Introduction
Gentiana straminea Maxim. (Gentianaceae), commonly known as ‘Mahua jiao’ in China, is a traditional Tibetan herb that belongs to the Gentiana L.Sect. Cruciata Gaudin (Yuan, Reference Yuan1993). This perennial herb is exclusively found in the Qinghai-Tibetan Plateau (Ho and Liu, Reference Ho and Liu2001). In traditional medicinal practices, the roots of this herb, along with the roots of G. macrophylla Pallas, G. dahurica Fischer and G. crassicaulis Duthie ex Burk, are used in traditional Chinese medicine as ‘Qinjiao’ (Radix Gentianae Macrophyllae) (Chinese Pharmacopoeia Commission, 2015). Notably, G. straminea is abundant in iridoid bioactive compounds, including gentiopicroside and loganic acid, which have been traditionally employed for the treatment of rheumatic arthritis, hemiplegia, pain and jaundice (Wang et al., Reference Wang, Xu, Wang, Yang, Yang and Zhang2013). Furthermore, a diet supplemented with G. straminea also had beneficial effects on animal growth, feed digestibility and energy utilization, making the supplement a good source for ruminant nutrition (Xie et al., Reference Xie, Wang, Guo, Zhang, Zhu and Hou2022). However, the species faces challenges due to its high pharmacological efficacy and extensive exploitation, resulting in the loss of germplasm within the fragile ecosystem of the Qinghai-Tibetan Plateau. To ensure the successful management and sustainable development of this valuable traditional herb resource, it is imperative to comprehend its genetic diversity (Deng et al., Reference Deng, Pang, Lu, Zhu, Duan, Tan, Huang, Li, Chen and Liang2016).
Although some molecular markers, such as random amplification of polymorphic DNA (RAPD), amplified fragment length polymorphism and inter simple sequence repeats (ISSR) have been developed for ‘Qinjiao’ (Li et al., Reference Li, Yang and Liu2008; Cao, Reference Cao2010; Wang et al., Reference Wang, Zhao, Ni, Gaawe and Mi2017; Cheng et al., Reference Cheng, Wang, Zhou, Chen, Wang, Shi, Shen and Lei2019), SSR markers have demonstrated superior performance due to their robustness and polymorphism. Moreover, the extensive polymorphic nature and genome-wide distribution of SSR markers make them particularly valuable for applications in molecular breeding (Yu et al., Reference Yu, Park, Poysa and Gepts2000; Collard and Mackill, Reference Collard and Mackill2008; Miah et al., Reference Miah, Rafii, Ismail, Puteh, Rahim, Islam and Latif2013). In recent years, the advancement of sequencing technology has facilitated the acquisition of a substantial number of expressed sequence tag-simple sequence repeat (EST-SSR) markers through transcriptome sequencing (Yang et al., Reference Yang, Zhong, Tian, Wang, Zhao, Li and Sun2018; Chapman, Reference Chapman2019; Zheng et al., Reference Zheng, Cheng, Yang, Xu, Tang, Xie, Huang, Bao, Zheng, Diao, You and Hu2019). In comparison to genomic SSR markers, EST-SSR markers offer several advantages, including high interspecific transferability, lower development costs and association with functional traits (Kalia et al., Reference Kalia, Rai, Kalia, Singh and Dhawan2011).
In the past decade, several molecular markers have been employed to investigate the genetic diversity of G. straminea, including RAPD (Li et al., Reference Li, Yang and Liu2008) and ISSR. Recent studies have further expanded the repertoire of markers by designing numerous SSR primers through transcriptome analysis of G. straminea and related species (Zhou et al., Reference Zhou, Zhao, Zhou, Chen, Jia and Bai2023). However, it is noteworthy that, to date, there is a lack of research reporting the utilization of EST-SSR markers in assessing the genetic diversity of G. straminea.
Accordingly, to gain further insight into the genetic structure of the G. straminea and to contribute to the conservation of genetic diversity in populations on the QTP, we used EST-SSR to analyse the genetic structure of G. straminea populations. In this study, a total of 96 EST-SSR primer pairs were tested, resulting in the identification of 10 novel EST-SSR markers. These markers exhibited a high degree of polymorphism and demonstrated transferability to two other species within the sect. Cruciata, namely G. macrophylla and G. dahurica.
Experimental
During the flowering period, the fresh leaves of 92 samples were collected from four distinct populations, 20–26 individuals were sampled, with a distance of at least 20 m between sampled individuals. Additionally, we sampled 46 individuals from eight populations of G. macrophylla (30) and five populations of G. dahurica (16) (Fig. 1, online Appendix 1, Supplementary Fig. 1).
Figure 1. Distribution of four populations of G. straminea, eight populations of G. macrophylla and five populations of G. dahurica. (Mapping was performed by the ArcGIS 10.2 program on the map of China, the size of the pie chart is directly proportional to the number of populations. The area highlighted within the red circle represents the geo-herbalism of Gentiana straminea.)
The unigenes used to develop SSR markers were obtained from G. straminea transcriptome sequencing data in our previous study (Zhou et al., Reference Zhou, Gao, Wang, Chen, Shen, Gao, Lei, Yin and Liu2016). Primer pairs were designed in a batch module manner complementary to the unique flanking regions of the SSR motifs using the Primer 3 software tool (Rozen and Skaletsky, Reference Rozen, Skaletsky, Misener and Krawetz2000). Primers were designed only for SSR-containing contigs, and primer specificity was greater than 10 bp on either side of the SSR with a maximum product size of 100–280 bp. The following parameters were used for optimization: size of primer was set as 18 bp with maximum up to 24 bp, melting temperature 55°C with minimum 50°C and maximum 70°C, maximum GC content of 65%, and the product size ranged from 150 to 200 bp. A total of 7591 EST-SSR primer pairs were designed and obtained from 78,764 unigenes (Zhou et al., Reference Zhou, Gao, Wang, Chen, Shen, Gao, Lei, Yin and Liu2016). Among the 7591 SSR markers, 96 primer pairs were randomly selected and designed using Primer 3 software with default settings (Rozen and Skaletsky, Reference Rozen, Skaletsky, Misener and Krawetz2000). All primers were synthesized by Genewiz Biotech (Suzhou, China) for validation.
A modified CTAB method was adopted for total DNA extraction from the silica gel dried leaves (Doyle and Doyle, Reference Doyle and Doyle1987). The quality of DNA was verified with 1% agarose gel electrophoresis, and the concentration was qualified with a NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, DE, USA). DNA was diluted at 50 ng/μl and stored at −80°C for PCR amplification. Polymerase chain reactions (PCRs) were performed in a final volume of 20 μl containing 1 × PCR buffer, 1 μl MgCl2, 0.5 μl 2.5 nM dNTPs, 0.5 μl forward and reverse primers (10 μmol), 0.3 μl of Taq DNA polymerase (5 U/μl) (Takara Com, Dalian, China) and 25 ng of template DNA. The PCR procedure consisted of 5 min of initial denaturation at 95°C; 35 cycles of 45 s at 95°C, 30 s at the annealing temperature (Table 1) and 30 s of synthesis at 72°C; followed by a final 15 min extension step at 72°C and a 4°C holding temperature. PCR products were run on 1% agarose gel electrophoresis and 8% non-denaturing polyacrylamide gel electrophoresis (Native-PAGE) using TBE buffer, stained with ethidium bromide and then visualized and photographed using a gel documentation system (Bio-Rad, Hercules, CA, USA) (Cai et al., Reference Cai, Zhu, Zhang, Li, Zhao, Zeng and Lin2019).
Table 1. Characteristics of 10 polymorphic SSR markers developed for G. straminea
Ta = annealing temperature.
Two species of ‘Qinjiao’, G. macrophylla and G. dahurica, were collected in the grass field near the Qinghai-Tibetan Plateau and were used to evaluate the potential value of the developed EST-SSR markers in sect. Cruciata. Genomic DNA was extracted, and PCR was performed as described above, except for the annealing temperatures, which were reoptimized for these species for each locus.
According to PAGE results, the absence or presence of bands was scored as zero or one in all SSR loci, and two binary qualitative data matrices were generated. The length of the fragment was determined by comparing it with the 2 K marker. POPGENE version 1.32 software (Yeh et al., Reference Yeh, Yang, Boyle, Ye and Mao1997) was used to calculate genetic diversity parameters such as the number of observed alleles per locus (Na), observed heterozygosity (Ho), effective number of alleles (Ne), observed heterozygosity (He) and Hardy–Weinberg equilibrium (HWE) (Kalinowski et al., Reference Kalinowski, Taper and Marshall2007). Polymorphic information content (PIC) was obtained using PIC-CALC 0.6 software (Koelliker et al., Reference Koelliker, Enkerli and Widmer2006). All 17 populations were clustered based on a similarity matrix using a heuristic and well-resolved algorithm unweighted pair group method with arithmetic average (UPGMA) using the PAUP* Version 4.0 program and edited by iTOL (https://itol.embl.de/).
Results and discussion
In this study, a preliminarily screening of 96 primer pairs was conducted using PCR amplification and agarose gel electrophoresis. Among the 96 primer pairs, 32 (33.33%) produced more than one band, appeared polymorphic and provided genetic information (online Appendix 2). Subsequently, the 32 primer pairs were further screened using PCR amplification and native PAGE. Among the 32 primer pairs, 10 pairs of primers were highly polymorphic and alleles converted into a workable format for software analysis (Table 1, online Appendix 3). As Table 2 shows, significant deviation from HWE for each population and linkage disequilibrium for each primer pair were examined. Ten pairs of primers were highly polymorphic, with a number of alleles ranging from 3 to 14 per locus with a mean of 8.50. The Ho and He ranged from 0.078 to 0.722 and 0.238 to 0.884, with averages of 0.310 and 0.498, respectively (Table 2). The PIC varied in the four G. straminea populations, and the average values were 0.467, 0.433, 0.342 and 0.327 in the HZG, QZG, DRG and BMG populations, respectively. Although the average PIC value was no more than 0.500, three primer pairs exceeded 0.500, showing a high level of informativeness. Moreover, 7 out of 10 primer pairs significantly deviated from HWE within one or more populations, which could be expected considering small and inbred populations or the presence of null alleles (Čortan et al., Reference Čortan, Krak, Vít and Mandák2019). However, the value of He was considerably higher at almost all loci. Therefore, this deviation from HWE is likely to be explained by null alleles rather than by inbreeding and high-resolution melting markers can effectively solve the problem. There are notable variations in banding patterns observed among different regions, particularly among the three populations originating from the Yellow River source region (QZG, DRG and BMG) and Haidong agriculture region (HZG). The genetic diversity of G. straminea is influenced by geographical factors, similar to the distribution of active ingredients within the plant (Zhou et al., Reference Zhou, Lv, Zhang, Cheng, Wang, Lin, Shi, Chen and Shen2021).
Table 2. Genetic characterization of 10 newly developed markers in four G. straminea populations
A, number of alleles; He, expected heterozygosity; Ho, observed heterozygosity.
a χ 2 test for Hardy–Weinberg equilibrium. Locus showed significant deviations from Hardy–Weinberg equilibrium (P < 0.001).
Genomic SSR markers of Gentiana were developed and used in other related species in previous works, and the SSR markers from G. macrophylla, G. triflora and G. rigescens have been validated on a set of G. kurroo Royle accessions (Li et al., Reference Li, Li, Chen and Ge2007; Malhotra et al., Reference Malhotra, Jain and Bansal2021). However, the transferability of SSR markers from G. straminea in sect. Cruciata has not yet been assessed. To test the EST-SSR markers transferability, we selected 10 SSR markers identified in G. straminea to study eight populations of G. macrophylla and five populations of G. dahurica. The results of the amplification of the EST-SSRs in two related species are summarized in Table 3. The amplification efficiency was 100% with different alleles (2–10). Primer Un26568 showed the lowest Ho value (0.067), while primer Un1398 appeared to have the highest Ho value (0.900) in G. macrophylla populations. For the He value, primer Un26568 had the lowest value (0.066), and primer Un27221 had the highest value. In G. dahurica populations, three primers, Un1398, Un28224 and Un35051, all had the highest Ho value (1.000), and primer Un39037 had the lowest Ho value. For the He value, primer Un27221 had the highest value of 0.804, and primer Un39037 still had the lowest value. Moreover, the primers Un1398 and Un27221 showed higher PIC values in both G. macrophylla and G. dahurica selected populations, and 10 EST-SSR primers showed clear differences in the populations of two closely related species (Table 3). These results suggested that the new set of EST-SSR markers developed in this study may be informative for genetic studies of G. straminea and other related species in sect. Cruciata. Moreover, the EST-SSR markers were able to clearly differentiate the Radix Gentianae Macrophyllae into three main groups (Fig. 1): the first included G. straminea populations in Qinghai Province, the second clades contained G. macrophylla and G. dahurica, and two subclades were separated clearly. Among the clade or subclade, populations from different regions could also be clearly differentiated (Fig. 2). However, its detection efficiency may decrease due to species differences. For instance, markers such as Un26568 (G. macrophylla: 0.062) and Un39037 (G. macrophylla: 0.090; G. dahurica: 0.110) show relatively low PIC compared to G. straminea (Table 3).
Table 3. Cross-species amplification of 10 SSR markers developed for G. straminea in two related species
Na, observed number of alleles; Ne, effective number of alleles; He, expected heterozygosity; Ho, observed heterozygosity; PIC, polymorphic information content.
a Eight populations of G. macrophylla.
b Five populations of G. dahurica.
Figure 2. UPGMA dendrogram of G. straminea, G. macrophylla and G. dahurica populations (photographs: Ma xiaolei, Wang et al., Reference Wang, Ahmad, Duan, Zeng and Huang2016).
‘Qinjiao’ is an important traditional herb in China and has some adulterants in the market (Luo et al., Reference Luo, Ma, Yao, Xin, Hu, Zheng, Huang, Liu and Song2012). Although morphological characteristics could be applied to identify ‘Qinjiao’, authenticating medicinal plants could be very difficult because of similarities in morphological appearance (Wu et al., Reference Wu, Bligh, Leon, Li, Wang, Branford-White and Simmonds2012; Meng et al., Reference Meng, Chen, Song, Yao, Li, Zeng, Li and Cheng2013). Recently, DNA barcoding based on ITS, ITS2 and trnH-psbA, rbcL and matK has been developed in sect. Cruciata (Liu et al., Reference Liu, Yan and Ge2016). Here, our results showed that the cross-species transferability of the 10 markers was tested in eight populations of G. macrophylla, and five populations of G. dahurica could provide alternative molecular marker methods for the identification of ‘Qinjiao’ in the future. Furthermore, compared to genomic SSRs, EST-SSRs are more transferable across taxonomic boundaries, the identified markers can be effectively utilized in subsequent population genetics studies, specifically in investigating the dynamics of gene flow.
Conclusion
The findings of our study have significant implications, as they contribute to the establishment of a DNA fingerprint database for G. straminea and provide valuable tools for investigating genetic variation, preserving germplasm and facilitating molecular breeding efforts for this traditional Tibetan herb in the future.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S1479262124000224
Acknowledgements
This work was supported by grants from the Foundation of Science in Qinghai (2021-ZJ-734), the Construction Project for Innovation Platform of Qinghai Province (2022-ZJ-Y20) and Institute of Medicine Herb. We thank Ma Xiaolei for sharing photos of Gentiana straminea Maxim. and Gentiana dahurica Fischer.
Author contributions
Dangwei Zhou designed the study and wrote the manuscript; Tingfeng Cheng, Huan Wang and Jianwei Shen performed the research; Tingfeng Cheng, Kun Zheng, Jin Meng, Yuanwen Zhuang, Xingqiang Hu and Xing Ye tested the data; Pengcheng Lin and Shengbo Shi gave advice on the research.
Competing interests
The authors declare that there are no conflicts of interest associated with this publication, and there has been no significant financial support for this work that could have influenced its outcome.
