Introduction

Qingke (Hordeum vulgare L. var. nudum Hook. f.), also known as naked barley or hulless barley and belongs to the barley genus in the family Gramineae, is a variety of barley in which the inner lemma of the grain is separated from the caryopsis at maturity, and the grain is exposed (Yao et al. 2021; Liang et al. 2012). Qingke is rich in β-glucan, dietary fiber, trace elements, and other nutrients and has health functions, such as chronic disease prevention, including diabetes, blood lipid reduction, diabetes prevention, and anti-tumor properties (Lyu et al. 2022). Owing to its short reproductive cycle, cold and drought tolerance is necessary to adapt to the extreme environment of the plateau (Lyu et al. 2022). Qingke is mainly distributed in five provinces and regions, namely Xizang, Qinghai, Gansu, Sichuan, and Yunnan (Chen et al. 2022), with a planting area of more than 270,000 hectares and an annual production of more than 1 million tons in China (Guo et al. 2020).

It is well known that the molecular identification of cultivars is a key step in a plant improvement strategy. Qingke is mainly planted on the Qinghai–Xizang Plateau (Chen et al. 2023). In the process of breeding new cultivars, cultivars within the region crossbreed with each other so that the parents and core germplasm containing excellent genes are repeatedly utilized. Thus, the genetic distance is becoming increasingly closer, reducing the genetic diversity. The similarity between new cultivars has increased, and the identification of genetic material in close proximity is sometimes difficult (Mériam et al. 2018). Cultivar identification is an effective tool for variety rights protection. With the development of molecular biology, the use of molecular marker technology to construct varietal DNA fingerprints to identify species has emerged as a more rapid, simple, economical, and reliable identification method than morphological identification (Mériam et al. 2018; Liang et al. 2023). To analyze the genetic diversity of existing primary Qingke cultivars, it is necessary to establish a Qingke DNA fingerprint library. Currently, simple sequence repeats or microsatellites (SSRs) method used in DNA fingerprints, has the advantages of high polymorphism, stability, good reproducibility, and mature technology (Sharan et al. 2024; Ilyas et al. 2023). The main methods for detecting SSR-labeled fragments are polyacrylamide gel electrophoresis (PAGE) and capillary electrophoresis (MCE) (Elumalai and Srinivasan 2023). They have been successfully applied to construct fingerprint profiles in sweet potato (Luo et al. 2023), Chimonanthus (Li et al. 2023), azuki bean (Vigna angularis), mung bean (Vigna radiata L.) (Zhao et al. 2022), wheat (Türkoğlu et al. 2023), and Amomum villosum (Li et al. 2022). However, this has not yet been reported for Qingke.

This study utilized SSR molecular markers to distinguish 12 Qingke cultivars using the existing 837 pairs of barley primers. A total of 18 pairs of SSR markers were screened and used to analyze the genetic diversity of 63 Qingke primary cultivars. DNA fingerprinting of Qingke cultivars was constructed to provide technical support for rapid and accurate identification and protection of cultivars.

Materials and methods

Plant materials

The 63 Qingke primary cultivars used in this study were bred and preserved by Academy of Agricultural and Forestry Sciences, Qinghai University (Table 1). Nine cultivars of them were from Sichuan 20 cultivars from Qinghai, 17 cultivars from Xizang, six cultivars from Yunnan, nine cultivars from Gansu, and two cultivars from Heilongjiang. Three young leaves were collected from each cultivars, frozen in liquid nitrogen, and stored in a − 80 °C low-temperature freezer.

Table 1 Information sheet of the 63 tested materials
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Methods

DNA extraction

The sample was placed in a 2.0-mL centrifuge tube and 700-μL CTAB extract preheated to 65 °C was added. The tubes were shaken well and incubated in a 65 °C thermostatic water bath for 45–60 min. Every 10 min, the centrifuge tube was removed and cooled to room temperature. After incubation, an equal volume of chloroform: isoamyl alcohol (24:1, V/V) solution was added, and the tubes were shaken gently up and down several times until the liquid was milky white. They were then centrifuged at 12,000 rpm for 10 min. The supernatant was transferred to a new 2.0-mL centrifuge tube, and 1.5 times the volume of precooled anhydrous ethanol was added. After gently mixing, the tubes were centrifuged at 12,000 rpm for 3 min to separate the phases. The tubes were removed from the centrifuge, and the supernatant was discarded. The samples were washed twice with 70% ethanol solution and dried under natural conditions. To dissolve the precipitate, 50 μL 1 × TE buffer (PH 8.0) was added. The quality of the DNA stock solution was tested using 0.8% agarose gel electrophoresis, and the concentration of the DNA stock solution was detected using a nucleic acid concentration meter. The stock solution was diluted to 50–150 ng/μL. The DNA was stored at − 20 °C.

SSR molecular marker screening

In this study, 12 primary Qingke cultivars (Table 1) and 837 pairs rom the barley genome and the literature were used. First, polyacrylamide gel electrophoresis was used to select consistency, stability, clear bands, polymorphism, etc., to co-screen candidate SSR molecular marker primers. Secondly, based on the principles of high efficiency, economy and uniform distribution, marker primers were selected as the preferred markers for authenticity identification of Qingke cultivars. The primers screened initially were examined for polymorphism by capillary electrophoresis. Primers were synthesized by Beijing Qingke Biotechnology Co (Beijing, China).

PCR amplification system

The PCR reaction system volume was 20 μL (Table 2). The PCR amplification program was as follows: 94 °C for 5 min; 94 °C for 30 s, 60–50 °C for 60 s (0.8 °C drop per cycle, total 12 cycles), and 72 °C for 30 s; 23 cycles of 94 °C for 30 s, 50 °C for 45 s, and 72 °C for 30 s; and final 72 °C for 10 min. The amplification products were stored at 4 °C.

Table 2 Polymerase chain reaction (PCR) amplification reaction system
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Capillary electrophoresis fluorescence detection

Sample preparation

Fluorescence detection by capillary electrophoresis required the use of fluorescently labeled primers. Depending on the size range of the amplified fragments of the allelic variants, SSR primers were combined by labeling with four fluorescent dyes, which needed to be labeled at the 5' end of either the upstream or downstream primer to match the emission and absorption wavelengths of the capillary electrophoresis instrument.

According to the pre-determined combination of the primers, equal volumes of different fluorescent-labeled amplification products of the same combination of primers were obtained separately and mixed well. For genetic analysis, 1 μL of the mixture was added to a 96-well plate. To each well, 0.1 μL of molecular weight internal standard and 8.9 μL of deionized formamide were added. The samples were placed in the PCR instrument to denature at 95 °C for five min. They were removed, immediately placed on ice, cooled for more than 10 min, centrifuged for 10 s, and prepared for use.

Electrophoretic detection

The DNA analyzer (ABI 3730XL) was turned on to check the working conditions of the instrument. Buffer was added, and the glue was filled. A 96-well upper plate with samples was placed on the sample rack base. Data collection software was used following the genetic analyzer manual. The sample table was edited, and the run program was executed. The data were saved.

Data processing

GeneMaker V2.2.0 software was used to create the raw data according to the size of the molecular fragments of the amplification products. PowerMarker 3.25 and Popgen32 software were used to calculate Na, effective alleles (Ne), Shannon’s information index (I), PIC, major allele frequency (MAF), He, and Ho as indicators of the genetic diversity of the 18 pairs of primers. Genetic diversity indexes were calculated for 18 primer pairs using GenAIEx 6.51 and raw data on amplification product size. Nei’s genetic distance between the cultivars was assessed using PowerMarker 3.25, and a grouping tree was constructed using the neighbor-joining (NJ) method and visualized using iTOL (iTOL: Interactive Tree of Life (embl.de)). The population structure was analyzed using Bayesian modeling with Structure 2.3.4 and a Markov chain Monte Carlo (MCMC) approach with preset population groupings (K). Calculating, sampling, and grouping of individuals were based on allele frequencies. The parameter settings were as follows: K value range, 1–10; each K value for 10 independent runs; number of parameter iterations (length of burn in period), 100,000. The optimal K value was calculated on the STRUCTURE HARVESTER (http://taylor0.biology.ucla.edu/struct_harvest/) website. Finally, using the raw data on the size of amplification products, principal co-ordinates analysis (PCoA) was performed on 63 Qingke cultivars using GenAIEx 6.51.

DNA fingerprinting

Raw data (unit bp omitted) were created from the size of molecular fragments of the amplification products of 18 pairs of SSR primers in 63 primary Qingke cultivars using GeneMaker V2.2.0 software. The 18 pairs of SSR polymorphism primers were coded in a fixed order and recorded as 1–18 to read 63 primary Qingke cultivars in the form of allelic markers in the primer amplification of the product size. They were separated by “-” in the middle of the primer number, and site reads with “:” were connected to form a combination of allelic marker configurations. The time of the combination was separated by “/.” The tandem of 18 primers and allele configuration combinations constituted the DNA digital fingerprinting code for the cultivar.

Results

Primer screening

Utilizing the 12 primary Qingke cultivars (remarks in Table 1), we selected stable repeatability and excellent polymorphic primers from 837 SSR primer pairs. Based on the principles of efficiency, economy and simplicity, 18 pairs of SSR primers were selected as preferred markers for the identification of Qingke cultivars (Table 3). In addition, these 18 pairs of SSR primers were evenly distributed on Qingke chromosome 7, and their polymorphism contents varied. The SSR primers were combined into three sets of primers by labeling four fluorescent dyes according to the size range of the amplified fragments of the allelic variants (Table 4).

Table 3 Eighteen pairs of simple sequence repeat (SSR) marker primers
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Table 4 Eighteen pairs of simple sequence repeat (SSR) primers primed by labeling four fluorescent dyes into three sets of primers
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Analysis of genetic diversity

Fluorescence capillary electrophoresis was performed on 63 primary Qingke cultivars using 18 pairs of SSR primers. These included a total of 83 Na (Table 5). 83 Na uniquely genotype the 63 individuals, indicating that the 18 SSR markers had a high discriminatory ability. The number of Na ranged from three to 11, with an average of 4.61 per pair. Among them, Bmag0496 and GBM1516 had more bit points (11 and seven, respectively). The MAF ranged from 0.37 to 0.75, with a mean value of 0.54. The PIC ranged from 0.36 to 0.74, with a mean value of 0.52. The I value ranged from 0.71 to 1.80, with a mean value of 1.07. The He values ranged from 0.40 to 0.77, and the mean value was 0.59. The Ho values ranged from 0.13 to 0.67, with a mean value of 0.32. The data showed that the selected SSR markers were rich in polymorphism, and the 63 primary Qingke cultivars had high heterozygosity and rich genetic diversity.

Table 5 Polymorphism detection of 18 pairs of simple sequence repeat (SSR) primers in 63 primary Qingke cultivars
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Population structure analysis of 63 primary Qingke cultivars

Genetic distances and phylogenetic tree analysis

To understand the inter-individual genetic relationships Nei’s genetic distances among 63 primary Qingke cultivars were assessed using PowerMarker 3.25, and a phylogenetic tree was constructed based on the genetic distances using the NJ method (Fig. 1). The results of Nei’s genetic distance showed large genetic differences among 63 primary Qingke cultivars, with an average genetic distance of 0.55. The largest was between Kunlun 13 and Yunke 4, with a genetic distance of 0.94, which showed the most distant kinship. The smallest was between Zangqing 78 and Zangqing 80, with a genetic distance of 0.12, which showed the most closest kinship. The phylogenetic tree divided them into three groups. Group I contained 26 Qingke cultivars, 14 from Xizang, seven from Qinghai, three from Sichuan, and two from Gansu. Group II contained 16 Qingke cultivars, six from Yunnan, three from Sichuan, three from Xizang, two from Heilongjiang, one from Gansu, and one from Qinghai. Group III contained 21 Qingke cultivar, 12 from Qinghai, six from Gansu, and three from Sichuan. Among the 63 primary Qingke cultivars, Qingke from Xizang was mainly distributed in group I. Qingke from Qinghai was mainly distributed in groups III and I. Qingke from Yunnan and Heilongjiang were distributed in group II, and Qingke from Gansu was mainly distributed in group III. On the whole, most of the qualities from the same source were clustered in the same branch, showing close affinities. The results suggested that the geographic location of genetic cultivars had important relevance in cluster analysis. However, this correlation was not absolute due to environmental factors and artificial breeding choices, and the primary Qingke cultivars from Sichuan had three copies in each of the three groups.

Fig. 1
figure 1

Phylogenetic tree of 63 primary Qingke cultivars. Orange, green, and blue-green dots correspond to Groups 1, 2, and 3, respectively. (Color figure online)

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Structure analysis

To further assess the genetic characterization of primary Qingke cultivars, a population structure analysis was carried out in this experiment using STRUCTURE 2.3.4 and Evanno et al. (2005) of STRUCTURE HARVESTER (Fig. 2). The results showed that deltaK (ΔK) had a maximum value when K = three, indicating that the 63 primary Qingke cultivars could be categorized into three groups (Fig. 2A). As shown in Fig. 2B, when K = two, group II was divided into groups I and III, forming only two groups. When K = four, group I was divided into two groups, resulting in the formation of 4 groups. When K = three, in group I, the Q value was greater than 0.8 with 11 materials, accounting for 44% of such groups. Zangqing 1218, Zangqing 13, Zangqing 2000, Zangqing 25, Zangqing 28, Zangqing 320, Zangqing 78, Zangqing 80, Zangqing 811, Zangqing 83, and Ximala 22 belonged to group I in the phylogenetic tree and were all from Xizang. In group II, there were seven Qingke materials with a Q value greater than 0.8, accounting for 50% of such groups. Cultivars Diqing 3, DuanbaiQingke, Ganqing 1, Longke 4, Longke 5, Yunke 4, and ChangheiQingke belonged to group II in the phylogenetic tree. Except Ganqing 1 from Gansu, the other cultivars were from Yunnan and Heilongjiang. In group III, there were 15 Qingke materials with a Q value greater than 0.8, accounting for 62.5% of such groups. In group III, there were 15 Qingke materials with a Q value greater than 0.8, accounting for 62.5% of this group. Beiqing 1, Beiqing 3, Beiqing 4, Beiqing 6, Beiqing 8, Dulihuang, Ganqing 2, Ganqing 4, Ganqing 7, Huangqing 2, Kangqing 2, Kunlun12, Kunlun 13, Kunlun 14, and Kunlun 18 belonged to group III in the phylogenetic tree. Except for Kangqing 2, which was from Sichuan, the rest of the cultivars were from Qinghai and Gansu. In the three groups, only 50.7% of the Qingke cultivars were relatively homogeneous, and some of the cultivars were mixed types, indicating that there was also extensive hybridization among the three subgroups, especially in Sichuan, where the Qingke cultivars were distributed in all three groups (Fig. 2C).

Fig. 2
figure 2

Structure analysis of 63 primary Qingke cultivars. A Distribution of ΔK for different values of K. B Population structure analysis of 63 primary Qingke cultivars when K = 2–4; C Population structure analysis of 63 primary Qingke cultivars when K = 3. With K = 3, red, green, and blue bars correspond to Groups 1, 2, and 3, respectively. (Color figure online)

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3.3.4 Principal component analysis (PCoA)

PCoA was performed on 63 primary Qingke cultivars using GenAIEx 6.51. The 63 primary Qingke cultivars were equally divided into 3 groups. The Qingke cultivars contained in each group were consistent with the results of the phylogenetic tree. They were consistent with the primary Qingke cultivars with a Q value greater than 0.8 in the STRUCTURE grouping groups and inconsistent with some primary Qingke cultivars with a Q value less than 0.8, namely Huangqing 1, Kangqing 3, Kangqing 6, Kunlun 17, and Kunlun 8, which all belonged to the STRUCTURE grouping analysis in the mixed type (Fig. 3).

Fig. 3
figure 3

The 63 primary Qingke cultivars were subjected to principal coordinate analysis (PCoA) analysis based on genetic distance. Orange, green and blue dots correspond to Groups 1, 2, and 3, respectively. (Color figure online)

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DNA fingerprinting of 63 primary Qingke cultivars

DNA fingerprinting could effectively identify the purity of Qingke quality, providing strong support for the identification, protection, and utilization of Qingke cultivars. Simplified fingerprints of 63 primary Qingke cultivars were constructed by combining the raw data of 63 primary Qingke cultivars established by the size of the molecular fragments amplified using 18 pairs of SSR polymorphic primers. The fingerprints constructed by this method intuitively reflected the unique bands of each cultivar and quickly and accurately identified 63 primary Qingke cultivars (Table 6).

Table 6 Simple sequence repeat (SSR) fingerprinting codes of 63 primary Qingke cultivars
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Discussion

Genetic diversity of primary Qingke cultivars

Genetic diversity reflected the differences in genetic composition between populations or between individuals within populations, and was an important reference value for research on the origin and evolution of species, as well as their exploitation and utilization. SSR molecular markers can directly reflect the DNA level evolutionary relationships and genetic variation, providing technical security in the study of genetic polymorphism and population structure of species (Cheng et al. 2023). In this study, we analyzed the genetic diversity of 63 primary Qingke cultivars’ genotypes using 18 SSR molecular markers. 18 SSR molecular markers were distributed on seven chromosomes of the Qingke genome, which can be used as effective markers for the genetic diversity analysis of primary Qingke cultivars. Na, Ne, I, PIC, MAF, He and Ho indices were important indicators for assessing polymorphism of SSR markers and for evaluating the genetic diversity of organisms (Zeng et al. 2019). Different forms of Na were located in genes at the same location or genetic locus on chromosomes, and the level of Na reflected one of the indicators of population genetic variation (Ji et al. 2017). In this study, a total of 83 Na were identified, with the number of Na ranging from three to 11, with an average of 4.61per pair. These values were higher than those for the 70 Na connected to points ranging from two to 10, with an average of 3.68 achieved through 19 SSR primers for 60 Qingke cultivars from three counties in the Shangri-La region, Yunnan Province, which were reported by Guo et al.(2012). This indicated that the SSR markers applied in this study showed high polymorphism and excellent genetic quality in 63 primary Qingke cultivars. The results showed that the method could provide a good technical support for genetic diversity evaluation and kinship identification of 63 primary Qingke cultivars. The Na values obtained in this study were lower than those for the amplification of 562 large Qingke germplasm cultivars using 93 SSR primers (two–16, average 5.55) reported by Xu et al.(2017) and the amplification of 107 local Qingke cultivars from the Nepalese plateau (Pandey et al. 2006),utilizing 44 SSR primers (average 5.54). The low mean value of the number of Na was mainly attributed to the difference in the number of SSR marker primers screened. Whereas in this study, the SSR primers were screened based on stability, polymorphism, and high efficiency and were mainly used as preferred markers for the identification of Qingke cultivars. It is an index to estimate community biodiversity by using genetic information theory. The I values ranged from 0.71 to 1.80, with a mean value of 1.07, which was higher than 0.305 (Xu et al. 2017). PIC was a measure of the amount of information a genetic marker polymorphism could provide in a linkage analysis (Alaaeldin et al. 2024). PIC values were a measure of good and poor microsatellite marker polymorphisms. The larger the PIC, the greater the proportion of heterozygotes in a population and consequently in that seat, the higher the genetic information provided (Parada et al. 2012 ). Previously, the polymorphism of primers was categorized into three intervals based on PIC values as PIC < 0.25, 0.25 < PIC < 0.5, and PIC > 0.5 (Botstein 1980). The PIC values in this study ranged from 0.37 to 0.74, with a mean value of 0.52, which was significantly higher than 0.157 (Xu et al. 2017) and 0.3 (Guo et al. 2012). This indicated that the SSR markers selected in this study exhibited a high degree of polymorphism and were able to objectively reveal the level of genetic diversity of the 63 primary Qingke cultivars. Among them, 7 pairs of SSR markers had PIC values between 0.25 and 0.5, with medium polymorphism, and 11 pairs of SSR primers had PIC values > 0.5, which were highly polymorphic markers, accounting for 64.7% of all markers. The results showed that a large proportion of heterozygotes at these loci in 63 primary Qingke cultivars provided high genetic information and more genetic variation. Higher genetic diversity could be used to infer genetic distances between cultivars and for subsequent population structure analysis.

Phylogenetic tree, population structure, and principal component analysis of primary Qingke cultivars

Custer analysis can reflect the relationship between individuals (Amritha et al. 2024). Population structure analysis better reflects the genetic background and gene exchange among the 63 Qingke primary cultivars than cluster analysis (Zhao et al. 2021). Principal component analysis can not only visualize and three-dimensionally indicate the genetic distance and kinship between the 63 Qingke primary cultivars, but also reflect the degree of dispersion between different categories (Zhang et al. 2022). The results obtained based on group analysis, population structure, and principal component analysis of 63 Qingke primary cultivars were highly consistent and corroborated each other. The results showed that they were divided into three groups, which were analyzed in relation to their geographic origins. Group I mainly contained the primary cultivars of Xizang and Qinghai. Group II mainly included the primary cultivars of Qinghai and Gansu, and group III mainly included the primary cultivars of Yunnan and Heilongjiang, indicating that the grouping results of these primary cultivars were closely related to their geographic origins. Chen et al. (2023) and Wang et al. (2014) similarly indicated that the population structure of Qingke in the Qinghai–Xizang Plateau region is closely related to its geographic origin. Population structure analysis showed that 52.38% of Qingke cultivars had a Q value greater than 0.8. This germplasm was relatively singular, and the genetic structure was relatively simple, which could provide a research basis for subsequent Qingke genetic breeding. However, the genotypes of some cultivars in the three groups were mixed; for example, the genotypes of nine primary Qingke cultivars from Sichuan were mixed, accounting for three in each of the three groups, suggesting that the genotypes of these Qingke cultivars showed high heterozygosity and that the correlation with geographic location was not noticeable. Similarly, geography had less influence on the genetic structure of Ethiopian barley local cultivars, with climatic factors accounting for 37.4% of the explained variation (Abebe et al. 2015). In summary, most Qingke cultivars had a certain correlation between taxon division and geographic location, while the correlation of some cultivars with mixed genotypes was not clear. This might be the r were divided into three actors, such as environmental factors, gene exchange, and artificial selection. The analyzed data told us that the results of cluster analysis, population structure and principal component licensing could be used as a reference when selecting breeding parents. Priority is given to the more distantly related cultivars in preference to those with a simple genetic structure in the population structure analysis, so that the genetic differences in the progeny material obtained are richer.

DNA fingerprinting of primary Qingke cultivars

The DNA fingerprinting technique analyzes the genetic material itself, avoiding the influence of factors such as the environment, sample morphology, and the source of the material, and identifies the germplasm genotype as an indicator at the molecular level, which is regarded as the baseline method for cultivar identification (Zhang et al. 2023). Currently, DNA fingerprinting is widely reported in plants, such as sugar beet (Liang et al. 2023), cotton (Santosh et al. 2022), Atractylodes chinensis (fam. Asteraceae) (Ma et al. 2022), and sunflower (Ibrar et al. 2022). Šurlan-Momirović et al. 2013 used SSR markers for DNA fingerprinting of 145 barley from Serbia, and Jaiswal et al. (Jaiswal et al. 2007) used randomly amplified polymorphic DNA markers for DNA fingerprinting of 26 barley species. However, research related to the construction of the DNA fingerprints of Qingke has not been reported. In this study, we successfully constructed 63 digital DNA fingerprints of Qingke cultivars to provide fast and accurate technical support for the detection of Qingke cultivars, to ensure the seed quality of cultivars from the source, and to play the role of cultivar on yield.

Conclusion

Genetic diversity and population structure of markers for SSR analysis and their fingerprints were constructed using 18 pairs of polymorphic primers for 63 primary Qingke cultivars from Sichuan, Qinghai, Xizang, Yunnan, Gansu, and Heilongjiang. The average values of Na, PIC, I, He, and Ho were 4.61, 0.52, 1.07, 0.59, and 0.32, which were within acceptable limits. According to the genetic distance construction of the evolutionary tree, population structure and PCoA showed that the three grouping results were basically the same. There was rich and high genetic diversity among the genotypes of 63 primary Qingke cultivars, which were divided into three groups. In this study, efficient SSR marker primers of Qingke were screened to more accurately assess the genetic characteristics. Based on the results of DNA fingerprints of 63 primary Qingke cultivars, we can be applied to the identification of new cultivars of Qingke and the authenticity of cultivars. Based on the results of genetic diversity and population structure analyses of 63 primary Qingke cultivars, we can select cultivars that are genetically far apart when selecting parents for breeding, thus maintaining rich genetic differences in offspring. This study lays the foundation for guiding the selection of breeding parents and new cultivars of Qingke in Sichuan, Qinghai, Tibet, Yunnan, Gansu and Heilongjiang, and promoting the innovation of germplasm resources in the future.