Introduction

Carrot (Daucus carota L.), a major source of provitamin A carotenes in the human diet, is consumed worldwide1. Carrots accumulate abundant carotenoids in their taproots, and these carotenoids (which are responsible for the orange pigmentation in the carrot roots) are thought to provide health benefits2. A variety of colors has been observed in carrot taproots, including orange, white, yellow, red, and purple. Quantitative trait loci (QTL) analyses and association studies for carrots' root color and carotenoid contents have been performed in several populations, and important and useful QTLs have been reported3,4,5,6. These studies used populations derived from crosses between accessions showing clearly different root colors such as orange and white3,4,5 and orange and dark orange4, and other studies used inter-crossed populations derived from white, yellow, red, and orange carrots6.

Carotenoid biosynthesis is well established, and a highly conserved carotenoid biosynthesis pathway has been characterized in many plant species (Fig. 1)7,8,9. In carrot, several carotenoid biosynthetic genes have been mapped3, and the released carrot whole-genome sequences showed orthologous and homologous genes involved in the carotenoid biosynthesis pathway10,11. Several genes involved in carotenoid biosynthesis and accumulation in carrot have also been identified. An ortholog of carotene hydroxylase CYP97A3 in the carotenoid biosynthesis pathway has been identified in carrot; it controls the α-carotene, total carotenoid contents, and the α/β carotene ratio12. A candidate gene association study of the carotenoid biosynthesis pathway revealed associations between the total carotenoid and β-carotene contents and the genes zeaxanthin epoxidase (ZEP), phytoene desaturase (PDS), and carotenoid isomerase (CRTISO), between the α-carotene content and the genes CRTISO and plastid terminal oxidase (PTOX), and between color components and the gene ZEP6.

Figure 1
figure 1

Carotenoid biosynthesis pathways. The carotenoid biosynthesis pathway is shown in black, with carotenoid biosynthesis genes indicated in blue. Figure compiled and summarized from Stanley et al.8 and Al-Babili et al.9. PSY, phytoene synthase; PDS, phytoene desaturase; Z-ISO, ζ-carotene isomerase; ZDS, ζ-carotene desaturase; CRTISO, carotene isomerase; LCYE, lycopene ε-cyclase; LCYB, lycopene β-cyclase; CYP97A3, cytochrome P450-type β-hydroxylase; CYP97C1, cytochrome P450-type ε-hydroxylase; CYC-B, chromoplast-specific lycopene β-cyclase; BCH, β-carotene hydroxylase; ZEP, zeaxanthin epoxidase; NSY, neoxanthin synthase; CCS, capsanthin-capsorubin synthase.

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It was also reported that not only genes in the carotenoid biosynthesis pathway but also genes that have other functions considerably affect carotenoid contents. Y and Y2 loci account for most of the color differences of orange, yellow, and white carrot roots13. The Y gene has been identified, and this gene has been hypothesized to regulate photosystem development and functional processes, including photomorphogenesis and root de-etiolation10. The Y2 locus has been mapped to an approx. 650-kb genomic region; in addition, no annotated gene involved in the carotenoid biosynthesis pathway was located within the candidate region14. An Orange (Or) gene, which was first identified in cauliflower and accounted for an abnormally elevated β-carotene accumulation15, was identified in carrot and is associated with the presence of carotenoid in carrot16. However, the genes, polymorphisms, and QTLs involved in carotenoid biosynthesis and the carotenoid accumulation that cause quantitative differences in root color and carotenoids are not fully understood, especially within the orange carrots.

In Japan, consumers prefer a bright orange root color for carrots, and a cultivar showing uniform root colors is popular. There are accessions showing quantitative color differences in bright orange roots, and breeders in Japan have selected the best 'bright orange' and uniform color among the accessions that have bright orange roots. DNA markers that can be used to distinguish quantitative differences within bright orange color have thus been sought in Japanese carrot breeding. Toward this goal, there has been no study using populations derived from a cross between orange root carrots with quantitative color differences, but the recent release of whole genome sequences of carrot has made it easier to analyze whole-genome constitutions with high marker density, even in the populations derived from genetically close orange carrots10,11.

In the present study, we developed two F2 populations that have a common parent. Both populations were derived from crosses between orange-root parents. We performed an association and QTL analyses to detect QTLs that cause quantitative but important differences in the root color and carotenoid contents within carrots with orange root color.

Methods

Plant materials

We developed two F2 populations (A and B) using orange-colored carrot plants bred by a Japanese seed company, Fujii Seed (Osaka, Japan). Population A was derived from a cross between Fs001 and Fs002, and population B was derived from a cross between Fs002 and Fs003 (Fig. 2). Fs002 was the pollen parent for F2 population A and the seed parent for F2 population B. Plants of F2 populations A (n = 146) and B (n = 136) were cultivated from mid-February to early June 2018 in a natural field at Narashino, Chiba, Japan, and used for DNA extraction and the visual evaluation of root colors. Roots of population A were also used for the quantification of carotenoid content by high-performance liquid chromatography (HPLC) and the measurement of color components.

Figure 2
figure 2

Lineage images of the plant materials, F2 populations A and B, and breeding line C. Fs002 was used as a common breeding material.

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To examine a developed DNA marker on Or gene, we also used breeding line C, which was bred by Fujii Seed. This line was developed by using Fs002 as one of the breeding materials (Fig. 2). Breeding line C was cultivated from the end of March to early July 2017 in a natural field at Oirase, Aomori, Japan, and 40 plants were used for DNA extraction and the visual evaluation of root colors.

Experimental research and field studies on plant materials comply with relevant institutional, national, and international guidelines and legislation.

Visual evaluation of root colors and evaluation of color components

The visual evaluation of root colors was performed by two experienced breeders at Fujii Seed. The root colors were visually evaluated to ten grades of orange darkness in F2 population A, and to seven grades in F2 population B, and to three grades in breeding line C. In the F2 population A, color components (L*, a* and b*) were measured with a spectrocolorimeter (model CM2600d, Minolta, Tokyo) equipped with a 5-mm measuring area. The color components L*, a* and b* are components of CIELAB (also known as or CIE L*a*b*) color space. The color component L* represents perceptual lightness and defines black as 0 and white as 100. The color component a* represents the green–red opponent colors, with negative values toward green and positive values toward red. The color component b* represents the blue-yellow opponents, with negative values toward blue and positive toward yellow. The surface of the middle part of washed carrot root was measured three times, and the average values were used for phenotypic data.

Quantification of carotenoid contents (α-carotene, β-carotene, and lutein) by HPLC

Carrot root surface, i.e., approx. 1–2 mm of epidermis and outer phloem in the middle of roots was cut and collected. The collected samples were immediately frozen in liquid nitrogen and stored at − 80 °C. Root epidermis and outer phloem was used for HPLC because the visual and color component evaluations were performed on the carrot root surface. The extraction for HPLC was performed as described6 with a scale-down and some modifications. Frozen samples were crushed into a powdery status with a tube mill control (S001, IKA, Staufen, Germany). Extraction was done on approx. 50 mg (50 mg ± 5%) of crushed frozen material to which 50 µL of b-apo-8'-carotenal at 5 µg/mL was first added as an internal standard. Samples were mixed with 600 µL of MgCO3 0.57%, 3,5-di-tert-butyl-4-hydroxytoluene (BHT) 0.1% in methanol, then vortexed, and mixed with 600 µL of 0.1% BHT-containing chloroform. After 10 times of vertical mixing and incubation for 15 min in darkness at 4 °C, 600 µL of ultrapure water was added, and samples were centrifuged at 236 g for 10 min. Next, 400 µL from the lower layer was concentrated under vacuum evaporation, and the dry extract was dissolved in 50 µL of acetone containing 0.1% BHT. Samples were kept at 4 °C and protected from direct light during the entire procedure.

The carotenoid quantification was done on an Ultimate 3000 HPLC system coupled with a diode array detector (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer's instruction with slight modifications. Carotenoids were separated on an Acclaim C30 column (150 × 2.1 mm, 3 µm, Thermo Fisher Scientific). The mobile phases were acetonitrile as eluent A, methanol/acetic ether (1:1, v/v) as eluent B, and 10 mM formic acid (pH 3.0) as eluent C. The elution program was as follows: the proportions of solvent A, B and C were 85% A, 14.5% B, and 0.5% C at 0–2 min; 85%–44.5% A, 14.5%–55% B, and 0.5% C at 2–7 min; 44.5% A, 55% B, and 0.5% C at 7–21 min; and returned to the initial conditions (85% A, 14.5% B, and 0.5% C) at 21.1–28.5 min. The flow rate was 0.4 mL/min. The injection volume of the filtered sample by a 0.22-µm PTFE membrane filter was 3.9 µL. Analytes were detected by a photodiode array detector at 450 nm. The data were analyzed using Chromeleon 7 software (Thermo Fisher Scientific) based on internal calibration using b-apo-8'-carotenal and the extraction yield.

Double-digest restriction site-associated DNA sequencing (ddRAD-seq)

Total genomic DNA was extracted from young leaves of carrot plants with the DNeasy Plant Mini Kit (Qiagen, Hilden, Germany). A double-digest restriction site-associated DNA sequencing (ddRAD-seq) analysis was performed as described17 with the restriction enzymes PstI and MspI. The ddRAD-seq libraries were constructed and sequenced on a HiSeq 4000 platform (Illumina, San Diego, CA) in paired-end 101-nucleiotide (nt) mode as described17. Primary data processing such as deleting low-quality bases and trimming adapters, mapping onto reference genome, and filtering single-nucleotide polymorphisms (SNPs) to obtain high-confidence SNPs were performed as described with some modifications18. In brief, low-quality sequences were removed and adapters were trimmed using PRINSEQ (ver. 0.20.4)19 and fastx_clipper in the FASTX-Toolkit (ver. 0.0.13) (http://hannonlab.cshl.edu/fastx_toolkit). The filtered reads were mapped onto carrot genome Daucus carota v2.010 with Bowtie 2 (ver. 2.1.0; parameters: –minins 100 –no-mixed)20. The resultant sequence alignment/map format (SAM) files were converted to binary sequence alignment/map format (BAM) files and subjected to SNP calling using the mpileup option of SAMtools (ver. 0.1.19; parameters: default)21 to yield a variant call format (VCF) file including SNP information. The VCF files were filtered with VCFtools (ver. 0.1.14)22. The parameters for VCFtools were as follows: –maf 0.05 –max-alleles 2 –min-alleles 2 –minDP 5 –minQ 999 –maxmissing 0.95 –remove-indels.

QTL detection by association and QTL analyses

For the association analysis, we detected QTLs based on a general linear model (GLM) by using trait analysis by association, evolution, and linkage (TASSEL) ver. 5.2.4023. The thresholds for the association were set as 1.6 × 10−5 (= 0.05/3159) and 2.6 × 10−5 (= 0.05/1901) at a significance level of 5% after Bonferroni correction in F2 populations A and B, respectively.

Linkage maps for the QTL analysis were constructed using Lep-MAP324 from filtered VCF files. A filtering module was used for the marker quality filtering set as dataTolerance = 0.001 to exclude segregation distorted markers. The Separate Chromosomes module was set as lodLimit = 8 for F2 population A and lodLimid = 20 for F2 population B following Join Singles and Order Markers modules set as informativeMask = 123 and sexAveraged = 1. QTL analyses were performed using composite interval mapping implemented by the Zmapqtl program (model 6) provided in ver. 2.5 of Windows QTL Cartographer25. Genome-wide threshold values (α = 0.05) were used to detect putative QTLs based on the results of 1,000 permutations.

Sanger sequencing of candidate genes

For the comparison of the genomic sequences of possible candidate genes between parental plants in F2 populations A and B, we performed Sanger sequencing from the start codon to the stop codon on the genes. The primers used in the Sanger sequencing are listed in Supplementary Table S1.

SNP genotyping with KASP marker

KASP marker, which genotypes an SNP on Or gene in this study, was developed and performed according to the manufacturer's instructions (Biosearch Technologies, Novato, CA).

Phylogenetic analysis

The sequences of LCYE, LCYB, CYC-B, NSY, and CCS in several reported plant species such as Solanum lycopersicum, Carica papaya, Citrus sinensis, Capsicum annuum, and Lillium lancifolium26,27,28,29, Arabidopsis7, and carrot30 were obtained from the public databases NCBI (http://www.ncbi.nlm.nih.gov) and Phytozome (https://phytozome.jgi.doe.gov/pz/portal.html#). We used CLUSTALW31 to align the amino acid sequences and constructed the phylogenetic tree by using the neighbor-joining method32 provided by MEGA X33.

Results

Association analysis for the visual evaluation of root color and evaluations of color components and carotene contents in roots of F2 populations A and B

F2 populations A and B both showed a normal distribution in all root color evaluations (Suppl. Fig. S1), suggesting polygenic inheritance in carrot root color. The ddRAD-seq analysis detected 3,159 and 1,901 high-confidence SNPs in F2 populations A and B, respectively. The associations were investigated using these genotypic data and values from the visual evaluation and evaluations of the color components and carotene contents in the carrot roots. In F2 population A, significant associations were detected for the visual evaluation of root color (Fig. 3a); color components a* (Fig. 3c) and b* (Fig. 3d); α-carotene (Fig. 3e), β-carotene (Fig. 3f), and lutein contents (Fig. 3g); and the β/α-carotene ratio (Fig. 3h) in root (Table 1). No significant associations were detected for color component L* (Fig. 3b).

Figure 3
figure 3

Manhattan plots for carrot taproot color in F2 population A. Plots for the visual evaluation (a), L* (b), a* (c), b* (d), α-carotene content (e), β-carotene content (f), lutein content (g), and the β/α-carotene ratio (h). Horizonal line indicates the Bonferroni correction (0.05).

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Table 1 Significant associations for carrot root color identified by association analysis in F2 population A and B.
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The associations for visual evaluation, color components a* and b*, and α- and β-carotene contents on chromosome 1 were detected at close physical positions, and the highest associations were detected at a physical position around 31 Mb (Fig. 3, Table 1), suggesting that these associations are caused by an identical QTL. The physical positions of the associations for the α- and β-carotene contents on chromosome 3 were close, and the highest associations were detected at a physical position around 6 Mb (Fig. 3, Table 1). An association detected in population B for visual color evaluation on chromosome 3 showed the highest association at physical position 5.4 Mb, and this physical position was similar to those of the associations detected in population A for α- and β-carotene contents (Figs. 3, 4, Table 1). These results suggest that the associations would be caused by an identical QTL. Interestingly, the association detected on chromosome 5 (showing the highest association for visual evaluation in F2 population A) was not detected in any other evaluations (Fig. 3, Table 1).

Figure 4
figure 4

Manhattan plots for carrot taproot color in F2 population B. Plots for the visual evaluation of carrot root color. Horizonal line: Bonferroni correction (0.05).

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QTL analysis for the visual evaluation of root color and evaluations of color components and carotene contents in roots of F2 populations A and B

To examine the validity of QTLs detected by the association analysis, we also performed a QTL analysis constructing linkage maps. Marker segregation distortion in the two F2 populations was examined by Chi-squared test against the expected 1:2:1 ratio. In populations A and B, 2,370 markers of a total of 3,159 markers and 1,442 markers of a total of 1,901 markers segregated at a 1:2:1 ratio (P < 0.01), respectively. We thus analyzed these two populations as F2 generations. With the use of Lep-MAP324, with segregation distorted markers excluded by the filtering module and non-grouped markers, 2,481 markers were mapped onto nine carrot chromosomes in F2 population A, and 1,586 markers were mapped onto seven carrot chromosomes and four linkage groups in F2 population B (Suppl. Tables S2–S4, Suppl. Figs. S2, S3).

The QTL analysis detected 31 QTLs for all traits examined in F2 population A (Table 2, Suppl. Fig. S4). Based on the physical position of the nearest marker, 11 QTLs were detected on the regions corresponding to the results of the association analysis (within 2 Mb) (Table 2). The QTL at a physical position around 31 Mb on chromosome 1 was detected for visual evaluation, color components a* and b*, and α- and β-carotene contents. This QTL was also detected by the association analysis for the same traits (Table 1, Fig. 3).

Table 2 QTLs for carrot taproot color in F2 population A and B detected by QTL analysis.
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Interestingly, an additive effect of Fs001 allele showed the opposite effect in a visual evaluation versus color components a* and b* and α- and β-carotene contents. The QTL at a physical position around 4.8 Mb on chromosome 3 was detected for α- and β-carotene contents, and this QTL was also detected by the association analysis. In the QTL analysis, a QTL for color component a* was also detected at a physical position that is similar to the QTL for α- and β-carotene contents on chromosome 3, and this QTL was not detected by the association analysis. A QTL for visual evaluation on chromosome 5, QTLs for lutein content on chromosome 5 and 6, and a QTL for the β/α-carotene ratio on chromosome 6 were also detected by the association analysis. A QTL detected at 6.7 Mb on chromosome 3 was detected for visual evaluation, color component L*, and lutein content. A QTL detected at 13.2 Mb on chromosome 7 was detected for color components a* and b*. Compared to the association analysis, the QTL analysis detected more minor QTLs.

In F2 population B, only one QTL for visual evaluation was detected at physical position 5.4 Mb on chromosome 3. This QTL was also detected by the association analysis. The physical position of the nearest marker of this QTL in the QTL analysis corresponded to the peak position in the associated analysis (Tables 1, 2, Fig. 4, Suppl. Fig. S5).

Correlations among visual evaluation, color components, and carotene contents in root of F2 population A

The Pearson correlation between each phenotype showed that three color components, i.e., L*, a* and b*, the α-carotene content, and the β-carotene content were highly correlated (Suppl. Table S5). The lutein content was slightly correlated with L*, a* and b* and highly correlated with the α-carotene content. As lutein is biosynthesized downstream of the α-carotene (Fig. 1), this high correlation of lutein and α-carotene is consistent with the biosynthesis pathway. The visual evaluation was not highly correlated with any other phenotypes.

Allelic effects of QTLs detected on chromosomes 1 and 3 for the α-carotene and β-carotene contents in F2 population A

We examined the allelic effects of the QTLs on chromosome 1 and 3 detected by the association and QTL analyses for the α- and β-carotene contents. At the median, the carrots with AA allele on the SNP showing the highest association for α-carotene (DCARV2_CHR1_30704558) had approx. 1.5-fold higher contents of α- and β-carotene than those with GG allele (Suppl. Fig. S6a,b). Similarly, at the median, the carrots with GG allele on the SNP showing the highest association for α-carotene (DCARV2_CHR3_5849853) had approx. 1.3-fold higher contents of α-carotene and approx. 1.2-fold higher contents of β-carotene compared to those with AA allele (Suppl. Fig. S6c,d). A clear genetic interaction such as epistasis was not observed between the QTLs detected on chromosomes 1 and 3 (Suppl. Fig. S7). Together with both QTLs detected on chromosomes 1 and 3, at the median, the carrots that had alleles showing higher carotenoid content in both QTLs also had approx. 2.6-fold higher α-carotene and approx. 1.8-fold higher β-carotene contents in the epidermis and outer phloem of carrot taproot compared to those with alleles showing lower carotenoid contents in both QTLs (Suppl. Fig. S7).

Considering of possible candidate gene for the QTL detected on chromosome 1 in F2 population A

The association and QTL analyses detected a QTL for visual evaluation, color components a* and b*, and α- and β-carotene contents at around 31 Mb on chromosome 1 (Tables 1, 2, Fig. 3, Suppl. Fig. S4). To explore the candidate gene of this QTL, we listed predicted genes within the confidence interval (2-LOD reduction on each side) of the physical position overlapping five traits (from 30,090,002 to 31,630,475 bp) in Supplemental Table S6. Within the confidence interval, 144 genes were predicted. Among them, DCAR_002576 encoding a photosystem II stability/assembly factor, chloroplast (HCF136), is located at 30.8 Mb. It has a function that is similar to that of a previously reported Y gene, which is involved in most of the carrot root color difference of white, yellow, and orange and has been hypothesized to regulate photosystem development and functional processes10. The genes encoding a transcription factor and unknown function were also located.

Considering a possible candidate gene for the QTL detected on chromosome 3 and the sequence comparison between parents in F2 populations A and B

By the association and QTL analyses, the QTL was detected around the physical position at 5–6 Mb on chromosome 3 for α-carotene and β-carotene contents in F2 population A (Fig. 3, Suppl. Fig. S4, Tables 1, 2). Both analyses detected the QTL for visual evaluation in F2 population B at 5.4 Mb on chromosome 3 (Fig. 4, Suppl. Fig. S5, Tables 1, 2). Within this region, the reported Or gene (DCAR_009172), which affects carotenoid contents in carrot16, is located at 5.2 Mb. To examine the involvement of Or, we performed Sanger sequencing of Or in the parents of populations A and B. The Sanger sequencing detected a T/G SNP at the fourth codon counting from the 3’ end; it causes a non-synonymous-amino acid substitution. The SNP was detected between both parents of F2 populations A and B (Fig. 5a). A thymine which was identical to that in the carrot reference genome10 in Fs001 and Fs003 was changed to guanine in Fs002, which resulted in a change from Tyr309 in the Fs001 and Fs003 to aspartic acid in the Fs002. No other SNPs causing non-synonymous amino acid substitutions were detected on Or between both parents of F2 populations A and B.

Figure 5
figure 5

The SNP on Or and the examination of its effect on carrot root color in breeding line C. (a) The SNP detected on Or between parental plants in F2 populations A and B. The SNP causes an amino acid substitution. The upper sequence is identical to the reference sequence of Iorizzo et al.10, and the lower sequence is a new allele of Or. (b) The allelic effect of the SNP on Or in another breeding line at Fujii Seed. TT and TG showed TT homozygote and heterozygote of the Or SNP, respectively. Carrot root color was visually evaluated as three grades: dark, middle, and light orange color (b,c). All of the plants with dark or middle orange color roots showed a heterozygote for the Or SNP, and all plants with the slightly light orange color roots showed TT homozygote for the Or SNP. (c) Examples of carrot root color visually evaluated as three grades.

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We developed a KASP marker which could genotype the SNP on Or. We applied the developed KASP marker to breeding line C whose root color was segregated and that is the progeny of Fs002 (Fig. 2). The root color of breeding line C was visually evaluated into three grades (Fig. 5c). The genotype of KASP marker on Or was clearly correlated with the visual evaluation (Fig. 5b). All of the carrots whose root color was dark and middle orange had a heterozygote for the SNP on Or, and all of the carrots whose root color was light orange had a TT homozygote for the SNP. The developed KASP marker could be used for marker-assisted selection in orange root carrot breeding.

Considering a possible candidate gene for the β/α-carotene ratio in population A, and the amino acid comparison between parents of population A

In the association and QTL analyses of F2 population A, the QTL for the β/α-carotene ratio was detected on chromosome 6 and showed the highest association and LOD value on the physical position at around 4.6 Mb (Tables 1 and 2, Fig. 3, Suppl. Fig. S4). Iorizzo et al.10 summarized the carrot orthologous and homologous candidate genes involved in the plastid 2-C-methyl-D-erythritol 4-phosphate (MEP) and carotenoid pathways in a table. According to the table, DCAR_022896 (which has a lycopene cyclase domain) is located on a physical position at 4.1 Mb on chromosome 6. Carotenoid biosynthesis bifurcates after lycopene to produce ε- and β-carotenoids by enzymatic activity of the two lycopene cyclases, lycopene ε-cyclase (LCYE) and lycopene β-cyclase (LCYB)34 (Fig. 1). In addition, it is known that the proportions of β-carotene and α-carotene are determined mostly by the comparative amounts and/or activities of the LCYB and LCYE enzymes26,35,36,37,38.

It is known that LCYB, neoxanthin synthase (NSY) (which catalyzes violaxanthin into neoxanthin), capsanthin-capsorubin synthase (CCS) (which catalyzes the conversion of antheraxanthin and violaxanthin into capsanthin and capsorubin, respectively) (Fig. 1), and chromoplast-specific lycopene β-cyclase (CYC-B) have high sequence homology and similar putative catalytic mechanisms26,27,39,40.

Our phylogenic analysis of DCAR_022896, LCYE, LCYB, NSY, CCS, and CYC-B in carrot and Arabidopsis as well as Solanum lycopersicum, Carica papaya, Citrus sinensis, Capsicum annuum, and Lillium lancifolium showed that DCAR_022896 belonged to the same clade as CYC-B in C. sinensis and C. papaya (Fig. 6a). At the amino acid level, DCAR_022896 had 76.9% identity to CYC-B in C. sinensis and 62.1% to CYC-B in C. papaya. CYC-B is a LCYB, and it converts lycopene to β-carotene in chromoplasts, where carotenoids are accumulated41,42, in a specific manner26 (Fig. 1). Moreover, our BLAST search of primers for the reported LCYB2 in carrot showed that CYC-B (DCAR_022896) in the present study is identical to LCYB25,6,43,44. We thus presume that DCAR_022896 might be a possible candidate gene for the β/α-carotene ratio, and we compared the amino acid sequences between the parents of F2 population A by Sanger sequencing. The amino acid comparison revealed five amino acid substitutions between the parents of F2 population A (Fig. 6b). These results suggested the possibility that CYC-B might be a candidate gene for the QTL and the involvement of CYC-B in the β/α-carotene ratio in carrot root.

Figure 6
figure 6

The phylogenetic tree based on the amino acid sequences of LCYE, LCYB, CYC-B, NSY, and CCS, and the amino acid substitutions between the parental plants of F2 population A on DCAR_022896. (a) The phylogenetic tree was drawn by the neighbor-joining method based on the amino acid sequences of Daucus carota DCAR_022896, D. carota LCYE (DCAR_028276), Arabidopsis thaliana LCYE (At5g57030), D. carota LCYB (DCAR_020544), A. thaliana LCYB (At3g10230), Solanum lycopersicum CYC-B, Carica papaya CYC-B (evm.model.supercontig_195.16), Citrus sinensis CYC-B (orange1.1g010693m.g), D. carota NSY (DCAR_017191), D. carota NSY(2) (DCAR_025914), A. thaliana NSY (At1g67080), S. lycopersicum NSY (CAB93342.1), Capsicum annuum CCS (Q42435.1), and Lillium lancifolium CCS (JF304153). Values at the nodes indicate the percentage consensus support as calculated using a bootstrapping test with 1,000 replications. (b) Five amino acid substitutions (black filled circle) were detected between seed (Fs001) and pollen (Fs002) parents of F2 population A on DCAR_022896. Similar substitutions are shown in gray background.

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Discussion

Our association and QTL analyses using the two F2 populations derived from orange root carrots detected 21 and 32 QTLs for carrot root color traits(Figs. 3, 4, Suppl. Figs. S4, S5, Tables 1, 2). The QTL detected at around 31 Mb on chromosome 1 was detected by both analyses and showed high -log10P and LOD values; this explained much of the phenotypic variance for visual evaluation, color components a* and b*, and α- and β-carotene contents. The G allele at the physical position at 30,704,558 bp on chromosome 1 was dominant to A allele for α- and β-carotene contents (Supp. Fig. S6). To breed and select carrots that have higher carotenoid contents, the selection of a homozygous AA allele for this locus would be necessary. The quantitative differences in root color and carotenoid contents are affected by environmental conditions such as temperature and the field and light conditions after harvest. A complete selection for root color and carotenoid contents by appearance is thus very difficult. DNA markers of the QTL at around 31 Mb on chromosome 1 as well as the QTL on the chromosome 3 would be helpful for orange carrot breeding (Suppl. Figs. S6, S7).

There are no annotated genes for MEP and carotenoid pathways within 5 Mb from the physical position of 31 Mb on chromosome 1 where the highest association and LOD score was detected10. However, DCAR_002576 (the gene encoding photosystem II stability/assembly factor) is located at 30.8 Mb, and this function is similar to that of Y, accounting for the color difference of white, yellow and orange in carrot root; both genes have a role in the photosystem10,45. In the storage root of sweet potato, several genes involved in plastid biosynthesis including photosystem II are differentially expressed between white mutant and β-carotene-accumulating orange sweet potato cultivars46. It might be likely that polymorphism of DCAR_002576 causes a quantitative difference in carotenoid contents and affects root color, although further analyses are needed to explore this possibility.

A major QTL for lutein content was detected in F2 population A on chromosome 5 (Fig. 3, Suppl. Fig. S4, Tables 1, 2), whereas there are no predicted genes annotated for MEP and carotenoid pathways10 or for chromatin-modifying histone methyltransferase, SDG8 (CCR1), which affects the lutein content in leaves47 around this locus except for neoxanthin synthase (NSY). The NSY gene is located approx. 1.1 Mb away from the physical position of the highest association for lutein content. NSY has a role downstream of another branch which does not include lutein in carotenoid biosynthesis (Fig. 1), and no feedback regulation between NSY and lutein content has been reported. However, we cannot exclude the possibility that the mutation of the NSY of another branch affects the flow rate of each branch, resulting in an effect on the lutein content. Further analyses such as a map-based strategy is necessary to narrow down the candidate regions and identify candidate genes for QTLs on chromosome 1 for several color phenotypes and chromosome 5 for lutein content, and for the other significant QTLs revealed in this study.

The QTL analysis detected QTL at 6.7 Mb on chromosome 3 for visual evaluation, color component L*, and lutein content. The physical position of the QTL is similar to those of the QTL detected at 4.1 Mb for color component a* and the QTL detected at 4.8 Mb for α- and β-carotene contents. Further analysis is necessary to determine whether or not these QTLs are identical. The QTLs exerting a large effect were detected by both the association and QTL analyses. However, QTLs exerting a small effect would not be detected by both analyses because of false-positive and false-negative detections. The 11 QTLs detected by both analyses in this study are more reliable.

The Pearson correlation showed no high correlation between visual color evaluation and other phenotypes (Suppl. Table S2). Experienced breeders evaluate root color comprehensively including the gloss and texture of the carrot surface, and thus the detected associations only for visual evaluation might be associated with these phenotypes.

Carrot Or was recently identified and is associated with the carotenoid presence in carrot root16. The proximity of physical positions and function of Or suggests that QTL detected at around 5–6 Mb on chromosome 3 were possibly caused by Or. An SNP causing a non-synonymous mutation was detected in the present study between the parents of F2 populations A and B by Sanger sequencing (Fig. 5a). We could not compare the sequences of the promotor region at the upstream of Or in the parental lines, and we therefore cannot exclude the possibility that polymorphism(s) at the promoter region causes the phenotypic difference. As breeding line C was derived from Fs002 (Fig. 2), a dark orange allele would be derived from the Fs002.

The association and QTL analyses in F2 population A revealed the QTL for the β/α-carotene ratio on chromosome 6; CYC-B is located on the QTL region (Fig. 3h, Suppl. Fig. S4h, Tables 1, 2). In several model plants such as Arabidopsis thaliana48, rice (Oryza sativa)49, and maize (Zea mays)35,50, LCYB is encoded by a single gene. However, LCYB is encoded by two genes in some plant species that accumulate high levels of carotenoids in non-photosynthetic organs, such as fruits and flowers44. These genes are differentially expressed in photosynthetic and non-photosynthetic organs, and genes that are expressed in non-photosynthetic organs were named CYC-B. As named, CYC-B is a chromoplast-specific lycopene β-cyclase.

Carrot has two LCYBs: LCYB1 and LCYB23. Our present phylogenetic analysis demonstrated that carrot LCYB1 (LCYB) and LCYB2 (CYC-B) belong to LCYB and CYC-B clades, respectively (Fig. 6a). The CYC-B was first reported in tomato (Solanum lycopersicum) as a fruit- and flower-specific lycopene β-cyclase26 and has also been reported to be responsible for fruit color in papaya (Carica papaya)28 and citrus (Citrus sinensis) and for high lycopene accumulation in red grapefruits29. In carrot, unlike plants that have organ-specific LCYBs, LCYB1 is expressed in both leaves and root, and the transcript level of LCYB1 increases as the carotenoid content increases during root development44,51. Since the association and QTL analyses detected a QTL around the CYC-B region in this study, we speculate that in carotenoid-accumulating carrot root, in addition to the LCYB (LCYB1), CYC-B (LCYB2) might also have a role in carotenoid biosynthesis. Further functional analyses such as an expression study of CYC-B (LCYB2) in several organs and developmental stages and an investigation of the subcellular location of CYC-B (LCYB2) in carrot are necessary to clarify the involvement of CYC-B in the carotenoid contents of carrot taproot and the functions of the two LCYBs in carrot.

Visual appearance traits are important targets in carrot breeding in Japan, and the 'best bright orange color' is selected based on a comparison of minute color differences as shown in Fig. 5c. The present study provides the first results of association and QTL analyses for carrot root color for the selection of bright orange color in orange root populations. The developed KASP marker on Or as well as the SNPs showing significant associations will contribute to orange carrot breeding.