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Article

Genome-Wide Analysis of Fruit Color and Carotenoid Content in Capsicum Core Collection

by
Nayoung Ro
*,
Hyeonseok Oh
,
Ho-Cheol Ko
,
Jungyoon Yi
,
Young-Wang Na
and
Mesfin Haile
*
National Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea
*
Authors to whom correspondence should be addressed.
Plants 2024, 13(18), 2562; https://doi.org/10.3390/plants13182562
Submission received: 13 August 2024 / Revised: 5 September 2024 / Accepted: 11 September 2024 / Published: 12 September 2024
(This article belongs to the Special Issue Molecular Marker-Assisted Technologies for Crop Breeding)
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Versions Notes

Abstract

:
This study investigated carotenoid content and fruit color variation in 306 pepper accessions from diverse Capsicum species. Red-fruited accessions were predominant (245 accessions), followed by orange (35) and yellow (20). Carotenoid profiles varied significantly across accessions, with capsanthin showing the highest mean concentration (239.12 μg/g), followed by β-cryptoxanthin (63.70 μg/g) and zeaxanthin (63.25 μg/g). Total carotenoid content ranged from 7.09 to 2566.67 μg/g, emphasizing the diversity within the dataset. Correlation analysis revealed complex relationships between carotenoids, with strong positive correlations observed between total carotenoids and capsanthin (r = 0.94 ***), β-cryptoxanthin (r = 0.87 ***), and zeaxanthin (r = 0.84 ***). Principal component analysis (PCA) identified two distinct carotenoid groups, accounting for 67.6% of the total variance. A genome-wide association study (GWAS) identified 91 significant single nucleotide polymorphisms (SNPs) associated with fruit color (15 SNPs) and carotenoid content (76 SNPs). These SNPs were distributed across all chromosomes, with varying numbers on each. Among individual carotenoids, α-carotene was associated with 28 SNPs, while other carotenoids showed different numbers of associated SNPs. Candidate genes encoding diverse proteins were identified near significant SNPs, potentially contributing to fruit color variation and carotenoid accumulation. These included pentatricopeptide repeat-containing proteins, mitochondrial proton/calcium exchangers, E3 ubiquitin-protein ligase SINAT2, histone–lysine N-methyltransferase, sucrose synthase, and various enzymes involved in metabolic processes. Seven SNPs exhibited pleiotropic effects on multiple carotenoids, particularly β-cryptoxanthin and capsanthin. The findings of this study provide insights into the genetic architecture of carotenoid biosynthesis and fruit color in peppers, offering valuable resources for targeted breeding programs aimed at enhancing the nutritional and sensory attributes of pepper varieties.

1. Introduction

Capsicum, commonly known as pepper, is a globally significant crop valued for its economic importance and nutritional benefits [1]. The genus Capsicum includes a diverse range of cultivars, with fruit color and carotenoid content being key traits of interest for both consumers and breeders [2]. The vibrant colors of pepper fruits are primarily determined by the accumulation of various carotenoids, which not only provide visual appeal but also contribute significantly to the fruit’s nutritional value [3]. Peppers are rich in bioactive components and essential nutrients, including vitamins (A, C, and E), colored pigments (zeaxanthin, β-carotene, violaxanthin, capsanthin, β-cryptoxanthin, lutein, and capsorubin), as well as phenolic compounds like capsaicinoids and flavonoids [4,5].
The variations in pigments in pepper fruits reflect combinations of three groups: chlorophylls, carotenoids, and anthocyanins [6,7]. Chlorophylls impart the fruit a green color, whereas the red color is mainly due to carotenoid pigments, such as capsanthin and capsorubin [6,8,9]. Yellow and orange hues primarily result from a varied accumulation of carotenoids, such as violaxanthin, lutein, and β-carotene [10]. In contrast, the purple color of unripe fruit arises from anthocyanidins, particularly delphinidin derivatives, in the fruit exocarp [11,12]. When very high levels of anthocyanins, chlorophyll, and some carotenoids coexist in the exocarp, the fruit appears black [13]. The biosynthesis and accumulation of carotenoids in Capsicum fruits involve complex metabolic pathways regulated at multiple levels [14].
Carotenoids play a crucial role in human health and nutrition, extending far beyond their function as colorful pigments in fruits and vegetables. These compounds are potent antioxidants that help protect cells from oxidative stress and reduce the risk of chronic diseases [15]. For instance, β-carotene serves as a precursor to vitamin A, essential for vision, immune function, and cell growth [16]. Lutein and zeaxanthin are vital for eye health, particularly in preventing age-related macular degeneration [17]. Lycopene, abundant in red peppers, has been associated with a reduced risk of certain cancers and cardiovascular diseases [18]. Moreover, capsanthin, a carotenoid unique to red peppers, has shown promising anti-inflammatory and anti-cancer properties [19]. The carotenoids found in Capsicum species not only contribute to the nutritional value of peppers but also are used to develop functional foods and nutraceutical products to promote human health [20]. The concentration of these compounds in pepper can exhibit significant differences influenced by factors such as pepper genotypes, and cultivation practices [5,21,22].
Understanding the genetic basis of these specific carotenoid contents is crucial for developing improved varieties with enhanced visual appeal and nutritional content. Studies have elucidated the genetic control of fruit color and carotenoid content in Capsicum. The Y locus, responsible for red fruit color, was identified as the capsanthin–capsorubin synthase (Ccs) gene [23]. The cl locus, controlling light yellow fruit color, has been associated with a mutation in the phytoene synthase (Psy) gene [24]. The capsanthin–capsorubin synthase (Ccs) gene exhibited polymorphism in PCR patterns within the segregating population [25]. This population originated from a cross between two pepper accessions: cv. msGTY-1 with orange fruits and cv. 277long with red fruits. Analysis revealed a deletion in the Ccs gene’s upstream region in orange-fruited plants [25]. Mutation in the β-carotene hydroxylase gene led to β-carotene buildup and changed pepper fruit color from red to orange [6]. Recent studies further expanded our understanding of carotenoid biosynthesis in peppers. Additionally, the role of a chromoplast-specific lycopene β-cyclase (CYC-B) in controlling β-carotene content was demonstrated [26]. These findings collectively contribute to a more comprehensive understanding of the complex genetic network governing fruit color and carotenoid biosynthesis in Capsicum, paving the way for targeted breeding efforts to enhance both the visual and nutritional qualities of peppers. However, further studies exploring more additional genes that contribute to fruit color and carotenoid production are important.
Genome-wide association study (GWAS) has emerged as a powerful tool for dissecting complex traits in Capsicum and other crop species. In Capsicum, GWAS was successfully applied to investigate various traits, including fruit-related characteristics, disease resistance, and metabolite content [27,28,29,30]. This approach has led to the identification of novel loci associated with important agronomic traits, providing valuable insights for pepper breeding programs. The applicability of GWAS extends beyond Capsicum, with successful implementations in other crops such as rice, maize, wheat, and tomato [31,32,33,34]. In these crops, GWAS has facilitated the discovery of genetic variants associated with yield components, quality traits, and stress tolerance. The success of GWAS across different plant species demonstrates its versatility and effectiveness in unraveling the genetic architecture of complex traits. Therefore, using a comprehensive genome-wide approach on a diverse core collection, this study aimed to provide additional insights into the genetic control of fruit color and carotenoid content in Capsicum.

2. Results

2.1. Fruit Colors and Carotenoid Content Variations

This study incorporated a total of 306 pepper accessions from diverse Capsicum species. The fruit color distribution among the pepper accessions is visualized in Figure 1. Red fruits were the most abundant, with 245 accessions. Orange peppers were the second most common, with 35 accessions, followed by yellow peppers, which had 20 accessions. Fruits with purple, brown, and other uncommon colors were rare, with only three accessions exhibiting dark purple and two accessions displaying brown. The descriptive statistics summary of carotenoid contents across 306 pepper accessions reveals the variability and distribution of these compounds (Table 1). The mean concentrations of the individual and total carotenoids exhibited significant diversity across the dataset. Among the individual carotenoids, capsanthin showed the highest mean concentration, followed by β-cryptoxanthin and zeaxanthin. The descriptive statistics also highlighted the variability within the dataset, with ranges extending from 7.09 to 2566.67 μg/g for total carotenoids. This diversity emphasizes the complexity and richness of carotenoid profiles within the pepper accessions studied. Analysis of carotenoid content in mature Capsicum fruits of different colors revealed variations in both capsanthin levels and total carotenoid content. Capsanthin, the predominant individual carotenoid analyzed, showed marked differences across fruit colors (Figure 2). Red Capsicum fruits exhibited the highest capsanthin content, followed closely by orange fruits and yellow fruits. The average carotenoid contents of pepper accessions, categorized by species, are summarized in Figure 3. Among the Capsicum species, C. frutescens exhibited the highest total carotenoid content (526.19 μg/g). Also, β-cryptoxanthin and capsanthin showing notable levels in subsequent order. C. baccatum had a total carotenoid content of 484.08 μg/g, characterized by elevated concentrations of capsanthin and zeaxanthin. C. annuum and C. chinense had lower total carotenoid contents, with C. annuum showing notable capsanthin levels. These variations may have been influenced by the differing number of accessions sampled for each species and fruit colors.

2.2. Correlation and Principal Components Analysis

Analysis of the correlation matrix among carotenoid compounds in pepper accessions provided valuable insights into the interrelationships between these bioactive compounds (Figure 4). Correlation coefficients revealed varying strengths and directions of associations between carotenoid pairs. For instance, a moderate positive correlation (r = 0.560) was observed between antheraxanthin and violaxanthin, suggesting that increases in the concentration of one are associated with increases in the concentration of the other. A strong positive correlation (r = 0.78 ***) between β-carotene and β-cryptoxanthin indicated a close association in their accumulation patterns. In contrast, some carotenoid pairs displayed weaker or negative correlations, such as capsanthin and lutein (r = −0.19 ***), suggesting an inverse relationship. Total carotenoid content exhibited strong positive correlations with several individual compounds, including capsanthin (r = 0.94 ***), β-cryptoxanthin (r = 0.87 ***), and zeaxanthin (r = 0.84 ***). These correlations suggest that these compounds significantly contribute to the overall carotenoid profile in peppers. The observed correlations offer insights into the complex dynamics of carotenoid accumulation in pepper varieties and may inform breeding strategies for enhanced nutritional and sensory attributes.
PCA was performed on individual and total carotenoid content data from 306 pepper accessions (Figure 5). The analysis accounted for 67.6% of the total variance. Principal Component 1 (PC1) and Principal Component 2 (PC2) explained 44.7% and 22.9% of the variance, respectively. The PCA results confirmed the clustering patterns observed in the correlation heatmap (Figure 5), revealing two distinct carotenoid groups. The first group included α-carotene, violaxanthin, antheraxanthin, and zeaxanthin, while the second group comprised capsorubin, capsanthin, zeaxanthin, β-cryptoxanthin, β-carotene, and total carotenoids. This grouping pattern provides additional evidence of the relationships between specific carotenoids in pepper accessions.

2.3. Genome-Wide Association Analysis

Association analysis was conducted to identify SNPs associated with fruit color and carotenoid content in peppers. The distribution patterns of SNPs across the 12 chromosomes, visualized in 1 Mb windows, are shown in Supplementary Figure S1. The association analysis revealed 91 significant SNPs: 15 linked to fruit color (10 genic, 5 intergenic) and 76 to carotenoid content (48 genic, 28 intergenic) (Table 2). Detailed information on all SNPs associated with carotenoids is provided in Supplementary Table S2. The GWAS results are visualized using Manhattan plots (Figure 6) and quantile–quantile (Q-Q) plots (Supplementary Figure S2). Among the carotenoids, α-carotene had the highest number of associated SNPs (28), followed by antheraxanthin (19), β-cryptoxanthin (9), and capsanthin (8). β-carotene was associated with seven SNPs, capsorubin and total carotenoid content had two each, and zeaxanthin had the fewest with one SNP. The significantly associated SNP distribution varied by chromosome as presented in Table 2. Analysis of the genomic regions surrounding significant SNPs associated with fruit color identified several candidate genes (Table 3). These genes encode a variety of proteins including the following: a pentatricopeptide repeat-containing protein At5g66520-like, a RING-type domain-containing protein, a PITH domain-containing protein, three instances of mitochondrial proton/calcium exchanger proteins, tropinone reductase 2, an upstream gene encoding gamete expressed protein 1, beta carbonic anhydrase 5 (chloroplastic), and a putative glutathione S-transferase. The list of significantly associated SNPs with carotenoid content, along with the genes where these SNPs are located, is summarized in Table 4. These genes encode proteins such as E3 ubiquitin-protein ligase SINAT2, sucrose synthase 6, pentatricopeptide repeat-containing protein (chloroplastic), transcription termination factor MTEF18, beta-glucosidase BoGH3B, a probably inactive leucine-rich repeat receptor-like protein kinase IMK2, lignin-forming anionic peroxidase, receptor-like protein 19, and histone–lysine N-methyltransferase ASHH2. These proteins represent diverse cellular functions, including protein degradation, carbohydrate metabolism, chloroplast function, transcription regulation, and various enzymatic activities. SNPs that exhibited significant associations with multiple carotenoid traits, suggesting possible pleiotropic effects, are found in Table 4. One SNP on chromosome 1 was linked to α-carotene and β-cryptoxanthin, while the remaining six SNPs on chromosomes 5, 6, 7, 8, 9, and 12 were associated with β-cryptoxanthin and capsanthin. The genes listed include an E3 ubiquitin-protein ligase, stamen-specific protein, RNA helicase, protein homolog, protein-tyrosine-phosphatase, and a guanine nucleotide exchange factor.

3. Discussion

Peppers show remarkable genetic diversity, leading to a wide range of fruit colors, shapes, and sizes. This diversity arises from natural variation, selective breeding efforts, mutations, and environmental influences over generations. Fruit color is a key trait that breeders have targeted to develop new varieties with diverse visual appeal and improved nutritional profiles. Variation in fruit color among pepper accessions is primarily due to differences in the accumulation and composition of pigments. In this study, fruit color distribution analysis among the 306 pepper accessions showed that red fruits were the most abundant, followed by orange and yellow. Red and yellow peppers are rich in carotenoids, contributing to their vivid colors [35]. Carotenoids contribute to the diverse colors of pepper fruits and provide various health benefits, such as acting as dietary sources of provitamin A and protecting against cardiovascular diseases and certain cancers [36,37]. Among the 306 accessions, dark purple and brown fruit colors were rare, with only a few accessions exhibiting these colors. These rare accessions are important because breeders have increasingly focused on developing pepper varieties with diverse fruit colors, such as white, purple, yellow, black, and orange, to meet consumer preferences and enhance the diversity of available pepper commodities [38]. The accumulation and proportion of pigments like chlorophylls, anthocyanins, and carotenoids, determine pepper fruit color [39,40,41,42]. Understanding the genetic basis of fruit color variation is crucial for breeding programs for developing pepper varieties with desirable color traits and nutritional properties.
The study revealed significant diversity in carotenoid profiles across 306 pepper accessions, highlighting the complexity of carotenoid composition in peppers. This diversity is likely attributed to genetic differences among accessions [43]. Capsanthin was identified as the predominant carotenoid, significantly contributing to the total carotenoid content. This finding is consistent with previous reports on C. chinense [43,44] and sweet red pepper (C. annuum) varieties [45]. In this study, capsanthin contributed an average of 54% to the total carotenoid content, which falls within the range reported in previous studies: 45% in C. chinense [44] and 60% as reported by Bosland [46]. Capsanthin is known for its potential health benefits [47,48,49]. Correlation analysis provided insights into the interplay between carotenoid compounds. Strong positive correlations were observed between several carotenoid pairs, including antheraxanthin and violaxanthin, β-carotene and β-cryptoxanthin, and total carotenoids with β-cryptoxanthin, capsanthin, and zeaxanthin. These correlations suggest that changes in one carotenoid’s concentration may correspond with changes in others, underscoring the complex dynamics of carotenoid accumulation within pepper varieties [49].
The number of SNPs associated with fruit colors and carotenoid contents are summarized in Table 3 and Table 4. A total of 15 SNPs significantly associated with fruit color were identified. Among these, some SNPs were located within genes, while others were in the intergenic regions. The genes where the significantly associated SNPs are located include beta carbonic anhydrase 5, chloroplastic, putative glutathione S-transferase, and pentatricopeptide repeat-containing protein (PPR). The association of PPR genes with fruit color traits is consistent with findings from various studies across different plant species. For instance, a genome-wide study in watermelon revealed that SNPs in four PPR genes were significantly correlated with flesh color variation [50]. Similarly, a recent genetic mapping study in watermelon identified a PPR gene co-segregating with the C2 locus, which controls yellow flesh color [51]. These findings suggest a conserved role for PPR genes in fruit color determination across cucurbit species. The involvement of PPR genes in fruit color regulation extends beyond the Solanaceae and Cucurbitaceae families. In melon (Cucumis melo), a QTL analysis identified CmPPR1 as a candidate gene for flesh color phenotype, representing one of two significant loci controlling this trait [52]. Furthermore, in tomato, reduced expression of a PPR-encoding gene was observed in the cnr (colorless non-ripening) mutant, which exhibits colorless pericarp in mature fruits [53]. While the exact mechanism linking PPR proteins to fruit color remains unclear, these proteins are known to influence organellar mRNA transcripts and regulate chloroplast size and thylakoid membrane structure [54,55]. PPR proteins have also been implicated in plastid-to-nucleus retrograde signaling, which can affect the expression of genes targeted to plastids, potentially regulating color variation in a quantitative manner [52,55]. Additionally, PPRs play a role in various RNA modifications, including editing, stabilization, and splicing [56]. A recent study on C. chinense further supports the importance of PPR genes in fruit color determination [57]. Their analysis of gene expression profiles revealed varied expression patterns of eight PPR genes across three C. chinense accessions with different fruit colors. Interestingly, four PPR genes were significantly upregulated in the red-fruited ‘Naga Morich’ cultivar, while the other four were downregulated, suggesting a complex regulatory network involving PPR genes in fruit color development.
One SNP associated with fruit color was identified in a gene encoding a putative glutathione S-transferase (GST) gene. This finding aligns with recent research on the GST role in anthocyanin transport and fruit pigmentation. Anthocyanins, water-soluble flavonoid pigments, are crucial for fruit color and have additional roles in plant defense and human health benefits [58,59,60]. While anthocyanin biosynthesis is well-understood [61,62], their transport to vacuoles is crucial for fruit coloration. GSTs, particularly the plant-specific Phi class, are involved in anthocyanin transport across various plant species [63]. Loss of GST function reduces anthocyanin accumulation in plants such as maize, petunia, and Arabidopsis [63,64,65,66]. In fruit crops, several GSTs are associated to pigmentation, including LcGST4 in litchi, VviGST4 in grapevine, RAP in strawberry, MdGSTF6 in apple, and PpGST1 in peach [67,68,69,70,71]. The SNP identified could affect GST function or expression, potentially influencing anthocyanin transport and fruit color. This is similar to the effects observed with the Bronze-2 (Bz2) GST gene knockout in maize [64].
Among the SNPs associated with carotenoids, we identified variants in genes encoding functional proteins such as E3 ubiquitin-protein ligase SINAT2, histone–lysine N-methyltransferase, protein SCAR1 (AtSCAR1), sucrose synthase 6 (AtSUS6), DENN domain and WD repeat-containing protein SCD1, hexokinase-1, putative disease resistance protein RGA1 (RGA3-blb), ribosomal biogenesis protein LAS1L, and 3-oxoacyl-[acyl-carrier-protein] synthase (mitochondrial). Of particular interest, an SNP on chromosome 1 (69188981 bp) associated with carotenoid content was found within a gene encoding an E3 ubiquitin-protein ligase. The association between E3 ubiquitin-protein ligases and carotenoid content is consistent with the known regulatory roles of these enzymes in plants. A previous study showed that SINAT2, a SINA-type E3 ligase in Arabidopsis, interacts with the transcription factor AtRAP2.2 to regulate carotenogenesis [72]. This SNP may represent a similar regulatory mechanism, potentially affecting key factors in the carotenoid biosynthetic pathway. SINA E3 ligases are involved in various aspects of plant development, including auxin signaling and lateral root development [73], flowering time regulation [74,75], and brassinosteroid signal transduction [76]. In tomato, SlSINA2 regulates shoot growth and leaf chlorophyll content [77]. These diverse functions highlight the potential interconnectedness of carotenoid metabolism with broader regulatory networks controlling plant growth and development. Findings on E3 ubiquitin-protein ligases suggest potential targets for breeding programs or genetic engineering to modify carotenoid content in plants. Further functional characterization is needed to confirm the direct role of these proteins in carotenoid regulation. The identification of SNPs in genes encoding various functional proteins, especially the E3 ubiquitin-protein ligase, associated with carotenoid content adds to the growing evidence linking these enzymes to carotenoid metabolism [78,79]. These results offer new insights into the regulation of carotenoid biosynthesis and open avenues for crop improvement strategies, focusing on nutritional quality and plant stress responses.
The GWAS results in Capsicum revealed an SNP associated with total carotenoid content in a gene encoding histone–lysine N-methyltransferase, contributing to the growing evidence of epigenetic regulation in carotenoid biosynthesis across plant species. This finding aligns with recent research in citrus, which identified CgSDG40, a novel histone methyltransferase gene, as a positive regulator of carotenoid biosynthesis [80]. Histone methylation’s role in carotenoid regulation seems to be conserved across plant species, as initially reported in Arabidopsis [81]. The conservation of these regulatory mechanisms is supported by findings that the genomic arrangement of SDG40 and PSY1 is conserved in Citrus and other plants [80]. Our findings, along with recent studies in Citrus and Arabidopsis, enhance the understanding of epigenetic regulation of carotenoid biosynthesis across plant species. This may lead to more comprehensive models of carotenoid regulation and inform breeding strategies for improved carotenoid content in crops. This study identified a significantly associated SNP with α-carotene levels in pentatricopeptide repeat-containing proteins (PRPs). Carotenoids, including α-carotene, are key pigments responsible for yellow to red coloration in fruits and vegetables. This PRP-carotenoid association is consistent with the identification of a PRP-encoding gene linked to yellow flesh in watermelon [82]. These findings extend previous research by linking PRPs to α-carotene, suggesting that PRPs may regulate particular steps in carotenoid biosynthesis across species. This association implies that PRPs influence fruit pigmentation through modulation of the carotenoid pathway, supported by previous studies demonstrating how genetic variations affect carotenoid accumulation and fruit color [83]. Additionally, the analysis revealed several SNP markers with pleiotropic effects on carotenoid traits, specifically α-carotene, β-cryptoxanthin, and capsanthin levels (Table 4). We identified one SNP associated with both α-carotene and β-cryptoxanthin, and six SNPs associated with β-cryptoxanthin and capsanthin. These markers were primarily found in genes, with associated proteins including E3 ubiquitin-protein ligase SINAT2, stamen-specific protein FIL1, and DEAD-box ATP-dependent RNA helicase 8, among others. The pleiotropic nature of these SNPs indicates shared genetic control mechanisms for multiple carotenoid traits, potentially involving biosynthesis regulation or interactions between metabolic pathways. These findings offer valuable insights into the genetic architecture of carotenoid accumulation and may guide future breeding strategies for modifying carotenoid profiles in plants.

4. Materials and Methods

4.1. Chemicals and Plant Material

For this study, high-purity reagents, extraction solvents, and carotenoid standards were employed. Chemical compounds were obtained from Sigma-Aldrich, including carotenoid reference materials such as zeaxanthin, β-carotene, capsanthin, violaxanthin, α-carotene, antheraxanthin, β-cryptoxanthin, and capsorubin. Additional reagents included ammonium acetate, ascorbic acid, dichloromethane, methanol, methyl tert-butyl ether, potassium hydroxide, and sodium chloride.
The study utilized 306 pepper accessions obtained from the gene bank of the National Agrobiodiversity Center (NAC) under the Rural Development Administration (RDA), Jeonju, Republic of Korea. These accessions represent five species: C. annuum (198 accessions), C. baccatum (43), C. chinense (43), C. frutescens (21), and C. chacoense (1). The plants were grown in the RDA research field (35°49′52.7″ N, 127°3′43.9″ E) in a greenhouse from March to October (2020), using standard agronomic practices according to RDA cultivation methods. From March to April, seedlings were prepared, and the temperature was maintained in the range 15–25 °C. In May, the seedlings were transplanted to the soil and cultivated until late October. During this period, the temperature inside the greenhouse was maintained in the range 15–40 °C, and irrigation was performed once or twice a week depending on plant conditions. Each accession consisted of ten pepper plants. Additional information regarding the accession numbers and the origins of the 306 pepper accessions is available in Supplementary Table S1.

4.2. Pepper Fruit Color Assessment and Analysis of Carotenoids

Visual assessment of pepper fruit color was performed at maturity on ten plants per accession. Due to variability in maturity time among accessions, regular assessments were carried out to monitor and determine the optimum maturity stage for each plant. The color of each fruit was recorded using predefined categories such as yellow, orange, red, dark purple, brown, and other, based on a standard color chart (QPcard) to ensure consistent evaluation. Examples of different fruit colors observed in pepper accessions are presented in Supplementary Figure S3.
This research utilized freeze-dried, powdered pepper samples for carotenoid analysis. The extraction, separation, and quantification of carotenoids were performed using a modified version of the protocol described by Kim et al. [84]. For extraction, 0.05 g of finely sieved pepper powder was combined with 3 mL of ethanol containing 0.1% (w/v) ascorbic acid. After briefly vortexing, the mixture was heated in an 85 °C water bath for 5 min. Saponification was then carried out for 10 min at 85 °C using 120 μL of 80% (w/v) potassium hydroxide. Following ice cooling, 1.5 mL of cold deionized water was added. The extraction was repeated twice with 1.5 mL of hexane. The extracts were centrifuged at 12,009× g, and the supernatant was filtered through a 0.2 μm syringe filter for analysis.
Carotenoid separation was achieved using an Agilent 1260/90 Infinity II High-Performance Liquid Chromatography (HPLC; Santa Clara, CA, USA) system equipped with a C30 YMC column (250 × 4.6 mm, 3 μm; Waters Corporation, Milford, MA, USA). Detection was performed at 450 nm. The mobile phase consisted of Solvent A (methanol:water, 92:8 v/v, with 10 mM ammonium acetate) and Solvent B (pure methyl tert-butyl ether). The gradient elution profile was set as follows: 0 min (83% A, 17% B), 23 min (70% A, 30% B), 29 min (59% A, 41% B), 35 min (30% A, 70% B), 40 min (30% A, 70% B), 44 min (83% A, 17% B), and 55 min (83% A, 17% B), with a flow rate of 1 mL/min. Quantification was performed using calibration curves constructed from the peak area ratios of four different concentrations of carotenoid standards.

4.3. Genomic DNA (gDNA) Extraction

Leaf samples from 306 pepper accessions were used to extract genomic DNA, employing a modified CTAB protocol based on the method outlined by Lee et al. [85]. The extracted DNA was initially diluted to 50 ng/μL with distilled water. Quantification was performed using the Quant-iT PicoGreen dsDNA Assay Kit in conjunction with a Synergy HTX Multi-Mode Reader. Subsequently, the DNA concentration was adjusted to a standard 12.5 ng/μL. The quantified DNA samples were then subjected to enzymatic digestion using ApeKI (New England Biolabs, Ipswich, MA, USA) for a duration of 3 h at 75 °C.

4.4. Library Preparation for Genotyping-by-Sequencing (GBS)

GBS libraries were prepared according to the methods described in previous studies [86,87], with minor modifications. After restriction digestion, the DNA fragments were ligated with adapters, including barcoded adapters for sample identification and common adapters, using T4 DNA ligase (New England Biolabs) at 22 °C for 2 h. The ligase was then inactivated by heating at 65 °C for 20 min. The adapter-ligated samples were pooled and purified using the NucleoSpin® Gel and PCR Clean-up Kit (Macherey-Nagel GmbH & Co. KG, Düren, Nordrhein-Westfalen, Germany). The pooled ligation products were amplified by multiplexing PCR in a 50 μL reaction volume using AccuPower Pfu PCR Premix (Bioneer) and the provided primers. The fragment size distribution of the PCR products was assessed using the BioAnalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). The GBS libraries were then sequenced on the Illumina NextSeq500 platform (Illumina, San Diego, CA, USA), generating 150 bp single-end reads.

4.5. SNP Calling, Filtering, and Sequence Preprocessing

The generated read sequences underwent preprocessing using Stacks [88] for demultiplexing, FastQC [89] for per-base read quality assessment, and Cutadapt [90] for adapter sequence removal. The reads were then aligned to the CM334 reference genome (C. annuum chromosome v1.6) using Bowtie2. To facilitate data integration into the GATK pipeline, read groups were added using Picard tools. Localized read realignments were performed using GATK’s ‘IndelRealigner’ and ‘RealignerTargetCreator’ arguments to correct misalignments caused by indels.
Initial variant calling was performed using GATK’s “HaplotypeCaller” and “SelectVariants” parameters. Variants were filtered using GATK’s “FilterVariant” module based on quality score (QUAL < 30), quality depth (QD < 5), and Fisher score (FS > 200). Further filtering was performed using vcftools (v. 0.1.15) to impose restrictions on maximum missing rate (--max-missing 0.95), minimum minor allele frequency (--maf 0.05), allele range (--min-alleles 2, --max-alleles 2), and average read depth (--min-meanDP 5). These steps aimed to identify high-quality SNPs for subsequent analysis.

4.6. Genome-Wide Association Study (GWAS)

Genome-wide association study (GWAS) was performed on 306 pepper individuals using 42,322 SNPs, employing TASSEL v.5.0 standalone software [91]. A mixed linear model (MLM) incorporating both population structure and kinship (PCA+K) was utilized. The kinship (K) matrix was derived from an identical-by-state (IBS) matrix, reflecting familial relatedness between lines. A significance threshold of –log10(p) > 6.0 was established after Bonferroni correction.
To identify potential candidate genes associated with significant SNPs, we examined a 200 kb region (100 kb on each side) surrounding each SNP. The basic local alignment search tool (BLAST) was used to search the C. annuum genome in both the Ensemble Plants genome database (https://plants.ensembl.org/Capsicum_annuum/Tools/Blast accessed on 7 May 2024) and the NCBI database. Flanking sequences of the significant SNPs were extracted from the C. annuum genome database and analyzed to identify genes or gene regions with alignment similarity.

4.7. Statistical Analysis

Data summary and descriptive statistics for the carotenoids were conducted using Microsoft Excel 2016 (Microsoft Corporation, Redmond, WA, USA). Correlation analysis (using the ‘pheatmap’ package) and principal components analysis were performed with R software (version 4.2.1).

5. Conclusions

This study of 306 pepper accessions revealed substantial diversity in fruit color and carotenoid profiles across Capsicum species. Pepper accessions with red fruits were predominant, with capsanthin identified as the primary carotenoid. Correlation and principal component analyses uncovered complex relationships among carotenoids. GWAS identified 91 significant SNPs associated with fruit color and carotenoid content, implicating several candidate genes involved in diverse cellular functions. Notably, seven SNPs exhibited pleiotropic effects on multiple carotenoid traits. Among the carotenoid-associated SNPs, some were located in genes encoding functional proteins such as E3 ubiquitin-protein ligases and histone–lysine N-methyltransferase, which have recently been identified as novel contributors to carotenoid biosynthesis in Citrus. These findings provide valuable insights into the genetic basis of fruit color and carotenoid accumulation in peppers, offering a foundation for future breeding programs aimed at enhancing both the nutritional quality and visual appeal of Capsicum varieties.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants13182562/s1, Figure S1. Distribution of SNPs across the chromosomes of Capsicum from 306 accessions. This heatmap visualization represents SNP density, with data aggregated into 1 Mb windows. The color intensity indicates the local SNP concentration, highlighting their distribution patterns along the 12 pepper chromosomes; Figure S2. Quantile–Quantile (Q-Q) plot represent the association between fruit color and carotenoids. a: fruit color, b: α-carotene, c: antheraxanthin, d: β-carotene, e: β-cryptoxanthin, f: capsanthin, g: capsorubin, h: violaxanthin, i: zeaxanthin, and j: total carotenoids. X-axis represents the expected p-value (−log(p-value)) and Y-axis represents the observed p-value (−log(p-value)); Figure S3. Examples of different fruit colors observed in pepper accessions from the core collections; Table S1. List of significantly associated SNPs to carotenoids; Table S2. Accessions number, species name, fruit colors, and carotenoid contents of 306 pepper genetic resources.

Author Contributions

Conceptualization, N.R. and M.H.; methodology, H.-C.K., J.Y. and H.O.; data curation, N.R. and Y.-W.N.; data analysis, M.H.; writing—original draft preparation, M.H.; writing—review and editing, M.H. and N.R. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Research Program for Agricultural Science and Technology Development (Project No. PJ016045) of the National Institute of Agricultural Sciences, Rural Development Administration (Jeonju, Republic of Korea).

Data Availability Statement

Relevant data are included in both the manuscript and the Supplementary Files.

Conflicts of Interest

The authors declare no conflicts of interest.

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Plants 13 02562 g001
Figure 1. The distribution of 306 pepper accessions based on fruit color at maturity.
Figure 1. The distribution of 306 pepper accessions based on fruit color at maturity.
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Plants 13 02562 g002
Figure 2. The average carotenoid contents of pepper accessions based on fruit color.
Figure 2. The average carotenoid contents of pepper accessions based on fruit color.
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Plants 13 02562 g003
Figure 3. The average carotenoid contents of pepper accessions based on species. These accessions represent five species: C. annuum (198), C. baccatum (43), C. chinense (43), and C. frutescens (21).
Figure 3. The average carotenoid contents of pepper accessions based on species. These accessions represent five species: C. annuum (198), C. baccatum (43), C. chinense (43), and C. frutescens (21).
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Plants 13 02562 g004
Figure 4. Heatmap depicting carotenoid correlations in a diverse set of 306 pepper accessions. This visualization presents Pearson correlation coefficients, with a color scale on the right indicating correlation strength and direction. The analysis includes the following carotenoids: violaxanthin, lutein, antheraxanthin, capsorubin, capsanthin, zeaxanthin, β-cryptoxanthin, α-carotene, β-carotene and total carotenoid content. Significance is represented by *, **, and *** for p-values of less than 0.05, 0.01, and 0.001, respectively.
Figure 4. Heatmap depicting carotenoid correlations in a diverse set of 306 pepper accessions. This visualization presents Pearson correlation coefficients, with a color scale on the right indicating correlation strength and direction. The analysis includes the following carotenoids: violaxanthin, lutein, antheraxanthin, capsorubin, capsanthin, zeaxanthin, β-cryptoxanthin, α-carotene, β-carotene and total carotenoid content. Significance is represented by *, **, and *** for p-values of less than 0.05, 0.01, and 0.001, respectively.
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Plants 13 02562 g005
Figure 5. PCA plot based on the carotenoid data of 306 pepper accessions: (a)—variables and (b)—individuals; each dot represents a single accession. The variables are a—α-carotene, b—antheraxanthin, c—β-carotene, d—β-cryptoxanthin, e—capsanthin, f—capsorubin, g—lutein, h—violaxanthin, i—zeaxanthin, and j—total carotenoid.
Figure 5. PCA plot based on the carotenoid data of 306 pepper accessions: (a)—variables and (b)—individuals; each dot represents a single accession. The variables are a—α-carotene, b—antheraxanthin, c—β-carotene, d—β-cryptoxanthin, e—capsanthin, f—capsorubin, g—lutein, h—violaxanthin, i—zeaxanthin, and j—total carotenoid.
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Plants 13 02562 g006
Figure 6. GWAS results for fruit color and carotenoid traits presented as Manhattan plots. The figure comprises plots for fruit color (a) and carotenoids: (b–j) α-carotene, antheraxanthin, β-carotene, β-cryptoxanthin, capsanthin, capsorubin, violaxanthin, zeaxanthin, and total carotenoids. In each plot, SNPs are represented as individual points, with chromosomes distinctly colored and labeled on the x-axis. The y-axis represents association strength as −log10(p). A grey dashed line at −log10(p) = 6.0 denotes the significance threshold (p < 0.05).
Figure 6. GWAS results for fruit color and carotenoid traits presented as Manhattan plots. The figure comprises plots for fruit color (a) and carotenoids: (b–j) α-carotene, antheraxanthin, β-carotene, β-cryptoxanthin, capsanthin, capsorubin, violaxanthin, zeaxanthin, and total carotenoids. In each plot, SNPs are represented as individual points, with chromosomes distinctly colored and labeled on the x-axis. The y-axis represents association strength as −log10(p). A grey dashed line at −log10(p) = 6.0 denotes the significance threshold (p < 0.05).
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Table 1. Descriptive statistics summary of carotenoid contents (μg/g) of 306 pepper accessions.
Table 1. Descriptive statistics summary of carotenoid contents (μg/g) of 306 pepper accessions.
CarotenoidMeanSESDMinimumMaximumNo. of Accessions with Measurable Pigment
α-carotene3.490.427.36086.94294
Antheraxanthin1.710.295.04053.5666
β-carotene36.622.2238.880272.15304
β-cryptoxanthin63.73.6664.060476.23296
Capsanthin239.1211.79206.2201348.53291
Capsorubin25.81.7530.570265.99289
Lutein1.630.5810.10113.9212
Violaxanthin3.761.119.170182.58106
Zeaxanthin63.253.3658.760352.25284
Total Carotenoid439.0619.75345.527.092566.67306
Table 2. The number of significantly associated SNPs with fruit color and carotenoids across chromosomes.
Table 2. The number of significantly associated SNPs with fruit color and carotenoids across chromosomes.
ChromosomeGenicIntergenicNumber of SNPs
1268
2213
3426
4246
56410
612113
77613
8516
9459
10202
11213
1210212
Total583391
Table 3. Key SNPs showing significant associations with fruit color in a diverse pepper (Capsicum spp.) germplasm collection.
Table 3. Key SNPs showing significant associations with fruit color in a diverse pepper (Capsicum spp.) germplasm collection.
TraitChr.Pos.−log (p-Value)Ref.AltSNP TypeProteinMinor AlleleMajor Allele
Fruit color at
mature stage		21670794976.66TCGenicRING-type domain-containing proteinCT
31375612216.00GTIntergenicIntergenicTG
31375611566.04AGIntergenicIntergenicGA
62008924577.20ATGenicPentatricopeptide repeat-containing proteinTA
6257891776.64GAGenicPITH domain-containing proteinAG
62006233956.03CTIntergenicIntergenicTC
72502124196.13GAIntergenicIntergenicAG
9461775126.48TAGenicTropinone reductase 2AT
9413915686.18TCGenicBeta carbonic anhydrase 5, chloroplasticCT
9376194226.02CTIntergenicIntergenicTC
9512461076.04CTGenicPutative glutathione S-transferaseTC
122433162986.58TGGenicMitochondrial proton/calcium exchanger proteinGT
122433163226.58TGGenicMitochondrial proton/calcium exchanger proteinGT
122433163356.58GAGenicMitochondrial proton/calcium exchanger proteinAG
12364100866.28ACGenicGamete expressed protein 1CA
Table 4. List of SNPs (genic) with strong associations to carotenoid traits in a diverse pepper collection.
Table 4. List of SNPs (genic) with strong associations to carotenoid traits in a diverse pepper collection.
TraitsChr.Pos.−log (p-Value)Ref.AltSNP TypeProtein Feature
α-carotene1691889816.32AGGenicE3 ubiquitin-protein ligase SINAT2
21397695886.64CTGenicProtein SCAR1 (AtSCAR1)
32576915637.83CTGenicSucrose synthase 6 (AtSUS6)
32787594588.02TGGenicDENN domain and WD repeat-containing protein SCD1
328240720810.25GAGenicHexokinase-1
514316937.96CAGenicPutative disease resistance protein RGA1
52127957856.16GAGenicRibosomal biogenesis protein LAS1L
677840157.98AGGenic3-oxoacyl-[acyl-carrier-protein] synthase, mitochondrial
61520070177.93GAGenicMolybdenum cofactor sulfurase (MCS)
62369072479.77ATGenicU-box domain-containing protein 13
71939798546.07AGGenicThymidylate kinase (AtTMPK)
8905135547.77CTGenicMitochondrial carrier protein CoAc1
81395076739.86TCGenicRibosome biogenesis protein bms1
91510613099.84GAGenicProtein SPA1-RELATED 3
102328605899.92CTGenicDisease resistance protein At4g27190,2
112536145329.84CAGenicPutative disease resistance RPP13-like protein 1
12376317099.79ATGenicPentatricopeptide repeat-containing protein, chloroplastic
Antheraxanthin117906087.04GAGenicTranscription termination factor MTEF18, mitochondrial
1136873466.76ATGenictRNA N(3)-methylcytidine methyltransferase
11058236836.02GAGenic1:Probable methyltransferase PMT2
410328365.97CTGenicPhosphatidylinositol 4-kinase alpha 1
62354012446.17GAGenicProtein disulfide isomerase-like 1–4
62354013096.16GAGenicProtein disulfide isomerase-like 1–4
7157060810.06CGGenicCA.PGAv.1.6.scaffold1357.17
7151800436.72GAGenicChaperone protein DnaJ 2
72159639307.84GTGenicProbable NADH dehydrogenase [ubiquinone]
81393069966.65CAGenicPeptide-N(4)-(N-acetyl-beta-glucosaminyl)asparagine amidase
109809497.44GAGenicSeptin and tuftelin-interacting protein 1 homolog 1
112518128316.06GAGenicBeta-glucosidase BoGH3B
122427405108.09GTGenicDisease resistance protein Roq1
122427405118.08CTGenicDisease resistance protein Roq1
β-carotene61259110506.61AGGenicProbably inactive leucine-rich repeat receptor-like protein kinase
72109038296.00GAGenicProbable beta-1,3-galactosyltransferase 2
β-cryptoxanthin1691889816.94AGGenicE3 ubiquitin-protein ligase SINAT2
32603329957.65TCGenicChaperone protein dnaJ 49
52281546578.18CAGenicProtein-tyrosine-phosphatase MKP1
6924427897.99CTGenicStamen-specific protein FIL1
7634907177.81AGGenicRop guanine nucleotide exchange factor 14
81247206277.89CTGenicDEAD-box ATP-dependent RNA helicase 8
121601787867.87GAGenicProtein MHF1 homolog (AtMHF1)
Capsanthin5178467486.56TCGenicLignin-forming anionic peroxidase
5321921126.08GCGenicTobamovirus multiplication protein 3
52281546578.01CAGenicProtein-tyrosine-phosphatase MKP1
6924427896.10CTGenicStamen-specific protein FIL1
7634907176.63AGGenicRop guanine nucleotide exchange factor 14
81247206276.10CTGenicDEAD-box ATP-dependent RNA helicase 8
121601787866.24GAGenicProtein MHF1 homolog
Capsorubin12538576465.99CTGenicAlanine--tRNA ligase
423418706.15CAGenicReceptor-like protein 19
Zeaxanthin12175937256.11CTGenicPleiotropic drug resistance protein 2
Total Carotenoid6974917746.13GCGenicAcid phosphatase 1
61841168346.10CTGenicHistone–lysine N-methyltransferase
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Ro, N.; Oh, H.; Ko, H.-C.; Yi, J.; Na, Y.-W.; Haile, M. Genome-Wide Analysis of Fruit Color and Carotenoid Content in Capsicum Core Collection. Plants 2024, 13, 2562. https://doi.org/10.3390/plants13182562

AMA Style

Ro N, Oh H, Ko H-C, Yi J, Na Y-W, Haile M. Genome-Wide Analysis of Fruit Color and Carotenoid Content in Capsicum Core Collection. Plants. 2024; 13(18):2562. https://doi.org/10.3390/plants13182562

Chicago/Turabian Style

Ro, Nayoung, Hyeonseok Oh, Ho-Cheol Ko, Jungyoon Yi, Young-Wang Na, and Mesfin Haile. 2024. "Genome-Wide Analysis of Fruit Color and Carotenoid Content in Capsicum Core Collection" Plants 13, no. 18: 2562. https://doi.org/10.3390/plants13182562

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