High-resolution genetic map and SNP chip for molecular breeding in Panax ginseng, a tetraploid medicinal plant

Ginseng ( Panax ginseng ) renowned as the king of medicinal plants. Ginseng grows slowly under shade conditions, requiring at least four years to produce a limited number of seeds. Molecular breeding of ginseng faces challenges due to its the tetraploid genome and the absence of an efficient molecular marker system. To overcome these obstacles, we adopted genotyping-by-sequencing to delve into genetic mapping and survey genetic diversity. We constructed a comprehensive genetic map comprising 24 linkage groups, each corresponding to one of the 24 chromosomes in the ginseng genome, based on 1 216 non-redundant SNPs obtained from an F 2 mapping population. Additionally, 431 103 SNPs were identified from 119 diverse ginseng genotypes. From these, 192 informative subgenome-specific single copy SNPs were selected to develop a SNP chip. The SNP chip was used to genotype a large ginseng collection, encompassing registered cultivars, breeding lines, wild-simulated ginseng


Introduction
Panax ginseng C. A. Meyer has garnered global recognition for its pharmacological efficacy and economic significance [1].In the current era, where consumer health is a prevailing trend, ginseng has gained substantial public interest [2].However, the inherent biological attributes of ginseng pose significant challenges.The plant demands a minimum of four years to reach the next generation and produces a limited number of offspring during each reproductive cycle [3].Additionally, ginseng is highly susceptible to environmental influences, making it a challenge to maintain consistent growth conditions for individual plants.These intricate characteristics render traditional hybrid breeding in ginseng a laborious and time-intensive process.Moreover, ginseng is prone to causing continuous cropping obstacles, which often necessitates the change of planting locations between generations.This further complicates the traditional trait determination.Consequently, the imperative need for a molecular breeding system has become increasingly evident, to expedite the breeding timeline and nurture the development of high-quality ginseng cultivars.
Recent studies have shown compelling evidence indicating that the ginseng genome has undergone two whole genome duplication events [4].The most recent genome duplication, a relatively recent occurrence, has given rise to the complex allotetraploid genome structure of ginseng, characterized by a chromosome count of 2n = 4x = 48 [5] and an estimated genome size exceeding 3.6 Gbp [4].It has been established that a significant portion of the ginseng genome (80%) is occupied by repetitive elements [6].Notably, the presence of paralogous regions, a consequence of the recent duplication event, has posed considerable challenges for researchers delving into the intricacies of the complex ginseng genome [7].Future studies must employ methods that can accurately overcome these challenges to pave the way for the development of a robust molecular breeding system.
With the rapid advancement of sequencing technologies and related research tools, various innovative methods for genomic research have emerged [8].The genotyping-by-sequencing (GBS) method stands out as an effective tool for the analysis of large genomes cost-effectively.GBS leverages the use of restriction enzymes to construct a reduced representation library, effectively mitigating the complexity inherent to large genomes [9].This reduction in the number of sequenced regions serves to increase read coverage, thereby enhancing the accuracy of genotype calling data and reducing the proportion of missing data [10].Furthermore, the GBS protocol, which incorporates the use of two different restriction enzymes, offers a more efficient means of focusing on restricted sequences, facilitating the analysis of large genomes [11].GBS analysis enables the discovery of sequence variants, in a high-throughput manner, particularly of single nucleotide polymorphisms (SNPs), and has the potential to yield large-scale molecular DNA markers for crop breeding applications [12].
A genetic map is a crucial tool in genetic and breeding research, especially for identifying qualitative and quantitative trait loci that play a vital role in crop improvement.Although several chromosome-level genome sequences are reported for ginseng [13,14], genetic map composed of credible SNP markers are unavailable up to now.DNA markers provide valuable insights for various genomic analyses, including studies on diversity [15], genetic mapping [15], cultivar authentication [14], and marker-assisted selection (MAS) [16].The combination of a genetic map and DNA marker information can generate a synergistic effect in crop improvement.Moreover, there is a pressing need for a reference genetic map in ginseng that can guide the chromosome-scale scaffolding of genome sequence assemblies.Such a map would be invaluable for advancing our understanding of ginseng genetics and facilitating the development of improved ginseng varieties.
However, many of these markers were designed without considering allotetraploid nature of the ginseng genome, leading to reduced reliability because they confound paralogous sequences [18].
Furthermore, these markers are based on labor-intensive and time-consuming gel electrophoresis.In recent times, new technologies such as Kompetitive Allele-Specific PCR (KASP), TaqMan, Fluidigm SNP chip, Affymetrix Axiom have been developed for high-throughput genotyping [19].
These technologies offer the advantage of cost, time, and labor efficiency by enabling the simultaneous analysis of numerous samples.These technologies have found applications in various crops, including rice, pumpkin, melon, cucumber, and wheat, aimed at improving crop breeding and enhancing agricultural practices.
In this study, we tried to develop a useful molecular breeding tool, well guided by genome sequences and genetic map.A high-resolution genetic map was constructed for the first time in ginseng from the thousands of SNPs produced by GBS analysis.Subsequently, we successfully developed a high-throughput genotyping system that leverages KASP, TaqMan and Fluidigm technologies to detect fluorescence signals.This system was applied to diverse ginseng genetic resources, including cultivars, breeding lines, wild ginseng and wild-simulated ginseng which refers to ginseng plants that are intentionally grown under conditions resembling the wild natural environment.These SNP chips represent a vital and practical tool for advancing digital breeding techniques aimed at enhancing ginseng breeding and development of ginseng industry.

Genetic map construction
The mapping population was generated by crossing the ginseng cultivars Chunpoong (CP) and Yunpoong (YP).CP and YP are the first registered varieties in Korea.Among them, we published a genome assembly paper on CP in 2018 [4].These two cultivars are still being cultivated and show distinct agricultural traits.CP has poor growth but excellent processing characteristics, while YP is resistant to light, forms multiple stems, and has excellent growth and high yield [20]. Due to their genetic stability and significant differences in agricultural traits, the Rural Development Administration (RDA, Eumseong, Korea) developed an F2 population between these cultivars, which we utilized in our study.Given that ginseng requires at least ten years to establish an F2 population due to its long generation time, we used this pre-established population.
Three GBS libraries were constructed in order to generate SNP data for a F2 population between YP and CP (Table 1).Following demultiplexing based on barcode sequences, a total of 1 622 million (M) trimmed reads were utilized for mapping to the reference genome.A total of 35.7 % of the reads that mapped to multiple locations were discarded.The number of reads uniquely mapped to each sample ranged from 1.4 M to 24.2 M, with an average of 10.2 M. Finally, 1 039 M reads were utilized for the calling of high-throughput SNP data.Initially, 615 812 raw variants were identified.
To ensure the selection of a suitable SNPs for genetic mapping, several filtering steps were implemented.A total of 10 440 SNPs were finally used in the construction of a high-density genetic map.

Table 1. Summary of GBS sequencing
Following the initial ordering of 10 440 SNPs, any incorrectly assigned genotypes were thoroughly reviewed and manually corrected.With the updated genotype data, SNP binning was carried out in order to create a non-redundant dataset.As a result, a total of 1 216 non-redundant SNPs were selected to construct a genetic map (Table S1).The 24 linkage groups, each representing one of the 24 chromosomes, were successfully obtained (Fig. 1).The total map length was 2 196.54 cM with the smallest linkage group of LG20, which containing 22 markers spanning a length of 43.34 cM, and the largest linkage group of LG9, which containing 80 markers spanning a length of 145.31 cM (Table 2).The mean distance between adjacent markers in each linkage group exhibited a range from 1.07 cM on LG6 to 3.47 cM on LG1, with an average of 1.92 cM.
As telomere-to-telomere genome sequence is available [13], we have examined the overlap between the linkage groups and the genome.Out of the 1 216 SNPs used to construct the genetic map, 1 211 were found to exactly match to the 24 chromosome sequences of the genome.The remaining 5 SNPs appear to be located in unplaced contigs.Each linkage group corresponds to a specific chromosome, indicating both a high quality of the genome assembly and the accuracy of the genetic map (Fig. S1).3).The 90 purple dots indicate SNPs identified between YP and CP mapping population and the other 96 orange dots indicate SNPs identified from GBS data of 119 ginseng collections.

SNP chip development
A total of 925 M (89 Gbp) reads were generated from 119 ginseng individuals by sequencing two GBS libraries (Table 1).Following the filtering process, 7 165 informative SNPs were obtained (Fig. S2).Among them, 5 000 SNPs randomly selected for discriminant analysis of principal components (DAPC) to assess the diversity of the genetic pool (Fig. 2).A total of 119 individuals dispersed widely and K-means clustering identified four distinct groups.Out of 7 165 informative SNPs, 323 single-locus unique SNPs were identified, which detect sub-genome unique targets.Among single-locus unique SNPs, 14 of them are randomly selected and developed into KASP markers for validation (Table S2, S3).These markers were then applied to the same 119 ginseng genotypes that had been used for GBS sequencing (Table S4).Each KASP marker displayed three distinct genotype clusters, which indicating two homozygous genotypes and one heterozygous genotype, on the endpoint fluorescence scatter plot (Fig. S3).Ultimately, a final set of 192 assays was selected for SNP chip, exhibiting precise and consistent signals accompanied by dense endpoint clusters (Table S5, S6).
The final 192 SNPs comprise 186 nuclear genome-derived SNPs and six plastid genome- derived SNPs (Table 3).Among the 186 nuclear genome-derived SNPs, 90 were found to be identical to the SNP markers included in the genetic map (Fig. 1, purple dots).Furthermore, the approximate positions of 96 SNPs that were polymorphic in the 119 ginseng accessions were estimated and marked on the genetic map (Fig. 1, orange dots).The wide distribution of the 192 SNPs across the genetic map provides compelling evidence of the genome-wide screening capabilities afforded by the SNP chip.Also, 186 SNPs derived from the nuclear genome were mapped across the 24 chromosomes of the telomere-to-telomere genome sequence [13] (Table S7).The assays were divided into two sets, each containing 96 assays, based on genetic distance calculated using the genotyping results to minimize genetic information bias between sets (Fig. S4).The SNP chip was applied to a diverse set of 919 ginseng genotypes (Table S4, S8).The genotype results were used to calculate the statistics for each marker (Table 3).The major allele frequency ranged from 0.5041 to 0.9931, with an average of 0.7787, while gene diversity ranged from 0.0137 to 0.5000, with an average of 0.3035.Observed heterozygosity varied from 0 to 0.6928, with an average of 0.0903, and polymorphic information content (PIC) values ranged from 0.0137 to 0.3750, with an average of 0.2464.

Genetic diversity and homozygosity of ginseng germplasms
The heterozygosity rate was calculated for 192 SNP loci across the collections of cultivars, breeding lines, wild-simulated ginseng and wild ginseng (Table S9, Fig. 3).In the majority of the genotypes, the genotype of the reference genome (green color) predominated (Fig. 3A).Commercial cultivars exhibited higher homozygosity rates than those of other genotypes (Fig. 3B).The majority of individuals within the categories of cultivars, breeding lines, wild-simulated ginseng, and wild ginseng displayed high homozygosity rates, rendering them suitable candidates for the rapid development of inbred cultivars.Specifically, 76.5% of cultivars, 55.6% of breeding lines, 46.3% of wild-simulated ginseng, and 54.7% of wild ginseng exhibited homozygosity levels above 95%.

Population structure analysis
A phylogenetic tree was constructed and genetic relationships were examined through principal component analysis (PCA) in the panel of 919 genotypes (Fig. 4A, 4D).Population structure analysis was also performed, and the ΔK method supported the presence of four genetically distinct clusters (i.e., K=4; Fig. 4B, S5), referred to as Groups 1 to 4 (Table S10).This is consistent with the findings of the phylogenetic tree and PCA.Individuals from each category of cultivar, breeding line, wildsimulated ginseng, and wild ginseng were all intermingled across the groups with no discernible pattern (Fig. 4C).The distribution of wild ginseng from Korea and China across various groups suggests the absence of genetic barriers between the two countries.In contrast, those from Russia were found to predominantly cluster in Group 4, which may be indicative of a shared origin from a single collection site.
The origin of the plants did not influence the grouping, which can be attributed to several factors.First, it could be because the genetic differences observed may not strictly correlate with the geographical origins but rather reflect a blended genetic background due to factors such as historical trade.Second, the 919 ginseng samples are primarily cultivated plants, not wild resources, and these cultivated plants can be traded between countries as seed, further blending their genetic backgrounds.
Third, we could not exclude the possibility of the SNP bias from the 192 SNPs.We also have primary phenotypic data for 119 genotypes (Table S11); however, no significant factors were identified that corresponded to the observed grouping patterns (Table S12, Fig. S6).The grouping pattern might be explained by underlying genetic structure, which could be revealed through more detailed genomic analysis or the inclusion of additional phenotypic traits not yet measured.
With regard to the genetic distance of groups, Group 1 and 2 exhibited a high average distance within group of 0.9808 and 0.9198, respectively (Fig. 4E).In contrast, Group 3 and 4 exhibited low average distances within the groups, at 0.2653 and 0.1969, respectively.The mean value of the fixation index (Fst) for Group 1 and 2 was 0.4152, indicating a significant differentiation between populations and a lack of shared genetic diversity against the other groups (Fig. 4E).Group  A number of different scenarios were encountered in relation to the homozygosity and homogeneity (Fig. 5).Firstly, seventeen accessions displayed complete homozygosity and

SNP chip development and accuracy assessment between genotyping methods
In this study, we employed a genotyping approach that involved the use of GBS, a SNP chip, and KASP markers.The resulting genotype data were then subjected to a comparative analysis (Table S13).The genotypes obtained from the SNP chip and KASP marker were identical, indicating a high level of consistency.However, among the 2 737 genotyping results, 55 instances of GBS data exhibited discrepancies from the other methods.Genotyping errors in GBS analysis are a recognized challenge, and it's noteworthy that other GBS studies have also reported lower heterozygosity values than the actual ones [21].The discrepancies were predominantly categorized into two groups: the first involved heterozygous genotypes in assays (SNP chip and KASP) but homozygous genotypes in GBS, while the second entailed homozygous genotypes in assays but heterozygous genotypes in GBS.The first case, observed 39 times, is likely attributable to sequencing bias at sites with heterozygous alleles.The second case, observed 16 times, is likely attributable to sequencing or mapping errors of some GBS reads.Both errors are further compounded by low read coverage of GBS data for certain duplicated targets.

Utility of the first genetic map
The construction of a genetic map for ginseng presents significant challenges due to its complex genetic nature.Firstly, ginseng has a tetraploid genome complicating the segregation and inheritance patterns [22].Secondly, individual ginseng plant produces approximately 40 seeds after four years of growth, leading to low seed production rates [23].Thirdly, it is difficult to maintain plant viability over extended periods [24,25].
Despite the availability of genome sequences, the absence of a comprehensive genetic map significantly hinders the broad application of the genome data.Without the foundational framework of a genetic map, interpreting and applying genomic data becomes significantly constrained.A highquality genetic map can assist in orientating and coordinating ginseng genome sequences, especially for the correcting of structural errors introduced during the Hi-C assembly.Furthermore, the development of a genetic map is of great importance for expanding pan-genome research, which aims to understand the complete set of genes within a species [26].In recent years, pan-genome studies have unveiled significant amounts of structural variations within species [27].Genetic map will enhance the resolution and accuracy of pan-genome analyses by providing the detailed genetic contexts.
The genetic map is essential for marker development and molecular breeding.The genetic map guide development of molecular markers related to agronomic traits.Quantitative Trait Loci (QTLs) linked to desirable agronomic traits or medicinal effects, such as yield, root size, and secondary metabolites, are influenced by multiple genes and environmental factors, making them complex for breeding.The map can provide frame for genetic mapping of QTLs using mapping population and also for genome wide association study using large collections.Markers associated to agronomic characteristics will improves marker-assisted breeding, enhancing the molecular breeding to develop elite ginseng cultivars.

The null genotype may reflect the indel events from the pan-genomes
The allotetraploid P. ginseng has undergone recent whole genome duplication events, resulting in the presence of highly similar paralogous sequences [4].While various molecular markers have been developed for ginseng [17], the process of genotyping has often been confounded by highly similar paralogous sequences, which has led to the formation of multiple amplicons.A well-known example of polyploidy in plants is bread wheat, which possesses an allohexaploid genome where repetitive and paralogous sequences occupy over 70% of the genome [28].Similar to wheat, the SNP markers developed in this study underwent a rigorous selection process involving diverse filtering steps to exclude SNPs detected from paralogous regions, ensuring the development of single locus targeting sub-genome specific markers [29].In selecting the SNPs, we opted for clarity in genotyping by exclusively selecting biallelic SNPs, those with only two types of alleles at the designated site.
Molecular markers are typically designed to amplify sequences containing either the reference or alternative allele.
Allelic drop-out, often referred to as allelic drop, is a phenomenon that can occur during the PCR amplification process, particularly in the context of genotyping [30].This issue arises by various factors, such as primer-site mutations, suboptimal PCR conditions, and low DNA quantity or quality.However, it could also be interpreted as indicative of the presence of a third allele.As pangenome studies have arisen, the importance of genomic research utilizing diverse gene pools is being increasingly emphasized [31].With regard to the molecular marker application, there are numerous opportunities to encounter germplasms with unexpected genotypes.Hence, the genotyped result labelled as "Null" should not be regarded as an error, but rather as a potential indication of a third allele.Rather than dismissing unamplified alleles, they should be considered carriers of homozygous indel variation.

Cross-species SNP chip application
The divergence between P. ginseng and P. quinquefolius occurred less than one million years ago, and the two species exhibit similar morphological characteristics (Fig. S7D) [32].We applied SNP chip for P. quinquefolius and P. vietnamensis individuals.The individuals of each species formed a distinct cluster that was separate from the P. ginseng groups (Fig. S7A S7C).In our previous study, phylogenetic analysis based on the chloroplast genomes of the Panax species provided insights into the divergence times of each species (Fig. S7D) [4].
The number of null genotypes observed from each species corresponds to their respective divergence times.Furthermore, given that ginseng is an allotetraploid [33], it can be categorized into

SNP chip database and molecular breeding
In our previous study, we constructed the Ginseng Genome Database (http://ginsengdb.snu.ac.kr/) [34].Subsequently, the database has been expanded to include a SNP chip database, accessible via the same web address.To date, we have applied to more than 1 200 ginseng individuals collected from cultivars, landraces, and mountain ginseng in Korea, China, and Russia.All genotyping results obtained via the SNP chip application will be stored and made accessible, along with providing clustering analysis services.This facilitates the assessment of genetic diversity and the establishment of a classification system.
Moreover, the SNP chip can assist in maintaining the purity of cultivars and can be utilized to protect breeder's rights by providing a cultivar-specific marker system.We could develop a cultivar-specific marker sets with a few SNP markers which can differentiate from all other ginseng collections.For instance, we developed a marker set by selecting a few reliable markers from 192 SNPs to identify cultivar 'Geumsun' and 'Cheonryang' from others (Table S14).
Ginseng is generally considered as a predominantly self-pollinating plant, with approximately 4% of hybrids occurring in its natural environment [35].Since ginseng bears seeds from its fourth-year, reducing the generation number is the most essential step to obtain a homozygous inbred line [3].Traditionally, ginseng breeding has been predominantly conducted through the pure line selection method.This involves the selection of superior individuals from the local landrace population and further self-fertilization over several generations [36].Most of registered cultivars has high homozygosity, but 23.5% exhibited heterozygosity levels ranging from 5% to 30%, indicating potential challenges in maintaining purity.Ensuring the purity of registered cultivars is crucial to preserve their superior characteristics.The utilization of the SNP chip will greatly facilitate this process in an efficient manner.
Furthermore, the SNP chip can be utilized to monitor the genotypes of the entire genome and verify the genetic homogenization in breeding lines.Selection of individuals with higher homozygosity will significantly reduce the breeding period.Selection of breeding lines with 100% homozygosity and 100% homogeneity will verify the genetic fixation as an inbred line, which can be evaluated as a candidate for cultivar registration.Eventually, this invaluable and informative SNP chip and its database represent a significant advancement in the establishment of a molecular breeding system for ginseng.[48].The population structure was presumed using STRUCTURE software [49] for subpopulation number estimation and the values of K were set from two to seven.
Simulations were run with 100 000 burn-in period, 100 000 Markov Chain Monte Carlo (MCMC) repeats, and five independent iterations.The optimal number of subpopulations was determined by the highest peak in the Delta K graph.Bar plots of STURCTURE analysis were rendered using the STRUCTURE Plot V2.0 program [50].919 individuals were sorted according to clustering analysis.
For cross-species SNP application result, phylogenetic analysis and population structure analysis were conducted with the same method with the analysis conducted only with ginseng individuals.

Fig. 1 .
Fig. 1.Genetic linkage map composed of 1 216 non-redundant markers and distribution of SNP chip markers.The 24 linkage groups have been arranged based on an unpublished chromosome-level genome assembled in our laboratory.The linkage group numbers are ordered from the pseudochromosome sequences, largest to the smallest, for sub-genome A (LG1-12) and sub-genome B (LG13-24).The purple and orange dots indicate the relative positions of 186 single-copy SNP chip (Table3).The 90 purple dots indicate SNPs identified between YP and CP mapping population and

Fig. 2 .
Fig. 2. DAPC scatterplot analysis of 119 ginseng accessions based on 5 000 SNPs randomly selected from the GBS data.The graph illustrates individuals as dots and represents groups using inertia ellipses.During the analysis, three discriminant eigenvalues were selected to elucidate the relationships among the clusters.The axes represent the first two Linear Discriminants.Each number depicted corresponds to a distinct subpopulation as identified through DAPC analysis.
O R R E C T E D M A N U S C R I P T Downloaded from https://academic.oup.com/hr/advance-article/doi/10.1093/hr/uhae257/7753521 by guest on 13 September 2024

Fig. 3 .
Fig. 3. Genotype information for 192 SNP loci across 919 ginseng germplasms.(A) Genotypes of 919 collections (X-axis) for 192 SNP locus.The 192 SNP loci were decoded as colors for red, blue, green, yellow, and gray for A, T, G, C and heterozygous (Up panel, Y axis).(B) The proportion of homozygous alleles in each individual.The homozygous genotypes were decoded as green (major type) and pink color (minor type) and heterozygous alleles were decoded as gray color (Low panel, Y axis).(C) Homozygosity rate for individuals belonged different populations.

3 and 4
exhibited the smallest Fst value of 0.0400, indicating the presence of numerous shared genotypes.The genetic distance between the groups is consistent with the results of phylogenetic and PCA analysis.

Fig. 4 .
Fig. 4. Population genetic analysis of 919 ginseng germplasms.(A) UPGMA phylogenetic tree, (B) population structure plot, (C) position information for each population, and (D) PCA analysis plot.Collections from Korea, China, and Russia are indicated with black, blue, and orange colors, respectively.(E) Mean Fst value of each group and genetic distance between groups.

Fig. 5 .
Fig. 5. Case study for application of SNP chip across inbreeding population which bred and maintained by pureline selection.Five accessions (A~E) were inspected and two individuals from each accession were randomly selected and genotyped by SNP chip.Homozygous genotypes were represented as A (red), T (blue), G (green), or C (yellow) and heterozygous genotypes were represented as H (grey). Individuals showed different genotypes were denoted as *.Homozygosity was revealed for each individual and homogeneity was revealed for each accession by comparing genotypes of two individuals.

Table 2 .
Information of genetic map *Bin: Number of non-redundant SNPs R I P T Downloaded from https://academic.oup.com/hr/advance-article/doi/10.1093/hr/uhae257/7753521 by guest on 13 September 2024

Table 3 .
Genome position and statistics of 192 SNP markers on the chip assays a SNPs derived from exon, intron, and 5 kb flanked region R I P T Downloaded from https://academic.oup.com/hr/advance-article/doi/10.1093/hr/uhae257/7753521 by guest on 13 September 2024 of wild ginseng showed 100% homozygosity.Conversely, 23.5 % of cultivars, 36.1% of breeding lines, 50.2% of wild-simulated ginseng, and 43.8% of wild ginseng displayed heterozygosity levels ranging from 5% to 30%.
homogeneity.For example, accession A showed 100.0%homozygous and uniform genotypes across 192 SNP sites, indicating a genetically stable and potentially cultivable state.Secondly, two accessions were observed having over 95.0% for both homozygosity and homogeneity.In accession B, for example, one individual exhibited 100.0%homozygosity, while the other exhibited 97.9%.In this case, proper selection and seed harvest from the individuals exhibiting high homozygosity will promote the development of an inbred line.Thirdly, three accessions were found having high homozygosity, over 99.0%, yet displaying a homogeneity below 80.0%.For instance, in accession Downloaded from https://academic.oup.com/hr/advance-article/doi/10.1093/hr/uhae257/7753521 by guest on 13 September 2024 C, both genotypes exhibited 100.0%homozygosity, but showed a notably low level of homogeneity, at just 74.9%.It can be postulated that seeds from two homozygous lines were inadvertently mixed maintained as a single accession.Lastly, a cross-pollinated individual among the breeding lines could be selected based on its heterozygosity.One individual of accession E (E-1) exhibited a low level of homozygosity of 67.7%, whereas another individual (E-2) exhibited 100.0%homozygosity (E-2).It can be postulated that the E-1 individual was derived by cross-pollination during the previous generation.On the basis of genotype, it can be inferred that accession D is the most probable pollen donor of the E-1 individual.This is because the two accessions share the same homozygous alleles at the 33.3% locus, while the other heterozygous alleles can be attributed to the combination of D and E.