based on the reference databases of validated sequences of three commonly used phylogenetic markers collected from public databases. The databases consist of 414 complete sequences of the nuclear rRNA internal transcribed spacers (ITS) 1 and 2, 583 sequence fragments of the gene encoding translation elongation factor 1-alpha (tef1), and 534 sequence fragments of the gene encoding RNA polymerase subunit 2 (rpb2). Through MIST, information from different DNA barcodes can be combined and the identification of Trichoderma species can be achieved based on the integrated parametric sequence similarity search (blastn) performed in the manner of a decision tree classifier. In the verification process, MIST provided correct identification for 44 Trichoderma species based on DNA barcodes consisting of tef1 and rpb2 markers. Thus, MIST can be used to obtain an automated species identification as...Continue Reading

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