1. Introduction
Natural antioxidants, having beneficial effects on human health, have been given considerable attention recently. Berry crops from the genera
Vaccinium,
Rubus,
Ribes, and
Fragaria are an abundant source of antioxidants of phenolic origin [
1,
2]. Of them, the red raspberry (
Rubus idaeus L.) is one of the most popular berries in the world due to its attractive color, excellent taste, and aroma. Interest in this berry is constantly growing. Production of the red raspberry, as well as of its related blackberry and black raspberry, reached 896 thousand tons in 2020, which is 72% more than in 2010 and 2.1 times more than in 2000 [
3]. Among berry crops, the raspberry is second only to the blueberry in terms of production increase rate. Russia is the largest raspberry producer, with Poland, Serbia, and the USA constantly among the top five leaders. The raspberry is a rich source of biologically active compounds (phenolics, including anthocyanins and ellagitannins) and nutrients (minerals, vitamins, carotenoids, and organic acids) [
4,
5].
Phenolic compounds are the most common secondary metabolites of plants [
6]. They include flavonoids, the most numerous class, as well as phenolic acids, stilbenes, lignans, and coumarins [
7]. Polyphenols protect plants from various biotic and abiotic stresses due to their antioxidant abilities based on the stabilization of free radicals [
8]. When used in food, polyphenols protect the body from oxidative stress considered to be the common mechanism for the occurrence and progression of the most widespread chronic diseases, thereby contributing to the prevention of cardiovascular, cancer, and inflammatory diseases [
9,
10]. Of particular interest are anthocyanins which, unlike other flavonoids that are colorless or yellow-colored, are pigment molecules that give attractive colors to flowers and fruits [
11]. In edible plants, red, blue, or purple berries are some of the most important sources of anthocyanins [
12].
Natural antioxidants are found not only in berries or fruits but in all parts of the plant too. Leaf extracts are currently attracting increasing attention as phytochemicals of nutraceutical importance [
13]. Leaves of berry crops have long been used in herbal teas and in traditional medicines. Raspberry leaves are widely used in herbal medicine for treating fever, influenza, diabetes, diarrhea, and colic pain [
14]. Experiments have shown that polyphenolic extracts from leaves of
Rubus spp. have anticancer, antioxidant, antimicrobial, and relaxant properties [
15]. Raspberry leaves have been included in the British Pharmacopoeia since 1983, and in 2014, the European Medicines Agency issued a community herbal monograph for the traditional use of red raspberry leaves [
16]. Additionally, the red raspberry is one of the most important plants for the preparation of recreational tea [
17].
Berries are the main commercial product of the raspberry, strawberry, currant, bilberry, and lingonberry, whereas leaves are considered agro-wastes or by-products [
18,
19]. However, it has long been shown that blackberry, raspberry, and strawberry leaves have an increased content of phenolics and enhanced antioxidant properties as compared with berries [
20]. Subsequent studies have confirmed this for the blueberry [
21], cranberry [
22], bilberry [
23], lingonberry [
24], and raspberry [
25]. Thus, the leaves can be used as an alternative source of bioactive natural products to develop food additives and nutraceuticals. The biosynthesis of polyphenols and the associated antioxidant activity in various parts of plants are under genetic control, but biotic and abiotic stresses can cause seasonal fluctuations in phenolic content [
18,
24]. This dependence of the polyphenol concentrations on the time of the year emphasizes the importance of determining the optimal time for collecting plant material when its biological activity is at a maximum.
It is believed that increasing the consumption of raspberry can be a practical strategy for the prevention of a number of chronic human diseases. In recent years the main direction of its breeding has changed from agronomic traits (yield and tolerance to stresses) to fruit quality (sensorial and nutritional) [
26]. Knowledge of the genetic diversity in relation to phenolic content in the raspberry germplasm can be used to develop breeding programs by choosing optimal combinations of parents [
11]. However, biochemical characteristics alone are not sufficient to confirm genetic diversity. Genotype identification using DNA markers is preferable due to their constancy and reliability because they do not depend on the environment [
27]. Microsatellite (simple sequence repeats, SSR) markers are very popular among DNA markers because of their multiallelic nature, codominant inheritance, extensive genome coverage, reproducibility, low cost, and high transferability across species [
28,
29]. Moreover, these molecular markers can be successfully used in marker-assisted selection to accelerate the creation of new cultivars [
30].
SSR markers along with biochemical data have been used to identify true skin color mutants of grapes [
31], select parents in potato breeding programs for nutritional quality [
32], and prevent the adulteration of olive oil [
33]. However, little is known about the relationship between molecular markers and antioxidants. As far as we are aware, the relationships between polyphenol content and genetic diversity have been studied only in the grape [
29], cranberry [
34], and blueberry [
11]. Furthermore, these and other studies have used markers randomly distributed throughout the genome but not associated with specific metabolic pathways. Earlier, we developed a set of SSR markers for structural and regulatory genes of flavonoid biosynthesis. Those markers have been used to compare genetic data with anthocyanin-determined coloration in various species from the genera
Rubus,
Fragaria, and
Ribes [
35,
36,
37].
The purpose of this work is (1) to evaluate the phenolic content and antioxidant activity in berries of new raspberry breeding lines versus the standard cultivars, (2) to compare the phenolic content and antioxidant activity of raspberry leaves when harvested in different phenological phases, and (3) to assess the genetic diversity of raspberry cultivars and breeding lines by SSR markers from flavonoid biosynthesis genes and evaluate their relationship with biochemical data.
2. Materials and Methods
2.1. Plant Materials
In total, 25 genotypes were used: red raspberry cultivars and breeding lines of Russian origin (lines from Bryansk State Agrarian University), as well as cultivars Polana, Polesie, Polka, Porana Rosa (Poland), Himbo Top (Switzerland), Octavia (UK), and the raspberry × blackberry hybrid Silvan (Australia) (
Table 1). All genotypes were propagated in the traditional way, planted in 10-L pots (5 for each genotype) in 2017, and grown under open-air conditions. Berries and leaves were collected from three randomly selected pots (3 replicates) in 2020. Young fully expanded leaves from the upper part of the shoot were collected in the phases of flowering (I), fruit development (II), and fruit ripening (III), which corresponded to stages 65, 77, and 895 of the raspberry phenological scale [
38]. Berries were harvested at full maturity at the same time as the last leaf harvest. Leaf and berry samples were frozen immediately upon collection and stored at −80 °C for further use.
Dry matter content of fruits and leaves was determined after drying at 105 °C for 24 h (
Table S1).
2.2. Preparation of Extracts
In total, 5 g of frozen fruits or 2.5 g of frozen leaf tissue (three replicates for each genotype) were ground with liquid nitrogen using a mortar and then extracted using 15 mL of 80% ethanol in an orbital shaker in the dark for 18 h at room temperature. The supernatant was obtained by centrifugation (4500 rpm, 20 min), and the residue was re-extracted with 6 mL of 80% ethanol in an orbital shaker for 1 h. After centrifugation, supernatant 2 was combined with supernatant 1, and then the combined solution was filled up to 30 mL with 80% ethanol.
2.3. Total Phenolic Content (TPC)
Total phenolics were measured using the Folin–Ciocalteau method [
39]. In total, 100 µL of the extracts, standards, and blanks were added to 900 µL of the Folin–Ciocalteu reagent (10%) and incubated for 5 min. After incubation, 800 µL of Na
2CO
3 (7.5%) was added, mixed, and incubated in the dark for 90 min at room temperature. The absorbance at 760 nm was measured on a Shimadzu UV-1800 spectrophotometer. The calibration curve was plotted using gallic acid solutions at concentrations of 10–300 µg/mL, and the results were expressed in mg of gallic acid equivalents (GAE) per 100 g fresh weight (FW).
2.4. Total Flavonoid Content (TFC)
The total flavonoid content was determined by the colorimetric method of Zhishen et al. [
40]. Aliquots (200 µL) of extracts or standard solution were added to 600 µL of water and mixed with 60 µL of NaNO
2 (5%). After 5 min, 60 µL of AlCl
3 (10%) was added and allowed to stand for 6 min, then 400 µL of 1M NaOH was added to the mixture and the solution was diluted with 480 µL of water. The absorbance was determined at 510 nm. The standard curve was prepared using different concentrations of rutin (50–1000 µg/mL), and the results were expressed as mg rutin equivalents (RE) per 100 g FW.
2.5. Total Anthocyanin Content (TAC)
The monomeric anthocyanin content was determined by the pH differential method [
41] using two buffers—0.025 M KCl, pH 1.0 and 0.4 M NaAc, pH 4.5. A diluted sample of 0.2 mL was mixed with 1.8 mL of a corresponding buffer and, after a 30 min incubation at room temperature, was read against a blank at 510 and 700 nm. The anthocyanins were calculated as cyanidin-3-glucoside (cyan-3-G) equivalents using an extinction coefficient of 26,900 and molecular weight of 449.2, and the results were expressed as mg per 100 g FW.
2.6. ABTS (2,20-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) Diamonium Salt) Assay
The antioxidant activity of the extracts against ABTS radical cation was determined according to Re et al. [
42]. ABTS°+ stock solution was produced by reacting 7 mM of ABTS and 2.45 mM potassium persulfate after incubation in the dark at room temperature for 16 h. The ABTS°+ working solution was obtained by diluting with ethanol to an absorbance of 0.70 ± 0.02 at 734 nm. Samples were diluted with ethanol so as to give 20–80% inhibition of the blank absorbance. In total, 40 μL of a sample or blank was mixed with 1960 μL of ABTS°+ solution and read at 734 nm after 6 min of incubation in the dark using a Shimadzu UV-1800 spectrophotometer. The calibration curve was plotted using Trolox (0.05–1 mM) as a standard, and the results were expressed as
μmol Trolox equivalents (TE) per g FW.
2.7. FRAP (Ferric Reducing Antioxidant Power) Assay
The FRAP assay was performed using a colorimetric method by Benzie and Strain [
43]. The FRAP reagent was prepared by mixing an acetate buffer (300 mM, pH 3.6), a solution of 10 mM TPTZ in 40 mM HCl, and 20 mM FeCl
3 at 10:1:1 (
v/
v/
v). The diluted extract (0.2 µL) and FRAP reagent (1.8 µL) were mixed and incubated for 10 min at 37 °C. The absorbance was measured at 593 nm. Trolox was used as a standard for a calibration curve (0.05–1 mM), and the results were expressed as μmol Trolox equivalents (TE) per g FW.
2.8. DNA Isolation, PCR Amplification and Fragment Analysis
Total genomic DNA was extracted from young expanding leaves using the STAB method [
44]. The quality and quantity of extracted DNA were determined by the NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA). The final concentration of each DNA sample was adjusted to 50 ng/μL in TE buffer before the PCR amplification.
For genotyping, the PCR was performed separately for each primer pair using a forward primer labeled with 6-FAM fluorescent dye and an unlabeled reverse primer (Syntol Comp., Moscow, Russia). A total of 11 primer pairs were used: 10 primer pairs were developed from flavonoid biosynthesis genes (RcFH01, FaFS01, FaFS01, RiAS01, FaAR01, RhUF01, RiMY01, RiTT01 [
35], FaFH01, RiHL01 [
36]), and one pair was developed from an
R. idaeus Genbank sequence (RiG001, [
45]). The PCR amplification was performed in a total volume of 20 μL consisting of 50 ng genomic DNA, 10 pmol labeled forward primer, 10 pmol unlabeled reverse primer, and the PCR Mixture Screenmix (Eurogen JSC, Moscow, Russia). After an initial denaturation at 95 °C for 3 min, DNA was amplified during 33 cycles in a gradient thermal cycler (Bio-Rad Laboratories, Inc., Hercules, CA, USA) programmed for a 30 s denaturation step at 95 °C, a 20 s annealing step at the optimal annealing temperature of the primer pair, and a 35 s extension step at 72 °C. A final extension step was done at 72 °C for 5 min. The PCR generating clear, stable, and specific DNA fragments within an expected length (200–400 bp) were considered successful PCR amplifications.
Separation of amplified DNA fragments was performed in an ABI 3130xl Genetic Analyzer using the S450 LIZ size standard (Syntol Comp., Moscow, Russia). Peak identification and fragment sizing were done using the Gene Mapper v4.0 software (Applied Biosystems, Foster, CA, USA).
2.9. Statistical Analysis
The content of phenolic compounds was calculated traditionally: in berries, per 100 g FW; in leaves, per g dry weight (DW). Due to a significant difference in dry matter content in berries and leaves, the content of phenolic compounds in berries for their correct comparison was recalculated per g DW. The antioxidant activity of berries, traditionally measured per g FW, was also recalculated per g DW for comparison with leaves. Data for antioxidant activity, total phenolic, flavonoid, and anthocyanin contents are presented as the mean value ± standard error (SE) of three replications. Statistical analysis was made using Statistica 10 (StatSoft, Tulsa, OK, USA). Significant differences (p ≤ 0.05) between the means were evaluated by one-way ANOVA and Duncan’s multiple range test. For comparison of the results of the TPC, TFC, TAC, FRAP, and ABTS assays, the coefficients of correlation were determined by a Pearson correlation test.
Genetic statistics were calculated for polymorphic SSR markers. The number of alleles observed (Ho) and expected (He) heterozygosities, and the value of the polymorphic information content (PIC) for 24 diploid red raspberry cultivars were calculated using the Power Marker 3.25 software [
46]. The UPGMA dendrogram was built using data from the Power Marker 3.25 software package and visualized using Tree ViewX Version 0.5.0 software [
47]. To test the correlations between the biochemical parameters and the genetic component, the Mantel test was carried out [
48]. A correlation was made between a Euclidean matrix of dissimilarity distances generated using averages of biochemical data and a matrix generated for genetic locus size values for each cultivar generated using R v.4.2.1 (
https://cran.r-project.org/bin/windows/base/ (accessed on 20 August 2022)).