Evaluation of five regions as DNA barcodes for identification of Lepista species (Tricholomataceae, Basidiomycota) from China

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Biodiversity and Conservation

Introduction

Lepista (Fr.) W.G. Sm., a genus in the family Tricholomataeae, was erected by Smith in 1870 and contains about 50 species (Kirk et al., 2008). A total of 12 Lepista species have been reported in China where they are widely distributed (Mao, 2000; Li et al., 2011). Some Lepista species are popular edible mushrooms in China, and these include Lepista nuda (Bull.) Cooke, L. sordida (Schumach.) Singer, and L. irina (Fr.) H.E. Bigelow (Dai et al., 2010).

The genus Lepista can be distinguished from other genera by the coarse surface of its spores, a white to pale-pink spore print, and clamped hyphae (Singer, 1986; Bon, 1987). Within the genus, however, the limited morphological characteristics make it difficult to distinguish among the species. As a result, misidentification is common both between and within species of Lepista. For example, L. irina and L. panaeola have a similar whitish pileus. According to Alvarado et al. (2015), the two species differ in spore size and spore wall structure but the assessment of these characters varies among observers. In addition, other morphological characteristics including the color of the pileus often vary with environmental factors. The pileus of L. nuda, for example, was described as gray brown or russet brown in some studies but as purple brown in others (Bon, 1987; Hansen & Knudsen, 1992).

Accurate identification of species is important for conserving the genetic resources of Lepista, and rapid and reliable species identification is now possible via DNA barcoding. DNA barcoding, which uses short DNA sequences of standard genomic regions, has become increasingly important in identifying species (Badotti et al., 2017; Li et al., 2017) and discovering new species (Zhao et al., 2011; Al-Hatmi et al., 2016). DNA barcoding also could provide the primary information for species delimitation in poorly known groups (Vogler & Monaghan, 2007) and help identify candidate exemplar taxa for a comprehensive phylogenetic study (Hajibabaei et al., 2007). Based on the requirements for standardized DNA barcoding, the sequences of all candidate markers should be short and should have high rates of successful amplification and high rates of successful sequencing. DNA barcoding also requires that candidate markers have substantial inter-specific variation but not intra-specific variation. The internal transcribed spacer (ITS) region of the nuclear ribosomal RNA gene has been used as a general barcode marker for some groups in the Basidiomycota (Dentinger, Didukh & Moncalvo, 2011; Cai, Tang & Yang, 2012; Buyck et al., 2014; Badotti et al., 2017). Other candidate segments that have been used as barcoding markers for mushrooms previously, including the mitochondrial cytochrome oxidase I gene (cox1) (Vialle et al., 2009), the second subunit of RNA polymerase II (RPB2) (Li et al., 2017), and the β-tubulin and elongation factor 1-α (tef1) (Guo et al., 2016).

The goal of the present study was to test the utility of DNA barcodes to the identification of the Lepista species as edible species to address the question, that is, due to the limited morphological characteristics within the genus Lepista, misidentification often happened. To address the question, we evaluated the following five markers as DNA barcodes for identification of eight Lepista species: ITS region, the intergenic spacer (IGS), the large nuclear ribosomal RNA subunit (nLSU), the mitochondrial small subunit rDNA (mtSSU), and tef1.

Materials and Methods

Ethics statement

Lepista species are neither protected nor endangered in the sampled areas, and all samples were collected by researchers following current Chinese regulations. None of the sampled locations are privately owned or protected by law.

Sampling

In a previous study (Alvarado et al., 2015), the genus Lepista was divided into three clades. The current study included two species from each of the three clades plus two unidentified Lepista species. A total of 34 samples of the eight Lepista species were collected from September 2012 to August 2017 (Table 1). Tissue blocks were removed from the inner part of the fresh basidiomata for DNA analyses. The specimens were dried with an electric air ventilation drier and deposited in the Fungal Herbarium of Shenyang Agricultural University (SYAU-FUNGI).

Table 1:
The Lepista samples used in this study.
Taxon Specimen vouchera ITSb IGSb nLSUb mtSSUb tef1b
Lepista densifolia SYAU-FUNGI-022 MK116588 MK389519 MK389570
Lepista irina SYAU-FUNGI-023 MK116589 MK389520 MK389546 MK389571 MK551215
Lepista irina SYAU-FUNGI-024 MK116590 MK389521 MK389547 MK389572 MK551216
Lepista irina SYAU-FUNGI-025 MK116591 MK389548 MK389573
Lepista nuda SYAU-FUNGI-021 MH428843 MK389523 MK389549 MK389575 MK440311
Lepista nuda SYAU-FUNGI-026 MK116594 MK440315
Lepista nuda SYAU-FUNGI-017 MH428839 MK389524 MK389550 MK389576 MK440312
Lepista nuda SYAU-FUNGI-019 MH428841 MK389551 MK389577 MK440313
Lepista nuda SYAU-FUNGI-027 MK116593 MK389525 MK389552 MK389578 MK440314
Lepista nuda SYAU-FUNGI-014 MH428836 MK389526 MK389553 MK389579 MK440315
Lepista nuda SYAU-FUNGI-028 MK116595 MK389554 MK389580 MK440317
Lepista nuda SYAU-FUNGI-029 MK116592 MK389522 MK389574 MK440310
Lepista panaeola SYAU-FUNGI-030 MK116597 MK389527 MK389581
Lepista panaeola SYAU-FUNGI-031 MK116598
Lepista panaeola SYAU-FUNGI-032 MK116599 MK389529 MK389583 MK551218
Lepista panaeola SYAU-FUNGI-033 MK116600 MK389530 MK389555 MK389584
Lepista panaeola SYAU-FUNGI-034 MK116601 MK389531 MK389556 MK389585
Lepista panaeola SYAU-FUNGI-035 MK116596 MK389528 MK389557 MK389582 MK551217
Lepista saeva SYAU-FUNGI-036 MK116602 MK389532 MK389558 MK389586
Lepista saeva SYAU-FUNGI-037 MK116603 MK389533 MK389559 MK389587
Lepista saeva SYAU-FUNGI-038 MK116604 MK389534 MK389560 MK389588
Lepista sordida SYAU-FUNGI-039 MK116605 MK389535 MK389561 MK389589 MK551219
Lepista sordida SYAU-FUNGI-040 MK116606 MK389536 MK389590
Lepista sordida SYAU-FUNGI-041 MK116607 MK389537 MK389563 MK389591
Lepista sordida SYAU-FUNGI-042 MK116609 MK389539 MK389564 MK389594 MK551221
Lepista sordida SYAU-FUNGI-043 MK116610 MK389540 MK389565 MK389593 MK551222
Lepista sordida SYAU-FUNGI-044 MK116608 MK389538 MK389562 MK389592 MK551220
Lepista sp 1 SYAU-FUNGI-045 MK116611 MK440305
Lepista sp 1 SYAU-FUNGI-046 MK116612 MK389567 MK440306
Lepista sp 1 SYAU-FUNGI-047 MK116613 MK389541 MK389568 MK389597 MK440307
Lepista sp 1 SYAU-FUNGI-048 MK116614 MK389542 MK389566 MK389595 MK440308
Lepista sp 1 SYAU-FUNGI-049 MK116615 MK389543 MK389596 MK440309
Lepista sp 2 SYAU-FUNGI-050 MK116617 MK389544
Lepista sp 2 SYAU-FUNGI-051 MK116616 MK389545 MK389569
DOI: 10.7717/peerj.7307/table-1

Notes:

SYAU-FUNGI: Fungal Herbarium of Shenyang Agricultural University, Shenyang, China;
GenBank accession numbers in bold indicate the sequences generated in this study.

Morphological observations

Morphological identification was based on previous studies (Singer, 1986; Bon, 1987; Li et al., 2015). Microscopic characteristics of the basidiomata were assessed by examining dried specimens that had been treated with 5% KOH solution and Melzer’s reagent with a light microscope.

DNA extraction, amplification, and sequencing

Genomic DNA was extracted from fresh blocks of tissue with a plant DNA extraction kit (Sunbiotech, Beijing, China). Crude DNA extracts were used as templates for PCR, and a total of five primers were used for amplification (Table 2). Reaction mixtures were as described by Yu et al. (2014). For the amplification of ITS, IGS, nLSU, and mtSSU, the PCR conditions consisted of an initial denaturation at 94 °C for 2 min; followed by 30 cycles of denaturation at 94 °C for 35 s, annealing at 45 °C for 35 s, and extension at 72 °C for 1 min; and a final extension at 72 °C for 10 min. For tef1, the PCR protocol consisted of initial denaturation at 94 °C for 2 min; followed by 10 cycles at 94 °C for 35 s, 57 °C for 35 s (decreasing 0.3 °C per cycle), and 72 °C for 1 min; followed by 29 cycles at 94 °C for 35 s, 54 °C for 35 s, and 72 °C for 1 min; and a final extension at 72 °C for 10 min. PCR products were checked on a 1.0% agarose gel and visualized by staining with ethidium bromide. Sequencing was performed on an ABI Prism 3730 genetic analyzer (PE Applied Biosystems, Foster City, CA, USA). The sequences generated from this study are listed in Table 1.

Table 2:
Primers used in this study.
Regions Primer Sequence (5′-3′) Reference
ITS ITS5 GGA AGT AAA AGT CGT AAC AAG G White et al. (1990)
ITS4 TCC TCC GCT TAT TGA TAT GC White et al. (1990)
IGS CNL12 CTG AAC GCC TCT AAG TCA G White et al. (1990)
5SA CAG AGT CCT ATG GCC GTG AT White et al. (1990)
nLSU LROR ACC CGC TGA ACT TAA GC Rehner & Samuels (1994)
LR7 TAC TAC CAC CAA GAT CT Vilgalys & Hester (1990)
mtSSU MS1 CAG CAG TCA AGA ATA TTA GTC AAT G White et al. (1990)
MS2 GCG GAT TAT CGA ATT AAA TAA C White et al. (1990)
tef1 tefF TAC AAR TGY GGT GGT ATY GAC A Morehouse et al. (2003)
tefR ACN GAC TTG ACY TCA GTR GT Morehouse et al. (2003)
DOI: 10.7717/peerj.7307/table-2

Data analyses

Sequences of each region were aligned with Clustal X (Thompson et al., 1997) and then manually edited with BioEdit 5.0.6 (Hall et al., 2003). The aligned sequences of each region were analyzed using DNAstar 7.1.0 (Lasergene, WI, USA) to calculate the similarity matrices. The intra- and inter-specific variations of the candidate barcode loci for each species were then assessed using TaxonGap 2.4.1 (Slabbinck et al., 2008). Finally, the results were processed and showed by GSview 4.9.

Genetic pairwise distances for evaluating the sequence variations within and between species of the potential barcode regions were computed using MEGA 7.0 (Kumar, Stecher & Tamura, 2016) based on the Kimura 2-Parameter (K2P) model (Kimura, 1980). Barcoding gaps comparing the distributions of the pairwise intra- and inter-specific distances for each candidate barcode with distance intervals of 0.004 (ITS, nLSU, and mtSSU) or 0.008 (IGS and tef1) were estimated in Microsoft Excel 2016.

Neighbor-joining tree reconstruction

To show the relationships among the eight Lepista species, a neighbor-joining tree was constructed based on the ITS region using MEGA with the K2P substitution model. Branch support was calculated by a bootstrap analysis with 1,000 replicates, and Tricholoma matsutake (AB699640) was used as the outgroup. For comparison, the combined dataset of five regions was used to construct a neighbor-joining tree. Alignments have been deposited in TreeBASE (http://purl.org/phylo/treebase/phylows/study/TB2:S24378).

Results

PCR amplification and sequencing

A total of 134 sequences of the five candidate DNA barcode regions were obtained from the eight Lepista species (Table 1). The five regions were then evaluated for their potential as barcoding markers (Table 3). Sequence lengths ranged from 400 bp for IGS to 1,000 bp for nLSU, that is, all five regions were sufficiently short to be used as barcode markers. The amplification success rate exceeded 90% for all regions except tef1, and the sequencing success rate was highest (100%) for ITS.

Table 3:
Results of the amplification and sequencing of five regions in the genomes of eight Lepista species.
Region Region length (bp) Total number of samples No. of PCR successes PCR success rate (%) No. of sequencing successes Sequencing success rate (%)
ITS 605–615 34 34 100 34 100
IGS 415–440 34 34 100 27 79
nLSU 934–939 34 33 97 24 71
mtSSU 662–740 34 32 94 28 82
tef1 861–920 34 23 68 21 62
DOI: 10.7717/peerj.7307/table-3

Intra- and inter-specific variation

According to TaxonGap analyses of the intra- and inter-specific variations of the candidate DNA barcode regions, ITS, IGS, tef1, and mtSSU provided a somewhat better resolution of the eight species than nLSU. Except for nLSU, the other four regions showed significant inter- and intra-specific variation (Fig. 1).

Intra- and inter-specific variations among the candidate barcode regions (ITS, IGS, nLSU, mtSSU, and tef1) from eight Lepista species.

Figure 1: Intra- and inter-specific variations among the candidate barcode regions (ITS, IGS, nLSU, mtSSU, and tef1) from eight Lepista species.

Graphs were generated by TaxonGap software. The black and gray bars represent the level of inter- and intra-specific variations, respectively. The thin black lines indicate the lowest inter-specific variation for each candidate barcode. Taxon names next to the dark bars indicate the most closely related species among the species listed on the left. Four regions, that is, ITS, IGS, tef1, and mtSSU, showed significant inter- and intra-specific variation.

Barcoding gaps

Three regions, that is, ITS (Fig. 2A), IGS (Fig. 2B), and tef1 (Fig. 2E), had relatively clear barcoding gaps. The two remaining candidate barcodes (mtSSU and nLSU) had overlaps between their intra- and inter-specific distances (Figs. 2C and 2D).

Frequency distributions of intra- and inter-specific Kimura-2-Parameter pairwise distances among ITS, IGS, nLSU, mtSSU, and tef1 datasets from eight Lepista spp.

Figure 2: Frequency distributions of intra- and inter-specific Kimura-2-Parameter pairwise distances among ITS, IGS, nLSU, mtSSU, and tef1 datasets from eight Lepista spp.

The black and gray bars represent the level of intra- and inter-specific variations, respectively. Three regions, that is, ITS, IGS, and tef1, had relatively clear barcoding gaps. (A) ITS. (B) IGS. (C) nLSU. (D) mtSSU. (E) tef1.

Neighbor-joining analysis

In a tree generated by a neighbor-joining analysis of the ITS region, the eight species were well-separated from each other and formed independent terminal branches (Fig. 3). Sequences from different samples of the same species showed high bootstrap values. Two clades, named Lepista sp 1 and L. sp 2, were supported by high bootstrap values and were inferred to represent new species of Lepista. The topology of the combined dataset tree was similar to that produced by ITS region (Fig. S1).

A neighbor-joining tree generated by analysis of ITS from eight Lepista spp.

Figure 3: A neighbor-joining tree generated by analysis of ITS from eight Lepista spp.

Bootstrap values ≥70% are shown above the relevant branches. The eight Lepista spp. are highlighted in bold.

Discussion

There are two important factors for evaluating candidate DNA barcodes: a high success rate of PCR amplification and sequencing, and substantially greater inter-specific than intra-specific variation. In the current study, the ITS region had high success rates of amplification and sequencing, substantially greater inter-specific than intra-specific variation, as well as clear barcoding gaps among the Lepista species. Based on the criteria, we therefore conclude that the ITS region would be useful for the identification of Lepista species and determine that the ITS is a suitable DNA barcode for the genus Lepista.

The ITS region has been proposed as a universal barcode for fungi (Schoch et al., 2012). The region is present in several chromosomes and is arranged in tandem repeats that are thousands of copies long (Ajmal Ali et al., 2014). Because of the high copy number, the ITS region is easy to amplify and sequence, even with samples from very old specimens (Larsson & Jacobsson, 2004). ITS has been found to be a suitable barcode for some groups in the Agaricales, including the genus Cortinarius (Liimatainen et al., 2014; Stefani, Jones & May, 2014) and the family Lyophyllaceae (Bellanger et al., 2015).

Although IGS had a high PCR success rate (100%) and suitable inter- and intra-specific variation, its sequencing success rate was relatively low (82%), which made it the second best marker after ITS for identification of Lepista species. IGS has been previously used to differentiate among species and even among strains within the same species in yeasts (Fell et al., 2000; Scorzetti et al., 2002). In the current study, the regions of nLSU and mtSSU lacked barcoding gaps in the analysis of intra- and inter-specific distance. tef1 showed clear barcoding gaps, but its amplification and sequencing success rates were low.

In preliminary studies, we also assessed the largest subunit of RNA polymerase II (RPB1) and RPB2, but we obtained only six sequences of RPB2 and one sequence of RPB1. These numbers of RPB1 and RPB2 sequences were too small for analysis of barcoding, and the two regions were therefore not included in this study.

According to the phylogenetic analysis based on the ITS region, the eight Lepista species received high support (≥98%), which demonstrates that ITS could be used for the identification of Lepista species. The two new clades identified in the present study may represent two new species. Identification of cryptic species by DNA barcoding has been reported in the other groups, such as Amillariella (Guo et al., 2016) and Pleurotus (Li et al., 2017). In future research, the morphological characteristics of Lepista sp 1 and L. sp 2 should be described, and the utility of ITS as a barcode for identification of additional Lepista species should be evaluated.

Conclusions

In this study, we assessed five regions for identifying a DNA barcode for eight Lepista species. Only the ITS region had the highest success rates of amplification and sequencing, substantially greater inter-specific than intra-specific variation. Therefore, we propose that the ITS region could be used as a suitable DNA barcode for the genus Lepista. And the ITS region also could separate all the tested Lepista species in the phylogenetic analyses. Overall, the ITS region was proved as a reference marker for the other species.

Supplemental Information

A neighbor-joining tree generated by analysis of five regions from eight Lepista spp.

Figure S1. A neighbor-joining tree generated by analysis of five regions from eight Lepista spp. Bootstrap values ≥70% are shown above the relevant branches. The eight Lepista spp. are highlighted in bold.

DOI: 10.7717/peerj.7307/supp-1

The 30 ITS sequences used in this study.

DOI: 10.7717/peerj.7307/supp-2

The 27 IGS sequences used in this study.

DOI: 10.7717/peerj.7307/supp-3

The 24 nLSU sequences used in this study.

DOI: 10.7717/peerj.7307/supp-4

The 28 mtSSU sequences used in this study.

DOI: 10.7717/peerj.7307/supp-5

The 21 tef1 sequences used in this study.

DOI: 10.7717/peerj.7307/supp-6

Combined regions tree.

DOI: 10.7717/peerj.7307/supp-8
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