Strawberry soluble solids QTL with inverse effects on yield

Abstract

Sugars are the main drivers of strawberry sweetness, and understanding their genetic control is of critical importance for breeding. Large-scale genome-wide association studies were performed in two populations totaling 3399 individuals evaluated for soluble solids content (SSC) and fruit yield. Two stable quantitative trait loci (QTL) on chromosome 3B and 6A for SSC were identified. Favorable haplotypes at both QTL for SSC decreased yield, though optimal allelic combinations were identified with reduced impacts on yield. Metabolites in the starch and sucrose metabolism pathway were characterized and quantified for 23 contrasting genotypes in leaves, white fruit, and red fruit. Variations in sucrose concentrations/efflux indicated genetic variation underlying sucrose accumulation and transportation during fruit ripening. Integration of genome-wide association studies and expression quantitative locus mapping identified starch synthase 4 (FxaC_10g00830) and sugar transporter 2-like candidate genes (FxaC_21g51570) within the respective QTL intervals. These results will enable immediate applications in genomics-assisted breeding for flavor and further study of candidate genes underlying genetic variation of sugar accumulation in strawberry fruit.

Acknowledgements

The authors wish to thank the strawberry breeding team at UF/IFAS GCREC for data collection and curation, in particular Ms Angelita Arredondo and Dr Cheryl Dalid. Financial support for this project was provided by USDA National Institute of Food and Agriculture Hatch project 1025494 via the Florida Agricultural Experiment Station and two USDA/NIFA Specialty Crop Research Initiative projects: “RosBREED: Combining disease resistance with horticultural quality in new rosaceous cultivars” under award number 2014-51181-22378 and “Next-Generation Disease Resistance Breeding and Management Solutions for Strawberry” under award number 2017-51181-26833.

Author contributions

Z.F., V.W, S.L, and Y.W. conceptualized the project. Z.F., S.V., and H.L. curated data and conducted data analyses. Z.F., H.L., and Y.J. conducted experiments. Z.F. and S.V. wrote the initial manuscript. All authors reviewed and edited the manuscript.

Data availability

All raw data is provided in the supplementary files.

Conflict of interest statement

The authors declare that there is no competing interest.

Supplementary information

Supplementary data is available at Horticulture Research online.

References

[1] Fan Z, Plotto A, Bai J. et al. Volatiles influencing sensory attributes and Bayesian modeling of the soluble solids-sweetness relationship in strawberry. Front Plant Sci. 2021; 12:640704

[2] Fan Z, Hasing T, Johnson TS. et al. Strawberry sweetness and consumer preference are enhanced by specific volatile compounds. Hortic Res. 2021; 8:1-15

[3] Lerceteau-Kohler E, Moing A, Guérin G. et al. QTL analysis for sugars and organic acids in strawberry fruits. Acta Hortic. 2006; 708:573-8

[4] Zorrilla-Fontanesi Y, Cabeza A, Domínguez P. et al. Quantitative trait loci and underlying candidate genes controlling agronomical and fruit quality traits in octoploid strawberry (Fragaria × ananassa). Theor Appl Genet. 2011; 123:755-78

[5] Lerceteau-Köhler E, Moing A, Guérin G. et al. Genetic dissection of fruit quality traits in the octoploid cultivated strawberry highlights the role of homoeo-QTL in their control. Theor Appl Genet. 2012; 124:1059-77

[6] Castro P, Lewers KS. Identification of quantitative trait loci (QTL) for fruit-quality traits and number of weeks of flowering in the cultivated strawberry. Mol Breed. 2016; 36:1-19

[7] Alarfaj R, El-Soda M, Antanaviciute L. et al. Mapping QTL underlying fruit quality traits in an F1 strawberry population. Journal of Horticultural Science and Biotechnology. 2021; 96:634-45

[8] Rey-Serra P, Mnejja M, Monfort A. Shape, firmness and fruit quality QTLs shared in two non-related strawberry populations. Plant Sci. 2021; 311:111010

[9] Vallarino JG, Pott DM, Cruz-Rus E. et al. Identification of quantitative trait loci and candidate genes for primary metabolite content in strawberry fruit. Hortic Res. 2019; 6:1-17

[10] Verma S, Zurn JD, Salinas N. et al. Clarifying sub-genomic positions of QTLs for flowering habit and fruit quality in U.S. strawberry (Fragariaananassa) breeding populations using pedigree-based QTL analysis. Hortic Res. 2017; 4:17062

[11] Whitaker VM, Osorio LF, Hasing T. et al. Estimation of genetic parameters for 12 fruit and vegetative traits in the University of Florida strawberry breeding population. J Am Soc Hortic Sci. 2012; 137:316-24

[12] Ren Y, Liao S, Xu Y. An update on sugar allocation and accumulation in fruits. Plant Physiol. 2023; 193:888-99

[13] Rennie EA, Turgeon R. A comprehensive picture of phloem loading strategies. Proc Natl Acad Sci U S A. 2009; 106:14162-7

[14] Julius BT, Leach KA, Tran TM. et al. Sugar transporters in plants: new insights and discoveries. Plant Cell Physiol. 2017; 58:1442-60

[15] Liu HT, Lyu WY, Tian SH. et al. The SWEET family genes in strawberry: identification and expression profiling during fruit development. S Afr J Bot. 2019; 125:176-87

[16] Jiu S, Salman Haider M, Kurjogi MM. et al. Genome-wide characterization and expression analysis of sugar transporter family genes in woodland strawberry. Plant Genome. 2018; 11:170103

[17] Liu HT, Ji Y, Liu Y. et al. The sugar transporter system of strawberry: genome-wide identification and expression correlation with fruit soluble sugar-related traits in a Fragaria × ananassa germplasm collection. Hortic Res. 2020; 7:132

[18] Rashid A, Ruan H, Wang Y. The gene FvTST1 from strawberry modulates endogenous sugars enhancing plant growth and fruit ripening. Front Plant Sci. 2022; 12:774582

[19] Forney CF, Breen JP. Sugar content and uptake in the strawberry fruit. J Am Soc Hortic Sci. 1986; 111:241-7

[20] Zhao YUANH, Hua PANGF, Jian CAIW. et al. Genome-wide analysis of the invertase genes in strawberry (Fragaria × ananassa). J Integr Agric. 2021; 20:2652-65

[21] Whitaker VM, Osorio LF, Peres NA. et al. Florida Beauty’ strawberry. Hort Science. 2017; 52:1443-7

[22] Williams LE, Lemoine R, Sauer N. Sugar transporters in higher plants - a diversity of roles and complex regulation. Trends Plant Sci. 2000; 5:283-90

[23] Braun DM, Slewinski TL. Genetic control of carbon partitioning in grasses: roles of sucrose transporters and tie-dyed loci in phloem loading. Plant Physiol. 2009; 149:71-81

[24] Shaw DV. Genotypic variation and genotypic correlations for sugars and organic acids of strawberries. J Am Soc Hortic Sci. 1988; 113:770-4

[25] Cockerton HM, Karlström A, Johnson AW. et al. Genomic informed breeding strategies for strawberry yield and fruit quality traits. Front Plant Sci. 2021; 12:724847

[26] Rousseau-Gueutin M, Lerceteau-Köhler E, Barrot L. et al. Comparative genetic mapping between Octoploid and diploid Fragaria species reveals a high level of colinearity between their genomes and the essentially disomic behavior of the cultivated Octoploid strawberry. Genetics. 2008; 179:2045-60

[27] Chitwood-Brown J, Vallad GE, Lee TG. et al. Characterization and elimination of linkage-drag associated with fusarium wilt race 3 resistance genes. Theor Appl Genet. 2021; 134:2129-40

[28] Chetelat RT, DeVerna JW, Bennett AB. Effects of the Lycopersicon chmielewskii sucrose accumulator gene (sucr) on fruit yield and quality parameters following introgression into tomato. Theor Appl Genet. 1995; 91:334-9

[29] Zhang J, Wang X, Yu O. et al. Metabolic profiling of strawberry (Fragaria × ananassa Duch.) during fruit development and maturation. J Exp Bot. 2011; 62:1103-18

[30] Fridman E, Pleban T, Zamir D. A recombination hotspot delimits a wild-species quantitative trait locus for tomato sugar content to 484 bp within an invertase gene. Proc Natl Acad Sci. 2000; 97:4718-23

[31] Nakai H, Yasutake D, Hidaka K. et al. Starch serves as an overflow product in the regulation of carbon allocation in strawberry leaves in response to photosynthetic activity. Plant Growth Regul. 2023; 2023:1-8

[32] Crumpton-Taylor M, Pike M, Lu KJ. et al. Starch synthase 4 is essential for coordination of starch granule formation with chloroplast division during Arabidopsis leaf expansion. New Phytol. 2013; 200:1064-75

[33] Lu KJ, Pfister B, Jenny C. et al. Distinct functions of STARCH SYNTHASE 4 domains in starch granule formation. Plant Physiol. 2018; 176:566-81

[34] Szydlowski N, Ragel P, Raynaud S. et al. Starch granule initiation in Arabidopsis requires the presence of either class IV or class III starch synthases. Plant Cell. 2009; 21:2443-57

[35] Gámez-Arjona FM, Li J, Raynaud S. et al. Enhancing the expression of starch synthase class IV results in increased levels of both transitory and long-term storage starch. Plant Biotechnol J. 2011; 9:1049-60

[36] Vimolmangkang S, Zheng H, Peng Q. et al. Assessment of sugar components and genes involved in the regulation of sucrose accumulation in peach fruit. J Agric Food Chem. 2016; 64:6723-9

[37] Ma QJ, Sun MH, Liu YJ. et al. Molecular cloning and functional characterization of the apple sucrose transporter gene MdSUT2. Plant Physiol Biochem. 2016; 109:442-51

[38] Osorio LF, Gezan SA, Verma S. et al. Independent validation of genomic prediction in strawberry over multiple cycles. Front Genet. 2021; 11:596258

[39] Fan Z, Whitaker VM. Genomic signatures of strawberry domestication and breeding. bioRxiv. 2023;596258

[40] Bassil NV, Davis TM, Zhang H. et al. Development and preliminary evaluation of a 90 K axiom® SNP array for the Allo-octoploid cultivated strawberry Fragaria × ananassa. BMC Genomics. 2015; 16:155

[41] Verma S, Bassil NV, van de Weg E. et al. Development and evaluation of the Axiom® IStraw35 384HT array for the Allo-octoploid cultivated strawberry Fragaria × ananassa. Acta Hortic. 2016; 1156:75-82

[42] Hardigan MA, Feldmann MJ, Lorant A. et al. Genome Synteny has been conserved among the Octoploid progenitors of cultivated strawberry over millions of years of evolution. Front Plant Sci. 2020; 10:1789

[43] Huang M, Liu X, Zhou Y. et al. BLINK: a package for the next level of genome-wide association studies with both individuals and markers in the millions. Gigascience. 2019; 8:1-12

[44] Wang J, Zhang Z. GAPIT version 3: boosting power and accuracy for genomic association and prediction. Genomics Proteomics Bioinformatics. 2021; 19:629-40

[45] Barrett JC, Fry B, Maller J. et al. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005; 21:263-5

[46] Suh JH, Guha A, Wang Z. et al. Metabolomic analysis elucidates how shade conditions ameliorate the deleterious effects of greening (Huanglongbing) disease in citrus. Plant J. 2021; 108:1798-814

[47] Dahl WJ, Hung WL, Ford AL. et al. In older women, a high-protein diet including animal-sourced foods did not impact serum levels and urinary excretion of trimethylamine-N-oxide. Nutr Res. 2020; 78:72-81

[48] Bernardini C, Santi S, Mian G. et al. Increased susceptibility to chrysanthemum yellows phytoplasma infection in Atcals7ko plants is accompanied by enhanced expression of carbohydrate transporters. Planta. 2022; 256:43

[49] Fan Z, Tieman DM, Knapp SJ. et al. A multi-omics framework reveals strawberry flavor genes and their regulatory elements. New Phytol. 2022; 236:1089-107

[50] Zhou X, Stephens M. Genome-wide efficient mixed-model analysis for association studies. Nat Genet. 2012; 44:821-4

[51] Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014; 30:1312-3