Genetic diversity assessment of a germplasm collection of Salvia miltiorrhiza Bunge. based on morphology, ISSR and SRAP markers

Biochemical Systematics and Ecology 55 (2014) 84–92

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Genetic diversity assessment of a germplasm collection of Salvia miltiorrhiza Bunge. based on morphology, ISSR and SRAP markers Liang Peng a, d, Mei Ru b, Bangqing Wang a, Yong Wang a, Bo Li a, Jing Yu a, Zongsuo Liang a, c, * a

College of Life Sciences, Northwest A&F University, Yangling, PR China Institute of Soil and Water Conservation, Chinese Academy of Sciences, Yangling, PR China College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, PR China d College of Pharmacy, Shaanxi University of Chinese Medicine, Xi’an, PR China b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 12 November 2013 Accepted 25 January 2014 Available online

Salvia miltiorrhiza is one of the most important traditional Chinese medicinal plants for its therapeutic effects. In the present study, morphological traits, ISSR (inter-simple sequence related) and SRAP (sequence-related amplified polymorphism) markers were used to analyze the genetic diversity of 59 S. miltiorrhiza phenotypes. Out of the 100 ISSR primers and 100 SRAP primer combinations screened, 13 ISSRs and 7 SRAPs were exploited to evaluate the level of polymorphism and discriminating capacity. The results showed that the 13 ISSRs generated 190 repeatable amplified bands, of which 177 (93.2%) were polymorphic, with an average of 13.6 polymorphic fragments per primer. The 7 SRAPs produced 286 repeatable amplified bands, of which 266 (93.4%) were polymorphic, with an average of 38.1 polymorphic fragments per primer. Cluster analysis readily separated different morphological accessions, wild and cultivated controls based on morphological traits, ISSR and SRAP markers. The study indicated that morphological traits, ISSR and SRAP markers were reliable and effective for assessing the genetic diversity of phenotypic S. miltiorrhiza accessions. The overall results suggested that the introduction of genetic variation from morphology-based germplasms enlarged the genetic base for the collection, conservation and further breeding program of S. miltiorrhiza germplasm. Ó 2014 Elsevier Ltd. All rights reserved.

Keywords: Salvia miltiorrhiza Genetic diversity ISSR SRAP Morphological traits

1. Introduction Salvia miltiorrhiza Bge., commonly known as Danshen in China, is one of the most important and widely used traditional herbal medicines in Asia countries for thousands of years (Lu and Yeap Foo, 2002). There is an increasing commercial demand for this plant due to its excellent prevention and treatment of cardiovascular diseases, hepatocirrhosis, chronic renal failure, Alzheimei’s disease, angina pectoris, myocardial ischemia, liver diseases, and diabetic nephropathy (Sugiyama et al., 2002; Cheng, 2006; Cao et al., 2013). The medical importance generates a great interest among researchers and companies to

* Corresponding author. College of Life Sciences, Northwest A&F University, Yangling, PR China. Tel./fax: þ86 029 87092262. E-mail address: [email protected] (Z. Liang). http://dx.doi.org/10.1016/j.bse.2014.01.020 0305-1978/Ó 2014 Elsevier Ltd. All rights reserved.

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assess the existing natural genetic diversity, for germplasm conservation, selection and further breeding of superior genotypes of S. miltiorrhiza. Currently, wild and cultivated S. miltiorrhiza mostly distribute in central and eastern China (Li et al., 2009). Breeding programs have tended to identify the genetic diversity of different S. miltiorrhiza germplasms in the primary stage of the breeding process (Song et al., 2010). Most of the current S. miltiorrhiza populations are complex hybrids with genetic backgrounds from several wild populations or cultivars (Li, 2008). In terms of the extent and pattern of genetic diversity among populations, genetic characterization is essential not only to unveil the magnitude of genetic diversity available in the germplasm for conservation but to determine useful genes for possible progress in future breeding programs. Screening and selection would be more likely to discover better and promising genotypes if germplasm sources are genetically diverse. Complete characterization of S. miltiorrhiza genetic resources is an important link between the conservation and utilization of this germplasm. Zhang et al. (2013) reported genetic variation exists among S. miltiorrhiza populations and it is usually seen as differences in distinct origins and resources. Prior research has mainly focused on yield, plant cultivation, metabolic profiles, pharmacological activity and considerable efforts hitherto have been made on systematic S. miltiorrhiza family (Liu et al., 2011; Yang et al., 2012; Liang et al., 2013). However, there has been a long lack of studies about morphologybased and molecular-based germplasm collections particularly for S. miltiorrhiza with different morphological traits. Qualitative and quantitative morphological characteristics are necessary to evaluate the genetic diversity among various sources before starting DNA-based studies (Tatineni et al., 1996; Tar’an et al., 2005; Smýkal et al., 2008). Molecular markers that reveal polymorphism at the DNA level have been considered as a powerful tool for the estimation of plant genetic diversity characterization and also to discriminate different morphological individuals from different sources (Smýkal et al., 2008; Li et al., 2010; Keneni et al., 2011). Various molecular markers have been successfully used to characterize S. miltiorrhiza germplasm, such as inter simple sequence repeat (ISSR) (Song et al., 2010; Zhang et al., 2013), sequence-related amplified polymorphism (SRAP) (Song et al., 2010), amplified fragment length polymorphisms (AFLP) (Guo et al., 2002; Yang et al., 2012), and simple sequence repeat (SSR) (Deng et al., 2009). Among them, ISSR is a simple and efficient marker system for estimation and identification of genetic diversity for plant germplasm collection. SRAP has been used in genetic diversity, gene tagging, map construction, and phylogenetic studies in a wide range of plants. To the best of our knowledge, there has been no detailed information about the genetic diversity of morphology-based S. miltiorrhiza germplasm. The objective of the present study was to assess the genetic diversity and characterization of 53 S. miltiorrhiza phenotypes compared to the wild and cultivated controls, using morphological traits, ISSR and SRAP markers. For the purpose of germplasm conservation and further progress in breeding, we have also established a germplasm repository of S. miltiorrhiza in medicinal botanical garden at Northwest A&F University, China. 2. Materials and methods 2.1. Plant material Samples containing 3 wild controls, 3 cultivated controls and 53 different morphological S. miltiorrhiza (Dms) were collected from Shaanxi province in China. Among the 53 different morphological accessions, Dms1 to Dms31 were from the wild species and Dms32 to Dms53 were from the cultivated species. All of the samples were planted in medicinal botanical garden at Northwest A&F University, China during 2011–2012. 2.2. Morphological characterization The morphological characterization of 59 accessions was accomplished in an experimental field during the summer season in 2012. All leaf related traits were recorded from the third fully expanded leaves. Eleven qualitative characters (leaf color, stem color, leaf frontal character, leaf fuzz, petiole color, flower color, hypanthium color, underlip margin color, underlip split depth, pistil color, leaf margin type) and nineteen quantitative characters (plant height, ramification number, first ramification number, leaflet number, petiole length, leaf length and width, leaf shape index, length and width of the longest stem, calyx length, inflorescence length, flower ring number per, flower number per ring, internode number, flower length, flower width, flower shape index, footstalk length) were analyzed. 2.3. DNA extraction Total genomic DNA was extracted from about 100 mg fresh leaves using the KangWei NuClean PlantGen DNA Kit. The DNA was then suspended in TE buffer. DNA concentration and quality were evaluated by electrophoresis on 1.0% agarose gel. DNA was stored at 20  C. 2.4. ISSR analysis A set of 100 ISSR primers was synthesized according to the sequences obtained from the University of British Columbia, Canada. All the 100 primers were screened for their amplification efficiency using six representative samples. According to

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Table 1 List of the ISSR and SRAP primers used in this study. ISSR primers

Sequences (50 /30 )

SRAP primer combinations

Forward primer sequences

Reverse primer sequences

UBC808 UBC809 UBC811 UBC818 UBC834 UBC835 UBC842 UBC846 UBC851 UBC855 UBC857 UBC866 UBC868

(AG)8GC (AG)8GG (GA)8AG (CA)8AG (AG)8YT (AG)8YC (GA)8YG (CA)8RT (GT)8YG (AC)8YT (AC)8YG (CT)8TC (GA)8AA

M1E3 M5E10 M6E9 M7E2 M7E9 M8E5 M8E6

TGAGTCCAAACCGGATA TGAGTCCAAACCGGAG TGAGTCCAAACCGGTA TGAGTCCAAACCGGTC TGAGTCCAAACCGGTC TGAGTCCAAACCGGTC TGAGTCCAAACCGGTC

GACTGCGTACGAATTGAC GACTGCGTACGAATTGCA GACTGCGTACGAATTACG GACTGCGTACGAATTTGC GACTGCGTACGAATTACG GACTGCGTACGAATTAAC GACTGCGTACGAATTGCT

the amplification efficiency and reproducibility, 13 pieces of primers (Table 1) were selected to test the whole accessions. All samples were amplified at least three times if the initial amplification failed. The PCR reaction mixtures (20 ml total volume) contained 2.0 ml of 10  PCR buffer, MgCl2 2.0 mM, dNTPs 200 mM, ISSR primers 0.8 mM, Taq DNA polymerase 1U (TaKaRa Biotechnology, Dalian, China) and template DNA approximately 15 ng. PCR amplification was performed on the AB Applied Biosystems (Gene Company Limited, USA), under the following PCR program: 10 min of denaturing at 94  C, 40 cycles of three steps: 30 s of denaturing at 94  C, 1 min of annealing at Ta and 1 min of elongation at 72  C, with a final elongation step of 10 min at 72  C. The PCR products were separated by electrophoresis on 1.5% agarose gel using 1  TBE buffer (pH 8.0) at room temperature, using 5000bp ladder molecular size standard (TaKaRa, Japan). The gel was visualized with ethidium bromide staining. 2.5. SRAP analysis SRAP analysis was carried out according to previously established protocols described by Li and Quiros (2001) with minor modification. 100 SRAP primer combinations were initially screened in six representative samples (Table 1). Primer combinations were excluded if their banding patterns were difficult to score or if they failed to amplify consistently in all lines. Of these 100 SRAP primer pairs, 7 primer combinations which consistently produced clear and diverse amplified bands were selected (Table 1). All samples were amplified at least three times if the initial amplification failed. The PCR reaction mixtures (20 ml total volume) contained 2.0 ml of 10  PCR buffer, MgCl2 2.0 mM, dNTPs 200 mM, forward primer 0.4 mM, reverse primer 0.4 mM, Taq DNA polymerase 1U (TaKaRa Biotechnology, Dalian, China) and template DNA approximately 20 ng. PCR amplification was performed on the AB Applied Biosystems (Gene Company Limited, USA), with the following PCR program: 5 min of denaturing at 94  C, 5 cycles of three steps: 1 min of denaturing at 94  C, 1 min of annealing at 35  C and 1 min of elongation at 72  C. In the following 35 cycles, the annealing temperature was increased to 50  C, with a final elongation step of 7 min at 72  C. The PCR products were separated on 6% non-denaturing polyacrylamide gel and SRAP bands were stained using silver sequence DNA staining reagents, using 5000bp ladder molecular size standard (TaKaRa, Japan). 2.6. Data analysis The morphological traits data were standardized, and then were used in the calculation of the Euclidean distance and genetic similarity among the different morphological, wild and cultivated accessions. Principal component analysis (PCA) was executed using the “Statistical Package” for Social Sciences program (SPSS 16.0, SPSS Inc., USA). One-way analysis of variance (ANOVA) was performed for the nineteen selected quantitative traits. Qualitative traits were described as separated variables for each accession. Then, Euclidean distance coefficient for all accessions was computed using NTSYS-pc software version 2.1 (Rohlf, 2000). Amplified bands were scored either as presence (1) and absence (0), and scored for a binary data matrix with polymorphic and reproducible bands. The matrix was then used for the following analysis: the number of effective loci, the percentage of polymorphic loci (PPB), the effective number of alleles (Ne), observed number of alleles (Na), Shannon’s information index (I) (Lewontin, 1972) and Nei’ gene diversity (H) (Nei, 1973) were obtained by the software package POPGENE 3.2 (version 1.31; Yeh et al., 1999). To further examine the genetic relationships among accessions, cluster analysis based on the genetic similarity matrix was performed with the UPGMA (unweighted pair group method with arithmetic mean) method (Sneath and Sokal, 1973), using the SHAN function of the NTSYS-pc version 2.1 (Rohlf, 2000). Mantel test was performed to estimate the correlation between the genetic distances (Nei, 1972) and different morphological traits using NTSYS-pc version 2.1 (1000 permutations, Rohlf, 2000).

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3. Results 3.1. Morphology-based characterization of samples diversity Significant differences occurred at P < 0.01 among the 59 accessions in three quantitative traits: leaflet number (P ¼ 0.001), flower width (P ¼ 0.002), flower shape index (P ¼ 0.006)) and at P < 0.05 for footstalk length (P ¼ 0.033) and hypanthium length (P ¼ 0.040). Other characters did not show statistically significant differences (P > 0.05). Plant height and leaf shape are two of the most important traits for characterization Salvia miltiorrhiza. In this study, plant height in the 59 accessions ranged from 32 to 112 ㎝, Dms28 was the highest with a value of 112 ㎝, followed by Dms31 of 107 ㎝, and Dms21 was the shortest with a value of 32 ㎝, followed by Dms4 of 51 ㎝. Leaf length ranged from 3.2 to 11.0 ㎝. Leaf shape index values in the samples ranged from 0.91 to 2.52, with an average of 1.64. Correlations were examined between quantitative traits; some showed strongly positive relationship, and some negative. For example, plant height with length of the longest stem (0.543; P < 0.01), leaflet number (0.466; P < 0.05), leaf length with leaf width (0.745; P < 0.05), inflorescence length with flower ring number per (0.732; P < 0.01), flower width with flower shape index (0.769; P < 0.01). Eleven of the nineteen quantitative traits were used to evaluate phenotypic diversity by PCA. The five PCs explained more than 79% of total variation of quantitative traits. PC1 accounted for 23%, which was positively defined by inflorescence length, flower ring number per, together with plant height. The most important eigenvectors for PC2 were leaf width and leaf length, which accounted for 19% of total variation. PC3, accounted for 14%, was positively influenced by flower shape index, negatively defined by flower width. First ramification number and leaflet number had highly positive influence on PC4, which accounted for 13% of total variation. PC5, accounted for 10%, was positively impacted by flower length and flower number per ring. Four of the eleven evaluated qualitative traits behaved significant differences among all accessions, namely leaf margin type (P ¼ 0.035), petiole color (P ¼ 0.024), leaf frontal character (P ¼ 0.047), and stem color (P ¼ 0.01). Other characters did not exhibit significant differences among all accessions (P > 0.05). All the eleven qualitative traits were then used for the estimation of morphological diversity, and more than 70% of total variation of qualitative traits was explained in 5 PCs. PC1 was positively influenced by stem color, leaf color, and petiole color. PC2 was positively defined by underlip margin color, flower color, and hypanthium color. PC3 was positively explained by leaf frontal character and leaf margin type. PC4 was mainly explained by underlip split depth and pistil color. Leaf fuzz exhibited highly positive influence on PC5. 3.2. ISSR analysis We surveyed 59 S. miltiorrhiza accessions using 13 ISSR primers (Table 1). A total of 190 bands were identified, of which 177 were polymorphic (93.2%) with a minimum of 10 (UBC-811) and a maximum of 19 (UBC-842) bands per primer (Table 2). Representative banding patterns, detected by the primer UBC-834, are shown in Supplementary Fig. 1. The size of amplified fragments ranged from 0.2 to 3 Kb with an average of 14.6 fragments per primer. The percentage of polymorphic bands produced by each primer ranged from 69.2% (UBC-868) to 100% (UBC-808, 809, 835, 842, 855, 857). Genetic similarity among all samples ranged from 0.36 to 1.0. Nei’s gene diversities (h) varied from 0.000 to 0.500, with an average of 0.279, and Shannon’s indices (i) ranged from 0.000 to 0.693, with an average of 0.429. The mean observed number of alleles (Na) ranged from 1.665 to 2.188, while the mean effective number of alleles (Ne) varied from 1.134 to 1.781. Table 2 Polymorphism revealed by SRAP and ISSR. ISSR

SRAP

Primer

Band generated

N

PPB (%)

Primer combinations

UBC808 UBC809 UBC811 UBC818 UBC834 UBC835 UBC842 UBC846 UBC851 UBC855 UBC857 UBC866 UBC868 Total Average

16 14 10 15 15 17 19 11 13 16 18 13 13 190 14.6

16 14 9 14 12 17 19 9 12 16 18 12 9 177 13.6

100 100 90 93.3 80 100 100 81.8 92.3 100 100 92.3 69.2 93.2

M1E3 M5E10 M6E9 M7E2 M7E9 M8E5 M8E6

37 51 54 35 41 30 32

34 47 53 35 40 36 28

91.9 92.2 98.2 100 97.6 83.3 87.5

Total Average

286 40.9

267 38.1

93.4

N: number of polymorphic bands. PPB: percentage of polymorphic bands.

Band generated

N

PPB (%)

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Fig. 1. UPGMA dendogram of 59 S. miltiorrhiza accessions based on morphological characters. Scale bar represents rescaled Euclidean distance.

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The analysis of the population genetic structure revealed a considerable level of genetic differentiation among the different morphological, wild and cultivated Salvia miltiorrhiza. The total gene diversity (HT) and gene diversity within populations (HS) were 0.254 and 0.090, respectively. The coefficient of genetic differentiation (GST) was 0.647. 3.3. SRAP analysis The same accessions were then analyzed with 7 SRAP primer combinations. They yielded a total of 286 fragments, of which 266 were polymorphic (93.4%), with a minimum of 32 (Me8Em6) and a maximum of 54 (Me6Em9) bands per primer combination. Representative banding patterns, detected by the primer Me1Em3, are shown in Supplementary Fig. 2. The size of amplified fragments ranged from 0.2 to 4 Kb with an average of 40.9 fragments per primer. The percentage of polymorphic bands produced by each primer pair ranged from 83.3% (Me8Em5) to 100% (Me7Em2). Genetic similarity among all samples ranged from 0.40 to 1.0. The genetic diversity demonstrated by the SRAP marker was similar to that revealed by the ISSR marker. Nei’s gene diversities (h) varied from 0.000 to 0.499, with an average of 0.272, and Shannon’s indices (i) ranged from 0.000 to 0.693, with an average of 0.417. The mean observed number of alleles (Na) ranged from 1.667 to 2.190, while the mean effective number of alleles (Ne) varied from 1.111 to 1.791. The analysis of the population genetic structure uncovered a substantial level of genetic differentiation among the samples. The total gene diversity (HT) and gene diversity within populations (HS) were 0.198 and 0.093, respectively. The coefficient of genetic differentiation (GST) was 0.529. 3.4. Cluster analysis 3.4.1. Morphological traits analysis Euclidean distance coefficients were calculated based on 19 quantitative and 11 qualitative traits. Euclidean distance between all accessions varied from 1.09 to 12.11, with a mean of 7.49. The closest accessions were Cul1 with Cul2, while the least similar accessions were Dms41 with Cul2. A dendrogram based on UPGMA analysis of the morphological data is shown

Fig. 2. UPGMA dendogram of 59 S. miltiorrhiza accessions based on ISSR. Scale bar represents rescaled simple matching coefficients.

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in Fig. 1. All accessions were divided into two main clusters (I, II). Cluster I comprised 50 different morphological accessions plus all wild and cultivated controls. Cluster II consisted of three different morphological accessions from the wild species. In this dendrogram, 3 wild and 3 cultivated controls formed a subcluster with a Euclidean distance of 3.84, and the 53 different morphological accessions could be separated from each other except Dms25 with Dms43, Dms17 with Dms29, and Dms6 with Dms44. With a Euclidean distance of 1.64, we could draw a distinction between wild and cultivated controls; meanwhile, all different morphological accessions could be distinguished from each other. Comparison of morphological characterizations demonstrates a highly various relationships among all samples. 3.4.2. ISSR analysis The GS coefficients among the 59 accessions that were based on ISSR markers varied from 0.36 to 1.00 (mean of 0.52), which demonstrated a high level of germplasm genetic diversity among these accessions. The highest similarity was acquired between Wild1 and Wild2, and the lowest similarity was detected between Dms51 and Cul1. Dendrogram based on UPGMA analysis of the ISSR data is shown in Fig. 2. The 59 samples were placed into two clusters (I, II) with a GS coefficient of 0.67. Cluster I comprised all wild and cultivated controls, and five different morphological accessions (Dms49, Dms50, Dms51, Dms52 and Dms53) from the cultivated species, and cluster II contained the other 48 different morphological accessions. Cluster I was further divided into three subclusters, Ia, Ib and Ic, with a GS coefficient of 0.72. The three wild controls were included in subcluster Ia and the three cultivated controls were included in subcluster Ib. Cluster II was divided into ten subclusters, IIa w IIj. Dms7, Dms10, Dms15, and Dms41 formed 4 different subclusters named IIa, IIi, IIg, IIj respectively; IIb (Dms1, Dms3, Dms4, Dms5, Dms6, Dms8), IIc (Dms17, Dms20), IId (Dms2, Dms14, Dms16, Dms18, Dms19), IIh (Dms9, Dms11, Dms13), all were from the wild species. IIe and IIf contained 15 and 13 different morphological accessions. 3.4.3. SRAP analysis The GS coefficients between all accessions ranged from 0.40 to 1.0 (mean of 0.56). The highest similarity was found between Cul1 and Cul2, and the lowest similarity was observed between Dms40 and Cul3. The SRAP-based dendrogram also showed two major clusters (I, II) (Fig. 3), one comprised all wild and cultivated controls and the other contained all different morphological accessions. Two subclusters were identified within the first cluster, with a GS coefficient of 0.83 that all different morphological accessions could be distinguished themselves from each other. The first subcluster contained all wild controls and the second one contained all cultivated controls. Cluster II could be distinctly divided into seven subclusters, IIa w IIg, with a GS coefficient of 0.72. Dms6, Dms16, and Dms17 formed 3 different subclusters, named IIa, IIe, IIf. The second

Fig. 3. UPGMA dendogram of 59 S. miltiorrhiza accessions based on SRAP. Scale bar represents rescaled simple matching coefficients.

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subcluster (IIb) contained seven different morphological accessions (Dms41, Dms48, Dms49, Dms50, Dms51, Dms52, Dms53) from the cultivar. IIc comprised eight accessions (Dms1, Dms2, Dms3, Dms7, Dms27, Dms4, Dms31, Dms21) from the wild and four accessions (Dms36, Dms37, Dms40, Dms39) from the cultivar. IIg contained two different morphological accessions Dms17 and Dms34. And IId harbored the other 29 different morphological accessions from the wild and cultivar. 4. Discussion S. miltiorrhiza, an important herbal medicine, is wildly used for treatment of cardiovascular diseases (Zhou et al., 2005). Hence, to ensure its sustainable utilization, it is necessary to collect, conserve and assess germplasm in such a way that the great diversity should be contained at phenotypic, genetic and molecular levels. Morphological characterization is the first step in new plant resource discovery and conservation, there have been a lot of successful examples in this area, such as rice (Chakanda et al., 2013), maize (Couto et al., 2013), wheat (Li et al., 2012), pea (Yadav, 2012; Jha et al., 2013). These studies suggested that high diversity in morphological traits could be a useful tool for germplasm collection. We selected 19 quantitative and 11 qualitative properties to characterize 53 phenotypic S. miltiorrhiza and investigated the reliability of morphological traits in genotypes identification. Most of these traits are convenient to investigate, and consequently could serve as targeted traits for germplasm collection. Morphology-based, wild and cultivated S. miltiorrhiza accessions were collected from different sample sites and then transplanted to the same place. As a consequence, the present phenotypic values have excluded the environment interference factor. Our findings demonstrate that morphology-based S. miltiorrhiza germplasm is a reliable source for germplasm collection and conversation. Morphological traits have been also identified duplicate existing in the germplasm collections, which has been proved by the analysis of AFLP (Niwa et al., 2004), RAPD, RFLP, SSR (Belaj et al., 2003; Ikegami et al., 2009; KeJun et al., 2009), microsatellites markers (Maruthi et al., 2013), and RALP (Sebastian et al., 2000). Therefore, we used PCR-based DNA molecular markers ISSR and SRAP to screen S. miltiorrhiza germplasm inventory for identifying potential duplicate samples. We eventually tested 13 ISSR primers and 7 SRAP primer combinations with the 59 S. miltiorrhiza samples, all of them acquired a high PPB. Here, SRAP was found to be equally efficient as ISSR, and it detected 93.4% polymorphic DNA markers while 93.2% for ISSR. Likewise, Song et al. (2010) reported 100% and 90.2% polymorphism in six populations of S. miltiorrhiza by using ISSR and SRAP markers; and Zhang et al. (2013) found 95.2% polymorphism in different S. miltiorrhiza germplasms by using ISSR marker. The clustering pattern derived from morphology, ISSR and SRAP markers indicated that almost independent results appeared among the morphology-based accessions. Yet, the wild and cultivated controls were closely clustered together in all dendrograms of morphology, ISSR and SRAP markers. Specifically, three wild controls and five morphological different accessions from the cultivated species were closely clustered together in one axis and then clustered together with three cultivated controls in ISSR dendrogram (Fig. 2). The wild and cultivated controls were also closely clustered together in morphology and SRAP dendrograms, while separated from 53 morphological different accessions (Fig. 3). Dendrogram did not show any obvious pattern of grouping of different morphological accessions according to the wild and cultivated species. Such sort of pattern confirmed that morphology-based accessions could be a reliable resource for the collection of S. miltiorrhiza germplasm. The genetic distances among the 59 samples were calculated according to the morphology traits, ISSR and SRAP markers. Matrices were constructed from these three respective genetic distance scores and their correlations were assessed according to Mantel test. The correlation coefficient between the morphology and ISSR matrices was calculated to be 0.3814 (P < 0.01), while that between the morphology and SRAP matrices was 0.3765 (P < 0.01), and between the ISSR and SRAP matrices was 0.7331 (P < 0.01). Thus, there was a particularly positive coincidence for the ISSR and SRAP analysis of genetic relationships among the samples. In conclusion, the present study showed that a great genetic diversity occurred among the 53 S. miltiorrhiza accessions due to their morphological differentiation. Morphology, ISSR and SRAP markers are powerful tools for evaluating the genetic diversity and relationships in different S. miltiorrhiza phenotypes, which ultimately would be useful in characterization of various phenotypes of S. miltiorrhiza germplasm resources. Collection, conservation and characterization of phenotypic germplasms are important to safeguard the sustainable development of this traditional Chinese medicinal herb. Acknowledgments We thank Shaanxi Tasly Plants Pharmaceutical Co.,LTD for sample collection. We would also like to thank the National Natural Science Foundation of China (81373908) and the Major Industrial Cluster Project in Shaanxi Province (2012KTCL0207) for financial support. Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.bse.2014.01.020. References Belaj, A., Satovic, Z., Cipriani, G., Baldoni, L., Testolin, R., Rallo, L., Trujillo, I., 2003. Comparative study of the discriminating capacity of RAPD, AFLP and SSR markers and of their effectiveness in establishing genetic relationships in olive. Theor. Appl. Genet. 107, 736–744.

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