Effectiveness of ITS and sub-regions as DNA barcode markers for the identification of Basidiomycota (Fungi)

Abstract

Background: Fungi are among the most abundant and diverse organisms on Earth. However, a substantial amount of the species diversity, relationships, habitats, and life strategies of these microorganisms remain to be discovered and characterized. One important factor hindering progress is the difficulty in correctly identifying fungi. Morphological and molecular characteristics have been applied in such tasks. Later, DNA barcoding has emerged as a new method for the rapid and reliable identification of species. The nrITS region is considered the universal barcode of Fungi, and the ITS1 and ITS2 sub-regions have been applied as metabarcoding markers. In this study, we performed a large-scale analysis of all the available Basidiomycota sequences from GenBank. We carried out a rigorous trimming of the initial dataset based in methodological principals of DNA Barcoding. Two different approaches (PCI and barcode gap) were used to determine the performance of the complete ITS region and sub-regions.

Results: For most of the Basidiomycota genera, the three genomic markers performed similarly, i.e., when one was considered a good marker for the identification of a genus, the others were also; the same results were observed when the performance was insufficient. However, based on barcode gap analyses, we identified genomic markers that had a superior identification performance than the others and genomic markers that were not indicated for the identification of some genera. Notably, neither the complete ITS nor the sub-regions were useful in identifying 11 of the 113 Basidiomycota genera. The complex phylogenetic relationships and the presence of cryptic species in some genera are possible explanations of this limitation and are discussed.

Conclusions: Knowledge regarding the efficiency and limitations of the barcode markers that are currently used for the identification of organisms is crucial because it benefits research in many areas. Our study provides information that may guide researchers in choosing the most suitable genomic markers for identifying Basidiomycota species.

Keywords: Barcode gap; Basidiomycota; ITS; ITS1; ITS2; Probable correct identification.

Fig. 1

Pie charts represent abundance (number) of sequences (a) and species (b) for the three subphyla represented in the dataset used in this study. The histograms show the number of species and sequences distributed for genera belonging to Agaricomycotina (c), Pucciniomycotina (d) and Ustilagomycotina (e) phylum

Fig. 2

Pairwise correlations (a, ITS X ITS1, b, ITS X ITS2 and c, ITS1 X ITS2) between PCI values of all genera from our dataset

Fig. 3

Examples of the barcode gap performance classifications used in this study. a. Clear barcode gap (identification performance classified as good) for the genera Agaricus, b. Intermediate separation between the intra- and interspecific distances for Hebeloma and c. A poor barcode gap for Lactarius

Fig. 4

PCI values for the genera classified in the Group 1 (a), Group 2 (b), Group 3 (c) and Group 4 (d) are represented for the ITS, ITS1 and ITS2 genomic region