Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

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

  • Jing Du ,

    Contributed equally to this work with: Jing Du, Hong-Bo Guo

    Roles Data curation, Writing – original draft

    Affiliation College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, Liaoning, China

  • Hong-Bo Guo ,

    Contributed equally to this work with: Jing Du, Hong-Bo Guo

    Roles Data curation, Formal analysis, Writing – original draft

    Affiliations College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, Liaoning, China, College of Life Engineering, Shenyang Institute of Technology, Fushun, Liaoning, China

  • Qi Li,

    Roles Data curation, Formal analysis

    Affiliation College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, Liaoning, China

  • Adrian Forsythe,

    Roles Methodology, Software

    Affiliation Department of Biology, McMaster University, Hamilton, Ontario, Canada

  • Xu-Hui Chen,

    Roles Resources

    Affiliation College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, Liaoning, China

  • Xiao-Dan Yu

    Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Resources, Software, Supervision, Writing – review & editing

    yuxd126@126.com

    Affiliation College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, Liaoning, China

Abstract

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 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.

Materials and methods

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.

thumbnail
Table 1. Sample sizes (number of basidiomata), locations, the type of climate and forest of eight Lepista nuda populations.

A total of 72 basidiomata were collected.

https://doi.org/10.1371/journal.pone.0202761.t001

thumbnail
Fig 1. Sampling sites of Lepista nuda in Northeast China.

Background information on the populations indicated in the right panel is provided in Table 1.

https://doi.org/10.1371/journal.pone.0202761.g001

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 GenBank 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 Master Mix (0.2 mM deoxynucleoside triphosphates, 4.0 mM MgCl2, and 2.5 U of Taq DNA polymerase), 1 μL of primer, 1 μL of template DNA, and 10.5 μL of ddH2O. The amplification included an initial denaturation at 94°C for 2 min; followed by 37 cycles of 35 s at 94°C, 45 s at 42–60°C, and 90 s at 72°C; and a final extension of 10 min at 72°C. For SRAP analysis, the reaction mixtures contained 12.5 μL of 2×Power TapPCR Master Mix, 1 μL of each primer, 1 μL of template DNA, and 9.5 μL of ddH2O. The amplification included an initial denaturation at 94°C for 5 min; followed by 35 cycles of 1 min at 94°C, 1 min at 50°C, and 1 min at 72°C; and a final extension of 10 min at 72°C. All of the PCR products were separated by electrophoresis on a 1.5% agarose gel with 1 × TBE buffer at 80 V for 3 h. The gels were stained with ethidium bromide and photographed under ultraviolet light (Bio-Rad ChemiDoc XRS, Hercules, CA, USA). The analyses were repeated at least twice, and molecular weights were estimated using a DNA marker (DNA Marker 2000, TIANGEN Biotech Co., Ltd., Beijing, China).

thumbnail
Table 2. ISSR and SRAP primer sequences for Lepista nuda.

https://doi.org/10.1371/journal.pone.0202761.t002

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 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 × (AControl—ASample)/AControl, 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.

Results

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 diversity was highest for the YC population (He = 0.2487, I = 0.3581) and lowest for the CBS population (He = 0.1291, I = 0.1835).

thumbnail
Table 3. Genetic diversity of Lepista nuda populations as indicated by ISSR and SRAP.

https://doi.org/10.1371/journal.pone.0202761.t003

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.

thumbnail
Table 4. Summary of the AMOVA results for 72 samples of Lepista nuda.

https://doi.org/10.1371/journal.pone.0202761.t004

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).

thumbnail
Fig 2. Relationship between geographic distance and genetic distance within the eight populations of Lepista nuda.

https://doi.org/10.1371/journal.pone.0202761.g002

thumbnail
Table 5. Nei’s genetic distance of Lepista nuda populations based on ISSR and SRAP.

https://doi.org/10.1371/journal.pone.0202761.t005

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.

thumbnail
Fig 3. UPGMA dendrogram of the eight populations of Lepista nuda.

https://doi.org/10.1371/journal.pone.0202761.g003

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 VC>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.

thumbnail
Fig 4. Column diagram analysis for antioxidant activity on water extract of each population.

Vitamin C was as a standard.

https://doi.org/10.1371/journal.pone.0202761.g004

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 [1315, 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.

Supporting information

S1 Fig. Fifty percent majority-rule Bayesian cladogram based on ITS sequence analyses.

The node support is indicated by Bayesian posterior probabilities on branch. Only support values greater than 0.60 in Bayesian are shown.

https://doi.org/10.1371/journal.pone.0202761.s001

(TIF)

S2 Fig. UPGMA dendrogram of 72 samples of Lepista nuda.

https://doi.org/10.1371/journal.pone.0202761.s002

(TIF)

Acknowledgments

We are thankful to Prof. Bruce Jaffee for correcting the English. This study was supported by the National Natural Science Foundation of China (No. 31200011, 31770014) and the Natural Science Foundation of Liaoning Province Science and Technology Department (201602668).

References

  1. 1. Dai YC, Zhou LW, Yang ZL, Wen HA, Bau T, Li TH. A revised checklist of edible fungi in China [in Chinese]. Mycosystema. 2010; 29:1–21. https://doi.org/10.1007/s10267-010-0068-1.
  2. 2. Singer R. The Agaricales in modern taxonomy. 4th ed. Koenigstein: Koeltz Scientific Books; 1986.
  3. 3. Phillips R. Mushrooms and other fungi of North America. Ontario: Firefly Books Ltd; 2010.
  4. 4. Li Y, Li TH, Yang ZL, Tolgor Dai YC. Atlas of Chinese Macrofungal Resources. Zhengzhou: Central Plains Farmers Press; 2015.
  5. 5. Toledo CV, Barroetaveña C, Fernandes Â, Barros L, Ferreira IC. Chemical and Antioxidant Properties of Wild Edible Mushrooms from Native Nothofagus spp. Forest, Argentina. Molecules. 2016; 21:1201. https://doi.org/10.3390/molecules21091201
  6. 6. Xu L, Wang Q, Wang G, Wu JY. Contents and Antioxidant Activities of Polysaccharides in 14 Wild Mushroom Species from the Forest of Northeastern China. Int J Med Mushrooms. 2015; 17:1161–1170. https://doi.org/10.1615/intjmedmushrooms.v17.i12.60 pmid:26854103
  7. 7. Alves MJ, Ferreira IC, Lourenço I, Costa E, Martins A, Pintado M. Wild mushroom extracts as inhibitors of bacterial biofilm formation. Pathogens.2014; 3:667–679.https://doi.org/10.3390/pathogens3030667 pmid:25438017
  8. 8. Liu JG, Diamond J. China’s environment in a globalizing world. Nature. 2005; 435:1179–1186.https://doi.org/10.1038/4351179a pmid:15988514
  9. 9. Beebee TJC, Rowe G. An introduction to Molecular ecology. 2nd ed. New York: Oxford university Press Inc.; 2008.
  10. 10. Wei HL, Liu ZX, Zhang WJ, He D, Li CX, Ma J. Analysis of genetic diversity of wild Lepista nuda population from Zhaotong, Yunnan [In Chinese]. Northern Horticulture.2015; 39:132–136.
  11. 11. Zlekienlcz E, Kafalskl A, Labuda D. Genome fingerprinting by simple sequence repeats (SSR)-anchored polymerase chain reaction amplification. Genomics. 1994; 20:176–183. https://doi.org/10.1006/geno.1994.1151 pmid:8020964
  12. 12. Li G, Quiros CF. Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction: Its application to mapping and gene tagging in Brassica. Theor Appl Genet. 2001; 103:455–461. https://doi.org/10.1007/s001220100570
  13. 13. Yao FJ, Lu LX, Wang P, Fang M, Zhang YM, Chen Y, Zhang WT, Kong XH, Lu J, Honda Y. Development of a Molecular Marker for Fruiting Body Pattern in Auricularia auricula-judae. Mycobiology. 2018; 46:72–78. https://doi.org/10.1080/12298093.2018.1454004 pmid:29998035
  14. 14. Liu J, Wang ZR, Li C, Bian YB, Xiao Y. Evaluating genetic diversity and constructing core collections of Chinese Lentinula edodes cultivars using ISSR and SRAP markers. J Basic Microbiol. 2015; 55:749–760. https://doi.org/10.1002/jobm.201400774 pmid:25589225
  15. 15. Zhang QS, Xu BL, Liu LD, Yuan QQ, Dong HX, Cheng XH, Lin DL. Analysis of genetic diversity among Chinese Pleurotu scitrinopileatus Singer cultivars using two molecular marker systems (ISSRs and SRAPs) and morphological traits. World J Microbiol Biotechnol. 2012; 28:2237–2248. https://doi.org/10.1111/mec.13408 pmid:22806047
  16. 16. Hasan HA, Almomany AM, Hasan S, Al-Abdallat AM. Assessment of Genetic Diversity among Pleurotus spp. Isolates from Jordan. J Fungi (Basel). 2018; 4:52. https://doi.org/10.3390/jof4020052
  17. 17. Yin Y, Liu Y, Li H, Zhao S, Wang S, Liu Y, Wu D, Xu F. Genetic diversity of Pleurotus pulmonarius revealed by RAPD, ISSR, and SRAP fingerprinting. Curr Microbiol. 2014; 68:397–403. https://doi.org/10.1007/s00284-013-0489-0 pmid:24241329
  18. 18. Ma DL, Yang GT, Mu LQ, Song YT. Application of SRAP in the genetic diversity of Tricholoma matsutake in northeastern China. Afr J Biotechnol. 2010; 9:6244–6250.
  19. 19. Zhang J, Chen H, Chen M, Wang H, Wang Q, Song X, Hao H, Feng Z. Kojic acid-mediated damage responses induce mycelial regeneration in the basidiomycete Hypsizygus marmoreus. PLoS One. 2017; 12:e0187351. https://doi.org/10.1371/journal.pone.0187351 pmid:29117227
  20. 20. Kaygusuz O, Kaygusuz M, Dodurga Y, Seçme M, Herken EN, Gezer K. Assessment of the antimicrobial, antioxidant and cytotoxic activities of the wild edible mushroom Agaricus lanipes (F.H. Møller & Jul. Schäff.) Hlaváček. Cytotechnology. 2017; 69:135–144. https://doi.org/10.1007/s10616-016-0045-4 pmid:28058568
  21. 21. Mercan N, Duru ME, Turkoglu A, Gezer K, Kivrak I, Turkoglu H. Antioxidant and antimicrobial properties of ethanolic extract from Lepista nuda (Bull.) Cooke. Annals of Microbiology. 2006; 56:339–344. https://doi.org/10.1007/bf03175028
  22. 22. Xu L, Wang Q, Wang G, Wu JY. Contents and Antioxidant Activities of Polysaccharides in 14 Wild Mushroom Species from the Forest of Northeastern China. Int J Med Mushrooms. 2015; 17:1161–1170. https://doi.org/10.1615/intjmedmushrooms.v17.i12.60 pmid:26854103
  23. 23. Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag; 2009.
  24. 24. Kahle D, Wickham H. ggmap: Spatial Visualization with ggplot2. The R Journal.2013; 5:144–161.
  25. 25. Geiger R. Klassifikation der Klimatenach W. Köppen" [Classification of climates after W. Köppen]. Landolt-Börnstein–Zahlenwerte und FunktionenausPhysik, Chemie, Astronomie, Geophysik und Technik, alte Serie. Berlin: Springer. 3. 1954. 603–607.
  26. 26. Geiger R. ÜberarbeiteteNeuausgabe von Geiger, R.: Köppen-Geiger / Klima der Erde. (Wandkarte 1:16 Mill.)–Klett-Perthes, Gotha. 1961.
  27. 27. Yu XD. Taxonomic and Molecular Systematic Studies on Tricholomataceae. Dissertation, Institute of Microbiology, Chinese Academy of Sciences. 2011.
  28. 28. White TJ, Bruns T, Lee S, Taylor J, 1990. Amplification and direct sequencing of fungal ribosomal RNA genes from phylogenetics. In: Innes MA, Gelfand DH, Sninsky JS, White TJ (eds), PCR protocols: methods and applications. Academic Press, London, pp 315e322.
  29. 29. Yu XD, Lv SX, Ma D, Li FF, Lin Y, Zhang L. Two new species of Melanoleuca (Agaricales, Basidiomycota) from northeastern China, supported by morphological and molecular data. Mycoscience. 2014; 55: 456–461. https://doi.org/10.1016/j.myc.2014.01.007
  30. 30. Alvarado P, Moreno G, Vizzini A, Consiglio G, Manjón JL, Setti L. Atractosporocybe, Leucocybe and Rhizocybe: three new clitocyboid genera in the Tricholomatoid clade (Agaricales) with notes on Clitocybe and Lepista. Mycologia. 2015;107:123–136.https://doi.org/10.3852/13-369 pmid:25344261
  31. 31. Hall TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series. 1999; 41: 95–98. https://doi.org/10.1007/978-1-4757-0905-6_31
  32. 32. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. The Clustal X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Research. 1997; 24: 4876–4882. https://doi.org/10.1093/nar/25.24.4876
  33. 33. Ronquist F, Huelsenbeck JP. MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics. 2003; 19: 1572–1574. https://doi.org/10.1093/bioinformatics/btg180 pmid:12912839
  34. 34. Nylander JAA. MrModelTest v2. Uppsala: Evolutionary Biology Center, University of Uppsala;2004.
  35. 35. Yeh FC, Boyle TJB. Population genetic analysis of co-dominant and dominant markers and quantitative traits. Belg J Bot.1997; 129: 157.
  36. 36. Peakall R, Smouse PE. Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes. 2006; 6: 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155
  37. 37. Miller M. Tools for Population Genetic Analysis (TFPGA), Version 1.3. A windows program for the analysis of allozyme and molecular population genetic data. Flagstaff: Department of Biological Sciences, Northern Arizona University;1997.
  38. 38. Rohlf F. NTSYS-pc Version 2.10 m, Numerical Taxonomy and Multivariate Analysis System (Computer Program). Steauket: Exeter Software; 2000.
  39. 39. Cheung LM, Cheung PCK, Ooi VEC. Antioxidant activity and total phenolics of edible mushroom extracts. Food Chemistry. 2003; 81: 249–255.https://doi.org/10.1016/s0308-8146(02)00419-3
  40. 40. Sun SJ, Gao W, Lin SQ, Zhu J, Xie BG, Lin ZB. Analysis of genetic diversity in Ganoderma population with a novel molecular marker SRAP. Appl Microbiol Biotechnol. 2006; 72: 537. https://doi.org/10.1007/s00253-005-0299-9 pmid:16411085
  41. 41. Ranker TA. Genetic diversity, mating systems, and interpopulation gene flow in neotropical Hemionitispalmata L. (Adiantaceae). Heredity. 1992; 69:175–183. https://doi.org/10.1038/hdy.1992.111
  42. 42. Zhao MR, Huang CY, Wu XL, Chen Q, Qu JB, Li YC, Gao W, Zhang JX. Genetic variability and population structure of the mushroom Pleurotuseryngii var. tuoliensis. Plos One. 2013; 8:e83253. https://doi.org/10.1371/journal.pone.0083253 pmid:24349475
  43. 43. Chen XH, Guan JJ, Ding R, Zhang Q, Ling XZ, Qu B. Conservation genetics of the endangered terrestrial orchid Liparis japonica in Northeast China based on AFLP markers. Plant Syst Evol.2013; 299:691–698. https://doi.org/10.1007/s00606-012-0744-z
  44. 44. Bao L, Kudureti A, Bai WN, Chen RZ, Wang TM, Wang HF, Wang HF, Ge JP. Contributions of multiple refugia during the last glacial period to current mainland populations of Korean pine (Pinus koraiensis). Sci Rep.2015; 5:18608. https://doi.org/10.1038/srep18608 pmid:26691230
  45. 45. Zeng YF, Wang WT, Liao WJ, Wang HF, Zhang DY. Multiple glacial refugia for cool-temperate deciduous trees in northern East Asia: the Mongolian oak as a case study. Mol Ecol.2015; 24:5676–5691. https://doi.org/10.1111/mec.13408 pmid:26439083
  46. 46. Debnath SC, Sion M. Genetic Diversity, Antioxidant Activities, and Anthocyanin Contents in Lingonberry. International Journal of Fruit Science.2009; 2: 185–199. https://doi.org/10.1080/15538360903005061
  47. 47. Sánchez C. Reactive oxygen species and antioxidant properties from mushrooms. Synthetic and Systems Biotechnology. 2016; 24:13–22. https://doi.org/10.1016/j.synbio.2016.12.001
  48. 48. Calvo AM, Wilson RA, Bok JW, Keller NP. Relationship between secondary metabolism and fungal development. Microbiology and Molecular Biology Reviews. 2002; 66:447–459. https://doi.org/10.1128/mmbr.66.3.447–459.2002 pmid:12208999