Loss-of-function mutations in the fruit softening gene POLYGALACTURONASE1 doubled fruit firmness in strawberry

Abstract

Wildtype fruit of cultivated strawberry (Fragaria × ananassa) are typically soft and highly perishable when fully ripe. The development of firm-fruited cultivars by phenotypic selection has greatly increased shelf-life, decreased postharvest perishability, and driven the expansion of strawberry production worldwide. Hypotheses for the firm-fruited phenotype include mutations affecting the expression of genes encoding polygalacturonases (PGs) that soften fruit by degrading cell wall pectins. Here we show that loss-of-function mutations in the fruit softening gene POLYGALACTURONASE1 (FaPG1; PG1-6A1) double fruit firmness in strawberry. PG1-6A1 was one of three tandemly duplicated PG genes found to be in linkage disequilibrium (LD) with a quantitative trait locus (QTL) affecting fruit firmness on chromosome 6A. PG1-6A1 was strongly expressed in soft-fruited (wildtype) homozygotes and weakly expressed in firm-fruited (mutant) homozygotes. Genome-wide association, quantitative trait transcript, DNA sequence, and expression-QTL analyses identified genetic variants in LD with PG1-6A1 that were positively correlated with fruit firmness and negatively correlated with PG1-6A1 expression. An Enhancer/Suppressor-mutator (En/Spm) transposable element insertion was discovered upstream of PG1-6A1 in mutant homozygotes that we hypothesize transcriptionally downegulates the expression of PG1-6A1. The PG1-6A1 locus was incompletely dominant and explained 26-76% of the genetic variance for fruit firmness among phenotypically diverse individuals. Additional loci are hypothesized to underlie the missing heritability. Highly accurate codominant genotyping assays were developed for modifying fruit firmness by marker-assisted selection of the En/Spm insertion and single nucleotide polymorphisms associated with the PG1-6A1 locus.

Acknowledgments

We are grateful for the outstanding support of the field superintendents and staff at the UC Davis Wolfskill Experiment Orchard (Winters, CA), UC Davis Department of Plant Sciences (Davis, CA), and Good Farms (Ventura, CA). This research was supported by grants to S.J.K. from the United Stated Department of Agriculture (USDA) (http://dx.doi.org/10.13039/100000199) National Institute of Food and Agriculture (NIFA) Specialty Crops Research Initiative (SCRI) (#2017-51181B6833), S.J.K., M.J.F., D.D.A.P., and M.B. from the USDA NIFA SCRI (#2022-51181-38328-0), and S.J.K., G.S.C., M.J.F., D.D.A.P., and M.B. from the California Strawberry Commission (http://dx.doi.org/10.13039/100006760).

Author Contributions

N.P.J., M.B., S.J.K., M.J.F., M.A.H., and G.S.C. conceived, designed, and planned field and greenhouse experiments. G.S.C., C.M.L.R., N.P.J., and M.A.M. conducted field and greenhouse studies. N.P.J., R.A.F., D.D.A.P., M.A.M., and M.B. collected and curated phenotypic, genotypic, and DNA and RNA sequence data. N.P.J., M.B., M.J.F., M.A.H., D.D.A.P., and S.J.K. conceived, conducted, and interpreted statistical and bioinformatic analyses. N.P.J, S.J.K., and M.J.F. drafted the manuscript. N.P.J., S.J.K., M.J.F., M.B., D.D.A.P, and G.S.C. revised the manuscript.

Data availability

The phenotypic and genotypic data and supplemental material for these studies are available in a DRYAD repository (10.5061/dryad.k3j9kd5hk). The long-read DNA sequences developed for this study have been deposited in the National Center for Biotechnology Information Sequence Read Archive under Bioproject #PRJNA1128720 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1128720).

Conflict of interest statement:

The authors declare no conflicts of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

References

[1] Fletcher SW. Strawberry-Growing. New York: The Macmillan Company; 1917

[2] Darrow GM. The Strawberry:History, Breeding, and Physiology.New York: Holt, Rinehart, and Winston; 1966

[3] Lawrence F, Galletta G, Scott D. Strawberry breeding work of the US Department of Agriculture. HortScience. 1990;25:895-6

[4] Shaw DV, Larson KD. Performance of early-generation and modern strawberry cultivars from the University of California breeding programme in growing systems simulating traditional and modern horticulture. J Hortic Sci Biotechnol. 2008;83:648-52

[5] Feldmann MJ, Pincot DDA, Cole GS. et al. Genetic gains under-pinning a little-known strawberry green revolution. Nat Com-mun. 2024a;15:2468

[6] Hancock J, Callow P, Dale A. et al. From the Andes to the Rock-ies: native strawberry collection and utilization. HortScience. 2001a;36:221-5

[7] Hancock J, Finn C, Hokanson S. et al. A multistate comparison of native octoploid strawberries from north and South America. J Am Soc Hortic Sci. 2001b;126:579-86

[8] Hancock JF, Finn CE, Luby JJ. et al. Reconstruction of the straw-berry, Fragaria × ananassa, using genotypes of F. virginiana and F. chiloensis. HortScience. 2010;45:1006-13

[9] Given N, Venis M, Gierson D. Hormonal regulation of ripening in the strawberry, a non-climacteric fruit. Planta. 1988;174:402-6

[10] Gu T, Jia S, Huang X. et al. Transcriptome and hormone anal-yses provide insights into hormonal regulation in strawberry ripening. Planta. 2019;250:145-62

[11] Symons G, Chua Y-J, Ross J. et al. Hormonal changes during non-climacteric ripening in strawberry. JExp Bot. 2012;63:4741-50

[12] Jouki M, Khazaei N. Effect of low-dose gamma radiation and active equilibrium modified atmosphere packaging on shelf life extension of fresh strawberry fruits. Food Packag Shelf Life. 2014;1:49-55

[13] Krivorot A, Dris R. Shelf life and quality changes of strawberry cultivars. Acta Hortic. 2002;567:755-8

[14] Matar C, Gaucel S, Gontard N. et al. Predicting shelf life gain of fresh strawberries ‘Charlotte cv’ in modified atmosphere packaging. Postharvest Biol Technol. 2018;142:28-38

[15] Shehata SA, Abdeldaym EA, Ali MR. et al. Effect of some citrus essential oils on post-harvest shelf life and physico-chemical quality of strawberries during cold storage. Agronomy. 2020;10:1466

[16] Petrasch S, Knapp SJ, Van Kan JA. et al. Grey mould of strawberry, a devastating disease caused by the ubiquitous necrotrophic fungal pathogen Botrytis cinerea. Mol Plant Pathol. 2019;20:877-92

[17] Petrasch S, Mesquida-Pesci SD, Pincot DDA. et al. Genomic prediction of strawberry resistance to postharvest fruit decay caused by the fungal pathogen Botrytis cinerea. G3. 2022; 12:jkab378

[18] Villarreal NM, Rosli HG, Martinez GA. et al. Polygalacturonase activity and expression of related genes during ripening of strawberry cultivars with contrasting fruit firmness. Posthar-vest Biol Technol. 2008;47:141-50

[19] Paniagua C, Sanchez-Raya C, Blanco-Portales R. et al. Silencing of FaPG1, a fruit specific polygalacturonase gene, decreased strawberry fruit fungal decay during postharvest. Biol Life Sci Forum. 2021;11:96

[20] Knapp SJ, Cole GS, Pincot DDA. et al. ‘UC Eclipse’, a sum-mer plant-adapted photoperiod-insensitive strawberry culti-var. HortScience. 2023;58:1568-72

[21] 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

[22] Lee H-E, Manivannan A, Lee SY. et al. Chromosome level assembly of homozygous inbred line ‘Wongyo 3115’ facili-tates the construction of a high-density linkage map and identification of QTLs associated with fruit firmness in octo-ploid strawberry ( Fragaria × ananassa). Front Plant Sci. 2021;12:696229

[23] Munoz P, Roldan-Guerra FJ, Verma S. et al. Genome-wide asso-ciation studies in a diverse strawberry collection unveil loci controlling agronomic and fruit quality traits. bioRxiv. 2024; 2024. 03.11.584394

[24] Prohaska A, Rey-Serra P, Petit J. et al. Exploration of a European-centered strawberry diversity panel provides markers and can-didate genes for the control of fruit quality traits. Hortic Res. 2024;11:uhae137

[25] Lopez-Casado G, Sánchez-Raya C, Ric-Varas PD. et al. CRISPR/Cas 9 editing of the polygalacturonase FaPG1 gene improves strawberry fruit firmness. Hortic Res. 2023;10:uhad011

[26] Paniagua C, Ric-Varas P, Garcia-Gago JA. et al. Elucidating the role of polygalacturonase genes in strawberry fruit softening. JExp Bot. 2020;71:7103-17

[27] Quesada MA, Blanco-Portales R, Pose S. et al. Antisense down-regulation of the FaPG1 gene reveals an unexpected central role for polygalacturonase in strawberry fruit softening. Plant Physiol. 2009;150:1022-32

[28] Paniagua C, Santiago-Domenech N, Kirby AR. et al. Structural changes in cell wall pectins during strawberry fruit develop-ment. Plant Physiol Biochem. 2017;118:55-63

[29] Pose S, Kirby AR, Paniagua C. et al. The nanostructural char-acterization of strawberry pectins in pectate lyase or poly-galacturonase silenced fruits elucidates their role in softening. Carbohydr Polym. 2015;132:134-45

[30] Posé S, Paniagua C, Cifuentes M. et al. Insights into the effects of polygalacturonase FaPG1 gene silencing on pectin matrix disassembly, enhanced tissue integrity, and firmness in ripe strawberry fruits. JExp Bot. 2013;64:3803-15

[31] Edger PP, Poorten TJ, VanBuren R. et al. Origin and evolu-tion of the octoploid strawberry genome. Nat Genet. 2019;51:541-7

[32] Hardigan MA, Lorant A, Pincot DDA. et al. Unraveling the com-plex hybrid ancestry and domestication history of cultivated strawberry. Mol Biol Evol. 2021a;38:2285-305

[33] Hardigan MA, Feldmann MJ, Lorant A. et al. Genome synteny has been conserved among the octoploid progenitors of culti-vated strawberry over millions of years of evolution. Front Plant Sci. 2020;10:1789

[34] Hardigan MA, Feldmann MJ, Pincot DDA. et al. Blueprint for phasing and assembling the genomes of heterozygous poly-ploids: application to the octoploid genome of strawberry. bioRxiv. 2021; 2021. 11.03.467115

[35] Albert FW, Kruglyak L. The role of regulatory variation in complex traits and disease. Nat Rev Genet. 2015;16:197-212

[36] Gilad Y, Rifkin SA, Pritchard JK. Revealing the architecture of gene regulation: the promise of eQTL studies. Trends Genet. 2008;24:408-15

[37] Kliebenstein D. Quantitative genomics: analyzing intraspe-cific variation using global gene expression polymorphisms or eQTLs. Annu Rev Plant Biol. 2009;60:93-114

[38] Lappalainen T, Sammeth M, Friedländer MR. et al. Transcrip-tome and genome sequencing uncovers functional variation in humans. Nature. 2013;501:506-11

[39] Zhang F-T, Zhu Z-H, Tong X-R. et al. Mixed linear model approaches of association mapping for complex traits based on omics variants. Sci Rep. 2015;5:10298

[40] Hill MS, Vande Zande P, Wittkopp PJ. Molecular and evolution-ary processes generating variation in gene expression. Nat Rev Genet. 2021;22:203-15

[41] Feschotte C, Keswani U, Ranganathan N. et al. Exploring repetitive DNA landscapes using REPCLASS, a tool that auto-mates the classification of transposable elements in eukaryotic genomes. Genome Biol Evol. 2009;1:205-20

[42] Liu T, Li M, Liu Z. et al.Reannotation of the cultivated straw-berry genome and establishment of a strawberry genome database. Hortic Res. 2021;8:41

[43] Salzberg SL. Next-generation genome annotation: we still struggle to get it right. Genome Biol. 2019;20:92

[44] Koonin EV. Orthologs, paralogs, and evolutionary genomics. Annu Rev Genet. 2005;39:309-38

[45] Session AM, Rokhsar DS. Transposon signatures of allopoly-ploid genome evolution. Nat Commun. 2023;14:3180

[46] Shulaev V, Sargent DJ, Crowhurst RN. et al. The genome of woodland strawberry (Fragaria vesca). Nat Genet. 2011;43:109-16

[47] Edger PP, VanBuren R, Colle M. et al. Single-molecule sequenc-ing and optical mapping yields an improved genome of woodland strawberry (Fragaria vesca) with chromosome-scale contiguity. Gigascience. 2018;7:1-7

[48] Guo J, Wang S, Yu X. et al. Polyamines regulate strawberry fruit ripening by abscisic acid, auxin, and ethylene. Plant Physiol. 2018;177:339-51

[49] Pincot DDA, Ledda M, Feldmann MJ. et al. Social network anal-ysis of the genealogy of strawberry: retracing the wild roots of heirloom and modern cultivars. G3. 2021;11:jkab015

[50] Cingolani P, Platts A, Coon M. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012b;6:80-92

[51] Cingolani P, Patel VM, Coon M. et al. Using Drosophila melanogaster as a model for genotoxic chemical mutational studies with a new program, SnpSift. Front Genet. 2012a;3:35

[52] Bennetzen JL. Transposable element contributions to plant gene and genome evolution. Plant Mol Biol. 2000;42:251-69

[53] Bennetzen JL, Wang H. The contributions of transposable elements to the structure, function, and evolution of plant genomes. Annu Rev Plant Biol. 2014;65:505-30

[54] McClintock B. The origin and behavior of mutable loci in maize. Proc Natl Acad Sci USA. 1950;36:344-55

[55] McClintock B. Controlling elements and the gene. Cold Spring Harb Symp Quant Biol. 1956;21:197-216

[56] Feschotte C, Jiang N, Wessler SR. Plant transposable elements: where genetics meets genomics. Nat Rev Genet. 2002;3:329-41

[57] Wessler SR. Phenotypic diversity mediated by the maize trans-posable elements Ac and Spm. Science. 1988;242:399-405

[58] Feldmann MJ, Pincot DDA, Hardigan MA. et al. A dominance hypothesis argument for historical genetic gains and the fix-ation of heterosis in octoploid strawberry. Genetics. 2024b; iyae159

[59] Paniagua C, Blanco-Portales R, Barceló-Muñoz M. et al. Anti-sense down-regulation of the strawberry β-galactosidase gene FaβGal4 increases cell wall galactose levels and reduces fruit softening. JExp Bot. 2016;67:619-31

[60] Ponce E, Núñez-Lillo G, Bravo C. et al. Cell wall disassem-bly, metabolome and transcriptome analysis in sweet cherry fruit with induced surface pitting. Postharvest Biol Technol. 2023;198:112262

[61] Jung C, Nguyen NH, Cheong J.Transcriptional regulation of pro-tein phosphatase 2C genes to modulate abscisic acid signaling. Int J Mol Sci. 2020;21:9517

[62] Zhou XE, Soon F, Ng L. et al. Catalytic mechanism and kinase interactions of ABA-signaling PP2C phosphatases. Plant Signal Behav. 2012;7:581-8

[63] Ahn SY, Kim SA, Yun HK. Differentially expressed genes during berry ripening in de novo RNA assembly of Vitis flexuosa fruits. Hortic Environ Biotechnol. 2019;60:531-53

[64] Soares CG, SBR d P, SCS A. et al. Systems biology applied to the study of papaya fruit ripening: the influence of ethylene on pulp softening. Cells. 2021;10:2339

[65] Xiong J, Liu Y, Wu P. et al. Identification and virus-induced gene silencing (VIGS) analysis of methyltransferase affecting tomato (Solanum lycopersicum) fruit ripening. Planta. 2024;259:109

[66] Hölzle A, Jonietz C, Törjek O. et al. A RESTORER OF FERTILITY-like PPR gene is required for 5’-end processing of the nad4 mRNA in mitochondria of Arabidopsis thaliana. Plant J. 2011;65:737-44

[67] Nakagawa N, Sakurai N. A mutation in At-nMat1a,which encodes a nuclear gene having high similarity to group II intron maturase, causes impaired splicing of mitochondrial NAD 4 transcript and altered carbon metabolism in Arabidopsis thaliana. Plant Cell Physiol. 2006;47:772-83

[68] Salentijn EMJ, Aharoni A, Schaart JG. et al. Differential gene expression analysis of strawberry cultivars that differ in fruit-firmness. Physiol Plant. 2003;118:571-8

[69] Doebley JF, Gaut BS, Smith BD. The molecular genetics of crop domestication. Cell. 2006;127:1309-21

[70] Meyer RS, Purugganan MD. Evolution of crop species: genetics of domestication and diversification. Nat Rev Genet. 2013;14:840-52

[71] Rodriguez-Leal D, Lemmon ZH, Man J. et al. Engineering quanti-tative trait variation for crop improvement by genome editing. Cell. 2017;171:470-480.e8

[72] Zsögön A, Čermák T, Naves ER. et al. De novo domestication of wild tomato using genome editing. Nat Biotechnol. 2018;36:1211-6

[73] Hirsch CD, Springer NM. Transposable element influences on gene expression in plants. Biochim Biophys Acta Gene Regul Mech. 2017;1860:157-65

[74] Castillejo C, Waurich V, Wagner H. et al. Allelic variation of MYB 10 is the major force controlling natural variation in skin and flesh color in strawberry (Fragaria spp.) fruit. Plant Cell. 2020;32:3723-49

[75] Sánchez-Sevilla JF, Vallarino JG, Osorio S. et al. Gene expression atlas of fruit ripening and transcriptome assembly from RNA-seq data in octoploid strawberry ( Fragaria × ananassa). Sci Rep. 2017;7:13737

[76] 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

[77] Semagn K, Babu R, Hearne S. et al. Single nucleotide poly-morphism genotyping using Kompetitive allele specific PCR (KASP): overview of the technology and its application in crop improvement. Mol Breed. 2014;33:1-14

[78] Covarrubias-Pazaran G. Genome-assisted prediction of quan-titative traits using the R package sommer. PLoS One. 2016;11:e0156744

[79] Lenth R. emmeans: estimated marginal means, aka least-squares means. In: R package version 1.3.1. 2018,

[80] Abbott JA. Quality measurement of fruits and vegetables. Postharvest Biol Technol. 1999;15:207-25

[81] Bates D, Mächler M, Bolker B. et al. Fitting linear mixed-effects models using lme4. arXiv. 2014;1406.5823

[82] Endelman JB. Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome. 2011;4:250-5

[83] Mathew B, Léon J, Sillanpää MJ. A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction. Heredity. 2018;120:356-68

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

[85] Zhou X, Stephens M. Efficient multivariate linear mixed model algorithms for genome-wide association studies. Nat Methods. 2014;11:407-9

[86] Pincot DDA, Hardigan MA, Cole GS. et al. Accuracy of genomic selection and long-term genetic gain for resistance to verticillium wilt in strawberry. Plant Genome. 2020;13:e20054

[87] Feldmann MJ, Piepho H-P, Bridges WC. et al. Average semi-variance yields accurate estimates of the fraction of marker-associated genetic variance and heritability in complex trait analyses. PLoS Genet. 2021;17:e1009762

[88] Thorvaldsdóttir H, Robinson JT, Mesirov JP. Integrative genomics viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinformatics. 2013;14:178-92

[89] Paysan-Lafosse T, Blum M, Chuguransky S. et al. Interpro in 2022. Nucleic Acids Res. 2023;51:D418-27

[90] Zhang Z, Schwartz S, Wagner L. et al. A greedy algorithm for aligning DNA sequences. JComputBiol. 2000;7:203-14

[91] Jung S, Lee T, Cheng C-H. et al.15 years of GDR: new data and functionality in the genome database for Rosaceae. Nucleic Acids Res. 2019;47:D1137-45

[92] Tang H, Bowers JE, Wang X. et al. Synteny and collinearity in plant genomes. Science. 2008;320:486-8

[93] Altschul SF, Gish W, Miller W. et al. Basic local alignment search tool. J Mol Biol. 1990;215:403-10

[94] Madeira F, Pearce M, Tivey AR. et al. Search and sequence analysis tools services from EMBL-EBI in 2022. Nucleic Acids Res. 2022;50:W276-9

[95] Dobin A, Davis CA, Schlesinger F. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15-21

[96] Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139-40

[97] Aulchenko YS, Ripke S, Isaacs A. et al. GenABEL: an R library for genome-wide association analysis. Bioinformatics. 2007;23:1294-6

[98] Kolde R. Package ‘pheatmap’. In: Rpackage version 1.0.12. 2015,

[99] Barbier FF, Chabikwa TG, Ahsan MU. et al. A phenol/chloroform-free method to extract nucleic acids from recalci-trant, woody tropical species for gene expression and sequenc-ing. Plant Methods. 2019;15:62

[100] Inglis PW, Pappas MCR, Resende LV. et al. Fast and inexpensive protocols for consistent extraction of high quality DNA and RNA from challenging plant and fungal samples for high-throughput SNP genotyping and sequencing applications. PLoS One. 2018;13:e0206085

[101] Porebski S, Bailey LG, Baum BR. Modification of a CTAB DNA extraction protocol for plants containing high polysaccha-ride and polyphenol components. Plant Mol Biol Report. 1997; 15:8-15

[102] Untergasser A, Cutcutache I, Koressaar T. et al. Primer3—new capabilities and interfaces. Nucleic Acids Res. 2012;40:e115-5

[103] Galli V, Borowski JM, Perin EC. et al. Validation of reference genes for accurate normalization of gene expression for real time-quantitative pcr in strawberry fruits using different culti-vars and osmotic stresses. Gene. 2015;554:205-14

[104] Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics. 2018;34:3094-100

[105] Danecek P, Bonfield JK, Liddle J. et al. Twelve years of SAMtools and BCFtools. Gigascience. 2021;10:giab008

[106] Kohany O, Gentles AJ, Hankus L. et al. Annotation, submission and screening of repetitive elements in Repbase: RepbaseSub-mitter and Censor. Bioinformatics. 2006;7:474

[107] Poplin R, Chang P-C, Alexander D. et al. A universal SNP and small-indel variant caller using deep neural networks. Nat Biotechnol. 2018;36:983-7

[108] Shabalin AA. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics. 2012;28:1353-8

[109] Falconer DS, Mackay TFC.Introduction to Quantitative Genetics. Harlow, Essex, UK: Longmans Green; 1996:

[110] Walsh B. Quantitative genetics in the age of genomics. Theor Popul Biol. 2001;59:175-84