Whole-genome and genome-wide association studies improve key agricultural traits of safflower for industrial and medicinal use

Abstract

Safflower (Carthamus tinctorius) is widely cultivated around the world for its seeds and flowers. The presence of linoleic acid (LA) in its seeds and hydroxysafflor yellow A (HSYA) in its flowers are the crucial traits that enable safflower to be used for industrial and medicinal purposes. Understanding the genetic control of these traits is essential for optimizing the quality of safflower and its breeding. To further this research, we present a chromosome-scale assembly of the genome of the safflower variety ‘Chuanhonghua 1’, which was achieved using an integrated strategy combining Illumina, Oxford Nanopore, and Hi-C sequencing. We obtained a 1.17-Gb assembly with a contig N50 of 1.08 Mb, and all assembled sequences were assigned to 12 pseudochromosomes. Safflower’s evolution involved the core eudicot γ-triplication event and a whole-genome duplication event, which led to large-scale genomic rearrangements. Extensive genomic shuffling has occurred since the divergence of the ancestor of dicotyledons. We conducted metabolite and transcriptome profiles with time- and part-dependent changes and screened candidate genes that significantly contribute to seed lipid biosynthesis. We also analyzed key gene families that participate in LA and HSYA biosynthesis. Additionally, we re-sequenced 220 safflower lines and carried out a genome-wide association study using high-quality SNP data for eight agronomic traits. We identified SNPs related to important traits in safflower. Besides, the candidate gene HH_034464 (CtCGT1) was shown to be involved in the biosynthesis of HSYA. Overall, we provide a high-quality reference genome and elucidate the genetic basis of LA and HSYA biosynthesis in safflower. This vast amount of data will benefit further research for functional gene mining and breeding in safflower.

Acknowledgements

This project is supported by grants from the National Natural Science Foundation of China (82274039, U19A2010), the Key R&D Plan of Science and Technology Department of Sichuan Province (2021YFYZ0012-5, 2020YFN0152), the Sichuan Provincial Central Guiding Local Science and Technology Development Special Project (2020ZYD058), the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (ZYYCXTD-D-202209), and the Xinglin Talent Program of Chengdu University of TCM (0300510007). We thank Genebang (www.genebang.com) for providing assistance in data analysis, and AJE (www.aje.cn) for polishing the article.

Author contributions

J.C., J.X., and J.P. conceived the study. J.C. and J.P. provided funding. X.H., R.W., D.J., Q.L., Z.H., and P.W. prepared the tissue samples for sequencing. J.C., S.G., X.Y., X.L., C.R., S.C., and J.X. led the bioinformatics analyses. S.G., X.Y., and X.L. conducted transcriptome sequencing and analysis. C.R., S.D., and C.C. conducted metabolome analysis. S.G., X.Y., and X.L. constructed the database. X..H, R.W., D.J., Q.L., Z.H., and P.W. recorded the agronomic characters and determination of oil content. J.C. and S.G. drew the figures. J.C. and S.G. drafted the manuscript. X.H., R.W., D.J., S.C., J.X., and J.P. contributed to the writing.

Data availability

The safflower genome sequence and annotation files have been uploaded to NGDC (National Genome Science Data Center); the project number is PRJCA009936 and the genome number is GWHBJIR00000000. All the RNA data have been uploaded to the Sequence Read Archive (SRA) (http://www.ncbi.nlm.nih.gov/) with accession number SUB13799758. The metabolic data of both seeds and flowers are listed as additional supporting information and can be found in the online version of this article.

Conflict of interest

The authors declare no conflict of interest.

References

[1] Knowles P, Ashri A . Safflower: Carthamus tinctorius (Compositae). In: Smartt J, Simmonds NW, eds. Evolution of Crop Plants. Longman: Harlow, 1995, 47-50

[2] Norris LE, Collene AL, Asp ML et al. Comparison of dietary conjugated linoleic acid with safflower oil on body composition in obese postmenopausal women with type 2 diabetes mellitus. Am J Clin Nutr. 2009; 90: 468-76

[3] Shimomura Y, Tamura T, Suzuki M . Less body fat accumulation in rats fed a safflower oil diet than in rats fed a beef tallow diet. J Nutr. 1990; 120: 1291-6

[4] Azami K, Hayashi T, Kusumi T et al. Total synthesis of carthamin, a traditional natural red pigment. Angew Chem Int Ed Engl. 2019; 58: 5321-6

[5] Mohammadi M, Tavakoli A . Effect of harvest time of spring safflower (Carthamus tinctorius L.) florets on the production of red and yellow pigments . Qual Assur Saf Crops Foods. 2015; 7: 581-8

[6] ChPC (Pharmacopoeia Commission of People’s Republic of China). Pharmacopoeia of the People’s Republic of China. Vol. 1 2020: 157-8

[7] Lou ZQ, Liu ML . A pharmacognostical study of the Chinese drug, Honghua. Carthami tinctor II. Acta Pharm Sin. 1956; 4: 233-9

[8] Ao H, Feng W, Peng C . Hydroxysafflor yellow a: a promising therapeutic agent for a broad spectrum of diseases. Evid Based Complement Alternat Med. 2018; 2018: 1-17

[9] Bai X, Wang WX, Fu RJ et al. Therapeutic potential of hydroxysafflor yellow A on cardio-cerebrovascular diseases. Front Pharmacol. 2020; 11: 01265

[10] Ekin Z . The resurgence of safflower (Carthamus tinctorius L.) utilization: a global view . J Agron. 2005; 4: 83-7

[11] Emongor V. Safflower (Carthamus tinctorius L.) the underutilized and neglected crop: a review . Asian J Plant Sci. 2010; 9: 299-306

[12] Kiran BU, Mukta N, Kadirvel P et al. Genetic diversity of safflower (Carthamus tinctorius L.) germplasm as revealed by SSR markers . Plant Genet Resour. 2017; 15: 1-11

[13] Majidi MM, Zadhoush S . Molecular and morphological variation in a world-wide collection of safflower. Crop Sci. 2014; 54: 2109-19

[14] Mokhtari N, Rahimmalek M, Talebi M et al. Assessment of genetic diversity among and within Carthamus species using sequence-related amplified polymorphism (SRAP) markers . Plant Syst Evol. 2013; 299: 1285-94

[15] Wu ZH, Liu H, Zhan W et al. The chromosome-scale reference genome of safflower (Carthamus tinctorius) provides insights into linoleic acid and flavonoid biosynthesis . Plant Biotechnol J. 2021; 19: 1725-42

[16] Gao L, Gonda I, Sun HH et al. The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor. Nat Genet. 2019; 51: 1044-51

[17] Wang WS, Mauleon R, Hu ZQ et al. Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature. 2018; 557: 43-9

[18] Qin P, Lu HW, Du HL et al. Pan-genome analysis of 33 genetically diverse rice accessions reveals hidden genomic variations. Cell. 2021; 184: 3542-3558.e16

[19] Bates PD, Stymne S, Ohlrogge J . Biochemical pathways in seed oil synthesis. Curr Opin Plant Biol. 2013; 16: 358-64

[20] Dar AA, Choudhury AR, Kancharla PK et al. The FAD2 gene in plants: occurrence, regulation, and role. Front Plant Sci. 2017; 8: 1789

[21] Li-Beisson Y, Shorrosh B, Beisson F et al. Acyl-lipid metabolism. Arabidopsis Book. 2013; 11: e0161

[22] Liu Q, Siloto RM, Lehner R et al. Acyl-CoA: diacylglycerol acyltransferase: molecular biology, biochemistry, and biotechnology. Prog Lipid Res. 2012; 51: 350-77

[23] Grotewold E. The genetics and biochemistry of floral pigments. Annu Rev Plant Biol. 2006; 57: 761-80

[24] Zhang Y, Butelli E, Martin C . Engineering anthocyanin biosynthesis in plants. Curr Opin Plant Biol. 2014; 19: 81-90

[25] Wang R, Ren C, Dong S et al. Integrated metabolomics and transcriptome analysis of flavonoid biosynthesis in safflower (Carthamus tinctorius L.) with different colors . Front Plant Sci. 2021; 12: 712038-50

[26] Liu D, Ji H, Yang Z . Functional characterization of three novel genes encoding diacylglycerol acyltransferase (DGAT) from oil-rich tubers of Cyperus esculentus. Plant Cell Physiol. 2020; 61: 118-29

[27] Turchetto-Zolet AC, Maraschin FS, de Morais GL et al. Evolutionary view of acyl-CoA diacylglycerol acyltransferase (DGAT), a key enzyme in neutral lipid biosynthesis. BMC Evol Biol. 2011; 11: 1-14

[28] Somerville C, Browse J . Dissecting desaturation: plants prove advantageous. Trends Cell Biol. 1996; 6: 148-53

[29] Ito T, Fujimoto S, Suito F et al. C-Glycosyltransferases catalyzing the formation of di-C-glucosyl flavonoids in citrus plants. Plant J. 2017; 91: 187-98

[30] Sasaki N, Nishizaki Y, Yamada E et al. Identification of the glucosyltransferase that mediates direct flavone C-glucosylation in Gentiana triflora. FEBS Lett. 2015; 589: 182-7

[31] Wang ZL, Gao HM, Wang S et al. Dissection of the general two-step di-C-glycosylation pathway for the biosynthesis of (iso)schaftosides in higher plants. Proc Natl Acad Sci USA. 2020; 117: 30816-23

[32] Bartholmes C, Hidalgo O, Gleissberg S . Evolution of the YABBY gene family with emphasis on the basal eudicot Eschscholzia californica (Papaveraceae). Plant Biol (Stuttg). 2012; 14: 11-23

[33] Bowman JL, Eshed Y, Baum SF . Establishment of polarity in angiosperm lateral organs. Trends Genet. 2002; 18: 134-41

[34] Nobuhiro S, Yuzo N, Eri Y et al. Identification of the glucosyltransferase that mediates direct flavone C-glucosylation in Gentiana triflora. FEBS Lett. 2015; 589: 182-7

[35] Ren C, Tang X, Chen J et al. Cloning and analysis of promoter regions of flavonoid biosynthesis genes in safflower. Plant Mol Biol Rep. 2018; 36: 239-46

[36] Bowers JE, Pearl SA, Burke JM . Genetic mapping of millions of SNPs in safflower (Carthamus tinctorius L.) via whole-genome resequencing. G3 (Bethesda). 2016; 6: 2203-11

[37] Kandhro A, Sherazi ST, Mahesar SA et al. GC-MS quantification of fatty acid profile including trans FA in the locally manufactured margarines of Pakistan. Food Chem. 2008; 109: 207-11

[38] Zelles L, Bai QY . Fractionation of fatty acids derived from soil lipids by solid phase extraction and their quantitative analysis by GC-MS. Soil Biol Biochem. 1993; 25: 495-507

[39] Woodfield HK, Cazenave-Gassiot A, Haslam RP et al. Using lipidomics to reveal details of lipid accumulation in developing seeds from oilseed rape (Brassica napus L.). Biochim Biophys Acta Mol Cell Biol Lipids. 2018; 1863: 339-48

[40] Katkade MB, Syed HM, Andhale RR et al. Fatty acid profile and quality assessment of safflower (Carthamus tinctorius) oil . J Pharmacogn Phytochem. 2018; 7: 3581-5

[41] Vanhercke T, Dyer JM, Mullen RT et al. Metabolic engineering for enhanced oil in biomass. Prog Lipid Res. 2019; 74: 103-29

[42] Zhang M, Li FD, Li K et al. Functional characterization and structural basis of an efficient di-C-glycosyltransferase from Glycyrrhiza glabra. J Am Chem Soc. 2020; 142: 3506-12

[43] Modolo LV, Blount JW, Achnine L et al. A functional genomics approach to (iso)flavonoid glycosylation in the model legume Medicago truncatula. Plant Mol Biol. 2007; 64: 499-518

[44] Tam V, Patel N, Turcotte M et al. Benefits and limitations of genome-wide association studies. Nat Rev Genet. 2019; 20: 467-84

[45] Tibbs Cortes L, Zhang Z, Yu J . Status and prospects of genome-wide association studies in plants. Plant Genome. 2021; 14: e20077

[46] Wang W, Barratt BJ, Clayton DG et al. Genome-wide association studies: theoretical and practical concerns. Nat Rev Genet. 2005; 6: 109-18

[47] Marçais G, Kingsford C . A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics. 2011; 27: 764-70

[48] Koren S, Walenz BP, Berlin K et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 2017; 27: 722-36

[49] Hu J, Fan J, Sun Z et al. NextPolish: a fast and efficient genome polishing tool for long-read assembly. Bioinformatics. 2020; 36: 2253-5

[50] Grabherr Manfred G, Haas Brian J, Moran Y et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011; 29: 644-52

[51] Manni M, Berkeley MR, Seppey M et al. BUSCO: assessing genomic data quality and beyond. Curr Protoc. 2021; 1: e323

[52] Flynn JM, Hubley R, Goubert C et al. RepeatModeler2 for automated genomic discovery of transposable element families. Proc Natl Acad Sci USA. 2020; 117: 9451-7

[53] Guindon S, Dufayard JF, Lefort V et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol. 2010; 59: 307-21

[54] Wang Y, Tang H, Debarry JD et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012; 40: e49

[55] Liu K, Zhao S, Wang S et al. Identification and analysis of the FAD gene family in walnuts (Juglans regia L.) based on transcriptome data . BMC Genomics. 2020b; 21: 1-12

[56] Zhao Q, Cui MY, Levsh O et al. Two CYP82D enzymes function as flavone hydroxylases in the biosynthesis of root-specific 4’-deoxyflavones in Scutellaria baicalensis. Mol Plant. 2018; 11: 135-48

[57] McKenna A, Hanna M, Banks E et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010; 20: 1297-303

[58] Danecek P, Auton A, Abecasis G et al. The variant call format and VCFtools. Bioinformatics. 2011; 27: 2156-8

[59] Browning BL, Zhou Y, Browning SR . A one-penny imputed genome from next-generation reference panels. Am J Hum Genet. 2018; 103: 338-48

[60] Purcell S, Neale B, Todd-Brown K et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007; 81: 559-75

[61] Kang HM, Sul JH, Service SK et al. Variance component model to account for sample structure in genome-wide association studies. Nat Genet. 2010; 42: 348-54

[62] Li MX, Yeung JM, Cherny SS et al. Evaluating the effective numbers of independent tests and significant p-value thresholds in commercial genotyping arrays and public imputation reference datasets. Hum Genet. 2012; 131: 747-56

[63] Wang K, Li M, Hakonarson H . ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010; 38: e164

[64] Sun Y, Xu DP, Qin Z et al. Protective cerebrovascular effects of hydroxysafflor yellow A (HSYA) on ischemic stroke. Eur J Pharmacol. 2018; 818: 604-9

[65] Chen C, Wang R, Dong S et al. Integrated proteome and lipidome analysis of naturally aged safflower seeds varying in vitality. Plant Biology. 2021; 24: 266-77

[66] Chen J, Wang J, Wang R et al. Integrated metabolomics and transcriptome analysis on flavonoid biosynthesis in safflower (Carthamus tinctorius L.) under MeJA treatment. Plant Biology. 2020; 20