Evaluation of genetic diversity among Piptoporus betulinus as revealed by inter simple sequence repeat markers

ABSTRACT

Four populations of Piptoporus betulinus from Maoer, Changbai, Daxing'an and Xiaoxing'an Mountains were sampled. DNA was isolated and purified from fruiting bodies. Inter simple sequence repeat markers were first used to evaluate the genetic diversity and differentiation of P. betulinus in this study. The results showed that the strains from Xiaoxing'an Mountain had the highest diversity among the four populations, followed by the samples from Maoer and Daxing'an Mountains, whereas the Changbai Mountain samples harboured the lowest value. Cluster analysis and principal coordinates analysis indicated that all of the populations had the same type of geographical distribution (geographical affiliations). These findings will provide useful information for further research and utilization of wood-rotting fungi and will lay the foundation for development of genetic diversity in P. betulinus from various geographic origins.

KEYWORDS:

• Piptoporus betulinus
• genetic diversity
• genetic differentiation
• geographical distribution
• ISSR

Introduction

In nature, wood-rotting fungi play an important role in the cyclic utilization of timber. These fungi have a wood biodegradation function due to an efficient enzyme system and include two main basidiomycetes: white-rot fungi, which can break down lignin using a lignin-degrading enzyme, and brown-rot fungi, which hydrolyse cellulose and hemicellulose using cellulase. Piptoporus betulinus is one of the most common of these fungi and can cause brown-rot disease in trees. In addition, this species has been widely used for many centuries in China as a traditional medicine to treat various diseases, including oral ulcer, gastroenteric disorder, hepatocirrhosis, inflammation and cancers [1] and as a source of antioxidant [2], anti-inflammatory [3], antidiabetic and antitumour agents [4]. Therefore, due to its health benefits, P. betulinus has obtained general acceptance worldwide as an effective medicine.

P. betulinus has a global distribution and is found in Europe, Asia, northern and southern Africa and eastern North America [5–7]. In general, the optimal growth temperature of brown-rot fungi is 27–38 °C [6]; thus, P. betulinus is suitably grown in northern China with good distribution, such as in the Heilongjiang, Inner Mongolia and Liaoning Provinces. This brown-rot fungus is especially parasitic on Betula platyphylla [8]. In particular, this fungus can be found in dead, standing trees. This species is easy to identify based on its external fruiting body and has a good distribution in China, making it amenable to population genetics research.

To date, many studies have assessed genetic variation in fungi using molecular marker techniques [9–11]. Among these techniques, inter simple sequence repeat (ISSR) markers are co-dominant traits following Mendelian patterns. This method has the advantages of random amplified polymorphic DNA and amplified fragment-length polymorphism. Accordingly, it shows simplicity, reliability, a moderate through-put ratio and easy sequencing of selected bands [12]. Therefore, ISSR markers have been applied for map construction [13], comparative genetics [14] and genetic diversity analyses [15].

Currently, there are large numbers of reports on genetic diversity using ISSR markers in different fungi, such as Chinese Lentinula [16], Solanum nigrum L. [17] and Tilletia controversa Kühn [18]. To increase the efficiency of characterization and utilization of P. betulinus germplasm resources, an ISSR marker was first used in this investigation to analyse the genetic variability and differentiation of this fungus, collected mainly from north-eastern China, for further effective protection, management and use of P. betulinus. Therefore, this work attempts to establish suitable media and to lay the foundation for further study and reasonable application of wood-degrading fungi.

Materials and methods

Strains

The four populations of P. betulinus were sampled from Maoer Mountain (Heilongjiang, China), Changbai Mountain (Jilin, China), Daxing'an Mountain (Heilongjiang, China) and Xiaoxing'an Mountain (Heilongjiang, China) (Figure 1). Detailed locations of the studied populations are provided in Table 1. Fruiting bodies were cut into small pieces (0.5 mm), surface sterilized in ethyl alcohol (75.0%, w/v) for 1 min, rinsed 4–5 times in sterile deionized water and cultured on potato dextrose agar at 28 °C in order to obtain mycelia. The mycelia were stored at 4 °C for genomic DNA extraction [19].

Figure 1. Sampling sites of P. betulinus.

Table 1. Sampling sites of P. betulinus.

Population	Sampling location	Geographical location	Sample size	Sample codes
Population 1	Xiaoxing'an Mountain	N47°43′ E128°50′	5	X2-1, X2-2, X2-3, X5, X6
Population 2	Daxing'an Mountain	N52°19′ E124°42′	3	D3, D4, D5
Population 3	Maoer Mountain	N47°43′ E128°54′	5	M4, M5-1, M5-2, M6-4, M7
Population 4	Changbai Mountain	N42°06′ E128°04′	2	C1, C2

DNA extraction

For each sample, genomic DNA was extracted from 0.1 g of mycelium using the cetyl trimethylammonium bromide method of Doyle [20]. The integrity and purity of isolated DNA was checked by gel electrophoresis in a 1.0% agarose gel. The DNA concentration was determined at 260 nm using a spectrophotometer (UV-1800, Shimadzu, Kyoto, Japan). Then, the DNA samples were diluted to 50 ng/μL and stored at −20 °C for polymerase chain reaction (PCR) amplification.

ISSR amplification

The ISSR reaction was performed as previously described by Meng et al. [21] with minor modifications. A total of 100 primers used in this study were obtained from the University of British Columbia, Vancouver, Canada (www.ubc.ca/). ISSR--PCR amplification was performed in a 200 μL centrifuge tube containing 50 ng of template DNA, 10 pmol primers, 0.25 mmol/L deoxyribonucleoside triphosphates, 0.5 U of Taq polymerase (TAKARA, Kyoto, Japan), 1× PCR buffer and 2.5 mmol/L Mg²⁺. DNA amplification was carried out in a Perkin–Elmer Cetus DNA 480 thermal cycler (Perkin-Elmer Cetus, Norwalk, CT, USA). The cycling programme was as follows: 1 cycle of 3 min at 94 °C; then 40 cycles of 1 min at 94 °C, 1 min at 55 °C and 1 min at 72 °C, followed by a final cycle of 10 min at 72 °C. The amplification products were detected in a 1.5% agarose gel in 1× Tris–acetate–ethylenediaminetetraacetic acid buffer for 1 h at 100 V and photographed by Bio Image Systems (GG/D2-GeneGenius2, Frederick, MD, USA), and their molecular weights were estimated based on the DL 2000 Marker (TAKARA, Kyoto, Japan).

Data analysis

Each primer was used to amplify all of the samples, and the band patterns with high resolution, good repeatability and reproducibility were scored manually as present (1) or absent (0) to produce a set of binary code for ISSR analysis. To estimate and embody the genetic diversity level of P. betulinus, several parameters were calculated using PopGen32 software (version 1.32), including the observed number of alleles (Na), the effective number of alleles (Ne), Nei's gene diversity (h), Shannon's information index (I), the number of polymorphic loci (PL) and percentage of polymorphic loci (PPL) of populations, Nei's genetic differentiation index (Gst), the total gene diversity (Ht), the genic diversity within a population (Hs), the gene flow (Nm), Nei's gene diversity (H) and Nei's genetic distance (D) [22]. Analysis of molecular variance was used to determine the genetic differentiation and relationship between populations [23,24]. The unweighted pair group method with arithmetic average (UPGMA) dendrogram construction based on Jaccard's similarity coefficients was performed with the SHAN program [25,26]. Finally, principal coordinates analysis (PCoA) was performed to generate three-dimensional (3D) scatter plots and evaluate the genetic distribution of individual accessions [27].

Results and discussion

In the present study, 7 out of 100 ISSR primers with clear high-intensity and relatively high polymorphism bands were selected and used to amplify 15 P. betulinus strains from four populations. A total of 74 reproducible fragments were obtained with an average of 10.57 fragments per primer, and the band size varied from 150 to 2000 bp. The number of PL ranged from 7 (I857) to 14 (I825) (Table 2). All of these amplified bands were polymorphic (100%).

Table 2. PCR products amplified by using each primer in P. betulinus based on ISSR markers.

Primer	Sequence (5′-3′)	Total bands	Number of polymorphic loci (PL)	Percentage of polymorphic loci (PPL) (%)	Band size (bp)
I818	(CA)8-G	11	11	100	200–1500
I825	(AC)8-T	14	14	100	400–2000
I834	(AG)8-YT	12	12	100	150–1300
I835	(AG)8-YC	12	12	100	300–1500
I847	(CA)8-RC	10	10	100	300–1000
I857	(AC)8-YG	7	7	100	350–1200
I873	(GACA)4	8	8	100	400–1200
Total		74	74	–	150–2000
Mean		10.57	10.57	100	–

Note: Y = (C, T), R = (A,G).

As shown in Table 2, the observed number of alleles (Na), the effective number of alleles (Ne), Shannon's index (I) and Nei's gene diversity (h) in population 1 (Xiaoxing'an Mountain) were the highest among the four populations (Na = 1.7435, Ne = 1.4418, I = 0.3896, h = 0.2591). The above four parameters were the lowest in population 3 from Maoer Mountain (Na = 1.1892, Ne = 1.1338, I = 0.1144, h = 0.0784). PL and PPL are important indicators for estimating the level of variation and are also significant for the diversity among species. Species harbouring a high PPL have strong environmental adaptiveness and competitiveness, whereas those with a low PPL have a weak environmental adaptiveness and may even be eliminated in long-term evolution. By analysing the number of alleles and PPL using ISSR, we found that the PL ratio in the four locations ranged from 18.9% to 74.3%, indicating high genetic variation of P. betulinus in these locations (Table 3).

Table 3. Nei's gene diversity analysis in P. betulinus from different collections.

Population	Observed number of alleles (Na)	Effective number of alleles (Ne)	Nei's gene diversity (h)	Shannon's information index (I)	Polymorphic bands (PB)	Percentage of polymorphic bands (PPB)
Population 1	1.7432 ± 0.4398	1.4418 ± 0.3722	0.2591 ± 0.1889	0.3896 ± 0.2633	55	74.3%
Population 2	1.540 5± 0.5018	1.3662 ± 0.3915	0.2103 ± 0.2073	0.3102 ± 0.2977	40	54.1%
Population 3	1.1892 ± 0.3943	1.1338 ± 0.2788	0.0784 ± 0.1633	0.1144 ± 0.2385	14	18.9%
Population 4	1.6351 ± 0.4847	1.3630 ± 0.3528	0.2182 ± 0.1911	0.3301 ± 0.2744	47	63.5%
Mean	2.0000 ± 0.0000	1.5160 ± 0.3134	0.3115 ± 0.1437	0.4766 ± 0.1769	74	100.0%

The highest values of PPL, PL and I observed through ISSR analysis in population 1 from Xiaoxing'an Mountain indicate higher genetic diversity of P. betulinus from Xiaoxing'an Mountain than in the population from Changbai Mountain, where these indices were the lowest. This difference might be due to the geographical location (Tables 2 and 3). Changbai Mountain, with relatively abundant rainfall, has the highest altitude of the four sampled areas and is affected by low temperature and ultraviolet stress, resulting in the relative isolation of P. betulinus. Indeed, similar results have been reported for Saccharomyces cerevisiae [28] and marine fungi [29]. Persson et al. [30] reported that the genetic diversity among populations of Lilium martagon L. was positively correlated with the total number of samples in a plant. However, 2–5 samples from each area, providing a total of 15 samples, might affect the estimate of diversity of the populations to a certain degree. It is noteworthy that the propagation characteristics of fungi are markedly different from those of plants, mainly depending on wind power; thus, further study of the relation between the population and diversity of fungi is needed.

Here, we found that the genetic identity of P. betulinus ranged from 0.1526 to 0.2289, and the distance from 0.7954 to 0.8585 (Table 4). These genetic data indicate that the four populations were related but not exactly the same. It could be expected that populations with lower genetic distance must have a higher genetic similarity.

Table 4. Nei's genetic similarity (above diagonal) and genetic distance (below diagonal) coefficient of groups of P. betulinus.

	Population 1	Population 2	Population 3	Population 4
Population 1	***	0.8522	0.8157	0.7954
Population 2	0.1599	***	0.8585	0.8422
Population 3	0.2037	0.1526	***	0.8422
Population 4	0.2289	0.1718	0.1847	***

Genetic similarity and distance reflect differentiation in different ways (Table 4). A high level of differentiation could be caused by genetic drift and gene flow [31]. There are multiple explanations for this, including that the diffusion and spread of conidiophores are important factors influencing gene flow, which further affects the genetic structure and diversity of populations [32,33]. In addition, wind power plays a vital role in the spreading process. The distance of spore dissemination is restricted by wind strength and environmental conditions (e.g. geographical isolation), resulting in gene exchange among different groups. On the other hand, P. betulinus is a major parasite that is found on dead standing trees or fallen trees of birch and related hosts, which are relatively few and scattered in these four sites, causing slow self-renewal and limited population expansion. Therefore, low gene flow, limited spore spreading and limited population sizes may be considered to have caused the genetic differentiation of the studied P. betulinus populations.

With a common node at a 60% Jaccard's similarity coefficient, the dendrogram clustered the different strains into two independent groups (Figure 2). Group I included all of the samples from population 1 and population 2. Except for D5, the samples from population 3 and population 4 were placed in the same group (Group II). This result suggests that the clustering depended on the sample collection, indicating a similar genetic background in a collection area. Interestingly, the PCoA clearly separated the 15 accessions into two groups, in accordance with the UPGMA cluster analysis (Figure 3). These results show the relationship between the genetic characteristics and the geographical distribution of P. betulinus.

Figure 2. UPGMA dendrogram of 15 P. betulinus strains based on Jaccard's coefficient of ISSR marker.

Figure 3. Principal coordinates analysis for ISSR markers of P. betulinus accessions.

Many previous reports have shown that the genetic diversity of species is markedly related to their geographical distribution [21,27,34]. In agreement with these findings, in this work, 15 individuals were separated into two independent clusters according to UPGMA and PCoA clustering analyses (Figures 2 and 3), reflecting the type of geographic distribution of these fungi. The 15 individual strains collected from four places in north-eastern China could represent the whole forest ecosystem of the Northeast. Group I represents the Songnen Plain, with fertile soil and an extremely low mean annual temperature. Group II samples were mainly found in the Liaodong Peninsula, with a relatively abundant rainfall and high altitude. These results clearly indicate a distinct genetic differentiation between P. betulinus from various geographic origins. Grouping by the two clustering methods revealed geographical affiliations [35]. Therefore, the differentiation of P. betulinus gene pools from different areas might lead to reproductive isolation and divergent natural selection arising from wide geographic separation. This study builds the basis for further effective protection, management and use of P. betulinus germplasm resources in genetics and ecosystems research.

Conclusions

The results from this study showed that, overall, ISSR markers are an effective tool for evaluating the genetic diversity of P. betulinus grown in north-eastern China. Cluster analysis and PCoA indicated that all of the populations had the same type of geographical distribution (geographical affiliations). This study could provide insight into the high level of genetic differentiation and a basis for further, more detailed investigations to understand the contribution to fungi conservation.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the Fundamental Research Funds for the Central University [2572014CA22].