Identification and characterization of GLOBE, a major gene controlling fruit shape and impacting fruit size and marketability in tomato

Abstract

Within large-fruited germplasm, fruit size is influenced by flat and globe shapes. Whereas flat fruits are smaller and retain better marketability, globe fruits are larger and more prone to cuticle disorders. Commercial hybrids are often developed from crosses between flat and globe shaped parents because flat shape is thought to be dominant and fruit size intermediate. The objectives of this study were to determine the genetic basis of flat/globe fruit shape in large-fruited fresh-market tomato germplasm and to characterize its effects on several fruit traits. Twenty-three advanced single plant selections from the Fla. 8000 × Fla. 8111B cross were selectively genotyped using a genome-wide SNP array, and inclusive composite interval mapping identified a single locus on the upper arm of chromosome 12 associated with shape, which we termed globe. A 238-plant F₂ population and 69 recombinant inbred lines for this region from the same parents delimited globe to approximately 392-kilobases. A germplasm survey representing materials from multiple breeding programs demonstrated that the locus explains the flat/globe shape broadly. A single base insertion in an exon of Solyc12g006860, a gene annotated as a brassinosteroid hydroxylase, segregated completely with shape in all populations tested. CRISPR/Cas9 knock out plants confirmed this gene as underlying the globe locus. In silico analysis of the mutant allele of GLOBE among 595 wild and domesticated accessions suggested that the allele arose very late in the domestication process. Fruit measurements in three genetic backgrounds evidenced that globe impacts fruit size and several fruit shape attributes, pedicel length/width, and susceptibility of fruit to weather check. The mutant allele of GLOBE appears mostly recessive for all traits except fruit size where it acts additively.

References

[1] FAO. FAOSTAT. Value of Agricultural Production. Last update June 13, 2018 (2018). Accessed Oct 8. http://www.fao.org/faostat/en/#data/QV.

[2] USDA-NASS. Vegetables 2016 summary (2017).

[3] Causse, M. et al. Consumer preferences for fresh tomato at the European scale: a common segmentation on taste and firmness. J. Food Sci. 75, S531-S541 (2010).

[4] Simone, A. H., Bridget, B. K. & Marshal, M. M. Consumers prefer low-priced and high-lycopene-content fresh-market tomatoes. Hort. Technology 16, 674-681 (2006).

[5] Paran, I. & van der Knaap, E. Genetic and molecular regulation of fruit and plant domestication traits in tomato and pepper. J. Exp. Bot. 58, 3841-3852 (2007).

[6] Tanksley, S. D. The genetic, developmental, and molecular basis of fruit size and shape variation in tomato. Plant Cell 16, S181-S189 (2004).

[7] Grandillo, S., Ku, H. M. & Tanksley, S. D. Identifying the loci responsible for natural variation in fruit size and shape in tomato. Theor. Appl. Genet. 99, 978-987 (1999).

[8] van der Knaap, E., Lippman, Z. B. & Tanskley, S. D. Extremely elongated tomato fruit controlled by four quantitative trait loci with epistatic interactions. Theor. Appl. Genet. 104, 241-247 (2002).

[9] Rodriguez, G. R. et al. Distribution of SUN, OVATE, LC, and FAS in the tomato germplasm and the relationship to fruit shape diversity. Plant Physiol. 156, 275-285 (2011).

[10] van der Knaap, E., Sanyal, A., Jackson, S. A. & Tanksley, S. D. High-resolution fine mapping and fluorescence in situ hybridization analysis of sun, a locus controlling tomato fruit shape, reveals a region of the tomato genome prone to DNA rearrangements. Genetics 168, 2127-2140 (2004).

[11] Xiao, H., Jiang, N., Schaffner, E., Stockinger, E. J. & van der Knaap, E. A retrotransposon-mediated gene duplication underlies morphological variation of tomato fruit. Science 319, 1527-1530 (2008).

[12] Wu, S., Xiao, H., Cabrera, A., Meulia, T. & van der Knaap, E. SUN regulates vegetative and reproductive organ shape y changing cell division patterns. Plant Physiol. 127, 1175-1186 (2011).

[13] Liu, J., Eck, J. V., Cong, B. & Tanksley, S. D. A new class of regulatory genes underlying the cause of pear-shaped tomato fruit. Proc. Natl Acad. Sci. USA 99, 13302-13306 (2002).

[14] Rodriguez, G. R., Kim, H. J. & van der Knaap, E. Mapping of two suppressors of OVATE (sov) loci in tomato. Heredity 111, 256-264 (2013).

[15] van der Knaap, E. et al. What lies beyond the eye: the molecular mechanisms regulating tomato fruit weight and shape. Front. Plant Sci. 5, 227 (2014).

[16] Lippman, Z. & Tanksley, S. D. Dissecting the genetic pathway to extreme fruit size in tomato using a cross between the small fruited wild species Lycopersicon pimpinellifolium and L. esculentum var. Giant Heirloom. Genetics 158, 413-422 (2001).

[17] Barrero, L. S. & Tanksley, S. D. Evaluating the genetic basis of multiple-locule fruit in a broad cross section of tomato cultivars. Theor. Appl. Genet. 109, 669-679 (2004).

[18] Barrero, L. S., Cong, B., Wu, F. & Tanksley, S. D. Developmental characterization of the fasciated locus and mapping of Arabidopsis candidate genes involved in the control of floral meristem size and carpel number in tomato. Genome 49, 991-1006 (2006).

[19] Muños, S. et al. Increase in tomato locule number is controlled by two single-nucleotide polymorphisms located near WUSCHEL. Plant Physiol. 156, 2244-2254 (2011).

[20] Xu, C. et al. A cascade of arabinosyltransferases controls shoot meristem size in tomato. Nat. Genet. 47, 784-792 (2015).

[21] Cong, B., Barrero, L. S. & Tanksley, S. D. Regulatory change in YABBY-like transcription factor led to evolution of extreme size during tomato domestication. Nat. Genet. 40, 800-804 (2008).

[22] Yuste-Lisbona, F. J. et al. ENO regulates tomato fruit size through the floral meristem development network. PNAS 117, 8187-8195 (2020).

[23] Frary, Anne et al. fw2.2: a quantitative trait locus key to the evolution of tomato fruit size. Science 289, 58-88 (2000).

[24] Cong, B., Lio, J. & Tanskley, S. D. Natural alleles at a tomato fruit size quantitative trait locus differ by heterochromatic regulatory mutations. PNAS 99, 13606-13611 (2002).

[25] Ito, T. & Meyerowitz, E. Overexpression of a gene encoding a cytochrome P450, CYP78A9, induces large and seedless fruit in Arabidopsis. Plant Cell 12, 1541-1550 (2000).

[26] Fang, W., Wang, Z., Cui, R., Li, J. & Li, Y. Maternal control of seed size by EOD3/CYP78A6 in Arabidopsis thaliana. Plant J. 70, 929-939 (2012).

[27] Chakrabarti, M. et al. A cytochrome P450 regulates a domestication trait in cultivated tomato. PNAS 110, 17125-17130 (2013).

[28] Alonge, M. et al. Major impacts of widespread structural variation on gene expression and crop improvement in tomato. Cell 182, 145-161.e23 (2020).

[29] Sun, L. et al. Candidate gene selection and detailed morphological evaluations of fs8.1, a quantitative trait locus controlling tomato fruit shape. J. Exp. Bot. 66, 6471-6482 (2015).

[30] Mu, Q. et al. Fruit weight is controlled by Cell Size Regulator encoding a novel protein that is expressed in maturing tomato fruits. PLOS Genet. 13, e1006930 (2017).

[31] Blanca, J. et al. Genomic variation in tomato, from wild ancestors to contemporary breeding accessions. BMC Genom. 16, 257 (2015).

[32] Gardner, R. G. ‘Carolina Gold’, a hybrid tomato, and its parents, NC 1Y and NC2Y. Hort. Science 35, 966-967 (2000).

[33] Scott, J. W. et al. ‘Solar Fire’ hybrid tomato: Fla. 7776 tomato breeding line. Hort. Science 41, 1504-1505 (2006).

[34] Panthee, D. R. & Gardner, R. G. ‘Mountain Majesty’: a tomato spotted wilt virus-resistant fresh-marker hybrid tomato and its parents NC 714 and NC 1CS. Hort. Science 46, 1321-1323 (2011).

[35] Brewer, M. T., Moyseenko, J. B., Monforte, A. J. & van der Knaap, E. Morphological variation in tomato: a comprehensive study of quantitative trait loci controlling fruit shape and development. J. Exp. Bot. 58, 1339-1349 (2007).

[36] Gonzalo, M. K. & van der Knaap, E. A comparative analysis into the genetic bases of morphology in tomato varieties exhibiting elongated fruit shape. Theor. Appl. Genet. 116, 647-656 (2008).

[37] Bishop, G. & Yokota, T. Plant steroid hormones, brassinosteroids: current highlights of molecular aspects on their synthesis/metabolism, transport, perception and response. Plant Cell Physiol. 42, 114-120 (2001).

[38] Ohnishi, T. et al. Tomato cytochrome P450 CYP734A7 functions in brassinosteroid catabolism. Phytochemestry 67, 189-1906 (2006).

[39] Anastasiou, E. et al. Control of plant organ size by KLUH/CYP78A5-dependent intercellular signaling. Dev. Cell 13, 846-856 (2007).

[40] Shinozaki, Y. et al. High-resolution spatiotemporal transcriptome mapping of tomato fruit development and ripening. Nat. Commun. 9, 364 (2018).

[41] Zhang, N., Brewer, M. & van der Knaap, E. Fine mapping of fw3.2 controlling fruit weight in tomato. Theor. Appl. Genet. 125, 273-284 (2012).

[42] Fulton, M., Chunwongse, J. & Tanksley, S. Microprep protocol for extraction of DNA from tomato and other herbaceous plants. Plant Mol. Biol. Report. 13, 207-209 (1995).

[43] Lee et al. A high-throughput genotyping system combining rapid DNA extraction and high-resolution melting analysis in allo-octoploid strawberry. Acta Horticulturae 1156, 89-94 (2016).

[44] Lee, T. G., Shekasteband, R., Menda, N., Mueller, L. A. & Hutton, S. F. Molecular markers to select for the j-2-mediated jointless pedicel in tomato. Hort. Science 53, 153-158 (2018).

[45] Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. arXiv:1207.3907 (2012).

[46] Buels, R. et al. JBrowse: a dynamic web platform for genome visualization and analysis. Genome Biol. 17, 66 (2016).

[47] Fernandez-Pozo, N. et al. The Sol Genomics Network (SGN)-from genotype to phenotype to breeding. Nucleic Acids Res. 43, D1036-D1041 (2015).

[48] Sim, S. C. et al. Development of a large SNP genotyping array and generation of high-density genetic maps in tomato. PLoS ONE 7, e40563 (2012).

[49] Kosambi, D. D. The estimation of map distances from recombination values. Ann. Eugen. 12, 172-175 (1944).

[50] van Ooijen, J. W. JoinMap® 4, software for the calculation of genetic linkage maps in experimental populations. Kyazma BV, Wageningen, Netherlands (2006).

[51] Li, H., Ye, G. & Wang, J. A modified algorithm for the improvement of composite interval mapping. Genetics 175, 361-374 (2007).

[52] Wang, J., Li, H., Zhang, L. & Meng, L. Users’ Manual of QTL IciMapping. The Quantitative Genetics Group, Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China, and Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico (2016).

[53] Lei, Y. et al. CRISPR-P: a web tool for synthetic single-guide RNA design of CRISPR-system in plants. Mol. Plant 7, 1494-1496 (2014).

[54] Jacobs, T. B., LaFayette, P. R., Schmitz, R. J. & Parrot, W. A. Targeted genome modifications in soybean with CRISPR/Cas9. BMC Biotechnol. 15, 16 (2015).

[55] Gupta, S. & Van Eck, J. Modification of plant regeneration medium decreases the time for recovery of Solanum lycopersicum cultivar M82 stable transgenic lines. Plant Cell Tissue Organ Cult. 127, 417-423 (2016).

[56] Brewer, M. T. et al. Development of a controlled vocabulary and software application to analyze fruit shape variation in tomato and other plant species. Plant Physiol. 141, 15-25 (2006).

[57] Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389-3402 (1997).

[58] Aflitos, S. et al. Exploring genetic variation in the tomato (Solanum section Lycopersicon) clade by whole-genome sequencing. Plant J. 80, 136-148 (2014).

[59] Lin, T. et al. Genomic analyses provide insights into the history of tomato breeding. Nat. Genet 46, 1220-1226 (2014).

[60] Razifad, H. et al. Genomic evidence for complex domestication history of the cultivated tomato in Latin America. Mol. Biol. Evol. 37, 1118-1132 (2020).

[61] Blouin, D. C., Webster, E. P. & Bond, J. A. On the analysis of combined experiments. Weed Technol. 25, 165-169 (2011).

[62] R Core Team . R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2017).

[63] Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1-48 (2015).

[64] Lenth, R. V. Least-squares means: the R package lsmeans. J. Stat. Softw. 69, 1-33 (2016).