Dissecting the genetic basis of relevant fruit quality traits in interspecific grapevines (Vitis spp.)

Venkateswara Rao Kadium , Ramesh Pilli , Andrej Svyantek , Zhuoyu Wang , John Stenger , Rajasekharreddy Bhoomireddy , Collin Auwarter , Xuehui Li , Harlene Hatterman-Valenti

Horticulture Research ›› 2026, Vol. 13 ›› Issue (4) : 353

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Horticulture Research ›› 2026, Vol. 13 ›› Issue (4) :353 DOI: 10.1093/hr/uhaf353
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Dissecting the genetic basis of relevant fruit quality traits in interspecific grapevines (Vitis spp.)
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Abstract

Understanding the genetic control of fruit composition traits in interspecific grapevines ( Vitis spp.) is crucial when breeding new cultivars with desirable fruit chemistry. To address this, a genome-wide association study (GWAS) was conducted using 587 genotypes derived from three elite selections. This study spanned 3 years (2020–2022) and with phenotyping conducted at three different timepoints within each season for a total of nine phenotyping events focused on nine fruit traits. Several strong and stable quantitative trait locus (QTL) associations were identified on chromosomes 6, 16, and 17 across multiple phenotyping events for most sugar- and acid-related traits. Notably, putative sugar transporter genes Vitvi16g00860 and Vitvi16g00861 on chromosome 16, which facilitate the movement of sugars and K + ions across membranes, were found to be associated with all sugar and acid traits studied. Additionally, several QTLs on chromosomes 1–5, 7, 14, and 18 were identified for various fruit quality traits across different phenotyping events. We determined functional connections between traits and scrutinized candidate genes by utilizing gene ontology annotations for genes located near significant SNPs. We also highlighted the effect of different forms of phenotype (best linear unbiased predictions and unmodified) in suppressing certain QTL associations. This GWAS study focused on fruit quality in grapes, establishing a necessary knowledge base regarding the genetic architecture of these traits to aid molecular breeders in further improving them.

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Venkateswara Rao Kadium, Ramesh Pilli, Andrej Svyantek, Zhuoyu Wang, John Stenger, Rajasekharreddy Bhoomireddy, Collin Auwarter, Xuehui Li, Harlene Hatterman-Valenti. Dissecting the genetic basis of relevant fruit quality traits in interspecific grapevines (Vitis spp.). Horticulture Research, 2026, 13 (4) : 353 DOI:10.1093/hr/uhaf353

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Acknowledgements

Field planting and training of grapevine plants was conducted with support from R. Ibrahim, N. Theisen, M. Brooke, I. Tatar, S. Bogenrief, B. Rana, M. Mzumura, B. Köse, and numerous students of the High Value Crops research team. Genotype data for GBS was generated with logistical support from Justin Hegstad. GBS genotyping and phenotypic data collection were supported by the USDA Specialty Crop Block Grant award ‘Identification of Economically Important Fruit Quality Traits in Diverse Grapevine Genotypes for Elite Germplasm Development’, award #2019-NOGA19-438. rhAmpSeq marker development was done with the support of Vitisgen2. Funding for VitisGen ‘Accelerating grape cultivar improvement via phenotyping centers and next generation markers’ is provided by a Specialty Crop Research Initiative Competitive Grant, Award No. 2011-51181-38240, of the USDA National Institute of Food and Agriculture.

Author contributions

V.R.K. conducted the experiment, executed data analysis, and drafted the manuscript; J.S., A.S., and H.H.-V. conceived the study; H.H.V., X.L., and A.S. obtained funding; V.R.K., R.P., A.S., Z.W., and C.A. helped in data collection; X.L. prepared genotype data; All authors participated in the discussion of the results, reviewed the manuscript, and contributed to the article’s development. The submitted version of the article has been approved by all authors.

Data availability

The data underlying the findings presented in this article are available in the Figshare repository. The phenotype (https://doi.org/10.6084/m9.figshare.29299808.v1), genotype (https://doi.org/10.6084/m9.figshare.29300051.v1), and the QTL genetic map data files (http://doi.org/10.6084/m9.figshare.30494765.v1) can be accessed using assigned DOIs.

Conflicts of interest statement

The authors have no conflicts of interest to declare.

Supplementary material

Supplementary material is available at Horticulture Research online.

References

[1]

Statistics | FAO | Food and Agriculture Organization of the United Nations, (n.d.). https://www.fao.org/statistics/en/ (accessed June 14, 2024)

[2]

Rice AC . Chemistry of winemaking from native American grape varieties. In: Webb AD (ed.), Chemistry of Winemaking; Advances in Chemistry Vol 137. Washington, DC: American Chemical Society, 1974, 88-115

[3]

DeBolt S, Ristic R, Iland PG. et al. Altered light interception reduces grape berry weight and modulates organic acid biosynthesis during development. Horts. 2008; 43: 957-61

[4]

Chen J, Wang N, Fang L-C. et al. Construction of a high-density genetic map and QTLs mapping for sugars and acids in grape berries. BMC Plant Biol. 2015; 15: 28

[5]

Conde C, Silva P, Fontes N. et al. Biochemical changes throughout grape berry development and fruit and wine quality. Food. 2006; 9: 11

[6]

C.R. Hale , Relation between potassium and the malate and tartrate contents of grape berries, Vitis - Berichte Ueber Rebenforschung Mit Dokumentation Der Weinbauforschung (Germany, F.R.) 16 (1977). https://agris.fao.org/search/en/providers/122514/records/64711f7b9dd8810bf64c14cf (accessed June 6, 2024)

[7]

Kliewer WM . Changes in concentration of glucose, fructose, and total soluble solids in flowers and berries of Vitis vinifera . Am J Enol Vitic. 1965; 16: 101-10

[8]

Jones GV, White MA, Cooper OR. et al. Climate change and global wine quality. Clim Chang. 2005; 73: 319-43

[9]

Köse B, Svyantek A, Kadium VR. et al. Death and dying: grapevine survival, cold hardiness, and BLUPs and winter BLUEs in North Dakota vineyards. Life . 2024; 14: 178

[10]

Svyantek A, Köse B, Stenger J. et al. Cold-hardy grape cultivar winter injury and trunk re-establishment following severe weather events in North Dakota. Horticulturae. 2020; 6: 75

[11]

Svyantek A, Stenger J, Auwarter C. et al. This is how we chill from ‘23 ‘til: breeding cold hardy grapevines for unprecedented and unpredictable climate challenges. Acta Hortic. 2024; 1: 127-38

[12]

Savadi S, Mangalassery S, Sandesh MS . Advances in genomics and genome editing for breeding next generation of fruit and nut crops. Genomics . 2021; 113: 3718-34

[13]

Migicovsky Z, Sawler J, Gardner KM. et al. Patterns of genomic and phenomic diversity in wine and table grapes. Hortic Res. 2017; 4: 17035

[14]

Adam-Blondon A-F, Martinez-Zapater J-M, Kole C , eds. Genetics, Genomics, and Breeding of Grapes . Boca Raton: CRC Press; 2011:

[15]

Edge-Garza DA, Luby JJ, Peace C . Decision support for cost-efficient and logistically feasible marker-assisted seedling selection in fruit breeding. Mol Breeding. 2015; 35: 223

[16]

Yang S, Fresnedo-Ramírez J, Sun Q. et al. Next generation mapping of enological traits in an F2 interspecific grapevine hybrid family. PLoS One . 2016; 11: e0149560

[17]

Ban Y, Mitani N, Sato A. et al. Genetic dissection of quantitative trait loci for berry traits in interspecific hybrid grape (Vitis labruscana × Vitis vinifera) . Euphytica. 2016; 211: 295-310

[18]

Mamani M, López ME, Correa J. et al. Identification of stable quantitative trait loci and candidate genes for sweetness and acidity in table grape using a highly saturated single-nucleotide polymorphism-based linkage map. Aust J Grape Wine Res. 2021; 27: 308-24

[19]

Negus KL, Chen L-L, Fresnedo-Ramírez J. et al. Identification of QTLs for berry acid and tannin in a Vitis aestivalis-derived ‘Norton’-based population . Fruit Res. 2021; 1: 1-11

[20]

Viana AP, Riaz S, Walker MA . Genetic dissection of agronomic traits within a segregating population of breeding table grapes. Genet Mol Res . 2013; 12: 951-64

[21]

Cardon LR, Bell JI . Association study designs for complex diseases. Nat Rev Genet. 2001; 2: 91-9

[22]

Zhu C, Gore M, Buckler ES. et al. Status and prospects of association mapping in plants. Plant Genome. 2008; 6: 20

[23]

Myles S, Peiffer J, Brown PJ. et al. Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell . 2009; 21: 2194-202

[24]

Skovbjerg CK, Sarup P, Wahlström E. et al. Multi-population GWAS detects robust marker associations in a newly established six-rowed winter barley breeding program. Heredity. 2025; 134: 33-48

[25]

Osorio-Guarín JA, Garzón-Martínez GA, Delgadillo-Duran P. et al. Genome-wide association study (GWAS) for morphological and yield-related traits in an oil palm hybrid (Elaeis oleifera x Elaeis guineensis) population. BMC Plant Biol. 2019; 19: 533

[26]

Flutre T, Le Cunff L, Fodor A. et al. A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs. G3 (Bethesda). 2022; 12: jkac103

[27]

García-Abadillo J, Barba P, Carvalho T. et al. Dissecting the complex genetic basis of pre and post-harvest traits in Vitis vinifera L. using genome-wide association studies . Hortic Res. 2024; 11: uhad283

[28]

Guo D-L, Zhao H-L, Li Q. et al. Yu, genome-wide association study of berry-related traits in grape [Vitis vinifera L.] based on genotyping-by-sequencing markers . Hortic Res. 2019; 6: 11

[29]

Thorat KD, Upadhyay A, Samarth RR. et al. Genome-wide association analysis to identify genomic regions and predict candidate genes for bunch traits in grapes (Vitis vinifera L.) . Sci Hortic. 2024; 328: 112882

[30]

Zhang C, Cui L, Fang J . Genome-wide association study of the candidate genes for grape berry shape-related traits. BMC Plant Biol. 2022; 22: 42

[31]

Fournier-Level A, Le Cunff L, Gomez C. et al. Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study . Genetics. 2009; 183: 1127-39

[32]

Sun L, Li S, Jiang J. et al. New quantitative trait locus (QTLs) and candidate genes associated with the grape berry color trait identified based on a high-density genetic map. BMC Plant Biol. 2020; 20: 302

[33]

Scott MF, Ladejobi O, Amer S. et al. Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding. Heredity. 2020; 125: 396-416

[34]

Korte A, Farlow A . The advantages and limitations of trait analysis with GWAS: a review. Plant Methods. 2013; 9: 29

[35]

Jun Im D . Genome-Wide Association Study on Berry Traits of Table Grapes . M.Sc. Thesis. Seoul Nat’l Univ. Seoul, Korea. 2020; 5: 42

[36]

Liu S, Zou W, Lu X. et al. Genome-wide association study using a multiparent advanced generation intercross (MAGIC) population identified QTLs and candidate genes to predict shoot and grain zinc contents in rice. Agriculture. 2021; 11: 70

[37]

Zhang Y, Zeng Z, Tuo F. et al. Genome-wide association analysis of four yield-related traits using a maize (Zea mays L.) F1 population. PLoS One. 2024; 19: e0305357

[38]

Li W, Boer MP, Zheng C. et al. An IBD-based mixed model approach for QTL mapping in multiparental populations. Theor Appl Genet. 2021; 134: 3643-60

[39]

Chen H, Naseri A, Zhi D . FiMAP: a fast identity-by-descent mapping test for biobank-scale cohorts. PLoS Genet. 2023; 19: e1011057

[40]

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: giy154

[41]

Amato A, Cardone MF, Ocarez N. et al. VviAGL11 self-regulates and targets hormone- and secondary metabolism-related genes during seed development. Hortic Res. 2022; 9: uhac133

[42]

Zou C, Karn A, Reisch B. et al. Haplotyping the Vitis collinear core genome with rhAmpSeq improves marker transferability in a diverse genus. Nat Commun. 2020; 11: 413

[43]

Molenaar H, Boehm R, Piepho H-P . Phenotypic selection in ornamental breeding: it’s better to have the BLUPs than to have the BLUEs. Front Plant Sci . 2018; 1: 14

[44]

Tello J, Ibáñez J . Review: status and prospects of association mapping in grapevine. Plant Sci. 2023; 327: 111539

[45]

Bernardo RN . Breeding for Quantitative Traits in Plants . Third ed. Woodbury, Minnesota: Stemma Press; 2020:

[46]

Ren R, Yue X, Li J. et al. Coexpression of sucrose synthase and the SWEET transporter, which are associated with sugar hydrolysis and transport, respectively, increases the hexose content in Vitis vinifera L. grape berries . Front Plant Sci. 2020; 1: 15

[47]

Ludewig F, Flügge U-I . Role of metabolite transporters in source-sink carbon allocation. Front Plant Sci. 2013; 1: 16

[48]

Kennedy J . Understanding berry development. Practical Winery and Vineyard. 2002; 1: 5

[49]

Bayo-Canha A, Costantini L, Fernández-Fernández JI. et al. QTLs related to berry acidity identified in a wine grapevine population grown in warm weather. Plant Mol Biol Report. 2019; 37: 157-69

[50]

Afoufa-Bastien D, Medici A, Jeauffre J. et al. The Vitis vinifera sugar transporter gene family: phylogenetic overview and macroarray expression profiling . BMC Plant Biol. 2010; 10: 245

[51]

Xin H, Zhang J, Zhu W. et al. The effects of artificial selection on sugar metabolism and transporter genes in grape. Tree Genet Genomes . 2013; 9: 1343-9

[52]

Alahakoon D, Fennell A, Helget Z. et al. Berry anthocyanin, acid, and volatile trait analyses in a grapevine-interspecific F2 population using an integrated GBS and rhAmpSeq genetic map. Plants. 2022; 11: 696

[53]

Duchêne É, Dumas V, Butterlin G. et al. Genetic variations of acidity in grape berries are controlled by the interplay between organic acids and potassium. Theor Appl Genet . 2020; 133: 993-1008

[54]

Taiz L . The plant vacuole. J Exp Biol. 1992; 172: 113-22

[55]

Terrier N, Sauvage F-X, Ageorges A. et al. Changes in acidity and in proton transport at the tonoplast of grape berries during development. Planta. 2001; 213: 20-8

[56]

Lu L, Delrot S, Liang Z . From acidity to sweetness: a comprehensive review of carbon accumulation in grape berries. Mol Hortic. 2024; 4: 22

[57]

Monder H, Maillard M, Chérel I. et al. Adjustment of K+ fluxes and grapevine defense in the face of climate change. Int J Mol Sci. 2021; 22: 10398

[58]

Reshef N, Karn A, Manns DC. et al. Stable QTL for malate levels in ripe fruit and their transferability across Vitis species. Hortic Res. 2022; 9: uhac009

[59]

Sweetman C, Deluc LG, Cramer GR. et al. Regulation of malate metabolism in grape berry and other developing fruits. Phytochemistry . 2009; 70: 1329-44

[60]

R.R. Gawel , A.J.W. Ewart , R. Cirami , Effect of Root Stock on Must and Wine Composition and the Sensory Properties of Cabernet Sauvignon Grown at Langhorne Creek, South Australia , (2000). https://digital.library.adelaide.edu.au/dspace/handle/2440/32458 (accessed June 17, 2024).

[61]

Malabarba J, Buffon V, Mariath JEA. et al. Manipulation of VviAGL11 expression changes the seed content in grapevine (Vitis vinifera L.) . Plant Sci. 2018; 269: 126-35

[62]

Zarouri B . Association Study of Phenology, Yield and Quality Related Traits in Table Grapes Using SSR and SNP Markers PhD Thesis,. Universidad Politécnica de Madrid; 2016

[63]

Rogiers SY, Coetzee ZA, Walker RR. et al. Potassium in the grape (Vitis vinifera L.) berry: transport and function . Front Plant Sci. 2017; 1: 19

[64]

Shen Y-Y, Duan C-Q, Liang X-E. et al. Membrane-associated protein kinase activities in the developing mesocarp of grape berry. J Plant Physiol. 2004; 161: 15-23

[65]

Iland P, Bruer N, Edwards G. et al. Chemical Analysis of Grapes and Wines, 2nd ed. Campbelltown, South Australia: Patrick Iland Wine Promotions Pty Ltd., 2013

[66]

Mazza G, Fukumoto L, Delaquis P. et al. Anthocyanins, phenolics, and color of cabernet franc, merlot, and pinot noir wines from British Columbia. J Agric Food Chem. 1999; 47: 4009-17

[67]

Poland JA, Brown PJ, Sorrells ME. et al. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS One. 2012; 7: e32253

[68]

Glaubitz JC, Casstevens TM, Lu F. et al. TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline. PLoS One. 2014; 9: e90346

[69]

Karn A, Zou C, Brooks S. et al. Discovery of the REN11 locus from Vitis aestivalis for stable resistance to grapevine powdery mildew in a family segregating for several unstable and tissue-specific quantitative resistance loci . Front Plant Sci. 2021; 3: 4

[70]

Rastas P . Lep-MAP3: robust linkage mapping even for low-coverage whole genome sequencing data. Bioinformatics. 2017; 33: 3726-32

[71]

Canaguier A, Grimplet J, Di Gaspero G. et al. A new version of the grapevine reference genome assembly (12X.v2) and of its annotation (VCost.v3). Genom Data. 2017; 14: 56-62

[72]

Remington DL, Thornsberry JM, Matsuoka Y. et al. Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc Natl Acad Sci . 2001; 98: 11479-84

[73]

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

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