2021 Volume 90 Issue 4 Pages 382-392
Genetic diversity analysis of worldwide Cucurbita genetic resources preserved in the Japanese Genebank can provide valuable information for breeding. In this study, 612 Cucurbita accessions of six species, including 40 accessions with no identification information, were genotyped with 30 SSR markers; 378 alleles were detected (12.6 alleles per marker; range, 4–24). By cluster analysis, the 40 unidentified and 53 likely misidentified accessions were (re)identified. The identification was verified by cluster analysis based on the sequence of the mitochondrial atp4–ccmC region. After correction of the identification information, C. pepo accessions had the highest diversity indices among the species analyzed and thus showed potential as an ideal genetic resource for breeding. Among the three major species (C. moschata, C. maxima, and C. pepo), the diversity indices of accessions from Japan were lower than those of overseas accessions, indicating that the overseas accessions preserved in Japan are more genetically diverse and can be used as materials for the development of new cultivars. STRUCTURE and principal coordinate analyses of C. moschata revealed that several Japan accessions constituted an indispensable part of global crop genetic resources owing to their differences from overseas accessions. Commercial cultivars of C. maxima showed genetic similarity to each other in principal coordinate analysis, suggesting that they may have similar breeding properties. This study corrects some identification errors in the Genebank and could help improve the breeding of Cucurbita vegetables.
Cucurbita L. (2n = 40) is a genus in the Cucurbitaceae family, which includes many edible cash crops (OECD, 2016). The fruits of this genus are known as squash, pumpkin, zucchini, or gourd, and by some other names such as “Japanese pumpkin” (C. moschata) and “Kabocha” (C. maxima) that refer to the cultivars from Japan. The genus is considered to have 12 to 27 species, of which five, C. ficifolia, C. maxima, C. mixta, C. moschata, and C. pepo, are cultivated. Cucurbita moschata, C. maxima, and C. pepo are the major cultivated species (Wang et al., 2011; OECD, 2016). They are thought to have originated in North and South America and are now widely cultivated on all continents (Nee, 1990). In addition to the fruits, stems, leaves, and seeds are also important nutrient sources in some countries. In recent years, about 27.4 million tons of Cucurbita fruits have been produced annually for use as food, in folk medicine, and as decorations (OECD, 2016). A large number of seedlings are used as rootstocks because some Cucurbita species exhibit strong growth and high resistance to diseases (Schulz et al., 2004; Xiao et al., 2010; Kong et al., 2014; FAO, 2020).
In Japan, the earliest record of Cucurbita plants dates back to 1548, when a Portuguese trading vessel brought Cucurbita fruits from Cambodia to Kyushu Island in western Japan (Rural Culture Association Japan, 2004). Later, the Japanese named this new vegetable “Kabocha” after the Cambodian name (Rural Culture Association Japan, 2004; de St. Maurice, 2017; Ministry of Agriculture, Forestry and Fisheries (Japan), 2020). The majority of Cucurbita crops cultivated in Japan before the 1960s were C. moschata, and many local cultivars were developed. However, over time, C. maxima became more popular with Japanese consumers because of its sweeter taste and softer texture (Rural Culture Association Japan, 2004). In addition, the unripe fruits of zucchini (C. pepo) have become increasingly popular in Japan since the 1980s, with annual production close to 10,000 tons (Food and Agricultural Materials Inspection Center (Japan), 2015). Currently, the annual squash production in Japan is 100,000 to 200,000 tons, half of which is from Hokkaido (northern region) (Food and Agricultural Materials Inspection Center (Japan), 2015). An F1 hybrid cultivar “Ebisu” (C. maxima, in some countries known as “Delica”) is the most widely cultivated (Agriculture & Livestock Industries Corporation (Japan), 2019). Due to their wide adaptability and high yield, Cucurbita cultivars bred in Japan have had a worldwide influence. In Australia, China, Europe, North America, New Zealand, and other regions, Cucurbita cultivars bred in Japan have been introduced and are widely cultivated; they are not only loved by local consumers, but are also used to improve local cultivars (Morgan and Midmore, 2003; Cumarasamy et al., 2010; Liu et al., 2010; Formiga et al., 2019; Agricola Don Camillo, 2020; Takii Europe, 2020).
Although a number of Cucurbita cultivars have been developed around the world in the past few decades, the demand for new cultivars is still urgent. One priority trait that should be improved is disease resistance. In Cucurbita production fields, many diseases such as powdery mildew, damping-off, and black root rot occur from time to time, and new cultivars with high resistance are desired by farmers. In addition, because Cucurbita plants with long vines and large leaves occupy large areas in fields, managing and harvesting them is time-consuming. Therefore, cultivars with short internodes are highly desirable (Hirai et al., 2004; Tsuji et al., 2011). New Japanese Cucurbita cultivars with the above-mentioned traits would increase the production of squash fruits. To develop new cultivars, it is necessary to identify species among the existing genetic resources and to clarify their characteristics and diversity at the phenotypic and genotypic levels.
In the last decade, the use of molecular markers to study genetic diversity has developed rapidly. Research methods based on RAPD, AFLP, ISSR, SRAP, SSR, SNP, and other markers are well established, and methods based on next-generation sequencing analysis are also developing rapidly (Schulman, 2007; Varshney et al., 2007; Liu et al., 2008; El-Esawi, 2017). SSR markers are widely used for genotyping plants because of their wide, codominant distribution in the genome, high variability, low analysis cost, and good repeatability (Guan et al., 2017; Abbasov et al., 2018; Chen et al., 2020). The applicability of SSR markers to study the genetic diversity of various Cucurbita species has been confirmed (Formisano et al., 2012; Kong et al., 2014; Martins et al., 2015; Kaźmińska et al., 2017; Verdone et al., 2018). When using molecular markers to study the diversity of genetic resources of various animal and plant species, many researchers have found that species identification was incorrect because it was based only on the phenotype, such as phenological and morphological characteristics, which are sometimes similar among species (Transue et al., 1994; Ren et al., 2010; Mason et al., 2015). Incorrect species identification may reduce the utilization efficiency of genetic resources, leading to unexpected experimental results. DNA barcoding of nuclear, chloroplast, and mitochondrial genes (or of all these genes combined) can help avoid this problem (Ren et al., 2010; Pečnikar and Buzan, 2013; Wang et al., 2013).
In Japan, the National Agriculture and Food Research Organization (NARO) has collected a large number of Cucurbita genetic resources derived from Japan and other countries. However, the genetic diversity of these resources remains to be explored. Many accessions have no information in terms of species identification or may be miss-identified. In this study, we aimed (1) to find a combination of SSR primers suitable for the simultaneous analysis of accessions of various Cucurbita species preserved in NARO collections; (2) to confirm or correct species identification of all accessions based on information on the polymorphism of their nuclear and organelle genes; and (3) to analyze the genetic diversity of Cucurbita genetic resources preserved in Japan.
We used 612 Cucurbita accessions from the Genetic Resources Center, Institute of Vegetable and Floriculture Science, and Hokkaido Agricultural Research Center of NARO, and commercial cultivars owned by a seed company. They included 323 accessions of C. moschata, 164 of C. maxima, 63 of C. pepo, 17 of C. ficifolia, three of C. mixta, two of C. foetidissima, and 40 of Cucurbita sp. (species unknown) (Table S1). Among them, 307 were Japanese local accessions and commercial cultivars, 286 were overseas accessions and cultivars from other continents, and the origin of 19 accessions was unknown.
Tissue collection and DNA extractionSeeds were germinated in 72-cell trays filled with Nippi Horticultural Soil No. 1 (Nihon Hiryo Co., Ltd., Tokyo, Japan). The first true leaf was collected and if the seeds did not germinate, cotyledons were collected from them. DNA was extracted using a DNeasy Plant Mini Kit (Qiagen GmbH, Hilden, Germany) and diluted in TE to a final concentration of 10 ng·μL−1.
SSR marker analysisA total of 77 Cucurbita nuclear SSR markers (Table S2) were prescreened against eight accessions (C001, C002, C003, C019, C117, C429, C431, C436) chosen based on their origins (Gong et al., 2012). Thirty SSR markers with a single peak and clear, reproducible, polymorphic amplification products were then applied to all other accessions (Table S2). PCR mixtures (10 μL) contained template DNA (10 ng), 1× KAPA 2G buffer A (KAPA Biosystems Inc., Woburn, MA, USA), 200 nM dNTPs, 0.5 mM MgCl2, 0.1 U KAPA 2G Fast DNA polymerase, 2 pmol reverse primer, and 0.5 pmol forward primer. The forward primers were 5′-labeled with the fluorescent dyes 6-FAM, VIC, NED, or PET (Shimizu and Yano, 2011). PCR was performed in a C1000 Thermal Cycler (Bio-Rad Laboratories, Inc., Hercules, CA, USA) with the cycling program described by Chen et al. (2020). PCR amplicons were analyzed using an automated DNA analyzer (model 3130xl) with a GeneScan-500LIZ size standard and GeneMapper v. 4.0 software (all from Thermo Fisher Scientific Inc., Waltham, MA, USA).
The number of alleles, major allele frequency, polymorphism information content (PIC), and F statistics indices were calculated in PowerMarker v. 3.25 software (Liu and Muse, 2005). Observed heterozygosity (Ho) and expected heterozygosity (He) were calculated in GenAlEx v. 6.502 software (Peakall and Smouse, 2012). Cluster analysis among accessions was performed using the unweighted pair-group method with an arithmetic mean (UPGMA) based on Nei’s genetic similarity (Nei et al., 1983) estimated using the 30 markers in PowerMarker. Hierarchical molecular variance analysis (AMOVA) of accessions of the three major species was calculated with Arlequin v. 3.5.2.2 software (Excoffier and Lischer, 2010). Genotype data for the SSR markers were also analyzed in the model-based STRUCTURE v. 2.3.4 software (Pritchard et al., 2000) to determine the most probable number of clusters (K value). These analyses were performed separately for all 612 accessions and for accessions that belonged to C. moschata, C. maxima, and C. pepo. The K value was determined by running an admixture and related frequency model with K = 1 to 10 (20 replications per K value); the burn-in period of each run was set to 100,000 and the Monte Carlo Markov Chain length was set to 1,000,000. The web-based program STRUCTURE HARVESTER was used to estimate the optimal K value (Earl and vonHoldt, 2012); this program follows the ΔK method of Evanno et al. (2005). Principal coordinate analysis (PCoA) was carried out using GenAlEx software separately for the 612 accessions and for the C. moschata, C. maxima, and C. pepo accessions.
Organelle marker analysisFor accessions that may have been misidentified in the phylogenetic tree based on SSR marker genotyping and accessions without identification information, re-identification was performed based on polymorphism of their organelle DNA sequences. Polymorphism of four chloroplast genome regions (matK, rbcL, trnL–trnF, rpl16–rpl14) and one mitochondrial genome region (atp4–ccmC) was tested by amplification and sequencing in four accessions from different species (C077, C243, C268, and C435) (Nakamura et al., 1997; Zheng, 2011). Because the number of C. mixta accessions was very small and its importance in agriculture is low, no accessions of this species were included. The primer sequences for amplification and sequencing are listed in Table S3. PCR cycling conditions and sequencing were as described by Nguyen et al. (2019). The sequences obtained were aligned and assembled in GeneStudio (GeneStudio, Inc. Suwanee, GA, USA). UPGMA trees were constructed in MEGA X (Kumar et al., 2018) using the sequence data.
Based on the polymorphism of these regions, the atp4–ccmC region was selected because it could distinguish all four different Cucurbita species. Then, 57 accessions with possible identification errors, 40 accessions without identification information, and 38 accessions (C. moschata, C. maxima, C. pepo, C. ficifolia, and C. mixta) that were considered to have no identification errors in the SSR marker analysis were analyzed as above (Table S1).
The 30 selected SSR markers amplified a total of 378 alleles in the 612 accessions, with an average of 12.6 alleles per marker (Table 1), ranging from 4 (CMTp248) to 24 (CMTp193). The mean genetic diversity indices of these accessions were 0.53 for major allele frequency (frequency of the allele with the highest frequency), 0.62 for He (indicating moderate to high levels of polymorphism), 0.10 for Ho (indicating that almost all individuals were highly homozygous), and 0.58 for PIC (indicating that these markers were informative).
Diversity indices of the 30 SSR markers used for genotyping of 612 Cucurbita accessions.
A phylogenetic tree of the 612 accessions revealed four major groups, each composed mainly of accessions of one species (C. ficifolia, C. pepo, C. maxima, and C. moschata; Fig. S1A). A considerable number (63) of accessions were found to have incorrect identification information. Forty accessions of unknown species were classified into all groups except that dominated by C. ficifolia.
Cluster analysis by organelle markerPhylogenetic trees based on organelle markers are shown in Figure S2. Only the sequence of the mitochondrial atp4–ccmC region could distinguish the four species used in this analysis. After multiple attempts, we were unable to obtain sequence information for five accessions for which DNA was directly extracted from seeds; these accessions were therefore excluded from the final analysis (Table S1). All accessions that were considered to be identified correctly by SSR marker analysis were grouped into a cluster according to their species (Fig. 1). For almost all of the accessions that had no identification information or with incorrect identification, analysis based on the atp4–ccmC region confirmed the results of SSR marker analysis. The only exception was C594: cluster analysis using SSR markers suggested that it belongs to C. moschata, whereas analysis of the atp4–ccmC region indicated that it belongs to C. maxima. Based on the combined results of both analyses, the phylogenetic tree established using SSR markers was repainted, and the Japanese and overseas accessions are marked with different colors in Figure S1B.
Phylogenetic tree of 130 Cucurbita accessions based on atp4–ccmC region sequences. “?” means the accession is probably belong to the species inferred by SSR marker analysis.
The genetic diversity indices for each Cucurbita species are summarized in Table 2 (C594 is not included). Among the seven species, the Na ranged from 1.27 (C. ficifolia) to 5.30 (C. pepo). The ranges for He, Ho, and PIC were 0.06–0.51, 0.004–0.22, and 0.08–0.46, respectively. Among the species, C. ficifolia had the lowest values and C. pepo had the highest. For C. moschata, C. maxima, and C. pepo, the diversity indices of Japan and overseas accessions were calculated separately. The Japanese accessions had the lowest values for He, Ho, and PIC, even though there were more Japanese accessions than overseas accessions (C. moschata and C. maxima).
Genetic diversity estimates in Cucurbita accessions for each species.
AMOVA of the three major Cucurbita species showed that for each species the genetic variation between Japanese and overseas accessions was much smaller than that within each of these groups (Table 3).
Analysis of molecular variance (AMOVA) of genetic diversity of 3 major Cucurbita species.
We used STRUCTURE analysis and PCoA to obtain information about the population structure of all the Cucurbita accessions and the three major species from allelic frequencies. In the STRUCTURE analysis of all 612 accessions, the computation of Evanno’s ΔK indicated K = 8 as the most likely model (Fig. S3), suggesting the presence of eight main clusters (1 to 8, Fig. 2). With 0.8 as the likelihood (Q-value) of classifying each accession into one of the eight clusters, each of 556 accessions (90.8%) was grouped into one of the eight clusters. Almost all accessions belonging to C. ficifolia, C. foetidissima, C. maxima, and C. mixta were grouped into species-specific clusters. Accessions of C. foetidissima and C. mixta were grouped into the same cluster, whereas those of C. moschata and C. pepo were grouped into multiple clusters. Most of the C. moschata accessions were grouped into cluster 4 or 5 depending on their origin (Japan or overseas, respectively), whereas the rest were mainly accessions from Nigeria grouped into cluster 6. The accessions of C. pepo were grouped into clusters 7 and 8. Cluster 8 contained mini-pumpkins (C167, C502, C555), indicating a certain genetic difference between mini-pumpkins and other C. pepo. For C594 (“Tetsukabuto”), which could not be unambiguously assigned to a species, the Q-values of clusters 3 and 4 were relatively high, but neither was greater than 0.8, indicating that it has a genetic background from both C. moschata and C. maxima.
Population structure of 612 Cucurbita accessions based on 30 SSR markers. At K = 8, all accessions were classified into 8 groups by STRUCTURE analysis.
The ΔK value was also relatively high when K = 4 (Fig. S3), indicating K = 4 as the next most-likely model. When K = 4, the accessions of C. ficifolia, C. foetidissima, and C. mixta were grouped into the same cluster (cluster 1, Fig. 2), showing a close genetic relationship between them. The C. moschata accessions from Nigeria were also grouped in this cluster. Most of the remaining accessions of C. moschata, C. maxima, and C. pepo were grouped into their respective clusters (Fig. 2). The results of PCoA for the 612 accessions are shown in Figure 3. The first two axes explained 28.12% of the variation in the genetic distance matrix. The results of the PCoA and phylogenetic analysis were in good agreement. A triangle-like distribution was found, with the three vertices being C. moschata, C. maxima, and C. pepo; the accessions belonging to the remaining species were distributed in the middle of the triangle. Accessions of the same species were grouped together, with no mixing between groups.
Scatter diagram from principal coordinate analysis of the 612 Cucurbita accessions.
In the STRUCTURE analysis of C. moschata accessions, the ΔK was highest at K = 3 (Fig. S4A), suggesting the presence of three main clusters, consistent with the results of analysis of all 612 accessions together: the Japanese and overseas accessions tended to be grouped into different clusters (Fig. 4A). PCoA also showed a difference between Japanese and overseas accessions, but they were not clearly divided into three different clusters (Fig. 4B). In the STRUCTURE analysis of C. maxima accessions, the ΔK was highest at K = 2 (Fig. S4B), suggesting the presence of two main clusters, which differed from the results of the analysis with all accessions. Most Japanese accessions were grouped into one cluster and most overseas accessions into another cluster (Fig. 4C). In Figure 4D, we marked the commercial C. maxima cultivars sold in Japan; they have a certain degree of centralized distribution and show a relatively close genetic relationship. In the STRUCTURE analysis of the C. pepo accessions, the ΔK was highest at K = 2 (Figs. 4E and S4C), suggesting the presence of two main clusters, consistent with the results of analysis of all 612 accessions together. However, PCoA analysis of the C. pepo accessions did not show two obvious clusters (Fig. 4F). The Q-values of the STRUCTURE analysis and the PCoA coordinates are listed in Table S4.
Population structure and scatter diagram from principal coordinate analysis of C. moschata, C. maxima, and C. pepo accessions based on 30 SSR markers. A, B: C. moschata; C, D: C. maxima; E, F: C. pepo.
In this study, the genetic diversity of worldwide Cucurbita genetic resources preserved in Japan was analyzed for the first time. A total of 30 single-locus SSR markers with clear amplification products were selected and used to analyze the genetic diversity of accessions belonging to six species of Cucurbita (C. moschata, C. maxima, C. pepo, C. ficifolia, C. mixta, and C. foetidissima). Amplification products were detected in all six species; most of the 30 markers had high PIC values (> 0.5) (Table 1) and were thus a suitable marker set for Cucurbita genetic diversity analysis.
Cluster analysis using these markers revealed that about 10% of the 612 accessions may have been misidentified (Fig. S1). This situation could lead to missing some accessions that may be interesting or mistakenly selecting accessions that turn out to be different from what is expected. This issue does not happen only in the gene banks in Japan (Cao et al., 1999; Mason et al., 2015). Forty accessions that had no identification information were classified into certain clusters, suggesting that they may belong to the same species as other accessions in the cluster. If their classification is confirmed, the barrier to the utilization of these genetic resources due to lack of identification will be eliminated. Currently, morphological traits have been used to distinguish different species in the Cucubita genus, but this method sometimes results in miss-identification. In the study of other species, molecular markers such as RAPD, SSR, chloroplast and mitochondrial markers have been used for species identification (Singh et al., 2004; Mugue et al., 2008; Tuler et al., 2015; Poovitha et al., 2016). The set of SSR markers we selected could meet the need for species identification of the Cucurbita species in this study.
We screened five organelle markers, and found that all six Cucurbita species could be identified with just one mitochondrial marker. The results of the analyses with SSR markers and with the mitochondrial marker were almost identical, confirming the accuracy of both DNA markers in species identification.
A good marker set, if widely used as a standard marker set, can be used to compare the results of different research groups around the world (Fukuda et al., 2013). The SSR marker set used in this study has high PIC values and can distinguish six Cucurbita species, so it has the potential to become a generic marker set for species identification of new accessions and genetic diversity analysis in Cucurbita collections.
Accession C594 requires a special mention. It was identified as C. moschata with SSR markers, but as C. maxima with the mitochondrial marker (Fig. 1). According to the breeding history of this cultivar, C594 is an interspecific hybrid between these species, so it is reasonable that it has genetic characteristics of two different species. Its nuclear genome is closer to that of C. moschata, whereas its mitochondria are derived from C. maxima. Some studies use only nuclear markers such as SSR markers to identify interspecific hybrids (Kimball et al., 2013; Pathirana et al., 2016; Saha et al., 2017), but this example shows that when it is impossible to find nuclear markers polymorphic between parents from different species, using organelle markers could help identify parents of interspecific hybrids.
After the identification information was corrected, C. pepo had the highest He and PIC values and showed higher genetic diversity than the other species (Table 2). The average number of alleles in C. pepo was 5.3, higher than the average of 3.0 (determined with 134 SSR markers) for 104 C. pepo accessions stored in the United States (Gong et al., 2012). The PIC value of C. pepo was 0.46, which is close to the 0.42 reported in a Spanish study (Formisano et al., 2012). Although the difference in the markers and accessions used allows only a rough comparison between studies, it still shows that the diversity of C. pepo accessions preserved in Japan is no lower than that in other countries, and that C. pepo could be an ideal resource for future breeding. In contrast, although C. moschata had the largest number of accessions, its diversity indices were almost as low as those of C. maxima. A study of the worldwide (mainly European) C. maxima accessions found a PIC value of 0.51 (Kaźmińska et al., 2017), which was higher than the 0.22 in this study, indicating lower genetic diversity of the C. maxima accessions preserved in Japan. Cucurbita ficifolia had the lowest diversity indices, and many accessions were very closely related to each other in the phylogenetic tree, although they came from different countries (Fig. 2; Table 2). A study on C. ficifolia in Mexico also revealed low diversity index values (Moya-Hernández et al., 2018). Among the three major species, the diversity indices of accessions from Japan were lower than those of overseas accessions, indicating that the overseas accessions preserved in Japan are more genetically diverse than the accessions bred in Japan. Therefore, the overseas accessions preserved in Japan can be used as a material library for the development of new cultivars. In fact, overseas Cucurbita accessions have already been used in Japanese squash and pumpkin breeding (Kami, 2015). Given the low genetic diversity of C. moschata and C. maxima accessions, to meet needs such as off-season supply, bush-type plants, and seedless fruits, introducing more exotic germplasms is an effective option (Kikuchi and Iizuka, 2014; Kami, 2015).
The phylogenetic tree in this study also reflects the relativeness among the investigated species. As can be seen in Figure 1, C. pepo is closer to C. moschata, and C. ficifolia is closer to C. maxima on the mitochondrial atp4–ccmC region. In contrast, the phylogenetic tree drawn based on nuclear SSR markers shows that C. pepo is closer to C. maxima, and C. moschata is closer to C. mixta (Fig. S1). In other studies based on mitochondrial and chloroplast regions, both showed that C. moschata and C. mixta were closer, while the relationship between C. pepo and C. maxima varied (Sanjur et al., 2001; Zheng, 2011), while all these studies showed that C. foetidissima is distant from C. pepo, C. maxima, C. moschata, and C. mixta. However, the phylogenetic tree based on SSR markers in this study showed that C. foetidissima is closer to C. moschata and C. mixta. These results show that the nuclear and cytoplasmic genetic differentiation of the Cucurbita genus may be not consistent. Since the results of these studies were based on partial genome information and a limited number of germplasms, further studies based on complete genome sequences using a greater number of germplasms are needed to confirm this phenomena.
In AMOVA, the genetic variation of the accessions of the three major Cucurbita species was mainly among individuals, and the correlation with their origin (Japan or overseas) was relatively low (Table 3). This indicates that Japanese accessions have no overall characteristics that distinguish them from overseas accessions. The STRUCTURE and PCoA analyses of C. moschata revealed that, among Japanese accessions, some are traditional cultivars similar to overseas accessions, but most are different from overseas accessions (Fig. 4). Japanese pumpkins originated overseas, so there should be some old cultivars that are similar to overseas accessions. The difference between Japanese and overseas accessions revealed that some native cultivars have been grown and bred over a long period. Crops introduced into Japan, such as loquat, rapeseed, and tea, often produce cultivars with Japanese characteristics (Fukuda et al., 2013; Taniguchi et al., 2014; Chen et al., 2017). Although these Japanese cultivars have different levels of genetic diversity, their uniqueness shows that they constitute an indispensable part of the global crop genetic resource.
In the PCoA of C. maxima, we analyzed the commercial cultivars sold in Japan separately (Fig. 4D). Although they came from different companies, they were not widely distributed in the PCoA chart, showing high genetic similarity. The development of new cultivars often involves selecting the best available cultivar, so genetically similar parents are repeatedly used for breeding, which may be the cause of this genetic similarity. The use of genetically similar parents for breeding may not be able to meet new requirements such as large-scale mechanized cultivation. Therefore, it is reasonable to consider using genetic resources that are genetically very distant from existing commercial cultivars (Kami, 2015).
We also found that some accessions with the same name are genetically very different. For example, C064, C195, and C373 are all named BGH4138, but C373 and the other two are not closely related according to STRUCTURE analysis and PCoA (Fig. 4; Table S4). Similarly, accessions C019, C122, C126, C129, C209, C252, C374, C490, and C598 are all named “Hyuuga 14”, but some of them are not closely related to each other. This misclassification may result in breeders choosing accessions that do not match their expectations. Therefore, we suggest that accessions with the same name in the Japanese Genebank should be confirmed using Table S4 of this paper to understand the genetic relationship between them before selection for breeding.
In this study, we selected 30 markers suitable for the analysis of six different species of Cucurbita crops, used them to study the genetic diversity of the Cucurbita accessions in Japan, and corrected errors in the identification of these genetic resources. These markers could help researchers better understand the genetic relationships within these species, and help breeders more wisely choose accessions to meet specific breeding goals.
We thank N. Nishi and H. Matsuo at the University of Tsukuba for technical advice and assistance. We are grateful to N. Tomooka, Y. Kawazu, and other members of the Plant Genetic Resources (PGRAsia) project for collecting and providing plant materials. Most of the plant materials were kindly provided by the NARO Genebank.
