Rapid identification of causal mutations in tomato EMS populations via mapping-by-sequencing

Abstract

The tomato is the model species of choice for fleshy fruit development and for the Solanaceae family. Ethyl methanesulfonate (EMS) mutants of tomato have already proven their utility for analysis of gene function in plants, leading to improved breeding stocks and superior tomato varieties. However, until recently, the identification of causal mutations that underlie particular phenotypes has been a very lengthy task that many laboratories could not afford because of spatial and technical limitations. Here, we describe a simple protocol for identifying causal mutations in tomato using a mapping-by-sequencing strategy. Plants displaying phenotypes of interest are first isolated by screening an EMS mutant collection generated in the miniature cultivar Micro-Tom. A recombinant F2 population is then produced by crossing the mutant with a wild-type (WT; non-mutagenized) genotype, and F2 segregants displaying the same phenotype are subsequently pooled. Finally, whole-genome sequencing and analysis of allele distributions in the pools allow for the identification of the causal mutation. The whole process, from the isolation of the tomato mutant to the identification of the causal mutation, takes 6–12 months. This strategy overcomes many previous limitations, is simple to use and can be applied in most laboratories with limited facilities for plant culture and genotyping.

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Figure 1: An overview of the experimental design of forward genetics screening and detection of causal mutation by mapping-by-sequencing in tomato.
Figure 2: Two-step bioinformatic pipeline for analysis of whole-genome sequencing data.
Figure 3: Mapping-by-sequencing of Micro-Tom EMS mutants.
Figure 4: Mutation in the phytoene synthase gene PSY1 affects fruit metabolism.

References

  1. 1

    Tomato Genome Consortium. The tomato genome sequence provides insights into fleshy fruit evolution. Nature 485, 635–641 (2012).

  2. 2

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

    Article  PubMed  Google Scholar 

  3. 3

    Bolger, A. et al. The genome of the stress-tolerant wild tomato species Solanum pennellii. Nat. Genet. 46, 1034–1038 (2014).

    Article  CAS  PubMed  Google Scholar 

  4. 4

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

    Article  CAS  PubMed  Google Scholar 

  5. 5

    Kobayashi, M. et al. Genome-wide analysis of intraspecific DNA polymorphism in 'Micro-Tom', a model cultivar of tomato (Solanum lycopersicum). Plant Cell Physiol. 55, 445–454 (2014).

    Article  CAS  PubMed  Google Scholar 

  6. 6

    Eshed, Y. & Zamir, D. An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield-associated QTL. Genetics 141, 1147–1162 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Menda, N., Semel, Y., Peled, D., Eshed, Y. & Zamir, D. In silico screening of a saturated mutation library of tomato. Plant J. 38, 861–872 (2004).

    Article  CAS  PubMed  Google Scholar 

  8. 8

    Meissner, R. et al. A new model system for tomato genetics. Plant J. 12, 1465–1472 (1997).

    Article  CAS  Google Scholar 

  9. 9

    Meissner, R., Chague, V., Zhu, Q., Emmanuel, E. & Elkind, Y. et al. A high throughput system for transposon tagging and promoter trapping in tomato. Plant J. 38, 861–872 (2000).

    Google Scholar 

  10. 10

    Emmanuel, E. & Levy, A.A. Tomato mutants as tools for functional genomics. Curr. Opin. Plant Biol. 5, 112–117 (2002).

    Article  CAS  PubMed  Google Scholar 

  11. 11

    Saito, T. et al. TOMATOMA: a novel tomato mutant database distributing Micro-Tom mutant collections. Plant Cell Physiol. 52, 283–296 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Carvalho, R.F. et al. Convergence of developmental mutants into a single tomato model system: ′Micro-Tom′ as an effective toolkit for plant development research. Plant Methods 7, 18 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. 13

    Monteiro, C.C. et al. Biochemical and histological characterization of tomato mutants. An. Acad. Bras. Cienc. 84, 573–585 (2012).

    Article  CAS  PubMed  Google Scholar 

  14. 14

    Just, D. et al. Micro-Tom mutants for functional analysis of target genes and discovery of new alleles in tomato. Plant Biotechnol. 30, 225–231 (2013).

    Article  CAS  Google Scholar 

  15. 15

    Isaacson, T. et al. Cutin deficiency in the tomato fruit cuticle consistently affects resistance to microbial infection and biomechanical properties, but not transpirational water loss. Plant J. 60, 363–377 (2009).

    Article  CAS  PubMed  Google Scholar 

  16. 16

    Nadakuduti, S.S. et al. Pleiotropic phenotypes of the sticky peel mutant provide new insight into the role of CUTIN DEFICIENT2 in epidermal cell function in tomato. Plant Physiol. 159, 945–960 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Yeats, T.H. et al. The identification of cutin synthase: formation of the plant polyester cutin. Nat. Chem. Biol. 8, 609–611 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. 18

    Kimbara, J. et al. Inhibition of CUTIN DEFICIENT 2 causes defects in cuticle function and structure and metabolite changes in tomato fruit. Plant Cell Physiol. 54, 1535–1548 (2013).

    Article  CAS  PubMed  Google Scholar 

  19. 19

    Shi, J.X. et al. The tomato SlSHINE3 transcription factor regulates fruit cuticle formation and epidermal patterning. New Phytol. 197, 468–480 (2013).

    Article  CAS  PubMed  Google Scholar 

  20. 20

    Petit, J. et al. Analyses of tomato fruit brightness mutants uncover both cutin-deficient and cutin-abundant mutants and a new hypomorphic allele of GDSL lipase. Plant Physiol. 164, 888–906 (2014).

    Article  CAS  PubMed  Google Scholar 

  21. 21

    Ronen, G., Carmel-Goren, L., Zamir, D. & Hirschberg, J. An alternative pathway to beta-carotene formation in plant chromoplasts discovered by map-based cloning of beta and old-gold color mutations in tomato. Proc. Natl. Acad. Sci. USA 97, 11102–11107 (2000).

    Article  CAS  PubMed  Google Scholar 

  22. 22

    Isaacson, T., Ronen, G., Zamir, D. & Hirschberg, J. Cloning of tangerine from tomato reveals a carotenoid isomerase essential for the production of beta-carotene and xanthophylls in plants. Plant Cell 14, 333–342 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. 23

    Fraser, P.D. et al. Manipulation of phytoene levels in tomato fruit: effects on isoprenoids, plastids, and intermediary metabolism. Plant Cell 19, 3194–3211 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. 24

    Galpaz, N., Wang, Q., Menda, N., Zamir, D. & Hirschberg, J. Abscisic acid deficiency in the tomato mutant high-pigment 3 leading to increased plastid number and higher fruit lycopene content. Plant J. 53, 717–730 (2008).

    Article  CAS  PubMed  Google Scholar 

  25. 25

    Ariizumi, T. et al. Identification of the carotenoid modifying gene PALE YELLOW PETAL 1 as an essential factor in xanthophyll esterification and yellow flower pigmentation in tomato (Solanum lycopersicum). Plant J. 79, 453–465 (2014).

    Article  CAS  PubMed  Google Scholar 

  26. 26

    Neuman, H., Galpaz, N., Cunningham, F.X., Zamir, D. & Hirschberg, J. The tomato mutation nxd1 reveals a gene necessary for neoxanthin biosynthesis and demonstrates that violaxanthin is a sufficient precursor for abscisic acid biosynthesis. Plant J. 78, 80–93 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. 27

    Fridman, E., Carrari, F., Liu, Y.S., Fernie, A.R. & Zamir, D. Zooming in on a quantitative trait for tomato yield using interspecific introgressions. Science 305, 1786–1789 (2004).

    Article  CAS  PubMed  Google Scholar 

  28. 28

    Schauer, N. et al. Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat. Biotechnol. 24, 447–454 (2006).

    Article  CAS  PubMed  Google Scholar 

  29. 29

    Mounet, F. et al. Gene and metabolite regulatory network analysis of early developing fruit tissues highlights new candidate genes for the control of tomato fruit composition and development. Plant Physiol. 149, 1505–1528 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Itkin, M. et al. Biosynthesis of antinutritional alkaloids in solanaceous crops is mediated by clustered genes. Science 341, 175–179 (2013).

    Article  CAS  Google Scholar 

  31. 31

    Sauvage, C. et al. Genome-wide association in tomato reveals 44 candidate loci for fruit metabolic traits. Plant Physiol. 165, 1120–1132 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. 32

    Colombié, S. et al. Modelling central metabolic fluxes by constraint-based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit. Plant J. 81, 24–39 (2015).

    Article  CAS  PubMed  Google Scholar 

  33. 33

    Schmitz, G. et al. The tomato Blind gene encodes a MYB transcription factor that controls the formation of lateral meristems. Proc. Natl. Acad. Sci. USA 99, 1064–1069 (2002).

    Article  CAS  PubMed  Google Scholar 

  34. 34

    Krieger, U., Lippman, Z.B. & Zamir, D. The flowering gene SINGLE FLOWER TRUSS drives heterosis for yield in tomato. Nat. Genet. 42, 459–463 (2010).

    Article  CAS  PubMed  Google Scholar 

  35. 35

    Busch, B.L. et al. Shoot branching and leaf dissection in tomato are regulated by homologous gene modules. Plant Cell 23, 3595–3609 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. 36

    Martín-Trillo, M. et al. Role of tomato BRANCHED1-like genes in the control of shoot branching. Plant J. 67, 701–714 (2011).

    Article  CAS  PubMed  Google Scholar 

  37. 37

    MacAlister, C.A. et al. Synchronization of the flowering transition by the tomato TERMINATING FLOWER gene. Nat. Genet. 44, 1393–1398 (2012).

    Article  CAS  PubMed  Google Scholar 

  38. 38

    Park, S.J. et al. Optimization of crop productivity in tomato using induced mutations in the florigen pathway. Nat. Genet. 46, 1337–1342 (2014).

    Article  CAS  PubMed  Google Scholar 

  39. 39

    Burko, Y. et al. A role for APETALA1/fruitfull transcription factors in tomato leaf development. Plant Cell 25, 2070–2083 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. 40

    Ichihashi, Y. et al. Evolutionary developmental transcriptomics reveals a gene network module regulating interspecific diversity in plant leaf shape. Proc. Natl. Acad. Sci. USA 111, 2616–2621 (2014).

    Article  CAS  Google Scholar 

  41. 41

    Ori, N. et al. Regulation of LANCEOLATE by miR319 is required for compound-leaf development in tomato. Nat. Genet. 39, 787–791 (2007).

    Article  CAS  PubMed  Google Scholar 

  42. 42

    Li, F. et al. MicroRNA regulation of plant innate immune receptors. Proc. Natl. Acad. Sci. USA 109, 1790–1795 (2012).

    Article  PubMed  Google Scholar 

  43. 43

    Semel, Y. et al. Overdominant quantitative trait loci for yield and fitness in tomato. Proc. Natl. Acad. Sci. USA 103, 12981–12986 (2006).

    Article  CAS  PubMed  Google Scholar 

  44. 44

    Kharkwal, M.C. & Shu, Q.Y. The role of induced mutations in world food security. In Induced Plant Mutations in the Genomics Era (ed. Shu, Q.Y.) 33–38 (Food and Agricultural Organization of the United Nations, Rome, 2009).

  45. 45

    Henikoff, S. & Comai, L. Single-nucleotide mutations for plant functional genomics. Annu. Rev. Plant Biol. 54, 375–401 (2003).

    Article  CAS  PubMed  Google Scholar 

  46. 46

    Minoia, S. et al. A new mutant genetic resource for tomato crop improvement by TILLING technology. BMC Res. Notes 3, 69 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. 47

    Okabe, Y. et al. Tomato TILLING technology: development of a reverse genetics tool for the efficient isolation of mutants from Micro-Tom mutant libraries. Plant Cell Physiol. 52, 1994–2005 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. 48

    Sreelakshmi, Y. et al. NEATTILL: a simplified procedure for nucleic acid extraction from arrayed tissue for TILLING and other high-throughput reverse genetic applications. Plant Methods 6, 3 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Baldet, P. et al. TILLING identification of ascorbate biosynthesis tomato mutants for investigating vitamin C in tomato. Plant Biotechnol. 30, 309–314 (2013).

    Article  CAS  Google Scholar 

  50. 50

    Yifhar, T. et al. Failure of the tomato trans-acting short interfering RNA program to regulate AUXIN RESPONSE FACTOR3 and ARF4 underlies the wiry leaf syndrome. Plant Cell 24, 3575–3589 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. 51

    Schneeberger, K. Using next-generation sequencing to isolate mutant genes from forward genetic screens. Nat. Rev. Genet. 15, 662–676 (2014).

    Article  CAS  PubMed  Google Scholar 

  52. 52

    Schneeberger, K. et al. SHOREmap: simultaneous mapping and mutation identification by deep sequencing. Nat. Methods 6, 550–551 (2009).

    Article  CAS  PubMed  Google Scholar 

  53. 53

    Austin, R.S. et al. Next-generation mapping of Arabidopsis genes. Plant J. 67, 715–725 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. 54

    Abe, A. et al. Genome sequencing reveals agronomically important loci in rice using MutMap. Nat. Biotechnol. 30, 174–178 (2012).

    Article  CAS  PubMed  Google Scholar 

  55. 55

    Fekih, R. et al. MutMap+: genetic mapping and mutant identification without crossing in rice. PLoS One 8, e68529 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. 56

    Takagi, H. et al. MutMap-Gap: whole-genome resequencing of mutant F2 progeny bulk combined with de novo assembly of gap regions identifies the rice blast resistance gene Pii. New Phytol. 200, 276–283 (2013).

    Article  CAS  Google Scholar 

  57. 57

    Takagi, H. et al. MutMap accelerates breeding of a salt-tolerant rice cultivar. Nat. Biotechnol. 33, 445–449 (2015).

    Article  CAS  PubMed  Google Scholar 

  58. 58

    Shirasawa, K., Hirakawa, H., Nunome, T., Tabata, S. & Isobe, S. Genome-wide survey of artificial mutations induced by ethyl methanesulfonate and gamma rays in tomato. Plant Biotechnol. J. 14, 51–60 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. 59

    Shirasawa, K. et al. SNP discovery and linkage map construction in cultivated tomato. DNA Res. 17, 381–391 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. 60

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. 62

    Petit, J. et al. The glycerol-3-phosphate acyltransferase GPAT6 from tomato plays a central role in fruit cutin biosynthesis. Plant Physiol. 171, 894–913 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Piron, F. et al. An induced mutation in tomato eIF4E leads to immunity to two potyviruses. PLoS One 5, e11313 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. 64

    Gady, A.L. et al. Induced point mutations in the phytoene synthase 1 gene cause differences in carotenoid content during tomato fruit ripening. Mol. Breed. 29, 801–812 (2012).

    Article  CAS  PubMed  Google Scholar 

  65. 65

    Hirakawa, H. et al. Genome-wide SNP genotyping to infer the effects on gene functions in tomato. DNA Res. 20, 221–233 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. 66

    Martí, E., Gisbert, C., Bishop, G.J., Dixon, M.S. & García-Martínez, J.L. Genetic and physiological characterization of tomato cv. Micro-Tom. J. Exp. Bot. 57, 2037–2047 (2006).

    Article  CAS  PubMed  Google Scholar 

  67. 67

    Causse, M. et al. Whole genome resequencing in tomato reveals variation associated with introgression and breeding events. BMC Genomics 14, 791 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. 68

    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, 5869 (2008).

    Google Scholar 

  69. 69

    Smith, S.M. & Maughan, P.J. SNP genotyping using KASPar assays. Methods Mol. Biol. 1245, 243–256 (2015).

    Article  CAS  PubMed  Google Scholar 

  70. 70

    You, F.M. et al. BatchPrimer3: a high throughput web application for PCR and sequencing primer design. BMC Bioinformatics 9, 253 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. 71

    Brukhin, V., Hernould, M., Gonzalez, N., Chevalier, C. & Mouras, A. Flower development schedule in tomato Lycopersicon esculentum cv. sweet cherry. Sex Plant Reprod. 15, 311–320 (2003).

    Google Scholar 

  72. 72

    Robinson, J.T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. 73

    Thorvaldsdóttir, H., Robinson, J.T. & Mesirov, J.P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform. 14, 178–192 (2013).

    Article  CAS  Google Scholar 

  74. 74

    Goecks, J. et al. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 11, R86 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  75. 75

    Blankenberg, D. Galaxy: a web-based genome analysis tool for experimentalists. Curr. Protoc. Mol. Biol. Chapter 19 Unit 19.10.1-21 (2010).

  76. 76

    Giardine, B. et al. Galaxy: a platform for interactive large-scale genome analysis. Genome Res. 15, 1451–1455 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. 77

    Lisec, J., Schauer, N., Kopka, J., Willmitzer, L. & Fernie, A.R. Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat. Protoc. 1, 387–396 (2006).

    Article  CAS  PubMed  Google Scholar 

  78. 78

    Cingolani, P. 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 6, 80–92 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. 79

    Scott, J.W. & Harbaugh, B.K. Micro-Tom. A Miniature Dwarf Tomato 1–6 (Florida Agricultural Experimental Station, 1989).

  80. 80

    Rothan, C. et al. Culture of the tomato Micro-Tom cultivar in Greenhouse. Methods Mol. Biol. 1363, 57–64 (2016).

    Article  CAS  PubMed  Google Scholar 

  81. 81

    Fernandez, A.I. et al. Flexible tools for gene expression and silencing in tomato. Plant Physiol. 151, 1729–1740 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. 82

    Ferreira e Silva, G.F. et al. microRNA156-targeted SPL/SBP box transcription factors regulate tomato ovary and fruit development. Plant J. 78, 604–618 (2014).

    Article  CAS  PubMed  Google Scholar 

  83. 83

    Brooks, C., Nekrasov, V., Lippman, Z.B. & Van Eck, J. Efficient gene editing in tomato in the first generation using the clustered regularly interspaced short palindromic repeats/CRISPR-associated9 system. Plant Physiol. 166, 1292–1297 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. 84

    Ron, M. et al. Hairy root transformation using Agrobacterium rhizogenes as a tool for exploring cell type-specific gene expression and function using tomato as a model. Plant Physiol. 166, 455–469 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. 85

    Orzaez, D. et al. A visual reporter system for virus-induced gene silencing in tomato fruit based on anthocyanin accumulation. Plant Physiol. 150, 1122–1134 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  86. 86

    Quadrana, L. et al. Coupling virus-induced gene silencing to exogenous green fluorescence protein expression provides a highly efficient system for functional genomics in Arabidopsis and across all stages of tomato fruit development. Plant Physiol. 156, 1278–1291 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. 87

    Senthil-Kumar, M. & Mysore, K.S. Tobacco rattle virus-based virus-induced gene silencing in Nicotiana benthamiana. Nat. Protoc. 9, 1549–1562 (2014).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the CEA-IG/CNG for conducting QC of DNA and Illumina sequencing. We thank A. Boland, M.T. Bihoreau and their staff. We are grateful to the Genotoul Toulouse Midi-Pyrenees bioinformatics platform and the Sigenae group (specially S. Maman) for providing help, as well as computing and storage resources. This project was funded by grants from INRA AIP Bioressources and the ERANET project 'TomQML'. F.W.J.T. was supported by a grant from ANR Bioadapt project 'Adaptom'.

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C.B., D.J., L.F., V.G. and C.R. developed the original protocol. D.B., J.-P.M. and A.B. performed the sequencing experiments. F.W.J.T. performed computational analyses. C.B., L.F., D.J., F.W.J.T., M.-C.L.P., K.A., S.A., A.R.F., P.D.F. and C.R. contributed sections to the manuscript. C.B., L.F., D.J. and C.R. collated and standardized the text. All authors read and approved the final version of the manuscript.

Corresponding author

Correspondence to Cécile Bres.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Software

The ‘compare_WT_mutant_samtools_vcf_v5.py’ script. (ZIP 4 kb)

Supplementary Table 1

Typical carotenoid content found in ripe fruit (Breaker+7) from yellow mutant as compared with the WT background (Micro-Tom line). Separations were performed by UPLC-PDA and quantitative determinations from dose response curves. FW: Fresh Weight. (PDF 41 kb)

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Garcia, V., Bres, C., Just, D. et al. Rapid identification of causal mutations in tomato EMS populations via mapping-by-sequencing. Nat Protoc 11, 2401–2418 (2016). https://doi.org/10.1038/nprot.2016.143

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