Genetic diversity of Lepista nuda (Agaricales, Basidiomycota) in Northeast China as indicated by SRAP and ISSR markers

Lepista nuda is a popular wild edible mushroom that grows in China. In this study, we used ISSR and SRAP molecular markers to analyze the genetic diversity of 72 samples of L. nuda from eight populations in Northeast China. In total, six ISSR primers and five pairs of SRAP primers that produced clear and polymorphic banding profiles were selected for assessing L. nuda genetic diversity. The results revealed a high level of genetic variation among the 72 samples (94.4% polymorphism) but a low degree of gene flow among the populations. Among L. nuda populations, genetic distance was not correlated significantly with geographic distance. The antioxidant activity of the samples from each population was also tested and the result showed that all the selected samples had more than 60% DPPH scavenging activities. Nonetheless, the antioxidant activity diversity is not coincident with both the genetic diversity and the geographic distribution. The results indicate that ISSR and SRAP molecular markers are useful for studying the genetic diversity of L. nuda. The results also suggest that L. nuda populations in Northeast China require protection.


Introduction
Lepista nuda (Bull.) Cooke is a popular edible mushroom in China [1], and natural populations are common throughout Northeast China. The species also grows naturally in Europe and North America but has not been grown commercially [2,3]. Lepista nuda can be distinguished from other species by its lilac to purple-pink pileus, its white to pale-pink spore print, and its distinctive odor [3,4]. This fungus is considered to be delicious by humans, and its fruiting bodies are also nutritious in that they contain high levels of proteins [5] and polysaccharides [6]. In addition, L. nuda extracts can inhibit the in vitro formation of biofilms by multi-drug-resistant bacteria [7].
In recent years in China, wild specimens of L. nuda have been extensively collected for their commercial value, and the habitat of the species has been frequently destroyed [8], suggesting that the species may be endangered in the country. Information on the genetic diversity of an a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 endangered species can provide insight into its genetic health [9] and perhaps into its conservation, domestication, and breeding. To date, however, little is known about the population genetics of L. nuda. An analysis of ITS sequences of 66 samples of L. nuda revealed a low level of genetic diversity, but these samples were collected from only one site in China [10].
DNA fingerprinting methods have been widely used to study the genetic diversity of fungi. These methods, including the use of ISSR (inter-simple sequence repeats) [11] and SRAP (sequence-related amplified polymorphism) [12], have proven to be useful for evaluating the genetic diversity of edible mushrooms such as Auricularia auricula-judae (Bull.) Quél. [13], Lentinula edodes (Berk.) Pegler [14], Pleurotus citrinopileatus Singer [15], Pleurotus eryngii (DC.) Quél. [16], Pleurotus pulmonarius (Fr.) Quél. [17], and Tricholoma matsutake (S. Ito & S. Imai) Singer [18]. Antioxidants play an important role to maintain the cell functioning and integrity of the cells. They can help neutralize the damaging free radicals of the human body. It has been reported that certain types of mushroom possess antioxidant properties [19,20]. Previous studies have shown that the sporophore of L. nuda has obvious antioxidant activity [21,22]. In the current study, ISSR and SRAP markers were used to investigate the genetic diversity of eight natural populations of L. nuda in Northeast China. In addition, relationship between antioxidant capacity and genetic diversity of each population was studied.

Ethics statement
Lepista nuda is 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
A total of 72 samples (basidiomata) were collected from eight sites in Northeast China from September 2012 to August 2015 (Fig 1). Sampling sites of Lepista nuda were drew by R Statistical Software [23] and packages ggplot2 and ggmap [24]. The sample size, the geographical coordinates and the types of climate and forest [25,26] for each site are listed in Table 1. Tissue blocks were removed from the inner part of the fresh basidiomata; the blocks were dried with silica gel for DNA analyses.

Identification of samples
Genomic DNA was extracted from the dried tissue blocks using a modified cetyltrimethyl ammonium bromide (CTAB) method [27]. The extracts were treated with 5 μl of RNase (10 mg/ml) in a 37˚C water bath for 1 h to remove RNA. The purity and quality of the genomic DNA were determined via spectrophotometry and electrophoresis on a 1.0% agarose gel. The DNA solution was stored at -20˚C. One sample was then randomly selected from each population, and the ITS regions of these samples (eight in total) were then amplified and sequenced to determine whether the collected fungi were Lepista nuda. Primers ITS5/ITS4 [28] were used for amplification of the ITS region including ITS1, 5.8S, and ITS2. Amplification reactions were performed in a PCR Amplifier (BIO-RAD S1000, Hercules, CA, USA) in 25-μL reaction mixtures. Both reaction mixtures and PCR conditions followed those in previous study [29]. The amplified products were purified and sequenced using ABI prism 3730 Genetic Aanlyzer (PE Applied Biosystems, Foster, CA, USA). The accession numbers are MH428836-MH428843.
Based on the results of Alvarado et al. [30], a total of 16 ITS sequences retrieved from Gen-Bank and aligned with the eight ITS sequences amplified from this study by BioEdit 5.0.6 [31] and Clustal X [32]. Two species Clitocybe favrei (GU234009) and C. vibecina (GU234049) were used as the outgroup. The data matrice for ITS sequences analysis was produced. Bayesian analysis was conducted with MrBayes v.3.1.2 [33]. The best-fitting model of sequence evolution was chosen by MrModelTest v.2.2 [34]. The Bayesian analysis was run, under the GTR  model, with four chains, and trees sampled every 500 generations. The average split frequencies were checked to determine optimal convergence of the chains below 0.01 after 2,000,000 generations. The first 25% of the sample trees was designated as burn-in, and the remaining samples were retained for further analyses. The topologies were used to generate a 50% majority-rule consensus tree for posterior probabilities (PP).

ISSR and SRAP amplification
A total of 14 primers that produced clearly distinguishable and reproducible fragments were selected and used in this study for ISSR and SRAP analyses ( Table 2). All of the amplification reactions were performed in a PCR Amplifier (BIO-RAD S1000, Hercules, CA, USA) in 25-μL reaction mixtures. For the ISSR analysis, the reaction mixture contained 12.5 μL of 2×Power TapPCR

Data analysis
Image Lab software (Bio-Rad ChemiDoc XRS, Hercules, CA, USA) combined with visual assessment was used to score DNA bands on the gels as "1" for present or "0" for absent, which generated a binary matrix. To increase the number of genetic loci, the DNA bands produced by ISSR and SRAP markers were combined. Genetic diversity analysis was performed using POPGENE version 1.31 [35]. Components of genetic variance within and among populations were estimated by analysis of molecular variance (AMOVA) using GenAlEx version 6.5 [36]. The correlation between population genetic distance and geographic distance was assessed by (GA) 8  Mantel tests using the TFPGA version 1.3 [37]. Finally, a UPGMA dendrogram was constructed by using NTSYS-pc version 2.10 [38].

Antioxidant activity analysis
One represented sample was randomly selected from each location and the dried mushrooms were ground into a fine powder by a crushed mill, and then were through a 0.15-mm sieve for further analysis. Mushroom powders were extracted by using distilled water for 3 hours at 75˚C. After centrifuging, the extracting solution was tested the antioxidant activity. The scavenging activity of the water extracts from each sample on DPPH radicals was measured according to the method of Cheung et al. [39] with some modifications. We tested concentration (40 μg/mL) of mushroom water extract and used water to instead of mushroom water extract as a control. We used vitamin C as a standard. The reaction mixture was vortex mixed at room temperature and the absorbance (Abs) was measuring at 517 nm with a spectrophotometer. The scavenging activity of the DPPH radical was calculated using the following equation: Scavenging activity (%) = 100 × (A Control -A Sample )/A Control , where A Control is the absorbance of the control reaction (containing all reagents except the test extract) and A Sample is the absorbance of the test compound.

Identification of samples
A phylogenetic tree based on ITS region showed that the eight sequences from this study and L. nuda formed a monophyletic clade with strong support (PP = 0.96). The result confirmed that the samples used in this study were the species of L. nuda (S1 Fig).

Genetic diversity of L. nuda populations
As noted earlier, POPGENE software was used to analyze the combined ISSR and SRAP data.
The results showed that the number of polymorphic bands in the eight populations ranged from 63 to 127 and that the percentage of polymorphic bands ranged from 29.4 to 59.4%, with an average of 47.6% (Table 3). Among all 72 samples, the number of polymorphic bands, the percentage of polymorphic bands, Nei's genetic diversity index, and Shannon information index were 202,94.4%,0.3411,and 0.5042, respectively. Among the populations, genetic The AMOVA revealed significant genetic differences among populations (Table 4), which was consistent with the Nei's genetic diversity analysis. The highest percentage of the total genetic variance was the variance within the separate populations (42%). The genetic variance was 29% both among regions and among populations within regions. The gene flow (Nm = 0.6265) between the populations of L. nuda was estimated by the AMOVA analysis.

Genetic distances between the populations
The genetic distances between the eight populations of L. nuda ranged from 0.0740to 0.3731 ( Table 5). The genetic distance was smallest between the BX and the HR population, which are located in the same region, and was largest between the MDJ population and the CBS population, which are located in Heilongjiang Province and Jilin Province, respectively. The Mantel test indicated an absence of significant correlation between genetic distance and the geographical distance (r = 0.271; P = 0.12) (Fig 2).

Cluster analysis
The ISSR and SRAP data were combined and analyzed by NTSYS software to generate UPGMA dendrogram (Figs 3 and S1). When the similarity coefficient was set at 0.64, the eight populations of L. nuda formed three clades. The three populations in clade I were from Heilongjiang Province, and the five populations in clade II were from Jilin and Liaoning Provinces. The one population in clade III was from Changbai Mountain.

Antioxidant activity analysis
The free radical scavenging of DPPH can be used to evaluate the antioxidant activity of extracts. In Fig 4, water extracts of eight samples exhibited more than 60% DPPH scavenging activities, indicating that all of the L. nuda samples had efficient antioxidant activity. The scavenging effects of water extracts from each population and standard on the DPPH radical decreased in the order of V C >YC>BX>CBS>HR>MDJ>CC>NI>SY and were 88.9, 77.7, 73.5, 72.0, 71.5, 67.4, 65.0, 64.2 and 63.8 at the concentration of 40 μg/mL, respectively.

Discussion
SRAP molecular marker were originally developed for gene tagging in Brassica oleracea L. to specifically amplify coding regions of the genome [12]. SRAP have application in the fields of systematics, conservation, biogeography, and ecology, because they are easy to develop and use, are inexpensive, required small amounts of tissue, and can be used to detect high levels of polymorphism. For fungi, SRAP was initially used to analyze the genetic diversity of Ganoderma strains  [40], then it was applied successfully in the studies of genetic diversity of some edible mushroom [13-15, 17, 18]. In this study, the genetic diversity of 72 samples of the wild edible mushroom Lepista nuda from Northeast China was investigated by use of ISSR and SRAP molecular markers. Six single primers for ISSR and five primer pairs for SRAP revealed a high level of genetic variation among the 72 samples. A total of 214 loci were found in the eight populations of L. nuda. Among them, 202 loci were polymorphic (91 loci for ISSR; 111 loci for SRAP), and the percentage of polymorphism was as high as94.4%. The results showed that the average polymorphic loci of each SRAP primer pair was much higher than some other species (22 loci for L. nuda vs. 12 loci for Lentinula edodes [14] and 8 for Pleurotus citrinopileatus [15]). The average polymorphic loci generated by each ISSR primer of L. nuda (15 loci) were similar to the other species, such as L. edodes (14 loci) [14] and P. citrinopileatus (8 loci) [15]. Therefore, the ISSR and SRAP markers were found to be useful tools for studying the genetic diversity of L. nuda. Generally, gene flow was low when Nm value was less than 1.0 [41]. In this study, the Nm value was 0.6265, which shows that the gene flow of L. nuda in Northeast China is weak. In comparison, the gene flow of Pleurotus eryngii var. tuoliensis was found to be 1.794 [42]. The weak gene flow of L. nuda has at least two possible explanations. First, the species usually grows during the rainy season, and rain might limit the spread of spores. Second, habitat fragmentation in Northeast China is likely to reduce the exchange of spores between populations.  The genetic distance between eight L. nuda populations was not correlated with their geographical distance. For example, the geographic distance was greatest between the YC population and BX population (909 km), but the genetic distance was highest between the MDJ and the CBS populations (0.3731). The results also showed that all of the genetic distances between the CBS population and the other populations were very high. A similar phenomenon was reported for the plant Liparis japonica in Northeast China [43]. This lack of significant correlation between geographic and genetic distance might be explained by Changbai Mountain, which is believed to have been a refuge in the Last Glacial Maximum [44,45]. A refuge in Changbai Mountain would enable the long-term survival of isolated L. nuda populations and might thereby promote the development of genetic differences unrelated to geographic distance.
Although L. nuda currently has a wide geographical distribution in Northeast China, the species may be endangered. On the one hand, the populations are small, and the habitat is increasingly fragmented. On the other hand, the results of this study indicate that gene flow among populations is low. We therefore suggest that measures are needed to protect the genetic resources of the species. We suggest that harvesting of L. nuda in Northeast China should be limited. It might also be useful to collect and store basidiomata as a gene bank for the species. The introduction of basidiomata from other places could increase the number of genotypes. Finally, domestication of L. nuda could reduce the harvesting of wild populations.
In the present study, the samples of each population showed antioxidant activity to some extent, while the trend of antioxidant activity diversity is not consistent with either the genetic diversity or the geographic distribution of each population. Samir and Mathilde [46] obtained a similar result in the study of Lingonberry. They suggested that the possible reason for the disagreement between the chemical and molecular diversity was that the noncoding genes of genome are not accessible to the expression of antioxidant activity. Fungi are able to produce many secondary metabolites with antioxidative activities including a number of phenolic compounds, ascorbic acid and so on [47]. The production of these antioxidant agents usually affected by the environmental factors, such as pH value and nutritional conditions [48]. Therefore, the differences in the collection time and location of the samples might have resulted in the inconsistent between the molecular and chemical diversity.