Analysis of telomere-to-telomere genome of red carrot TXH4 elucidates the role of DcLCYE and DcLCYB1 in lycopene accumulation in carrot

Abstract

Carrot taproots exhibit a wide range of colors due to variations in carotenoid and anthocyanin contents. TouXinHong4 (TXH4), a Chinese red carrot landrace from western China, is appreciated for its storability, stress tolerance, and good flavor. In this study, we generated a high-quality, telomere-to-telomere (T2T), gap-free genome assembly of TXH4, with a total size of 449.92 Mb. Repetitive sequences accounted for 48.6% of the genome. A total of 34 225 genes were identified, with 34 016 genes associated with at least one functional annotation. Comparison with two previously assembled carrot genomes, Daucus carota T2T (DcT2T) and D. carota v2.0 (DcRef), revealed 2 466 422 and 2 037 986 single nucleotide polymorphisms and 500 579 and 474 704 insertions/deletions in DcT2T and DcRef, respectively. Carotenoid analysis showed that the lycopene content in TXH4 roots was 1965-fold higher than that in the leaves, while α-carotene and β-carotene levels in the roots were only 2.7% and 3.5% of those in the leaves, respectively. This finding was consistent with the lack of transcription of lycopene β-cyclase 1 (LCYB1) and lycopene ε-cyclase (LCYE) in TXH4 roots. Furthermore, overexpression of DcLCYB1 and DcLCYE resulted in reduced lycopene levels, while their knockout led to elevated lycopene accumulation. Downregulation of DcLCYB1 and DcLCYE was identified as a critical factor contributing to lycopene accumulation, resulting in the red root phenotype of TXH4 roots. The gapless genome assembly of TXH4 offers important insights into the red carrot genome and expands the genomic resources for breeding, facilitating more efficient genome-assisted breeding strategies for crop improvement.

Acknowledgments

This research was supported by the Scientific and technological innovation capacity building project of BAAFS (KJCX20251008), the Technological Innovation Capacity Program of the Beijing Academy of Agricultural and Forestry Sciences (KJCX20230405), the Innovation and Development Program of the Beijing Vegetable Research Center (KJCX20230126 and KYCX202303), and the Collaborative innovation program of the Beijing Vegetable Research Center (XTCX202302).

Author contributions

X.J.L., X.M.S., A.S.X., and Y.L. designed the project and planned the experiments. X.J.L. performed the experiments and analyzed the results. Y.C.H., J.W.Z., C.H.Z., and X.M.S. analyzed the data. Y.H.W., J.X.T., and A.S.X. contributed the reagents/materials/analysis tools. X.J.L., Y.C.H., and X.M.S. wrote the manuscript. L.Z., A.S.X., and Y.L. were involved in finalizing the manuscript.

Data availability

The TXH4 genome assembly data are accessible in the China National Center for Bioinformation database https://ngdc.cncb.ac.cn/gwh/(CNA0423801).

Conflict of interests

The authors declare no competing interests.

Supplementary data

Supplementary data is available at Horticulture Research online.

References

[1] Iorizzo M, Senalik DA, Ellison SL. et al. Genetic structure and domestication of carrot (Daucus carota subsp. sativus) (Api-aceae). Am J Bot. 2013; 100:930-8

[2] Arscott SA, Tanumihardjo SA. Carrots of many colors pro-vide basic nutrition and bioavailable phytochemicals acting as a functional food. Compr Rev Food Sci Food Saf. 2010; 9: 223-39

[3] Grassmann J, Schnitzler WH, Habegger R. Evaluation of differ-ent coloured carrot cultivars on antioxidative capacity based on their carotenoid and phenolic contents. Int J Food Sci Nutr. 2007; 58:603-11

[4] Just BJ, Santos CA, Yandell BS. et al. Major QTL for carrot color are positionally associated with carotenoid biosynthetic genes and interact epistatically in a domesticated x wild carrot cross. Theor Appl Genet. 2009; 119:1155-69

[5] Banga O. Origin of the European cultivated carrot. Euphytica. 1957; 6:54-63

[6] Banga O. Main Types of the Western Carotene Carrot and their Origin. Zwolle: W. E. J. Tjeenk Willink. 1963

[7] Simon PW. Domestication, historical development, and modern breeding of carrot. Plant Breed Rev. 2000; 19:157-90

[8] Banga O. The development of the original European carrot mate-rial. Euphytica. 1957; 6:64-76

[9] Ma ZG, Kong XP, Liu LJ. et al. The unique origin of orange carrot cultivars in China. Euphytica. 2016; 212:37-49

[10] Rubatzky VE, Quires CF, Simon WP. Carrots and Related Vegetable Umbelliferae. Wallingford: CABI Publishing, 1999

[11] Garg V, Bohra A, Mascher M. et al. Unlocking plant genetics with telomere-to-telomere genome assemblies. Nat Genet. 2024; 56: 1788-99

[12] Wang B, Yang X, Jia Y. et al. High-quality Arabidopsis thaliana genome assembly with nanopore and HiFi long reads. Genomics Proteomics Bioinformatics. 2022; 20:4-13

[13] Deng Y, Liu S, Zhang Y. et al. A telomere-to-telomere gap-free reference genome of watermelon and its mutation library provide important resources for gene discovery and breeding. Mol Plant. 2022; 15:1268-84

[14] Fu A, Zheng Y, Guo J. et al. Telomere-to-telomere genome assem-bly of bitter melon (Momordica charantia L. var. abbreviata Ser.) reveals fruit development, composition and ripening genetic characteristics. reveals fruit development, composition and ripening genetic characteristics. Hortic Res. 2023;10:uhac228

[15] Xu XD, Zhao RP, Xiao L. et al. Telomere-to-telomere assembly of cassava genome reveals the evolution of cassava and divergence of allelic expression. Hortic Res. 2023;10:uhad200

[16] Zhou Y, Xiong J, Shu Z. et al. The telomere-to-telomere genome of Fragaria vesca reveals the genomic evolution of Fragaria and the origin of cultivated octoploid strawberry. Hortic Res. 2023;10:uhad027

[17] Zeng, He Z, He J. et al. The telomere-to-telomere gap-free refer-ence genome of wild blueberry (Vaccinium duclouxii) provides its high soluble sugar and anthocyanin accumulation. Hortic Res. 2023;10:uhad209

[18] Wei M, Huang Y, Mo C. et al. Telomere-to-telomere genome assembly of melon (Cucumis melo L. var. inodorus) provides a high-quality reference for meta-QTL analysis of important traits. Hortic Res. 2023;10:uhad189

[19] Mo C, Wang H, Wei M. et al. Complete genome assembly provides a high-quality skeleton for pan-NLRome construction in melon. Plant J. 2024; 118:2249-68

[20] Zeng Q, Wei M, Li S. et al. Complete genome assembly provides insights into the centromere architecture of pumpkin (Cucur-bita maxima). Plant Com. 2024; 5:100935

[21] Wang YH, Liu PZ, Liu H. et al. Telomere-to-telomere carrot (Dau-cus carota) genome assembly reveals carotenoid characteristics. Hortic Res. 2023;10:uhad103

[22] Coe K, Bostan H, Rolling W. et al. Population genomics identifies genetic signatures of carrot domestication and improvement and uncovers the origin of high-carotenoid orange carrots. Nat Plants. 2023; 9:1643-58

[23] Liu W, Xu S, Ou C. et al. T2T genomes of carrot and Alternaria dauci and their utility for understanding host-pathogen interactions during carrot leaf blight disease. Plant J. 2024; 120: 1643-61

[24] Just BJ, Santos CAF, Fonseca MEN. et al. Carotenoid biosynthesis structural genes in carrot (Daucus carota): isolation, sequence-characterization, single nucleotide polymorphism (SNP) mark-ers and genome mapping. Theor Appl Genet. 2007; 114:693-704

[25] Iorizzo M, Ellison S, Senalik D. et al. A high-quality carrot genome assembly provides new insights into carotenoid accumulation and asterid genome evolution. Nat Genet. 2016; 48:657-66

[26] Wang YG, Zhang YM, Wang YH. et al. The Y locus encodes a REPRESSOR OF PHOTOSYNTHETIC GENES protein that represses carotenoid biosynthesis via interaction with APRR2 in carrot. Plant Cell. 2024; 36:2798-817

[27] Wang HR, Zhang RR, Wang YH. et al. Carotene hydroxylase DcCYP97A3 affects carotenoids metabolic flow and taproot color by influencing the conversion of α-carotene to lutein in carrot. Hortic Res. 2025;12:uhaf054

[28] Wang YH, Li T, Zhang RR. et al. Transcript profiling of genes involved in carotenoid biosynthesis among three carrot cultivars with various taproot colors. Protoplasma. 2020; 257:949-63

[29] Apel W, Bock R. Enhancement of carotenoid biosynthesis in transplastomic tomatoes by induced lycopene-to-provitamin a conversion. Plant Physiol. 2009; 151:59-66

[30] Zhang J, Sun H, Guo S. et al. Decreased protein abundance of lycopene beta-cyclase contributes to red flesh in domesticated watermelon. Plant Physiol. 2020; 183:1171-83

[31] Kaur N, Alok A, Shivani. et al. CRISPR/Cas9 directed edit-ing of lycopene epsilon-cyclase modulates metabolic flux for beta-carotene biosynthesis in banana fruit. Metab Eng. 2020; 59: 76-86

[32] Wang YH, Zhang YQ, Zhang RR. et al. Lycopene epsilon-cyclase mediated transition of alpha-carotene and beta-carotene metabolic flow in carrot fleshy root. Plant J. 2023; 115: 986-1003

[33] Jain M, Olsen HE, Paten B. et al. The Oxford nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biol. 2016; 17:239

[34] Burton JN, Adey A, Patwardhan RP. et al. Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nat Biotechnol. 2013; 31:1119-25

[35] Li H, Durbin R. Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics. 2009; 25:1754-60

[36] Mosè M, Berkeley MR, Mathieu S. et al. BUSCO update: novel and streamlined workflows along with broader and deeper phyloge-netic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol Biol Evol. 2021; 38:4647-54

[37] Parra G, Bradnam K, Korf I. CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics. 2007; 23:1061-7

[38] Servant, Varoquaux N, Lajoie BR. et al. HiC-pro: an optimized and flexible pipeline for hi-C data processing. Genome Biol. 2015; 16:1

[39] Ellinghaus D, Kurtz S, Willhoeft U. LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons. BMC Bioinformatics. 2008; 9:18

[40] Zhao X, Hao W. LTR_FINDER: an efficient tool for the pre-diction of full-length LTR retrotransposons. Nucleic Acids Res. 2007;35:W265-8

[41] Ou S, Jiang N. LTR_retriever: a highly accurate and sensitive pro-gram for identification of long terminal repeat retrotransposons. Plant Physiol. 2017; 176:01310

[42] Huda A, Jordan IK. Analysis of transposable element sequences using CENSOR and RepeatMasker. Methods Mol Biol. 2009; 537: 323-36

[43] Gary B. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999; 27:573-80

[44] Sebastian B, Thomas T, Thomas M. et al. MISA-web: a web server for microsatellite prediction. Bioinformatics. 2017; 33:2583-5

[45] Baertsch MSMDR, Haussler D. Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics. 2008; 24:637-44

[46] Ian K. Gene finding in novel genomes. BMC Bioinformatics. 2004; 5:59

[47] Keilwagen J, Wenk M, Erickson JL. et al. Using intron position conservation for homology-based gene prediction. Nucleic Acids Res. 2016; 44:e89

[48] Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015; 12: 357-60

[49] Pertea M, Pertea GM, Antonescu CM. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015; 33:290-5

[50] Tang S, Lomsadze A, Borodovsky M. Identification of pro-tein coding regions in RNA transcripts. Nucleic Acids Res. 2014; 43:e78

[51] Grabherr MG, Haas BJ, Yassour M. et al. Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nat Biotechnol. 2013; 29:644-52

[52] Haas BJ, Salzberg SL, Zhu W. et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the program to assemble spliced alignments. Genome Biol. 2008;9:R7

[53] Haas BJ, Delcher AL, Mount SM. et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assem-blies. Nucleic Acids Res. 2003; 31:5654-66

[54] Huson DH, Buchfink B. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015; 12:59-60

[55] Zou Q, Guo J, Ju Y. et al. Improving tRNAscan-SE annotation results via ensemble classifiers. Mol Inform. 2016; 34:761-70

[56] Loman T.A novel method for predicting ribosomal RNA genes in prokaryotic genomes. Master’s thesis, Lund University. Depart-ment of Biology. 2017

[57] Nawrocki EP, Eddy SR Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics. 2013; 29:2933-5

[58] She R, Chu SC, Wang K. et al. genBlastA: enabling BLAST to identify homologous gene sequences. Genome Res. 2008; 19:143-9

[59] Birney E, Clamp M, Durbin R. GeneWise and genomewise. Genome Res. 2004; 14:988-95

[60] Emms DM, Kelly S. OrthoFinder: phylogenetic orthology infer-ence for comparative genomics. Genome Biol. 2019; 20:238

[61] Mistry J, Chuguransky S, Williams L. et al. Pfam:the protein families database in 2021. Nucleic Acids Res. 2020;49:D412-9

[62] Katoh K, Toh H. Recent developments in the MAFFT multiple sequence alignment program. Brief Bioinform. 2008; 9:286-98

[63] Lam-Tung N, Schmidt HA, Arndt VH. et al. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015; 32:268-74

[64] Han MV, Thomas GWC, Jose LM. et al. Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3. Mol Biol Evol. 2013; 30:1987-97

[65] Xing HL, Dong L, Wang ZP. et al. A CRISPR/Cas9 toolkit for multiplex genome editing in plants. BMC Plant Biol. 2014; 14:327