Introduction

Currants are botanically classified in the genus Ribes L. (Grossulariaceae family). Currants are shrubs, with more than 150 described species of Ribes L. native to northern Europe, Asia, North America, South America and Northwest Africa (Brennan 1996; Hummer and Barney 2002). According to FAO-2020 data, 687,467 tons of currants were produced worldwide. Russia (436,900 tons), Poland (146,500 tons), Ukraine, the United Kingdom, Germany and France provide 94.4% of the world’s production (FAOSTAT 2022).

Brennan (2008) reported that the taxonomy and phylogeny of the genus Ribes L. have not yet been completed. The cultivated species of the genus Ribes L. were grouped into three subgenera: Coreosma (black currants), Ribesia (red currants) and Grossularia (gooseberries). According to a DNA-based molecular characterization study carried out on a total of 47 Ribes species, it was necessary to differentiate taxa at the same level into two separate subgenera: (1) black currants and red currants and (2) gooseberries (Zdunic et al. 2016). Kissling (2020) reported that the species Ribes petraeum, Ribes spicatum, Ribes rubrum, and Ribes multiflorum belonged in the European Ribes subgenus Ribesia [(Berland.) Jancz. 1907]. In Brennan (1996), while Ribes nigrum and three cultivars of this species (var. europaeum, var. scandinavicum, var. sibiricum) and Ribes ussurience, Ribes bracteousum, and Ribes petiolare were specified as black currant species, Ribes sativum, Ribes patreaum, Ribes rubrum and Ribes multiflorum were defined as red currant species. White and pink are the colour forms of Ribes rubrum (Brennan 2008; Zdunic et al. 2016). As reported in Weigend (2007), the several thousand Ribes L. cultivars can be roughly subdivided into five groups: red currants, white currants, black currants, gooseberries, and currant–gooseberry hybrids (Zdunic et al. 2016).

Onur (2006) reported wild currant species at altitudes up to 1000 m from Artvin to Çanakkale in Northern Anatolia in Türkiye and on the slopes of mountains and in wet areas such as streams at altitudes up to 3000 m in Eastern and Central Anatolia. The currants, which belonged to real grapes in the botanical sense, displayed shrubby stems according to the classification scheme based on stem characteristics. According to the information given in Kendir et al. (2019), there are eight Ribes species in the Flora of Turkey. Among these, the species R. rubrum L. was cultivated, and seven other Ribes L. species [R. petraeum Wulfen (syn. R. biebersteinii Berl. ex. DC.), R. nigrum L., R. uva-crispa L., R. alpinum L., R. orientale Desf., and R. multiflorum Kit. ex. Romer & Schultes, R. anatolica Behçet (endemic)] were found in natural habitats. R. orientale and R. alpinum have been reported as unisexual species, while R. rubrum, R. petraeum and R. multiflorum have been reported as hermaphrodite species (Chamberlain et al. 1972; Chamberlain et al. 1988; Behçet 2001). In addition, the basic chromosome number of all Ribes L. species has been reported to be x = 8 (Zielinski 1953). The cultivars were found to be diploid (2n = 2x = 16), and the mean genome size was 2C = 1.91 pg (R. petraeum Wulf., R. rubrum and R. grossularia L.) (Chiche et al. 2003; Palmieri et al. 2013).

Globally, the relationship between the consumption of wild edible fruits and human health in Türkiye has become increasingly important for consumers. Today, the demand for natural, healthy, delicious, functional foods and fruits is quite high (Ercisli 2007). Currant species were among the best examples. Edible wild fruit species, including currant species (Ribes L.), are very genetically rich. Red-fruited currants and especially the black-fruited currants have very valuable components that affect human health. These fruits are preferred for fresh consumption in the food industry as well as in the pharmacology and cosmetics industries. Therefore, these plant species have high economic value. The propagation and growth of currants are not difficult, and they are important alternative products for producers. Their commercial value can be improved further if new cultivars of better quality and greater productivity are obtained through breeding research. In Türkiye, sales of foreign breeding products such as Rovada, Red Lake, Titania, Jonkheer van Tets, Goliath and White Pearl are common. Currants are mostly preferred as hobby plant products in home gardens and are sometimes sold by some manufacturers. Although some research has been carried out on Ribes L. species in this country, these investigations have generally involved morphological and biochemical evaluations.

As elsewhere around the world, plant genetic resources in our country are at risk of decreasing or even disappearing due to environmental and other pressures in the regions where they are located. Molecular characterization for breeding research is important, as is in situ or ex situ conservation of plant genetic resources. A molecular characterization study has been planned as a preliminary study to support breeding research of currant genetic resources in Türkiye. For this purpose, iPBS and SSR marker systems were preferred. Thus, the effectiveness levels of these two marker systems for currants will be compared.

Materials and methods

Plant materials

In this study, 10 currant cultivars (R. nigrum, R. rubrum) and one hybrid jostaberry cultivar (R. nigrum × nidigrolaria), which are breeding products of European countries but are the best known and have high commercial value in Türkiye, were used. One black currant cultivar from Türkiye was included. In addition to these cultivars, 14 currant genotypes naturally grown in the eastern Black Sea region and the northern parts of the Eastern Anatolian Region of Türkiye were used. The species, fruit colour, origin and pedigree information of the currant cultivars and genotypes used in the study are given in Table 1. In Fig. 1, the location information of 14 currant genotypes obtained from northeastern Türkiye is presented. Young leaf samples were taken from the currant plants, which first emerged in the spring (April–May 2022). The plant materials were transported to Atatürk University, Faculty of Agriculture, Agricultural Biotechnology Laboratory, under cold chain conditions and stored in a deep freezer (−80 °C).

Table 1 Species, fruit color, origin and pedigree information of currant cultivars and genotypes used in the study
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Fig. 1
figure 1

Location information of fourteen currant genotypes obtained from the northeast of Türkiye

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DNA isolation and analysis

Genomic DNA was extracted from young leaf tissues. The DNA isolation protocol modified from Li and Quiros (2001) was used. For each sample, 0.3 g of plant material was digested with liquid nitrogen and prepared for DNA isolation. 1000 µl of DNA extraction buffer (containing 0.2% β-mercaptoethanol and 0.2 g PVP) was added to the plant material in a 2 ml tube. After the isolation steps were completed, the DNA was washed with 70% ethanol and dissolved in 100 ml of 1X TE buffer. The DNA was suspended at + 4 °C for 24 h and stored at −20 °C. The DNA quantity and purity of the samples were determined. For this purpose, optical densitometric spectrophotometer (NanoDrop, ND-1000) readings were obtained at 260 and 280 nm. The DNA concentrations were adjusted to 50 ng/µl. The DNA was stored at −20 °C. For the qualitative determination of DNA samples, electrophoresis was performed at 60 V on a 0.8% (w/v) agarose gel prepared with 1X TBE buffer.

iPBS-PCR analysis

Fourteen iPBS primers specific to retrotransposon sequences designed by Kalendar et al. (2010) were used in this study (Table 2). Gradient PCR was performed between 50 and 60 °C to determine the annealing temperatures of the iPBS primers. The PCR steps were performed in the following order: 5 min at 95 °C for predenaturation, then 1 min at 94 °C for denaturation, 1 min 5 s at 50–60 °C for annealing, 1 min at 72 °C for elongation (40 cycles) and 10 min at 72 °C for final elongation. The following PCR components were used in addition to the QIAxcel DNA Kit for all the iPBS primers: 0,01 nM primer, 8 M of Taq DNA polymerase (Amplicon), 5 µl of ultrapure water, and 1 µl of genomic DNA (50 ng/µl). Electrophoresis of the PCR products was performed using a QIAxcel DNA Kit (with a QX alignment marker and a QX DNA size marker) on a Qiagen capillary analysis system.

Table 2 Marker names of the 14 inter-primer binding site (iPBS) primers used in this study, primer sequences, annealing temperature (Ta), size range (SR) of PCR product, number of average alleles (avNa), number of total alleles (Na), number of polymorphic alleles (Npa), polymorphism (P), mean heterozygosity (Havp), polymorphism information content (PIC), marker index (MI), discriminating power (D)
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SSR-PCR analysis

A total of 10 SSR loci were used in the study, namely, e2-L15, g1-F04, g3-A17 (Çelenk 2015), e1-O21, g1-I02, e3-B02, g2-G12 (Palmieri et al. 2013), RJL-2, RJL-6 and RJL-11 (Brennan et al. 2002; Antonious et al. 2012) (Table 3). Gradient PCR was performed between 50 and 60 °C to determine the annealing temperatures of the SSR primers. PCR steps were performed in the following order: 3 min at 95 °C for predenaturation, then 3 s at 94 °C for denaturation, 1 min at 57 °C for annealing, 1 min at 72 °C for elongation (35 cycles) and 30 min at 72 °C for final elongation. The following PCR components were used in addition to the QIAxcel DNA Kit for all SSR primers: 0,01 nM primer, 8 M of Taq DNA polymerase (Amplicon), 5 µl of ultrapure water, and 1 µl of genomic DNA (50 ng/µl). Electrophoresis of the PCR products was performed using a QIAxcel DNA Kit (with a QX alignment marker and a QX DNA size marker) on a Qiagen capillary analysis system.

Table 3 Locus names of the 10 simple sequence repeat (SSR) primers used in this study, primer sequences, annealing temperature (Ta), size range (SR) of PCR product, number of average alleles (avNa), number of total alleles (Na), number of polymorphic alleles (Npa), polymorphism (P), mean heterozygosity (Havp), polymorphism information content (PIC), marker index (MI), discriminating power (D)
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Scoring and data analysis for iPBS and SSR markers

The results of analyses at the molecular level using DNA-based markers can be evaluated using different statistical programs and methods. NTSYSpc-2.2 (Numerical Taxonomy Multivariate Analysis System), which is one of the statistical programs used in data analysis and is based on a numerical system, can be used for multivariate data (Rohlf 2000). The matrix is formed by using “1” for the presence of characters and “0” for the absence of characters in the variables. In the program, dendrogram construction and principal component analyses (2D and 3D) can be performed. Dendrograms are a representation of data divided into various levels, and vertical lines represent clusters that have come together. The positions of the lines in dendrograms indicate the distances at which the clusters come together. With cluster analysis, it is possible to group similar observations into a series of clusters based on the observed values of multiple variables for each individual. The principal component analysis (PCA) method is an orthogonal (vertical) transformation in which a set of possibly related variables are converted into a set of linearly unrelated variables called principal components (Ekinci 2020). Principal coordinate analysis (PCoA) is a multidimensional scaling method used to explore and visualize similarities or differences in data. PCoA is a generalization of PCA and involves measuring the similarity between variables. It starts with a similarity matrix or a dissimilarity matrix (distance matrix) and assigns a location for each element in a low-dimensional space as a 3D graphic (Karimizedeh et al. 2019).

The genetic similarity values among individuals were analysed using NTSYS (Rohlf 2000). The similarity coefficients and clustering analysis of plant samples were calculated and performed by using the Jaccard (1908) similarity coefficient with the help of UPGMA (unweighted pair group method with arithmetic mean) (Nei 1983). The polymorphism rate was calculated with the following formula: Polymorphism (%) = (Number of polymorphic bands/Total number of bands) × 100.

In addition, some indices of polymorphism were determined using the iMEC online tool (iMEC 2023). Among the IMEC indices, the value of heterozygosity (Havp) calculated for polymorphic markers was determined by the formula Havp = Σ Hn/np (observed heterozygosity). The polymorphism information content (PIC) was used to measure the information level of a genetic marker and was calculated with the following formula: PIC = 1—Σ pi2—Σ Σ pi2 pj2. This index differs from heterozygosity, expressing the value of a marker in detecting polymorphism based on the number of alleles and the distribution of their frequencies. The marker index (MI) was the product of the effective multiplex ratio and the mean heterozygosity for polymorphic markers and was determined by the formula MI = E Havp. The discriminating power (D) was determined by the formula D = 1—C. This index is based on the distribution of alleles in the sampled individuals and is strongly associated with the ability to distinguish among analysed samples. These indices are based on dominant and codominant DNA fingerprint markers. They allow the comparison of genetic markers and selection of the most suitable ones for a given dataset (Amiryousefi et al. 2018).

Results and discussion

There have been many investigations on currants (Ribes L.), especially in Europe. To date, the many currant cultivars that have been developed in terms of certain characteristics by selection and hybridization programs from their natural environments have been introduced and used with high commercial value (Hummer and Barney 2002). Plant genetic resources are the most important natural resource of countries. Türkiye displays rich biodiversity for many temperate- and subtropical-climate fruit species due to its geographical location and different climate and soil characteristics. However, due to interest in other fruit species (apple, cherry, almond, pistachio, olive, walnut, citrus species, etc.) with high economic value in this country, very few hybridization investigations have been carried out on currant species. The selection research on currants was mostly carried out as phenotypic and biochemical evaluations of genotypes in their natural environment.

Among the molecular characterization research carried out in currant species to date, efforts such as determining the genetic diversity levels of currant populations grown in their natural habitats, determining genetic relationships among currant cultivars that are the products of breeding research, genetic linkage mapping (Brennan et al. 2008; Pikunova et al. 2020) and genotyping by sequencing (Russell et al. 2014) can be found. In all these investigations performed at the molecular level, DNA-based RAPD (Lanham et al. 2000; Keller-Przyblkowicz et al. 2006; Huo et al. 2013; Butiuc-Keul et al. 2015; Lanham and Brennan 1999; Debnath 2015), AFLP (Lanham and Brennan 1999; Mattia et al. 2008; Brennan et al. 2008; Ipek et al. 2010), ISSR (Lanham et al. 2000; Keller-Przyblkowicz et al. 2006; Lanham and Brennan 1999; Debnath 2015; Gentili et al. 2015), SSR (Lanham and Brennan 1998; Brennan et al. 2002; Brennan et al. 2008; Sordo et al. 2008; Cavanna et al. 2009; Russell et al. 2011; Antonius et al. 2012; Palmieri et al. 2013; Gentili et al. 2015; Butiuc-Keul et al. 2015; Çelenk 2015; Mezhnina and Urbanovich 2017; Pikunova et al. 2019; Vidyaginan et al. 2021; Lacis et al. 2021), SNP (Sordo et al. 2008; Russell et al. 2011), cpSSR (Mattia et al. 2008), SCAR (Butiuc-Keul et al. 2015), and EST-SSR (Debnath 2015) marker techniques and methods were preferred, and the investigations were concluded successfully.

Results of iPBS analysis

Retrotransposons (Class-I transposons) are mobile genetic elements that can move within the genome by copying themselves through an RNA product and can be located in another location of the genome, resulting in an increase in the physical size of the genome. They cause changes in the amount of DNA in the genome and increase genetic diversity (Kalendar and Schulman 2006). Kalendar et al. (2010) developed a universal retrotransposon marker system called inter-Primer Binding Site (iPBS). In this system, retrotransposons can be found at different positions. The long tandem repeat (LTR) sequences are often located next to another retrotransposon, in which the primer binding site (PBS) sequences are often located next to the other PBS. In regions where the presence of retrotransposons is high in the genome, PBS sequences can be used because of the possibility of coexisting with other retrotransposon structures (Kuras et al. 2013; Orhan 2020). The iPBS method is an important method for characterizing and defining genetic diversity and relationships in plant species (Kalendar et al. 2010, 2011; Kalendar 2011; Kalendar and Schulman 2014; Nadeem et al. 2018).

The size ranges (SRs) of the amplification products obtained with the iPBS primers are given in Table 2. The minimum size range (18–500 bp) was obtained with the iPBS 2398 primer, while the largest size range was obtained with the iPBS 2228 (21–979 bp) and iPBS 2381 (22–979 bp) primers. The total number of alleles (Na) and the total number of polymorphic alleles (Npa) obtained from 14 iPBS markers for 26 currant samples were 4954 alleles (avg. 353.86 alleles). Therefore, the polymorphism rate (P) was determined to be 100% (Table 2). The average number of alleles (avNa) for the 26 currant samples was 13.63. This value was highest for the primers iPBS 2274 (24.58), iPBS 2373 (21.08) and iPBS 2387 (18.96).

According to the results, the mean heterozygosity (Havp) value was highest for the iPBS 2415 primer (0.277) and lowest for the iPBS 2246 (0.158) and iPBS 2376 (0.159) primers. The highest polymorphism information content (PIC) value was determined to be 0.175 for the iPBS 2246 primer, while the lowest PIC value was determined to be 0.157 for the iPBS 2415 primer (avg. 0.172). While the marker index (MI) values (avg. 0.181) were between 0.277 (iPBS 2415) and 0.158 (iPBS 2246), the discriminating power (D) values (avg. 0.182) were between 0.193 (iPBS 2373) and 0.159 (iPBS 2376) (Table 2).

According to the UPGMA dendrogram obtained with iPBS markers in our study and presented in Fig. 2, the genetic similarity among currant samples can be expressed as follows: (1) The genotypes of G13 (GC1) and G14 (GC2) (R. aureum) obtained from different geographical environments were determined to be the two most similar genotypes, with a similarity coefficient of 0.989. The hybrid jostaberry cultivar (R. nigrum × nidigrolaria) was determined to have a similar genetic relationship with these two genotypes, with a similarity coefficient value of 0.982. The black-fruited Goliath (0.969 similarity coefficient with jostaberry), G11 (EC1) (0.967 similarity coefficient with jostaberry), Titania and Wellington (R. nigrum) cultivars were determined closely related to these currant samples (mentioned above). (2) On the other hand, the samples of black-fruited (R. nigrum) [Ben Sarek, Tokat-3, G9 (ST2) and G8 (ST1)], red-fruited (R. rubrum) [Rovada, G4 (TV4), Jonker van Tets, G5 (UG1), G3 (TV3), G6 (UG2), G10 (GS2), G1 (TV1) and Rosetta] and white-fruited (R. rubrum) (White Pearl and Blanka) currants with varying similarity coefficient values were determined to be close relatives. (3) The red-fruited Red Lake cultivar together with the red-fruited genotypes G2 (TV2), G12 (EC2) and G7 (GS1) showed the lowest genetic similarity values in the dendrogram, except for the cultivars and genotypes mentioned above. The PCoA results obtained in the analysis of iPBS markers and the genetic similarities/differences among the 26 currant samples are shown in Fig. 3, and this PCoA was found to support the data obtained from the dendrogram (Fig. 2).

Fig. 2
figure 2

Unweighted pair group method with arithmetic mean (UPGMA) dendrogram of currant samples based on inter-primer binding site (iPBS) data

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Fig. 3
figure 3

Principal coordinate analysis (PCoA) plot of 26 currant samples based on inter-primer binding site (iPBS) data

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In this study, the amounts of amplification product produced using iPBS markers for currant species with different fruit colours were also compared (Table 4). According to the data in this table, for a total of 26 samples used in the study, the number of amplification products obtained from the red- and white-fruited cultivars and genotypes (R. rubrum) was greater than that from the black-fruited cultivars and genotypes (R. nigrum). While an average of 16.51 amplification products were detected in red-fruited currants, an average of 16.89 amplification products were detected in white-fruited currants. On the other hand, the number of amplification products in black-fruited currants, the hybrid jostaberry cultivar and golden currant genotypes (R. aureum) were 11.56, 4.50, and 3.11, respectively.

Table 4 Amplification products obtained with inter-primer binding site (iPBS) markers for currant cultivars and genotypes with different fruit colors (Ribes rubrum, Ribes nigrum), hybrid Jostaberry cultivar and Ribes aureum genotypes
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The use of retrotransposon-based iPBS markers for currant samples obtained from Türkiye was carried out for the first time in this study. iPBS markers have been successfully used in other fruit species such as grape (Guo et al. 2014), guava (Mehmood et al. 2013), and apricot (Baránek et al. 2012). According to the results of our study, the degree of genetic relatedness among currant samples can be determined with high accuracy by iPBS markers, which are DNA-based molecular markers.

Results of SSR analysis

(SSR) simple sequence repeat, microsatellite markers are composed of 2–6 repeated nucleotide groups that are distributed throughout eukaryotic genomes. Since SSRs are highly polymorphic, they provide much information about plants. In addition, the fact that they exhibit codominance and are easy to combine with PCR are among the reasons for them being highly preferred (Gupta et al. 1994; Röder et al. 1995; Yorgancılar et al. 2015). SSRs are widely distributed in plant genomes. The information based on such repeats more accurately represents the entire genome than that from other markers, as SSRs contains species-specific conserved domains. PCR is performed by developing specific primers that provide information specific to repetitive regions (Ganopoulos et al. 2011; Orhan 2020).

Table 3 shows the size ranges (SRs) of the amplification products obtained using the SSR primers in our study. The minimum size range was obtained for the RJL-11 primer (18–336 bp), while the largest size range was obtained for the e1-O21 primer (17–982 bp). While the total number of alleles (Na) and the total number of polymorphic alleles (Npa) obtained by amplification of SSR primers were 2475 alleles, the polymorphism rate (P) for currant samples was 100% (the same rate determined from iPBS markers). This high rate is thought to be related to the use of capillary electrophoresis. With the use of ten SSR primers, an average of 247.5 alleles were obtained for all the currants. Among the SSR primers with the greatest number of alleles, the g1-F04 primer produced a total of 311 alleles (avg. 11.96 alleles), and the e3-B02 primer produced a total of 300 alleles (avg. 11.54 alleles). The SSR primer that gave the fewest alleles was RJL-11 (avg. 6.62 alleles), with a total of 172 alleles. However, the average number of alleles (avNa) for the 26 currant samples ranged from 6.62 (RJL-11) to 11.96 (g1-F04) (avg. 9.52).

The mean heterozygosity (Havp) value was determined to be between 0.336 (RJL-6) and 0.213 (g3-A17) (avg. 0.243). The PIC values obtained with the SSR markers ranged from 0.207 (RJL-6) to 0.232 (g3-A17) (Table 3). In the same table, the marker index (MI) values ranged between 0.213 (g3-A17) and 0.336 (RJL-6) (avg. 0.244). The discriminating power (D) was between 0.212 (g3-A17) and 0.292 (RJL-6) (avg. 0.228).

The results obtained in our study were similar to those of many investigations using SSR markers reported in the literature. For example, Brennan et al. (2002) characterized Ribes nigrum L. samples using 11 RJL-encoded SSR markers. Among these markers, highly polymorphic results were obtained with the RJL2, RJL6 and RJL11 markers, which were also preferred in our study. With these markers, the researchers determined the allele size to be 207 bp, 291 bp and 215 bp; the number of alleles to be 16, 13 and 10; and the observed heterozygosity to be 0.555, 0.462 and 0.538, respectively. A successful genetic diversity analysis with 10 SSR markers with RJL coding was also performed by Antonious et al. (2012) for a total of 846 Ribes L. samples (400 R. nigrum, 202 R. rubrum, 242 R. uva-crispa and 2 jostaberry) from Northern Europe. Using the RJL2 marker (which was also preferred in our study), these researchers obtained alleles with sizes ranging from 197 to 238 bp, 192–252 bp and 205–279 bp for R. nigrum, R. rubrum, and R. uva-crispa, respectively. With the RJL6 marker, alleles ranging from 191 to 306 bp, 276–301 bp, and 215–308 bp in size were obtained for these species, respectively. For the same species, alleles with sizes ranging from 205 to 229 bp, 205–229 bp, and 229–263 bp were obtained with the RJL11 marker, respectively. Furthermore, Palmieri et al. (2013) reported that the observed heterozygosity and discriminating power values for 91 Ribes L. samples (85 cultivars and 6 selection products) were similar to those reported by Mezhnina and Urbanovich (2017). These researchers determined the observed heterozygosity (Ho) value to be 0.50 and the discriminating power to be 0.61 with the e3-B02 primer and the observed heterozygosity (Ho) value to be 0.84 and the discriminating power value to be 0.76 with the g2-G12 primer. In addition, heterozygosity (Ho) and discriminating power values were observed using the e1-O21 and g1-I02 primers (preferred in our study), which were determined to be 0.62 and 0.73 with the e1-O21 primer and 0.96 and 0.78 with the g1-I02 primer, respectively. On the other hand, the observed heterozygosity (Ho), effective allele number and discriminating power values obtained with the e3-B02 and g2-G12 markers (also used in our study) for the 65 Ribes L. samples by Mezhnina and Urbanovich (2017) were 0.508, 2.3 and 0.67 for the e3-B02 primer and 0.758, 8.2 and 0.95 for the g2-G12 primer, respectively. In a previous study conducted in Türkiye, Çelenk (2015) used 10 SSR markers in 5 Ribes alpinum L., 2 Ribes bieberstenii Berl. ex DC, 1 Ribes uva-crispa L. and 2 Ribes rubrum L. samples. In contrast to our study, in their study, taxonomic and phylogeographic relationships were investigated, and successful results were obtained.

In our study, according to the UPGMA dendrogram (Fig. 4) generated with SSR markers, the genetic similarity among currant cultivars and genotypes from different Ribes L. species can be expressed as follows: (1) the hybrid jostaberry cultivar (R. nigrum × nidigrolaria) and G11 (EC1) genotype (R. nigrum) were determined as the most similar samples (similarity coefficient, 0.909). The black-fruited Goliath cultivar (R. nigrum) and the cream–reddish-fruited genotype G13 (GC1) (R. aureum) were identified as two other examples with high similarity (similarity coefficient, 0.901). The G14 (GC2) genotype (R. aureum) showed similarity to these four samples and formed a subgroup (Subgroup-I) with them in the dendrogram.(2) On the other hand, the black-fruited cultivars Titania and Wellington (R. nigrum) were determined to be the two most closely related cultivars (similarity coefficient of 0.888). The red-fruited Jonker van Tets (R. rubrum) cultivar was similar to these two black-fruited cultivars and formed another subgroup with them in the dendrogram (Subgroup II).(3) The red-fruited Rovada cultivar (R. rubrum) and G6 (UG2) genotype (R. rubrum) were determined to be currants with similarity to each other (similarity coefficient, 0.865). These two cultivars were similar to Subgroup-I and Subgroup-II and formed a single group with them. On the other hand, the white-fruited cultivars White Pearl and Blanka (R. rubrum) (similarity coefficient, 0.866), which were determined to be similar to each other, were found to have high genetic similarity with this group. However, the red-fruited Red Lake cultivar (R. rubrum) and the G12 (EC2) and G1 (TV1) (R. rubrum) genotypes were also found to be closely related to this group. (4) All of the other black-fruited and red-fruited currant samples used in this study were found to have a certain genetic relationship with the group described above, with different similarity coefficient values. Furthermore, the PCoA results obtained by the analysis of SSR markers and the genetic similarities/differences among the 26 currant samples are shown in Fig. 5, and the PCoA results were found to support the data obtained from the dendrogram (Fig. 4).

Fig. 4
figure 4

Unweighted pair group method with arithmetic mean (UPGMA) dendrogram of currant samples based on simple sequence repeat (SSR) data

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Fig. 5
figure 5

Principal coordinate analysis (PCoA) plot of 26 currant samples based on simple sequence repeat (SSR) data

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As with the iPBS markers, a quantitative comparison of the amplification products obtained from the SSR primers was made for the currant samples with different fruit colours used in the study (Table 5). According to the data in this table, for the 26 samples used in this study, the number of amplification products obtained from the red- and white-fruited currant samples was greater than that from the black-fruited currant samples (avg. 9.20). While an average of 10.03 amplification products were detected in the red-fruited currant samples, an average of 10.35 amplification products were detected in the white-fruited currant samples. The numbers of amplification products of the hybrid jostaberry cultivar and golden currant genotype (R. aureum) were relatively low (avg. 7.40 and 8.10, respectively). As a matter of fact, as a result of a study conducted by Palmieri et al. (2013) using SSR markers, more amplification products were detected in red-/white-/pink-fruited currant samples (avg. 6.6) than in black-fruited samples (avg. 5.5). However, the amount of amplification product determined in our study was found to be quite high.

Table 5 Amplification products obtained with simple sequence repeat (SSR) markers for currant cultivars and genotypes with different fruit colors (Ribes rubrum, Ribes nigrum), hybrid Jostaberry cultivar and Ribes aureum genotypes
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In addition to the results discussed above, other explanations for the results obtained with iPBS and SSR analysis in this study are given below.

In our study, according to the dendrograms obtained from both iPBS and SSR analyses (Figs. 2 and 4), the red-fruited cultivars Rovada and Jonkheer van Tets were determined to be similar, related cultivars (0.902 similarity coefficient in the iPBS dendrogram; 0.867 similarity coefficient in the SSR dendrogram). According to the information given by Hummer et al. (2018) in Table 1, the genetic similarity of Rovada (‘Fay’s Prolific’ x ‘Heinemann’s Rote Spatlese’ R. rubrum) and Jonkheer van Tets (‘Fay’s Prolific’ seedling R. rubrum) has been proven by the markers used in our study. However, in the dendrogram obtained with iPBS markers (Fig. 2), the red-fruited Red Lake cultivar was determined to be distant from the red-fruited cultivars Rovada (similarity coefficient, 0.862) and Jonkheer van Tets (similarity coefficient, 0.860). According to the dendrogram obtained with SSR markers (Fig. 4), the red-fruited Rosetta cultivar [Jonkheer Van Tests × Heinemann’s Rote Spatlese (Zdunic et al. 2016; Palmieri et al. 2013)] was genetically distant from the Rovada cultivar (similarity coefficient, 0.872) and the Jonkheer van Tets cultivar (similarity coefficient, 0.861). According to the dendrogram obtained with SSR markers (Fig. 4), the red-fruited Red Lake cultivar was also genetically distant (similarity coefficient, 0.856) from the red-fruited cultivars Rovada and Jonkheer van Tets. According to the same dendrogram, Rosetta was distantly related to the Rovada (similarity coefficient, 0.827) and Jonkheer van Tets (similarity coefficient, 0.836) cultivars.

According to the SSR marker-based dendrogram (Fig. 4), the red-fruited genotypes G12 (EC2), G1 (TV1), G6 (UG2), G4 (TV4), G2 (TV2) and G3 (TV3) from Türkiye were found to be genetically closely related to the red-fruited currant cultivars originating from Europe. The red-fruited genotypes G10 (GS2), G7 (GS1) and G5 (UG1) from Türkiye were genetically distant from European-origin cultivars. According to the iPBS dendrogram (Fig. 2), the red-fruited genotypes G4 (TV4), G5 (UG1), G3 (TV3), G6 (UG2), G10 (GS2), and G1 (TV1) from Türkiye were closely genetically related to those originating from Europe. This may be because Türkiye is intercontinental. The areas of wild fruits in Türkiye are mainly concentrated in the Mediterranean, Black Sea, Middle, Eastern, Northeast and South Anatolian regions (Ercisli 2004; Ercisli et al. 2009).

When both the iPBS and SSR dendrograms were reviewed, the black-fruited cultivars Titania, Wellington, and Goliath (European origin) and the genotype G11 (EC1) from Türkiye were found to have close genetic relationships with each other (average similarity coefficient value of 0.888). Additionally, the other black-fruited currant samples [Ben Sarek, Tokat-3, G8 (ST1) and G9 (ST2)] were found to be related to these currants to different degrees. The finding that currant forms with white and pink fruit colours are different colour forms of red-fruited currants (R. rubrum) has been reported in various investigations (Brennan 2008; Zdunic et al. 2016). The results of our study confirmed these findings. In addition, the two Ribes aureum L. genotypes G13 (GC1) and G14 (GC2) used in our study showed close genetic relationships with jostaberry (a hybrid of black currant and gooseberry described in Hummer et al. 2018). Thus, the results obtained in this study contribute to the evaluation of red-/white-/black-fruited currant cultivars and genotypes and even hybrid currant breeding lines.

Conclusion

The use of retrotransposon-based iPBS markers in currants (Ribes spp.) was carried out for the first time in this study. Here, the genetic relationships among the currant materials were determined with iPBS markers. In addition, with the preferred SSR markers used in this study, the genetic relationships among currant plant materials could be determined.

The characterization of hybridization and selection research employing plant breeding methods and rapid evaluation of gene sources are important. SSR and iPBS markers can provide highly accurate results for molecular assessments. Therefore, it is necessary to carry out more comprehensive molecular breeding research on currant species in Türkiye by utilizing the results of this preliminary study.