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Article

Genetic Diversity Analysis of Capsicum frutescens Based on Simplified Genome Sequencing Technology

by
Lidong Wu
1,2,3,
Yinhui Qiu
1,2,3,*,
Shuting Lin
1,2,3,
Rui Zhang
1,2,3,
Lihao Wang
2,4,
Yongqing Li
1,2,3 and
Yacong Cao
2,4,*
1
Sanming Academy of Agricultural Sciences, Sanming 365509, China
2
National Vegetable Improvement Center—High and Super Hot Pepper Variety Innovation Center, Sanming 365509, China
3
Fujian Key Laboratory of Crop Genetic Improvement and Innovative Utilization for Mountain Area, Sanming 365509, China
4
Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2024, 10(9), 1004; https://doi.org/10.3390/horticulturae10091004
Submission received: 19 July 2024 / Revised: 30 August 2024 / Accepted: 19 September 2024 / Published: 21 September 2024
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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Abstract

:
Capsicum frutescens (C. frutescens) has rich germplasm resources, but there have been no reports on its genetic diversity analysis alone using simplified genome sequencing technology (GBS). To provide a basis for the breeding of new pepper varieties and the later development of C. frutescens SNP molecular markers, this study used GBS technology to sequence 65 collected pepper germplasm resources. A total of 1,399,391 SNP sites were obtained by GBS simplified genome sequencing, and there were 1,465,897 SNP variant sites. Through population genetic structure analysis, the population structure and phylogenetic tree of 65 C. frutescens germplasms were constructed. The GBS method is also suitable for the genetic relationship analysis of C. frutescens, and it also shows that there is an obvious separation of materials from different origins, and there is also a certain degree of genetic exchange. Most of C. frutescens varieties from Fujian Province and its surrounding areas are clustered together; C. frutescens varieties from western China are also clustered together. We selected T62 and T60 with a genetic distance of 0.2796 and a spiciness level of nine as the female and male parent combinations, respectively, and bred a new high-yield C. frutescens combination, ‘Mingjiao 308’. C. frutescens varieties from the same geographical origin are usually clustered together. These germplasms may contain the ancestry of multiple varieties. This result can also provide basic data for the later construction of an SNP fingerprint database.

1. Introduction

Due to the presence of capsaicin in the fruits of pepper (Capsicum spp.), which results in a spicy flavor, they are widely used as a condiment and vegetable with economic value [1]. Among the 35 Capsicum species, the five species Capsicum annuum, Capsicum baccatum, Capsicum chinense, Capsicum frutescens, and Capsicum pubescens are widely cultivated as a domesticated species. C. frutescens grows its berries skyward, and the fruits are generally cone-shaped [2]. C. frutescens is one of the most important varieties of peppers [3,4]. This is not only due to its high resistance to stress, but also due to the high capsaicin content and the size of the fruit, which make it suitable for direct consumption, but also make it suitable for the production of processed products, such as dried chili, chili powder, chili sauce, and so on [5,6]. Due to its adaptability and wide range of uses, C. frutescens is immensely popular all over the world and have a large scale of cultivation [6,7,8]. Compared with conventional species, hybrid C. frutescens has a higher yield and fruit consistency while maintaining the high capsaicin content of its parents [1]. Therefore, it is very important to select suitable parents for the breeding of C. frutescens. In marked contrast to other cultivars (C. annuum), much of the genetic variation in C. frutescens is difficult to distinguish directly using visualized phenotypes [9]. It is necessary to investigate and study the genetic background of C. frutescens germplasm resources, on the basis of which different C. frutescens germplasm resources can be distinguished. These efforts are important for understanding the breeding process of different sources of C. frutescens as well as for improving the breeding efficiency of C. frutescens.
C. frutescens shows a wide range of diversity in plant type, leaves, fruit, and other external morphological characteristics, especially in fruit shape, fruit color, spiciness, and other fruit characteristics of more abundant variation [10]. Currently, studies on the genetic diversity of C. frutescens have been reported. The genetic diversity of 103 Brazilian C. frutescens germplasm resources was analyzed using morphological characters and SSR markers, and they were successfully classified into six taxa [11]. Morphological and RAPD markers were applied to analyze the genetic diversity of 26 C. frutescens germplasm resources from two sources and to uncover virus-resistant genotypes among them [12]. A genetic clustering analysis of 22 materials of six pepper species (C. annuum, C. bacaccatum, C. chinense, C. eximium, C. frutescens, and C. luteum) was performed using twenty-seven RAPD and eight ISSR primers; morphological identification showed that the phenotypic difference of flowers was closely related to the genetic distance of pepper [13].
GBS (Genotyping By Sequencing) is a genotyping sequencing technology developed by Elshire et al. based on the second generation of simplified genome sequencing [14]. The technical route of GBS is to use restriction DNA cleavage and then sequence by attaching the GBS label, using the gene sequence information near the cleavage site to detect a large number of variant SNP sites with high accuracy. GBS is characterized by simple operation, high efficiency, good reproducibility, and low sequencing cost compared with other traditional sequencing technologies. Currently, it has been widely used in genetic diversity studies, genome-wide association analysis, and population genetic structure studies in horticultural crops [15,16,17,18,19]. Based on pea GBS data from the United States Department of Agriculture (USDA) and the Italian Commission Research and Economics of Agricultural (CREA), the evolutionary history of pea and the distribution of the localization of important genes in it were discovered [20]. The simplified genome sequencing of recombinant inbred line progeny locates important QTL determining cucumber fruit aroma [21]. The GBS analysis of 109 broccoli materials revealed that the allelic diversity of primordial species was 4.8 times higher than that of broccoli hybrids, and this work is of high value for preserving valuable broccoli primordial species resources and promoting broccoli breeding efforts [22]. The genotyping of two oilseed rape populations with extreme stain tolerance by the GBS method identified 1468 and 1450 SNP loci in the GIL (GH01 as a rotational parent) and ZIL (ZS9 as a rotational parent) populations, respectively, laying the foundation for the subsequent localization of stain tolerance genes in oilseed rape [23]. At present, GBS technology has been used to analyze the phylogenetic distribution and classification of Capsicum species. Dias et al. conducted GBS analysis on 190 pepper materials they collected from Spain and found that the separation of pepper varieties was closely related to fruit characteristics and origin [24]. Dennis et al. used GBS to assess the genetic diversity of 165 pepper genotypes from New Mexico, and found that the genetic diversity of the New Mexico pepper was low, requiring the introduction of more new alleles [25]. Abate et al. used GBS to analyze the level of genetic diversity and population structure of 142 pepper materials from Ethiopia, and they found that these materials could be divided into two distinct genetic populations, indicating a large genetic difference between C. annuum and C. frutescens [26]. In conclusion, GBS is very convenient for analyzing the genetic diversity of large genomes, complex genomic materials, and for genetic typing, but there are no reports of professionally simplified GBS genome sequencing analysis focusing on the genetic diversity of the germplasm resources of C. frutescens.
In this study, we used GBS simplified genome technology to sequence the introduced and self-selected high-generation C. frutescens self-inbred materials at home and abroad, to search and identify the SNPs of C. frutescens in the whole genome, to compare the relatives of C. frutescens varieties, to analyze the genetic evolutionary relationship, and to further lay the theoretical foundation for the in-depth understanding of the biological characteristics and relatives of the C. frutescens germplasm resources, as well as for the cultivation of C. frutescens of new varieties.

2. Materials and Methods

2.1. Materials

The 65 C. frutescens germplasm resources were provided by the Sanming Academy of Agricultural Sciences. The 65 C. frutescens germplasm resources were identified in the field for 2 consecutive years as highly pure, and germplasm resources with the local characteristics and core parental resources of C. frutescens breeding; they showed obvious differences in major agronomic traits and were obtained after years of multi-generation consecutive self-breeding (Table S1). Fruit shape, green ripe fruit color, and old ripe fruit color of C. frutescens germplasm resources were described with reference to the Specification for the Description of Capsicum Germplasm Resources of the National Crop Germplasm Resource Platform; the capsaicin content was determined by reference to the national standard (GB/T 21266-2007) [27], and the heat level was classified by reference to the local standard of Hunan Province, DB43/T276-2006 [28], “Methods for Sensory Evaluation of the spice levels of Chili Peppers and Chili Pepper Products”. and the specific information is given in Table S2.

2.2. Methods

2.2.1. DNA Extraction and GBS Library Construction

Young and tender leaves of C. frutescens were collected and a mixture of 10 plants per germplasm resource was sampled, and after quick freezing with liquid nitrogen, it was placed in the refrigerator at −80 °C for storage. The CTAB method was used to carry out the extraction of genomic sample DNA, and the quality of the extracted genomic sample DNA was tested using Qubit and Nanodrop. The quality-tested genomic sample DNA was digested with restriction endonuclease (EcoRI-NIaIII), uneven broken ends were patched with Taq polymerase and sticky ends were generated by adding prominent base A tails at both ends, and splices were added using the NEB Next ® ΜLtra™ DNA Library Prep Kit (NEB, Ipswich, MA, USA). The 300–400 bp DNA fragments of the gene sample set after restriction endonuclease cleavage were subjected to PCR amplification, and the PCR products were processed using the AMPure XP system (Beckman Coulter, Brea, CA, USA), and the constructed GBS Simplified Genome Typing sequencing libraries were detected using an Agilent 2100 Bioanalyser (Agilent, Santa Clara, CA, USA) and quantitated by RT-PCR. PCR products libraries were sequenced on the Novaseq 6000 llumina by Genedenovo Biotechnology Co., Ltd. (Guangzhou, China).

2.2.2. Filtering of GBS Genotyping Sequencing Data

First, the raw data from the sequencing platform were pre-filtered as follows: (1) remove low quality reads with unknown nucleotides (N) ≥ 10%; (2) remove reads with low scores (Q) ≤ 20 and more than 50% of bases; and (3) delete reads containing junctions. The filtered clean reads were subjected to data assembly, analysis of data volume, GC content, average sequencing depth, etc. Finally, the mem algorithm of the BWA comparison software (version 0.7.12) was used to compare with the pepper reference genome (ZUNLA-1), with the comparison parameter setting: -k32-M and tagged with picard (version 1.129).

2.2.3. Genome-Wide SNP Screening and Typing Analysis

To detect these variations, a series of data processing steps are required, such as local re-comparison and base quality correction using GATK software (version 4.4.0). (1) Local comparison: The region around the nDel is locally re-compared to obtain accurate information about the variations. (2) Base quality recalibration: This is performed to reduce sequencing errors, eliminate the likelihood of mismatches with the reference genome, and obtain reliable variants by recalibrating base quality data processing. The processed comparative data were screened for SNP variants across multiple samples and functionally annotated using GATK software.

2.2.4. Capsaicin Content Extraction and Assay

The samples were baked in an oven at 60 °C until the moisture content was ≤15%, then ground using an electric grinder, passed through a 50 mesh sieve, and 0.5 g of the samples were weighed into a 50 mL centrifuge tube. A total of 25 mL of methanol–tetrahydrofuran (1:1) solvent mixture was added to the sample, and it was sealed with cling film. Then, several small holes were made with a needle, and it was extracted with an ultrasonic oscillator under the conditions of a water bath at 60 °C for 30 min. It was then filtered through filter paper, the filtrate was collected, and then the filtrate residue was filtered again with filter paper into 25 mL, and extracted with an ultrasonic oscillator for 10 min, repeating twice. The filtrates collected from the three filtrations were combined and concentrated to 10–20 mL using a rotary evaporator at 70 °C, then fixed to 50 mL with methanol–tetrahydrofuran (1:1) and filtered through a 0.45 μm filter membrane for chromatographic analysis. Chromatographic column: Zorbax SB-C18 4.6 mm × 250 mm 5 µm; mobile phase: methanol + water (65 + 35); injection volume: 10 µL; flow rate: 1 mL/min; detection wavelength: 280 nm; column temperature: 30 °C. Standard solution of capsaicinoids: Accurately weigh the appropriate amount of capsaicinoid standard substance with purity ≥ 95% (Alta Technology Co., Ltd., Tianjin, China) and dihydrocapsaicinoid standard substance with purity ≥ 90% (Alta Technology Co., Ltd.) and dissolve them with methanol to prepare a mixed standard solution of capsaicinoid and dihydrocapsaicinoid with appropriate concentration.

2.3. Data Processing

The neighbor-joining algorithm was used to construct a genetic evolutionary tree for the population structure using treebest (1.9.2); principal component analysis was performed using the R package (version 4.4.1) (http://www.r-project.org/, accessed on 13 October 2021); the population structure analysis was first filtered with the filter parameter: -indep-pairwise 50 10 0.1. The population structure was analyzed using the plink (version 2.x) and admixture (version 1.3) software (default parameters).

3. Results

3.1. Genome Sequencing Quality Assessment

By selecting the published pepper genome (ZUNLA-1) as the reference genome, we enzymatically cut (EcoRI-NIaIII) the genome according to the restriction endonuclease sites on the reference genome. We performed genomic chromosome tags statistics; a total of 2,649,204,167 restriction endonuclease sections were obtained by e-enzymatic prediction in this experiment, and the total number of valid restriction endonuclease sections was 185,004,722. In addition, to check the efficiency of the enzymatic cuts and to analyze all of the tags, a total of 161.1 Greads of raw sequence data were obtained from the 65 C. frutescens germplasm resources sequenced by Illumina, and a total of 158.9 G of valid data (clean reads) were obtained after filtering, and the Q 20 ratio of the 65 simplified genomes sequenced reached an average of 97.5%, with an average GC content of 36.47%, an average sequencing depth of average GC content of 36.47%, an average sequencing depth of 13.4×, and an average comparison rate with the reference genome (ZUNLA-1) of 96.53%. The above results showed that the base distribution was normal and the quality of the simplified genome sequencing was high, which could meet the needs of subsequent analysis.

3.2. SNP Variation in 65 Pepper Germplasm Resources

As shown by the distribution of SNPs in the pepper genome (Figure 1A), the highest number of SNPs was found on chromosome 9 and the lowest number of SNPs was found on chromosome 8. Through the statistical analysis of SNP-InDel, it can be seen that a total of 1,399,391 SNP loci were detected in 65 pepper germplasm resources, with 1,465,897 SNP variant loci and 66,506 insertion or deletion changes in the gene sequence. These SNP sites were mainly distributed in the intergenic region (Figure 1B), accounting for 95.94%. Among them, chromosome 9 had the highest number of SNPs (175,069), while chromosome 8 had the lowest number of SNPs (53,503). The mutations of the SNPs could be categorized into two types, transition and transversion, and the number of transition-type SNPs (915,870) was much larger than that of transversion SNPs (483,521), and the ratio of transition to transversion (Ts/Tv) was 1.89, with a much higher rate of C⟶T transition (260,832) (Figure 1C).

3.3. Population Genetic Structure Analysis

3.3.1. Population Principal Component Analysis

The set of 1,465,897 SNPs was used for principal component analysis (PCA). The PCA results showed that the principal component contributions of PCA were PC1 7.31%, PC2 5.75%, and PC3 5.33%, and the total of the three was 18.39% (Figure 2). Compared with different spiciness grades, the use of different geographical sources as labels can more clearly distinguish the genetic background of these C. frutescens resources. However, the resources of high-spiciness (level 9) C. frutescens are significantly clustered together, suggesting that high-spiciness C. frutescens has a similar genetic background (Figure 2B).

3.3.2. Group Structure Analysis

Based on the SNP markers, a phylogenetic tree based on the genetic relationships among 65 C. frutescens germplasm resources was constructed using the neighbor-joining algorithm by treebest (1.9.2) software (Figure 3A). Each group in the evolutionary tree contained self-selected C. frutescens varieties. All varieties originating from Southeast Asia (Thailand and India) and independent selection were grouped into subgroup I, with a total of eight varieties; those originating from Korea, Japan and independent selection were grouped into subgroup II, with a total of four varieties; and local varieties collected domestically and independently selected varieties were grouped into subgroup III, with a total of 53 varieties.
The number of subpopulations with the lowest cross-validation error rate (K) can determine the optimal number of subpopulations, and the value of K in this study is three. It can be clarified that the optimal number of subpopulations for the population structure of C. frutescens germplasm resources should be three (Figure 3B), which also directly indicates that the 65 C. frutescens germplasm resources have been divided into three classes. From Figure 3B, it can be seen that there are signs of mutual crossing among each subpopulation, which also indicates that each subpopulation of the 65 C. frutescens germplasm resources is closer to each other. When K = 3, it was observed that it corresponded to Southeast Asian cultivar subpopulation I, Japanese and Korean cultivar subpopulation II, and domestic cultivar subpopulation III, respectively (Figure 3C). To subdivide the domestic subgroup III, the 65 C. frutescens can be divided into five groups by setting K = 5 (Figure 3C). The domestic subgroup (group III) was divided into three groups. Group 1 (III-1) consisted mainly of local varieties from Sichuan, Henan, Guizhou, Yunnan and Guangxi, such as ‘Sichuan Seven-star Pepper’, ‘Tiemen Pepper’, ‘Suiyang Bullet Head’, ‘Little Sparrow Pepper’, ‘White Rice Pepper’, and the vast majority of late independent selections that could be traced back to the parent. Group 2 (III-2), in addition to T64: Chongqing Pepper’, consisted of local varieties and self-selected varieties in Fujian Province, such as the local varieties ‘Zhenghe Pepper’, ‘Gutian Pepper’, ‘Zhiping Pepper’, and ‘Dongmen Pepper’. Group 3 (III-3) consisted mainly of local varieties from Hunan, Jiangxi, Guizhou, Hunan, Hebei, Sichuan, and other places in China, such as ‘Guiyang Pepper’, ‘Xinfeng Pepper’, ‘Zunyi Pepper’, ‘Baoqing Pepper’, ‘Jizhou Tianying Pepper’, ‘Zigong Pepper’, ‘Dongxing Pepper’, ‘Dongxi Pepper’, and some self-selected varieties. In addition, the heterogeneity of local varieties such as ‘Tiemen Pepper’ and ‘Chongqing Pepper’ at the genetic level can be clearly demonstrated, and the germplasm resources of these local varieties may have infiltrated more exogenous genes or retained more wild genes, and the focus is on conserving and using them as core germplasm. In the future, we will focus on conserving and using these local varieties as core germplasm. From the results of population differentiation, geographical isolation, interspecific hybridization and introgression, and domestication are important driving forces for the genetic differentiation of C. frutescens germplasm.
In summary, the results of the population structure analysis and phylogenetic evolutionary tree construction were basically consistent, and the fact that C. frutescens germplasm resources with the same genetic background could be clustered at the genetic level also demonstrated the accuracy of the clustering.
The results of the genetic differentiation coefficient (Fst) (using PopGenome_2.2.4) and genetic distance (DR) (used MEGA.X) analyses among 65 populations of C. frutescens germplasm resources classified on the basis of fruit shape (Table S1) showed that the Fst values between two of the four constructed populations (long lantern-shaped, long ram’s horn-shaped, long finger-shaped, and short ram’s horn-shaped) ranged from 0.0747 to 0.1530, and the DR values ranged from 0.2709 to 0.2839. The lowest Fst values were found between the long ram’s horn-shaped and long finger-shaped fruit shape groups, while the highest Fst values were found between the long lantern-shaped and short ram’s horn-shaped fruit shape groups (Table 1). An Fst ≥ 0.05 between populations classified on the basis of fruit shape would indicate that the 65 artichoke germplasm resources were genetically differentiated to a moderate or higher degree in fruit trait classification. Finally, the 65 C. frutescens germplasm resources were much more differentiated for long lantern-shaped than for long ram’s horn-shaped and long finger-shaped.
The results of the genetic analysis of genetic Fst and DR based on the classification of spiciness classes (Table S1) showed that the Fst values among these four populations (level 6, level 7, level 8, and level 9) varied in the range of 0.0588~0.1247, and the DR values varied in the range of 0.2721~0.2985 (Table 2). The smallest Fst values were between the groups of level 6 and level 7, and the largest Fst values were between the groups of level 6 and level 8 (Table 2). The Fst ≥ 0.05 between the spiciness classification populations indicated that all 65 C. frutescens germplasm resources had a moderate or higher degree of genetic differentiation in spiciness classification. It can be seen that 65 C. frutescens germplasm resources were much more differentiated in level 9 than in level 6, level 7, and level 8.
The results of genetic analysis Fst and DR based on the classification of old ripe fruit color (Table 3) showed that the Fst values of these four populations (old ripe fruit color: dark red, old ripe fruit color: orange-yellow, old ripe fruit color: orange-red, and old ripe fruit color: light red) varied between two groups in the range of 0.0623~0.1901, and the DR values varied in the range of 0.2521~0.3086, with the smallest Fst values between old ripe fruit color dark red and old ripe fruit color light red, and the largest Fst values between the old ripe color orange-yellow and old ripe color orange-red groups (Table 3). This showed that the Fst between populations based on old ripe fruit color was ≥0.05, indicating that 65 C. frutescens germplasm resources had a moderate or higher degree of genetic differentiation in old ripe fruit color classification.
The results of the genetic analysis of Fst and DR based on the classification of green ripe fruit color among 65 populations of C. frutescens germplasm resources (Table 4) showed that the Fst values among these four populations (green ripe fruit color: yellow-white, green ripe fruit color: yellow-green, green ripe fruit color: green, and green ripe fruit color: light-green) varied in the range of 0.0854~0.1673, and the DR values ranged from 0.2802 to 0.3333, with the smallest Fst values between the green and light green groups, and the largest Fst values between the yellow-white and light green groups (Table 3). The Fst ≥ 0.05 between the populations indicated that there was a moderate or higher degree of genetic differentiation between the 65 C. frutescens germplasm resource populations based on green ripe fruit color classification.
We performed a heat map analysis of genetic differentiation coefficients between individuals for 65 C. frutescens germplasm resources (Figure 4), and the results showed that the genetic distance between T24 (Zhiping pepper) and T2 (C22) was 0.034559, that between T24 and T5 (C3) was 0.02033, and that between T2 and T5 was 13035; the genetic distances between the three are very close. This indicates that T2, T5, and T24 have a relatively close relationship, but the T24 fruit type is a long finger shape, and T2 and T5 are the long ram’s horn shape. There are big differences in the appearance and the hotness of the three peppers, probably because there is gene exchange between them, and T2 and T5 may have come from the hybridization, isolation, and purification of T24 with other materials.
T40 (C389), a self-selected pepper cultivar, and T41 (C427), a C. frutescens cultivar introduced in Guizhou, showed different fruit shapes and colors of green and old ripe fruits, but because of their close genetic distance, they may be different plants with similar parental origins, which may be caused by the phenomenon of the homogenization of C. frutescens in the breeding process. The genetic distance of 0.075878 between T11 (Gutian pepper) and T63 (Fujian pepper) was also closer, and the fruit type, green ripe fruit color, old ripe fruit color, and spiciness grade were roughly comparable, with the origin being Fujian, and both of them were different strains isolated from the local variety ‘Fujian Chili King’ and have similar genetic backgrounds.
There is a correlation between genetic distance and yield hybrid dominance in C. frutescens, and materials with moderately large genetic distances can be selected to improve yield dominance in the selection of new pepper varieties. According to the heat map (Figure 4), when crossbreeding these C. frutescens materials, materials with a genetic differentiation coefficient above 0.25 (more red) were selected for crossbreeding. For example, by using hybrid advantage, we selected T62 (Dongmen) and T60 (S22), which have a larger genetic distance and higher spiciness, with a genetic distance of 0.279602 and a degree of nine in spiciness for both, and we formulated a combination with T62 (Dongmen) as the mother and T60 (S22) as the father, selecting and breeding a new variety of high spiciness C. frutescens called ‘Ming Jiao 308’ (Figure 5). This new variety exhibits high yield, strong spiciness, strong aroma, and other characteristics. It provides a higher production while maintaining the high capsaicin content of the parent.

4. Discussion

We investigated a method to analyze the genetic diversity of 65 C. frutescens resources based on GBS and found that genetic differences among C. frutescens resources could be effectively distinguished by GBS. Furthermore, based on the results of the analysis, the hybridization of selected C. frutescens resources with large differences in genetic background could significantly bring out the hybrid advantage.

4.1. Genetic Structure of C. frutescens Resources Can Be Significantly Differentiated Using GBS

In this study, based on GBS and strict quality control, 1,465,897 SNP variant sites were detected and 66506 insertion or deletion mutations occurred in the gene sequences. SNPs are the most common type of genetic variation, and by comparing variant SNP loci between individuals within a population, it is possible to study the genetic diversity, relatedness, and population genetic structure of populations [29,30]. The majority of these SNPs are base change mutations and they are mainly found in the intergenic regions. By examining SNP loci for PCA, we found that it was difficult to distinguish the 65 C. frutescens sources significantly, either in terms of geographic origin or spiciness rating. This indicates that their SNP similarity is high. In previous studies, PCA can be used to distinguish different cultivated pepper species well, but it is difficult to distinguish the difference between the same cultivated species only by PCA [24]. These results also confirm that artificial selection can lead to changes in the characteristics of some local specialty varieties [31].
We used all of the SNPs to construct phylogenetic trees of these C. frutescens resources. Similar to the finding of a previous study, an analysis of the population structure showed that geographic origin was closely related to relatedness among C. frutescens materials, with the closer the geographic origin of the C. frutescens materials, the closer the relatedness [25]. Most of the C. frutescens material collected around Fujian Province was from the same population, whereas the material from southwest China was also classified as belonging to a different population. This indicates that C. frutescens germplasm resources distributed within China have also undergone significant genetic differentiation due to differences in geographical distribution. In China, C. frutescens germplasm resources are in the form of intra-regional circulation, which may be due to the fact that it is easier to circulate germplasm resources within a given region [32].
In addition, we have found some genetic exchange of C. frutescens material from different source locations. This phenomenon has also been found in studies of other vegetables. The genetic differentiation coefficient (Fst) is an important indicator of the degree of genetic differentiation among populations. If the genetic differentiation index Fst < 0.05, there is no genetic differentiation between subpopulations. If the genetic differentiation index 0.05 ≤ Fst ≤ 0.15, there is moderate genetic differentiation between subpopulations. If the genetic differentiation index Fst > 0.15, there is high genetic differentiation between subpopulations. We calculated Fst values between taxonomic groups based on four phenotypic agronomic traits of high interest for C. frutescens germplasm resources: fruit shape classification, spiciness rating, old ripe fruit color, and green ripe fruit color [33,34,35,36]. Fst values ranged from 0.0747 to 0.1530, 0.0588 to 0.1247, 0.0854 to 0.1673, and 0.0623 to 0.1901, respectively, which also indicated that the highest degree of genetic differentiation was observed among the populations classified on the basis of the old ripe fruit color. Our results also demonstrate that there is substantial genetic differentiation within the C. frutescens resource, and that it is difficult to differentiate the genetic background of C. frutescens by only a single or a few observations of agronomic traits.
Our results confirm that GBS is a simple and economical method that can be used to distinguish the genetic structure of C. frutescens resources. GBS is suitable for the genetic relationship analysis of C. frutescens because it can effectively differentiate the genetic backgrounds of C. frutescens for different traits as well as different places of origin. It also provides important molecular information for the selection and breeding of new C. frutescens varieties using hybrid advantage.

4.2. Use of GBS Allows Easy and Rapid Exploitation of Pepper Hybrid Dominance

Pepper is a plant in which the expression of hybrid dominance is very pronounced, and it is often easier to obtain high quality pepper varieties by using parents with very different genetic backgrounds [37,38,39]. Therefore, analyzing the genetic background of pepper breeding materials and differentiating between pepper materials with different genetic backgrounds is very important for pepper breeding. C. frutescens is a popular and economically important domesticated pepper. We counted four agronomic traits in these 65 C. frutescens germplasm resources, and these agronomic traits differed more significantly among C. frutescens varieties. The current genetic analysis of pepper materials is often a mixed analysis of each cultivated pepper, because the genetic background and phenotypic differences between different cultivated peppers are very obvious, so the phenotype can be well used to distinguish these materials [24,25,26]. However, it is difficult to accurately differentiate the genetic backgrounds of C. frutescens using phenotypic trait observations alone, as there is also significant genetic differentiation within C. frutescens germplasm resources with the same phenotype. While C. frutescens from different geographical regions have significant differences in genetic background, we also observed some genetic exchange and penetration between C. frutescens from different regions. Therefore, it is difficult to differentiate the genetic background of C. frutescens based on phenotype and origin and to use heterotic for variety improvement, a phenomenon observed by other pepper breeders [10].
Using GBS technology, we detected abundant genetic variation within the C. frutescens population and, moreover, these genetic variants were difficult to distinguish by agronomic traits. Based on the Fst between individuals, we selected T62 as the male parent and T60 as the female parent to formulate a hybrid combination to obtain the new hybrid variety Mingjiao 308 C. frutescens. Compared to the parents, Mingjiao 308 produced significantly higher yields, although it did not have higher capsaicin content. This means that Mingjiao 308 may be more economically viable to grow while maintaining the current quality of C. frutescens. Existing studies have also shown that the hybrid advantage is more likely to be seen in offspring size than in yield [40,41].
In summary, we have analyzed the genetic background of 65 C. frutescens materials with high breeding value using GBS technology, and based on the results of the analyses, we have rapidly bred new high-yielding C. frutescens varieties. Our work demonstrates the power of modern biological technology in pepper breeding.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae10091004/s1, Table S1: Germplasm and main fruit characters of 65 C. frutescens; Table S2: Capsaicin content of 65 C. frutescens.

Author Contributions

Conceptualization and methodology, L.W. (Lidong Wu) and Y.Q.; software, R.Z.; formal analysis, L.W. (Lidong Wu); resources, Y.L.; data curation, S.L.; writing—original draft preparation, Y.C.; writing—review and editing, Y.Q.; visualization, L.W. (Lihao Wang) All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key R&D Programme for the 14th Five-Year Plan (2023YFD1200101), Special Project for Local Development Guided by the Central Government (2021L3043).

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Acknowledgments

We thank the Sanming City People’s Government Funding. We thank Yang Sheng of Fujian Agriculture and Forestry University for technical support. We thank Guangzhou Genedenovo Biotechnology Co., Ltd. for assisting in sequencing and bioinformatics analysis.

Conflicts of Interest

The authors declare no conflicts of interest.

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Horticulturae 10 01004 g001
Figure 1. The distribution of SNPs in the pepper genome. (A) The number distribution of SNPs in each chromosome. (B) The distribution of SNPS in the genome sink. (C) Sntransform annotated statistical graph.
Figure 1. The distribution of SNPs in the pepper genome. (A) The number distribution of SNPs in each chromosome. (B) The distribution of SNPS in the genome sink. (C) Sntransform annotated statistical graph.
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Figure 2. The 3242 SNPs obtained were used for the principal component analysis (PCA) of 65 C. frutescens resources. (A) The results of PCA based on the geographical origin of C. frutescens. (B) The results of PCA labelled by spiciness rating.
Figure 2. The 3242 SNPs obtained were used for the principal component analysis (PCA) of 65 C. frutescens resources. (A) The results of PCA based on the geographical origin of C. frutescens. (B) The results of PCA labelled by spiciness rating.
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Figure 3. Population structure analysis. (A) Phylogenetic evolutionary tree. (B) Population structure cross validation error analysis chart. (C) An analysis of population structure based on selected SNPS, (K = 3) and (K = 5); colors represent different assigned clusters. The y-axis provides the probability of each accession belonging to the assigned cluster.
Figure 3. Population structure analysis. (A) Phylogenetic evolutionary tree. (B) Population structure cross validation error analysis chart. (C) An analysis of population structure based on selected SNPS, (K = 3) and (K = 5); colors represent different assigned clusters. The y-axis provides the probability of each accession belonging to the assigned cluster.
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Figure 4. Heat map of the genetic differentiation coefficient (Fst) between individuals.
Figure 4. Heat map of the genetic differentiation coefficient (Fst) between individuals.
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Figure 5. Breeding process and characters of ‘Ming Jiao 308’. (A) ‘Ming Jiao 308’ and its parental characters. (B) Capsaicin content and SHU of ‘Ming Jiao 308’ and its parents. (C) The production of ‘Ming Jiao 308’ and its parents in 2020 and 2021.
Figure 5. Breeding process and characters of ‘Ming Jiao 308’. (A) ‘Ming Jiao 308’ and its parental characters. (B) Capsaicin content and SHU of ‘Ming Jiao 308’ and its parents. (C) The production of ‘Ming Jiao 308’ and its parents in 2020 and 2021.
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Table 1. Genetic differentiation coefficient (Fst) and genetic distance (DR) among 65 pepper germplasm resource populations based on fruit shape classification.
Table 1. Genetic differentiation coefficient (Fst) and genetic distance (DR) among 65 pepper germplasm resource populations based on fruit shape classification.
PopulationLong Lantern-ShapedLong Ram’s Horn-ShapedLong Finger-ShapedShort Ram’s Horn-Shaped
Long lantern-shaped-0.27290.28390.2837
Long ram’s horn-shaped0.1375-0.27090.2717
Long finger-shaped0.14580.0747-0.2785
Short ram’s horn-shaped0.15300.08490.0825-
Note: The lower triangle is the genetic differentiation coefficient (Fst) between groups, and the upper triangle is the genetic distance between groups (DR). The same as below.
Table 2. Genetic differentiation coefficient (Fst) and genetic distance (DR) among 65 C. frutescens germplasm resource populations based on spiciness rating.
Table 2. Genetic differentiation coefficient (Fst) and genetic distance (DR) among 65 C. frutescens germplasm resource populations based on spiciness rating.
PopulationLevel 6Level 7Level 8Level 9
Level 6-0.28980.29850.2731
Level 70.0588-0.28910.2721
Level 80.07520.0672-0.2832
Level 90.09180.10480.1247-
Table 3. Genetic differentiation coefficient (Fst) and genetic distance (DR) among 65 pepper germplasm resource populations based on old ripe fruit color.
Table 3. Genetic differentiation coefficient (Fst) and genetic distance (DR) among 65 pepper germplasm resource populations based on old ripe fruit color.
PopulationDark RedOrange-YellowOrange-RedLight Red
Dark red-0.29790.27520.2761
Orange-yellow0.1530-0.30860.2984
Orange-red0.16930.1901-0.2938
Light red0.06230.08620.1077-
Table 4. Genetic differentiation coefficient (Fst) and genetic distance (DR) among five pepper germplasm resource based on green ripe fruit color.
Table 4. Genetic differentiation coefficient (Fst) and genetic distance (DR) among five pepper germplasm resource based on green ripe fruit color.
PopulationYellow-WhiteYellow-GreenGreenLight Green
Yellow-white-0.29080.33330.3039
Yellowish green0.1285-0.31150.2802
Green0.16090.1121-0.2881
Light green0.16730.10050.0854-
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MDPI and ACS Style

Wu, L.; Qiu, Y.; Lin, S.; Zhang, R.; Wang, L.; Li, Y.; Cao, Y. Genetic Diversity Analysis of Capsicum frutescens Based on Simplified Genome Sequencing Technology. Horticulturae 2024, 10, 1004. https://doi.org/10.3390/horticulturae10091004

AMA Style

Wu L, Qiu Y, Lin S, Zhang R, Wang L, Li Y, Cao Y. Genetic Diversity Analysis of Capsicum frutescens Based on Simplified Genome Sequencing Technology. Horticulturae. 2024; 10(9):1004. https://doi.org/10.3390/horticulturae10091004

Chicago/Turabian Style

Wu, Lidong, Yinhui Qiu, Shuting Lin, Rui Zhang, Lihao Wang, Yongqing Li, and Yacong Cao. 2024. "Genetic Diversity Analysis of Capsicum frutescens Based on Simplified Genome Sequencing Technology" Horticulturae 10, no. 9: 1004. https://doi.org/10.3390/horticulturae10091004

APA Style

Wu, L., Qiu, Y., Lin, S., Zhang, R., Wang, L., Li, Y., & Cao, Y. (2024). Genetic Diversity Analysis of Capsicum frutescens Based on Simplified Genome Sequencing Technology. Horticulturae, 10(9), 1004. https://doi.org/10.3390/horticulturae10091004

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