Introduction

The genus Brassica is characterized by a diverse array of plant species, and are extensively used for over 5000 years BCE, (Campbell et al. 2016; Watson and Preedy 2010). This family comprises 338 genera and 3709 species, displaying significant morphological diversity encompassing various crop species with commercial importance, including industrial oilseeds, spices, vegetables, and fodder crops (Li, et al. 2017), which offer a diverse array of end products due to their varied range of use.

Brassica rapa L. is a source of vegetable oil for cooking, food processing, and industrial applications (Chew 2020). The seeds of Brassica arvensis L. could be used for biofuel production (Gidik, et al. 2023). Brassica nigra L. is a popular spice used in many cuisines as well as its paste is used as a condiment (Kayacetin 2020). Brassica juncea L. is another popular spice used in South Asian cuisines (Kumar, et al. 2011). Brassica napus L. is a hybrid of B. rapa L. and B. oleracea L. and is a source of vegetable oil, which is used for animal feed and industrial purposes (Das, et al. 2022). Following U's triangle model, the interspecific hybridization of B. rapa × B. nigra produces the amphidiploid species B. juncea [AABB (n: 18)], derived from two fundamental diploid species, B. rapa [AA (n: 10)] and B. nigra [BB (n: 8)].

Mustard species, including Sinapis alba (white mustard or yellow mustard), B. nigra (black mustard), B. juncea (brown mustard), B. rapa (also known as B. campestris, field mustard, or turnip), represent a distinguished germplasm, which serve as primary raw materials for numerous agriculture-based industries globally including Turkey (Kayacetin 2020). S. alba is commonly utilized as a seasoning agent in its dry form, while B. nigra holds significance not only as a condiment but also for its medicinal purposes (Aslan and Eryilmaz 2020; Kayacetin 2023a, b; Tomar and Shrivastava 2014). B. juncea is employed as a biofuel feedstock and spice, whereas B. rapa finds widespread use as a biofuel feedstock (Kayacetin 2023a, b; Kwon, et al. 2020).

Mustard and rape breeding programs require information on the diversity and relationships within and among landraces to facilitate germplasm recognition, preservation, and application (Rabbani et al. 1998; Ilyas et al. 2018). Previous research (Ali, et al. 2003; Azam, et al. 2013; Jan, et al. 2017; Naheed, et al. 2016; Neeru, et al. 2016) indicated that breeders extensively assess this germplasm exploring both morphological and genetic diversity before incorporating it into breeding programs. Nevertheless, molecular markers offer a more robust approach, representing a highly efficient, reproducible, and resource-saving strategy for selecting diverse genotypes.

Among the various molecular markers, retrotransposons stand out as versatile, reproductive, and efficient tools for determining genetic diversity in plant species. Retrotransposons, also known as jumping elements, constitute between 50 and 90% of plant genomes (SanMiguel, et al. 1996). There are two main types of retrotransposons: long terminal repeat (LTR) and non-LTR, serving as predominant type markers in plant genomes. ParadoxicallyKalendar, et al. (2010) has proposed a universal DNA fingerprinting technique applicable to both plants and animals, termed as the "inter primer binding site (iPBS)," introducing a new marker system. This technique allows for the analysis of both LTR and non-LTR retrotransposons. Inter primer binding site primers are designed for reverse transcription during the retrotransposon replication cycle, based on primer binding site (PBS) sequences with conserved tRNA segments (Guo, et al. 2014; Kalendar, et al. 2010).

The efficiency of the iPBS-retrotransposon marker system has been demonstrated in a wide range of crops including laurel (Karık, et al. 2019), chickpea (Andeden, et al. 2013), pea (Baloch, et al. 2015b, a), lens (Baloch, et al. 2015b, a), quinoa (Barut, et al. 2020), Turkish okra (Yıldız, et al. 2015), safflower (Ali, et al. 2019), pepper (Yildiz and Arbizu 2022), Turkish wild and cultivated Emmer (Arystanbekkyzy, et al. 2019), Turkish bread wheat (Nadeem 2021), common bean (Aydın and Baloch 2019) and grapevine (Güler, et al. 2024). Despite the extensive use of SSR markers to differentiate for species (Thakur, et al. 2017), genetic diversity (Hobson and Rahman 2016; Raza, et al. 2019; Yin, et al. 2023), yield potential (Wolko, et al. 2022), and breeding (Singh, et al. 2022); the iPBS marker system have not yet been employed for genetic diversity assessment.

As far as we know, this study constitutes the initial efforts to utilize iPBS markers for evaluating genetic diversity within Brassica species.

Materials and methods

Plant growth conditions

The Brassica accessions (shown in Table 1) were surface sterilized following the procedure as described previously (Aslam, et al. 2022). The seeds were washed in running tap water followed by surface sterilization using 20% (v/v) commercial bleach (Domestos) for 15 min, followed by 5 × 3 rinses with sterile distilled water. Subsequently, the seeds were placed in Petri plates containing sterile filter paper moistened with sterile water for germination of the seedlings. The growth chamber conditions were 16 h light/8 h dark, 25 °C temperature, and 65% humidity.

Table 1 Brassica genotypes for molecular characterization with inter primer binding site (iPBS) markers
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Plant genomic DNA extraction from Brassica plant

Brassica seedlings were crushed into a fine powder using a mortar and pestle that had been pre-chilled with liquid nitrogen. The genomic DNA was isolated following the plant genomic DNA kit protocol (Exgene™ Plant SV, GeneAll co. LTD, Seoul, South Korea. The DNA was stored at -80 °C for future use.

Genomic DNA gel electrophoresis

Thegel electrophoresis was performed using TAE buffer at 100 V for 60 min in an agarose gel (1%) to determine the purity and quantity of the isolated genomic DNA. The gel was stained with ethidium bromide solution for 5 min and rinsed with distilled water to remove excess of the dye. The gel was visualized under the gel documentation system (Bio-Rad) and photographe.

iPBS-retrotransposon analysis and agarose gel electrophoresis

The primers utilized were derived from the work of Kalendar, et al. (2010) in this study. Initially, 80 iPBS-retrotransposon primers were tested on a randomly selected group of 10 Brassica accessions. Thereafter, 10 most polymorphic primers were identified and subsequently employed for PCR amplification across all 33 Brassica accessions (refer to Table 2 for details). The amplification conditions of iPBS-PCR were adapted based on the protocol outlined by Kalendar et al. (2010), with minor modifications (Saba, et al. 2020). The PCR reaction mixture included 30 ng of template DNA, 1 × Taq reaction buffer, 200 µM of dNTPs, 0.2 µM primer for 11–15 length oligonucleotides or 18-bases long oligonucleotides, and 1.25 U Taq polymerase (Promega, Life Technologies, NEB) in a 25 μL reaction volume.

Table 2 Certain characteristics of the inter primer binding site (iPBS) molecular markers employed in the investigation
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The PCR reaction procedure included an initial denaturation phase at 94 °C for 3 min, succeeded by 40 denaturation cycles at 94 °C for 15 s, an annealing step at a temperature ranging from 49 °C to 65 °C, based on the oligonucleotides used, for 1 min, and a final extension at 72 °C for 10 min (Kalendar et al. 2010). The amplified retrotransposon bands were subjected to analysis using 3% (w/v) agarose gel electrophoresis at 120 V. The resulting amplified bands were observed and documented using a gel documentation system (Bio-Rad GDS, California, USA).

Genetic diversity analysis

Retrotransposons were employed as markers to assess the relationships among individual plant genotypes within the collection. An iPBS marker-based neighbor-joining tree was constructed. The dissimilarity matrix was calculated using the Manhattan index in TASSEL software (Bradbury et al. 2007) to construct both the tree and principal coordinate analyses (PCoA). Different diversity parameters were also computed using GenAlEx V6.5 (Peakall and Smouse 2006) to investigate genetic differences between landraces and cultivars.

Results

Following PCR amplification of retrotransposon markers, the resulting products were separated on agarose gels and visualized using a gel documentation system. Thereafter the bands were scored, and the genetic diversity analysis was performed on the Brassica genotypes listed in Table 1. On average, each primer produced 14 bands, and the mean count of polymorphic bands was 13.5. Notably, iPBS 2376 exhibited the maximum rate of polymorphism (94.12%), followed by 88.24% bands by iPbS 2376 and minimum percentage of 64.17 was noted for iPBS 2074 primers. The values for Polymorphic Information Content (PIC) varied from 0.13 for iPBS 2074 to 0.30 for iPBS 2081. Additional details regarding the primer performance metrics are provided in Table 2. Across all primers, recessive alleles (q) were more frequent. The primers iPBS2376, and iPBS2081 exhibited the greatest allele count (Na), had values in close proximity to 1.882 and 1.824 correspondingly. Although iPBS 2074 exhibited the lowest values of Na at 1.294, the Shannon’s information index (I) was the highest for iPBS 2081 and the lowest for iPBS 2074. The effective alleles (Ne) were the highest for iPBS 2081 and the lowest for iPBS 2074. The values of He (expected heterozygosity) in this study ranged 0.148 (iPBS 2074) to 0.370 (iPBS 2081).

Similarly, the values of uHe (unbiased expected heterozygosity) for the same set of primers varied between 0.150 to 0.376. The Brassica genotypes were classified into three clades according to the Neigbor-joining clustering analysis. The first clade consisted of 11 genotypes all of which were from B. juncea species except one BO1 from B. oleracea clustered with BJ10. The second group consisted of 10 genotypes both from B. napus and rapa. There were 6 B. rapa and 4 B. napus accessions in this clade. Out of total 12 members in the third clade, 7 genotypes belonged to S. alba and one to B. nigra. Rest of four from B. oleracea showed diverse nature of genotypes that were grouped under the same clade (Fig. 1) (Table 3).

Fig. 1
figure 1

The genetic tree of Brassica genotypes, constructed using neighbor-joining algorithm

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Table 3 Genetic diversity parameters for the inter primer binding site (iPBS) primers and populations used in this study
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STRUCTURE analysis using the Evanno method (Fig. 2) identified that three populations (K = 3) had the optimal number of genetic clusters. This conclusion was supported by the maximum ΔK value of 302.71 observed at K = 3. The FST values, indicative of genetic differences, were computed as 0.64, 0.65, and 0.40 for the Brassica populations q1 to q3, correspondingly. Furthermore, the structure analysis depicted the proportions of genetic diversity within these three populations (Fig. 3). Notably, clustering analysis provided similar results in identifying distinct populations. The structural analysis offered the added advantage of visualizing the proportional contributions of genetic diversity.

Fig. 2
figure 2

The Delta K value indicates the existence of three populations in the Brassica species germplasm based on the inter primer binding site (iPBS)-retrotransposons marker system

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Fig. 3
figure 3

The population structure analysis of Brassica germplasm, utilizing the inter primer binding site (iPBS)-retrotransposons marker system, reveals the presence of three distinct groups: Group 1 (represented in red), Group 2 (represented in green), and Group 3 (represented in blue)

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PCoA further confirmed the clustering observed with the model-based structure algorithm, as evidenced by the separation of the 33 Brassica accessions into three populations (Fig. 4).

Fig. 4
figure 4

Principal Coordinate Analysis (PCoA) of Brassica accessions was performed utilizing the inter primer binding site (iPBS) retrotransposons marker system

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Genetic variation among the genotypes was assessed through Analysis of Molecular Variance (AMOVA). As presented in Table 4, approximately 38% of the total variation was attributed to disparities among populations accounted for, while the remaining 62% of the variation was observed within the populations.

Table 4 Analysis of Molecular Variance (AMOVA) results of 10 inter primer binding site (iPBS) primers
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Discussion

Genetic variation within plant populations is a crucial resource for breeders. It allows them to develop improved cultivars with traits desired by farmers, industry, and consumers (Govindaraj, et al. 2015). Numerous research endeavors have explored relationships within Brassicaceae family, employing SSR markers (El-Esawi, et al. 2016; Singh, et al. 2018; Thakur, et al. 2017). Similarly, several investigations have utilized ISSR markers for assessing genetic associations within the Brassicaceae family (Khalil and El-Zayat 2019; Safari, et al. 2013; Shen, et al. 2016; Wang, et al. 2017). Nevertheless, to the best of our information, this study marks the first instance where the iPBS-retrotransposon marker system has been employed to evaluate genetic diversity in 5 different Brassica species populations.

A set of 10 highly polymorphic iPBS-retrotransposon primers was employed to investigate the genetic variability and structure of populations of Brassica species. These iPBS primers generated a total of 144 bands, with 135 of them identified as polymorphic (refer to Table 2). The total and polymorphic bands identified in this study surpassed those reported by Raza, et al. (2019) using SSR markers. However, it is worth noting that the PIC value was lower in the case of iPBS.

In contrast to another study utilizing ISSR markers with a set of 7 primers, where the number of polymorphic bands was higher (20) compared to iPBS (13), this discrepancy could be attributed to the limited number of primers and the marker system employed. Similarly, in another study of ISSR, the average number of polymorphic bands in B. rapa var. chinensis was 6.3, which is lower than the findings in the present study (Shen, et al. 2016). Furthermore, a study applying ISSR markers to Amphidiploid lines of B. juncea (2n = 4x = 36), reported a lower PIC value (0.18) compared to our iPBS system, highlighting the influence of species and marker choice on genetic diversity estimates.

This findings of current study on genetic diversity are comparable to those obtained by Wang et al. (2017) using ISSR markers. The average diversity index (I), effective allele number (Ne), and average genetic diversity (He) were 0.4045, 1.4557, and 0.2684, respectively. While a study by Thakur et al. (2018) reported a higher number of alleles (Na) using SSR markers for B. napus, these values were close to those obtained with iPBS markers in this study. However, the lowest allele count observed in the SSR study exceeded compared to iPBS markers. These variations likely stem from differences in both plant species analyzed and the marker systems employed.

The observed variations in scores for different diversity indices in this investigation may have arisen from disparities in germplasm and the inherent characteristics of the utilized molecular markers. The iPBS-retrotransposons marker system, known for its high reproducibility and universal applicability, has been validated in several investigations (Shimira, et al. 2021; Yildiz and Arbizu 2022). Hence, the marker system could be the adopted choice for molecular profiling of Brassica genotypes over co-dominant and dominant marker systems.

Importantly, AMOVA findings emphasized that the highest genetic variances in Brassica germplasm exist within populations. These findings align with previous research that also reported higher genetic variations within populations (Jozová, et al. 2023; Tesfaye, et al. 2023).

Nei's genetic distance analysis suggests that B. nigra accessions BN1 and BN3 belong to a distant clade. This genetic distance makes them potential parents for cross-pollination breeding programs aimed at improving mustard quality. For the accessions of species B. oleracea such as BO1 and BO3 could be desired candidate for heterosis research. These combinations could enhance mustard pungency and glucosinolate contents and yield potential. The use of iPBS in marker-assisted breeding is particularly advantageous for gaining insights into genetic potential and diversity among species or cultivars, expediting molecular-based breeding.

The model-based structure algorithm categorized 33 Brassica genotypes into three distinct populations primarily based on their species level (refer to Fig. 3). Population III, comprising 36.36% (12) accessions, is a mixed population of S. alba and B. oleracea. Population I, accounting for 33.33% (11) accessions, mainly consists of B. juncea, except for one that is from B. oleracea. Population II was the smallest and included 30.30% (10) genotypes, encompassing B. rapa and B. nigra. The presence of B. nigra and B. rapa in Population II, and S. alba and B. oleracea in Population III, contributed to the high diversity of these populations. Neighbor-joining analysis, as depicted in Fig. 1, aligns with the population structure (Fig. 3), showing congruence and support the diversity pattern with multiple lines of evidence. Furthermore, PCoA echoes the distribution pattern of genotypes seen in the neighbor-joining tree and structure analysis, underscoring the consistency and reproducibility of the analyses.

STRUCTURE analysis revealed higher genetic variations within populations III and II, which was further confirmed by AMOVA analysis. Importantly, AMOVA analysis confirms that most genetic variation resides within Brassica germplasm populations. This high within-population diversity holds promise for future breeding efforts aimed to improve mustard paste quality and yield. PCoA analysis further supports the clustering observed by the model-based structure algorithm, segregating Brassica accessions into three populations (refer to Fig. 4).

Conclusion

The current investigation offers a comprehensive understanding of genetic variations within a germplasm consisting of 5 Brassica species utilizing the iPBS-retrotransposons marker system. The study identified BN1, BN3, BO1, and BO3 as genetically diverse accessions within the germplasm, making them promising putative candidates for breeding programs. AMOVA findings emphasized increased genetic variations within populations compared to variations among populations. Notably, population II and III, as identified through structure clustering, exhibited higher diversity, suggesting that accessions within these populations should be prioritized for future Brassica breeding initiatives. The structure algorithm based on a model and PCoA successfully separated the examined germplasm into distinct populations, primarily attributed to their diverse genetic potential and increased heterozygosity. This study further corroborated the practicality and widespread applicability of the retrotransposons markers, positioning them as valuable tools for exploring genetic diversity in Brassica crops.