Qiannan Buyi and Miao Autonomous Prefecture is the central region of Theaceae plant distribution in Guizhou Province. The natural environment with high altitude, little sunshine and abundant rainfall provides good growth conditions for tea trees (Zhang et al., 2016). The tea industry with Duyun Maojian as the main brand is the characteristic pillar industry of the economic development of Qiannan Prefecture (Yang et al., 2019, South China Agriculture, 13(6): 103-104). Duyun Maojian is one of the top ten famous teas in China. During the Han and Tang dynasties, it was already regarded as a tribute tea and was named "Fishhook Tea" by Emperor Chongzhen due to its resemblance to a fishhook. In 1956, Chairman Mao suggested renaming it to "Maojian". From then on, Duyun Maojian has been used to this day, and Duyun City is the original habitat of Duyun Maojian with a long history of tea cultivation. According to historical records, "the Yellow River and Dacao have the best tea production and are exported to various regions in border Guangdong Province." The Yellow River and Dacao are now the Yellow River Group and Dacao Group of Chanongcun of Xiaoweizhai in Duyun (Luo and Meng, 2013, Modern Horticulture, (8): 17, 21; Guo et al., 2014). At present, the main raw materials for fresh leaves of Duyun Maojian are Fuding white tea imported from other places, with a few being local varieties of Duyun (Zhang et al., 2016; Guo et al., 2014). Many local varieties in Duyun have resistance to unfavorable natural environments and genetic characteristics of good quality traits. The leaves are soft and tender, with a higher amino acid content compared to Fuding white tea, and lower phenolic and ammonia content compared to Fuding white tea. The quality is significantly better than Fuding white tea, such as ‘Duyun 79’ (native place: Duyun Tuanshan) and ‘Duyun 67’ (native place: Duyun Yellow River), which are high yield and high-quality native tea tree strains with certain promotion value (Xie et al., 2010; Wang et al., 2011; Yan et al., 2012). However, due to the relatively lagging work in variety selection, no widely promoted and planted local variety in Duyun has yet been selected. Therefore, the unique appearance, quality, and style of Duyun Maojian cannot be guaranteed (Ou and Lin, 2014, Journal of Guizhou Tea, 42(4): 24-27). Native tea trees in Duyun are rich in gene resources, with many varieties and types. Most of them grow in the margin of forest or scattered shrubs mixed with other crops (Xie and Zhang, 2008). Strengthening the classification and evaluation of these local tea resources provides an important reference value for the breeding of fine varieties of tea trees, and is conducive to the formation of local tea industry with characteristics (Guo et al., 2014). DNA molecular marker is an effective means for genetic diversity and variety identification of tea resources. SSR (Simple sequence repeat) marker technology has become one of the widely used genetic marker technologies in the construction of tea molecular fingerprint at present due to its advantages of codominance inheritance, rich polymorphism, good repeatability and simple operation (Wang et al., 2010; Xu et al., 2014). For example, Liu et al. (2018) used SSR molecular marker technology to analyze the genetic diversity and phylogenetic relationships of 41 Sichuan transplanted wild tea tree germplasm resources, while Luo et al. (2019) used SSR marker technology to analyze the genetic diversity of 35 ancient tea accessions from Chongqing.

This study applied SSR marker technology to analyze the genetic diversity of tea germplasm resources with different morphological characteristics from Chanongcun, the original habitat of Duyun Maojian, based on the Specification for Description of Tea Germplasm Resources (NY/T 2943-2016), and constructed a DNA fingerprinting, providing a theoretical basis for further exploring excellent genes and breeding varieties.

1 Results and Analysis

1.1 SSR primer markers and genetic diversity analysis of resources

In this experiment, 15 pairs of SSR primers were selected from 30 pairs of primary screening primers, and they showed good PCR amplification effect on 11 germplasm resources of tea tree from the original habitat of Duyun Maojian (Figure 1). The results showed that 15 pairs of SSR primers had high polymorphism, and the amplified bands were 109~484 bp in all samples. SSR genetic diversity results of 11 tea tree resources (Table 1) showed that 138 observed alleles (Na) and 89.773 effective alleles (Ne) were amplified by SSR primers, and the number of observed alleles ranged from 8 to 11 (average 9.2). The number of effective alleles varied from 4.653 8 to 7.562 5 (mean 5.984 9). The observed heterozygosity (Ho) ranged from 0.272 7 to 1.000 0, and the mean value was 0.612 1. The expected heterozygosity (He) ranged from 0.822 5 to 0.909 1, and the mean value was 0.869 0. The polymorphism information content (PIC) ranged from 0.758 7 to 0.853 8, with an average of 0.810 4. Shannon information index (I) ranged from 1.767 8 to 2.145 8, with an average value of 1.975 8. These results showed that 15 pairs of SSR primers could effectively identify the genetic diversity of 11 Dunyun local varieties, and the PIC values of all 15 pairs of primers were greater than 0.5, showing high polymorphism (Shang et al., 2018).

1.2 Genetic relationship of different germplasm resources

The similarity coefficient is a measure of the degree of similarity between groups or individuals. The higher the similarity coefficient is, the greater the degree of similarity between groups or individuals and the closer the genetic relationship is (A et al., 2020). The genetic identity and genetic distance among germplasm resources of tea trees from the origin of Duyun Maojian were analyzed. The results showed that the genetic identity and genetic distance among the 11 tea trees ranged from 0.023 8 to 0.512 9 and 0.667 7 to 3.736 5, respectively, indicating that the genetic variation of all the resources was large. Among the 11 tea tree resources, T5 and T9 had the highest genetic consistency (0.512 9), T3 and T4 had the lowest genetic consistency (0.023 8), T5 and T9 had the lowest genetic distance (0.667 7), T3 and T4 had the largest genetic distance (3.736 5), indicating that T5 and T9 had the most similar genetic background. The genetic background of T3 and T4 was significantly different, and the genetic relationship was the farthest. The clustering result analysis (Figure 2) showed that when the similarity coefficient was 0.30, 11 tea tree resources could be clustered into three complex clusters, and the correlation coefficient of Cophenetic correlation test was 0.674 6, indicating that UPGMA clustering results were good (Table 2).

1.3 Construction of DNA molecular fingerprinting

During the construction of DNA molecular fingerprinting, primer combinations are generally selected based on the diversity index of primers and the size difference of amplified fragments, so that fewer primers can be used to distinguish more resources. In this study, five pairs of primers, SSR03, SSR12, SSR21, SSR23 and SSR26, were used to encode the DNA fingerprint database of tea tree resources and construct the DNA fingerprinting. According to the method of Chen et al. (2017) and Chen et al. (2011), all alleles amplified by the selected 5 pairs of primers were sorted in order of molecular weight of amplified fragments from smallest to largest, and values were assigned from "1 to 9" in sequence (Table 3), and the selected alleles that were not amplified were assigned as "0". For primers with more than 9 alleles, only 9 bands were considered. It is assumed that two alleles can be obtained from the amplification of tea tree DNA by each pair of primers. If the size of alleles amplified is the same, the two digits encoded by the fingerprint are assigned as "0" and the corresponding number of this segment respectively. According to the above assignment principle, 5 pairs of primers encode 11 tea tree resources from the origin of Duyun Maojian in sequence, and the digit combination after each encoding series is the DNA fingerprint database encoding of the resource (Table 3). Based on these 5 markers, the allelic band type combination of each tea tree resource was coded, and the unique 10-digit molecular fingerprint database coding of each tea tree resource was obtained (Table 4). According to the fingerprint database of 11 germplasm resources of tea tree in the origin of Duyun Maojian (Figure 3), these germplasm resources can be identified relatively quickly.

2 Discussion

Tea tree (Camellia sinensis (L.) O. Kuntze) is a perennial woody cross-pollinated plant, the genetic diversity of local tea tree varieties is rich, rare characteristic tea germplasm resources are the material basis for the sustainable development of Guizhou tea industry and variety breeding. The genetic basis of tea tree seeds is complex, and most local varieties are sexual genetic populations established by seed livestreaming, with certain regional characteristics (Chen et al., 2014). In this study, SSR analysis was conducted on the germplasm resources of local tea trees from the origin of Duyun Maojian. The results showed that 11 tea trees had high genetic diversity, and the mean Shannon information index (I) and polymorphism information content (PIC) were 1.975 8 and 0.810 4, respectively. These results were higher than those obtained by Zhang et al. (2016) on germplasm resources of 60 wild tea trees in southern Guizhou (I=1.4 644, PIC=0.572 5), Guo et al. (2016) on 40 ancient tea trees in Guizhou (I=0.936 3, PIC=0.462 0), and Zhang and Ma (2012) on 14 new varieties of tea trees (I=0.756 0, PIC=0.387 0). Each of the 11 tea tree resources maintains the gene source of the local tea tree parents, and each resource corresponds to a unique fingerprint code, which is unique and irreplaceable. Previous studies have shown that genetic diversity of sexual line resources is generally higher than that of inbred line or clonal resources (Nybom, 2004; Dumini et al., 2007), and Guo et al. (2016) concluded that genetic diversity among populations of sexual species of ancient tea tree resources was relatively high and primitive. Therefore, the germplasm resources of each tea tree in this study may be relatively primitive sexual lines and preliminarily divided into 3 groups. To evaluate the genetic diversity of germplasm resources of tea plant at molecular level can cultivate new varieties more effectively. It is an important means to breed new plant varieties by hybridizing with superior varieties or selecting superior individual plants from natural population variation (Chen et al., 2007). The lower the genetic similarity between the parents, the higher the probability of obtaining superior individual plants from the hybrids. Therefore, the use of DNA molecular marker technology to fully understand the genetic background of parents provides a reference for hybrid breeding. Qiao et al. (2019) found that the genetic basis for tea tree breeding in Guizhou is narrow, with the application of Fuding white tea and Yunnan tea tree germplasm being the main ones, and the utilization of local tea tree resources is limited.

Therefore, this study analyzed the genetic diversity of the germplasm resources of tea trees from the origin of Duyun Maojian, and the results provided a theoretical reference for further screening of excellent individual plants and breeding suitable for Duyun Maojian characteristic varieties.

3 Materials and Methods

3.1 Test materials

Local practitioners had a comprehensive understanding of the origin of Duyun Maojian and the distribution of local strains of tea trees. Therefore, the research group and local practitioners collected 11 local strain resources with different morphological characteristics in collaboration with Chanongcun of Xiaoweizhai in Duyun, Guizhou (Table 5). One bud and two leaves were picked in spring and stored at -80℃ for later use.

3.2 SSR amplification

Genomic DNA was extracted using Ezup Column Plant Genomic DNA Purification Kit (B518261, Sangon Biotech). The primer of this experiment was SSR fluorescent marker primer, which was synthesized by Sangon Biotech (Shanghai) Co., Ltd. Thirty pairs of primers with good amplification effect were selected from the research reports of Zhang et al. (2016), Liu et al. (2018), Ma et al. (2010), and four random test materials were used for PCR amplification. Finally, 15 pairs of SSR primers with high polymorphism and good stability were selected (Table 6).

3.3 PCR amplification

PCR amplification reaction system: Template DNA 1.0 μL (20~50 ng/μL), 10×PCR reaction buffer 2.5 μL, upstream and downstream primers 1.0 μL, dNTPs 1.0 μL (10 mmol/L), Taq DNA polymerase 0.5 μL (5 U/μL), ddH₂O supplement reaction system to 25 μL. Utilizing Veriti™ 96-Well Thermal Cycler (ABI, USA) PCR machine for landing PCR. The procedure is as follows: the first round of PCR through predenaturation (95℃, 3 min), denaturation (94℃, 30 s), annealing (60℃, 30 s), extension (72℃, 30 s). After 10 cycles, the second round of PCR was performed, which was denatured (94℃, 30 s), annealed (55℃, 30 s) and extended (72℃, 30 s). After 35 cycles, the PCR was repaired and extended (72℃, 5~8 min). The PCR products were detected by capillary electrophoresis and fluorescence. The purified PCR products were added with 1 μL respectively into 96 Wells of upper sample. The 990 μL formamide (HIDI) and 10 μL molecular weight internal standard (LIZ500) were mixed, and the absorbed mixture of 1 μL was added to the 96-well reaction plate respectively. Centrifuge 1 200 r/min for 30 s, denaturate 5 min at 98℃, cool rapidly and centrifuge 1 200 r/min for 15 s in a plate centrifuge. DNA sequencer 3730XL (America ABI) was used to detect samples.

3.4 Data statistics and analysis

GeneMapper v 3.2 software was used to determine the amplified fragment length. According to the method proposed by Ge and Ren (2011), the statistical DNA segment length was converted into codominant molecular marker genotype data such as A and B. PopGene Ver.1.32 software was used to analyze the observed number of alleles, effective number of alleles, observed heterozygosity, expected heterozygosity, estimated value of Shannon information diversity index, genetic consistency and genetic distance among different resources. The polymorphism information content of primers was analyzed by PIC_Calc 0.6 software. By referring to the method proposed by Xia and Lu (2009), 0 and 1 data matrices were established, UPGMA cluster analysis was carried out in NTSYS 2.10e software, and tree diagrams of genetic distance system of 11 tea tree resources were constructed. The Matrix comp.plot function in the software is used to analyze the correlation between the clustering results and the similarity coefficient matrix, so as to evaluate the quality of the clustering results.

Authors’ contributions

YYX was the experimental designer and executor of this study. YYX and ZMZ participated in the data collation and the writing of the first draft of the paper. LLP and CSJ participated in part of the experiment. LJ was the leader of the project, directing experimental design, paper writing and revision. All authors read and approved the final manuscript.

Acknowledgments

This study was jointly supported by the Open Fund Project of Duyun Maojian Tea Engineering Research Center of Guizhou Colleges and Universities (QJHKY [2016]020-01), the Key Scientific Research Project of Guizhou Colleges and Universities on Education Quality Improvement (2011017), the Science and Technology Program Project of Guizhou Province (QKHJC[2020]1Y120), and the Natural Science Fund Project of Guizhou Education Department (QJHKY [2019]211) and Qiannan Normal University for Nationalities University-level Project (qnsy201601).

References

A Q.L., Wei X.X., Liu Y., and Liu W.H., 2020, SSR genetic diversity analysis of 42 Poa L. germplasm resources, Fenzi Zhiwu Yuzhong (Molecular Plant Breeding), 18(1): 222-230.

Chen C.W., Cao K., Wang L.R., Zhu G.R., and Fang W.C., 2011, Molecular ID establishment of main China peach varieties and peach related species, Zhongguo Nongye Kexue (Scientia Agricultura Sinica), 44(10): 2081-2093.

Chen L., Zhou Z.X., and Yang Y.J., 2007, Genetic improvement and breeding of tea plant (Camellia sinensis) in China: from individual selection to hybridization and molecular breeding, Euphytica, 154: 239-248.

https://doi.org/10.1007/s10681-006-9292-3

Chen S.J., Zhang M.Z., Yao Y.X., and Xie W.B., 2017, Establishment of DNA fingerprinting for tea germplasm from Qiannan prefecture by SSR markers, Zhiwu Yichuan Ziyuan Xuebao (Journal of Plant Genetic Resources), 18(1): 106-111.

Chen Z.W., Gong X., Li Q.Y., Wang L.J., and Zhou Y.F., 2014, Research and analysis on optimal adjustment of planting tea varieties in Guizhou, Zhongzi (Seed), 33(6): 81-85.

Duminil J., Fineshi S., Hampe A., Jordano P., Salvini D., Vendramin G.G., and Petit R.J., 2007, Can population genetic structure be predicted from life-history traits, Am. Nat., 169(5): 662-672.

https://doi.org/10.1086/513490
PMid:17427136

Ge H.M., and Ren M., 2011, Data trans1.0, a software for microsatellite data processing based on excel macro, Fenzi Zhiwu Yuzhong (Molecular Plant Breeding(Online)), 9(48): 1359-1365.

Guo J.J., Liu T., He C.N., Xu L.J., and Wang M., 2014, Application history and current research of Duyun Maojian tea, Anjisuan He Shengwu Ziyuan (Amino Acids and Biotic Resources), 36(3): 29-32, 39.

Guo Y., Liu S.C., Cao Y., Zhao H.F., Wei J., Yan D.H., and Zhou F.Y., 2016, Analysis of genetic diversity and construction of molecular fingerprinting with SSR markers for ancient tea germplasms in Guizhou, Xinan Nongye Xuebao (Southwest China Journal of Agricultural Sciences), 29(3): 491-497.

Liu G.Q., Tan L.Q., Wu C.P., Li X.S., Hu C., Hu Y., and Tang Q., 2018, Genetic diversity of Sichuan transplanted wild tea tree by SSR marker, Guizhou Nongye Kexue (Guizhou Agricultural Sciences), 46(4): 4-8.

Liu S.R., An Y.L., Li F.D., Li S.J., Liu L.L., Zhou Q.Y., Zhao S.Q., and Wei C.L., 2018, Genome-wide identification of simple sequence repeats and development of polymorphic SSR markers for genetic studies in tea plant (Camellia sinensis), Mol. Breed., 38(5): 59.

https://doi.org/10.1007/s11032-018-0824-z

Luo Y.S., Zhang X., Mao J.L., Li H.J., Liu Q.J., Tong H.R., Liang G.L., and Wei X., 2019, Analysis of genetic diversity in 35 ancient tea accessions from Chongqing with SSR markers, Fenzi Zhiwu Yuzhong (Molecular Plant Breeding), 17(19): 6549-6557.

Ma J.Q., Zhou Y.H., Ma C.L., Yao M.Z., Jin J.Q., Wang X.C., and Chen L., 2010, Identification and characterization of 74 novel polymorphic EST-SSR markers in the tea plant, Camellia sinensis (Theaceae), Am. J. Bot., 97(12): 153-156.

https://doi.org/10.3732/ajb.1000376
PMid:21616837

Nybom H., 2004, Comparison of different nuclear DNA markers for estimating genetic diversity in plants, Mol. Ecol., 13: 1143-1155.

https://doi.org/10.1111/j.1365-294X.2004.02141.x
PMid:15078452

Qiao D.H., Guo Y., Yang C., Li Y., Chen J., and Chen Z.W., 2019, Fingerprinting construction and genetic structure analysis of the main cultivated tea varieties in Guizhou province, Zhiwu Yichuan Ziyuan Xuebao (Journal of Plant Genetic Resources), 20(2): 412-425.

Shang W.Q., Duan Z.F., Yang Y.J., Li Y.Y., Cheng H., Liu J., Yang X.R., Yang S.M., Yi B., Liu B.Y., and Bi X.Q., 2018, Genetic diversity analysis of daye tea germplasm in Yunnan based on EST-SSR markers, Shandong Nongye Kexue (Shandong Agricultural Sciences), 50(1): 16-22.

Wang L.Y., Jiang Y.H., Duan Y.S., Cheng H., Zhou J., Zeng J.M., and Wei K., 2010, Genetic diversity of tea landraces using SSR markers, Zuowu Xuebao (Acta Agronomica Sinica), 36(12): 2191-2195.

https://doi.org/10.3724/SP.J.1006.2010.02191

Wang Y.W., Xie W.B., and Gu J.S., 2011, Study on native tea tree of Duyun Maojian, Anhui Nongye Kexue (Journal of Anhui Agricultural Sciences), 39(9): 5378-5379, 5382.

Xia H.B., and Lu B.R., 2009, Software for transforming co-dominant genotype scores into binary data matrix: its application to genetic diversity research, Zhiwu Yichuan Ziyuan Xuebao (Journal of Plant Genetic Resources), 10(1): 97-102.

Xie W.B., and Zhang G.Z., 2008, Situation and protection countermeasures of original/wild resouces of Duyun Maojian tea, Anhui Nongye Kexue (Journal of Anhui Agricultural Sciences), 36(36): 16257-16258.

Xie W.B., Zhang G.Z., and Song L.S., 2010, Breeding of native tea varieties of Duyun Maojian tea, Anhui Nongye Kexue (Journal of Anhui Agricultural Sciences), 38(3): 1229-1234.

Xu L.J., Hou Q.L., Hou C.Y., Zhang T., Zhang X.H., Ni Z.F., and Liang R.Q., 2014, Genetic diversity analysis of wheat varieties with different aphids-resistant by simple sequence repeat (SSR) markers, Huabei Nongxuebao (Acta Agriculturae Boreali-Sinica), 29(5): 119-124.

Yan D.H., Liu S.C., Wei J., Liu H.M., Luo X.Y., and Chen Y.A., 2012, Identification and utilization of Guizhou local tea germplasm resources, Xinan Nongye Xuebao (Southwest China Journal of Agricultural Sciences), 25(6): 1972-1976.

Zhang L.J., Liu Q., and Yang Q., 2016, Advantage and utilization of tea germplasm resources in Qiannan prefecture of Guizhou province, Zhongguo Chaye Jiagong (China Tea Processing), (1): 38-41.

Zhang M.Z., Yao Y.X., and Chen S.J., 2016, Genetic diversity analysis of tea germplasm in Qiannan prefecture by SSR markers, Xibei Zhiwu Xuebao (Acta Botanica Boreali-Occidentalia Sinica), 36(6): 1117-1124.

Zhang Z.F., and Ma J.Q., 2012, Analysis of genetic diversity and construction of molecular fingerprinting for new tea tree varieties based on SSR markers, Hunan Nongye Kexue (Hunan Agricultural Sciences), (19): 1-4.