Letter | Open | Published:

The tomato genome sequence provides insights into fleshy fruit evolution

Nature volume 485, pages 635641 (31 May 2012) | Download Citation

Abstract

Tomato (Solanum lycopersicum) is a major crop plant and a model system for fruit development. Solanum is one of the largest angiosperm genera1 and includes annual and perennial plants from diverse habitats. Here we present a high-quality genome sequence of domesticated tomato, a draft sequence of its closest wild relative, Solanum pimpinellifolium2, and compare them to each other and to the potato genome (Solanum tuberosum). The two tomato genomes show only 0.6% nucleotide divergence and signs of recent admixture, but show more than 8% divergence from potato, with nine large and several smaller inversions. In contrast to Arabidopsis, but similar to soybean, tomato and potato small RNAs map predominantly to gene-rich chromosomal regions, including gene promoters. The Solanum lineage has experienced two consecutive genome triplications: one that is ancient and shared with rosids, and a more recent one. These triplications set the stage for the neofunctionalization of genes controlling fruit characteristics, such as colour and fleshiness.

Main

The genome of the inbred tomato cultivar ‘Heinz 1706’ was sequenced and assembled using a combination of Sanger and ‘next generation’ technologies (Supplementary Information section 1). The predicted genome size is approximately 900 megabases (Mb), consistent with previous estimates3, of which 760 Mb were assembled in 91 scaffolds aligned to the 12 tomato chromosomes, with most gaps restricted to pericentromeric regions (Fig. 1A and Supplementary Fig. 1). Base accuracy is approximately one substitution error per 29.4 kilobases (kb) and one indel error per 6.4 kb. The scaffolds were linked with two bacterial artificial chromosome (BAC)-based physical maps and anchored/oriented using a high-density genetic map, introgression line mapping and BAC fluorescence in situ hybridization (FISH).

Figure 1: Tomato genome topography and synteny.
Figure 1

A, Multi-dimensional topography of tomato chromosome 1 (chromosomes 2–12 are shown in Supplementary Fig. 1). a, Left: contrast-reversed, 4′,6-diamidino-2-phenylindole (DAPI)-stained pachytene chromosome; centre and right: FISH signals for repeat sequences on diagrammatic pachytene chromosomes (purple, TGR1; blue, TGR4; red, telomere repeat; green, Cot 100 DNA (including most repeats)). b, Frequency distribution of recombination nodules (RNs) representing crossovers on 249 chromosomes. Red stars mark 5 cM intervals starting from the end of the short arm (top). Scale is in micrometres. c, FISH-based locations of selected BACs (horizontal blue lines on left). d, Kazusa F2-2000 linkage map. Blue lines to the left connect linkage map markers on the BAC-FISH map (c), and to the right to heat maps (e) and the DNA pseudomolecule (f). e, From left to right: linkage map distance (cM/Mb, turquoise), repeated sequences (% nucleotides per 500 kb, purple), genes (% nucleotides per 500 kb, blue), chloroplast insertions; RNA-Seq reads from leaves and breaker fruits of S. lycopersicum and S. pimpinellifolium (number of reads per 500 kb, green and red, respectively), microRNA genes (transcripts per million per 500 kb, black), small RNAs (thin horizontal black and red lines, sum of hits-normalized abundances). Horizontal grey lines represent gaps in the pseudomolecule (f). f, DNA pseudomolecule consisting of nine scaffolds. Unsequenced gaps (approximately 9.8 Mb, Supplementary Table 13) are indicated by white horizontal lines. Tomato genes identified by map-based cloning (Supplementary Table 14) are indicated on the right. For more details, see legend to Supplementary Fig. 1. B, Syntenic relationships in the Solanaceae. COSII-based comparative maps of potato, aubergine (eggplant), pepper and Nicotiana with respect to the tomato genome (Supplementary Information section 4.5 and Supplementary Fig. 14). Each tomato chromosome is assigned a different colour and orthologous chromosome segment(s) in other species are shown in the same colour. White dots indicate approximate centromere locations. Each black arrow indicates an inversion relative to tomato and ‘+1’ indicates a minimum of one inversion. Each black bar beside a chromosome indicates translocation breakpoints relative to tomato. Chromosome lengths are not to scale, but segments within chromosomes are. C, Tomato–potato syntenic relationships dot plot of tomato (T) and potato (P) genomic sequences based on collinear blocks (Supplementary Information section 4.1). Red and blue dots represent gene pairs with statistically significant high and low ω (Ka/Ks) in collinear blocks, which average Ks ≤ 0.5, respectively. Green and magenta dots represent genes in collinear blocks which average 0.5 < Ks ≤ 1.5 and Ks > 1.5, respectively. Yellow dots represent all other gene pairs. Blocks circled in red are examples of pan-eudicot triplication. Inserts represent schematic drawings of BAC-FISH patterns of cytologically demonstrated chromosome inversions (also in Supplementary Fig. 15).

The genome of S. pimpinellifolium LA1589 was sequenced and assembled de novo using Illumina short reads, yielding a 739 Mb draft genome (Supplementary Information section 3). Estimated divergence between the wild and domesticated genomes is 0.6% (5.4 million single nucleotide polymorphisms (SNPs) distributed along the chromosomes (Fig. 1A and Supplementary Fig. 1)).

Tomato chromosomes consist of pericentric heterochromatin and distal euchromatin, with repeats concentrated within and around centromeres, in chromomeres and at telomeres (Fig. 1A and Supplementary Fig. 1). Substantially higher densities of recombination, genes and transcripts are observed in euchromatin, whereas chloroplast insertions (Supplementary Information sections 1.22 and 1.23) and conserved microRNA (miRNA) genes (Supplementary Information section 2.9) are more evenly distributed throughout the genome. The genome is highly syntenic with those of other economically important Solanaceae (Fig. 1B). Compared to the genomes of Arabidopsis4 and Sorghum5, tomato has fewer high-copy, full-length long terminal repeat (LTR) retrotransposons with older average insertion ages (2.8 versus 0.8 million years (Myr) ago) and fewer high-frequency k-mers (Supplementary Information section 2.10). This supports previous findings that the tomato genome is unusual among angiosperms by being largely comprised of low-copy DNA6,7.

The pipeline used to annotate the tomato and potato8 genomes is described in Supplementary Information section 2. It predicted 34,727 and 35,004 protein-coding genes, respectively. Of these, 30,855 and 32,988, respectively, are supported by RNA sequencing (RNA-Seq) data, and 31,741 and 32,056, respectively, show high similarity to Arabidopsis genes (Supplementary Information section 2.1). Chromosomal organization of genes, transcripts, repeats and small RNAs (sRNAs) is very similar in the two species (Supplementary Figs 2–4). The protein-coding genes of tomato, potato, Arabidopsis, rice and grape were clustered into 23,208 gene groups (≥2 members), of which 8,615 are common to all five genomes, 1,727 are confined to eudicots (tomato, potato, grape and Arabidopsis), and 727 are confined to plants with fleshy fruits (tomato, potato and grape) (Supplementary Information section 5.1 and Supplementary Fig. 5). Relative expression of all tomato genes was determined by replicated strand-specific Illumina RNA-Seq of root, leaf, flower (two stages) and fruit (six stages) in addition to leaf and fruit (three stages) of S. pimpinellifolium (Supplementary Table 1).

sRNA sequencing data supported the prediction of 96 conserved miRNA genes in tomato and 120 in potato, a number consistent with other plant species (Fig. 1A, Supplementary Figs 1 and 3 and Supplementary Information section 2.9). Among the 34 miRNA families identified, 10 are highly conserved in plants and similarly represented in the two species, whereas other, less conserved families are more abundant in potato. Several miRNAs, predicted to target Toll interleukin receptor, nucleotide-binding site and leucine-rich repeat (TIR-NBS-LRR) genes, seemed to be preferentially or exclusively expressed in potato (Supplementary Information section 2.9).

Comparative genomic studies are reported in Supplementary Information section 4. Sequence alignment of 71 Mb of euchromatic tomato genomic DNA to their potato8 counterparts revealed 8.7% nucleotide divergence (Supplementary Information section 4.1). Intergenic and repeat-rich heterochromatic sequences showed more than 30% nucleotide divergence, consistent with the high sequence diversity in these regions among potato genotypes8. Alignment of tomato–potato orthologous regions confirmed nine large inversions known from cytological or genetic studies and several smaller ones (Fig. 1C). The exact number of small inversions is difficult to determine due to the lack of orientation of most potato scaffolds.

A total of 18,320 clearly orthologous tomato–potato gene pairs were identified. Of these, 138 (0.75%) had significantly higher than average non-synonymous (Ka) versus synonymous (Ks) nucleotide substitution rate ratios (ω), indicating diversifying selection, whereas 147 (0.80%) had significantly lower than average ω, indicating purifying selection (Supplementary Table 2). The proportions of high and low ω between sorghum and maize (Zea mays) are 0.70% and 1.19%, respectively, after 11.9 Myr of divergence9, indicating that diversifying selection may have been stronger in tomato–potato. The highest densities of low-ω genes are found in collinear blocks with average Ks > 1.5, tracing to a genome triplication shared with grape (see below) (Fig. 1C, Supplementary Fig. 6 and Supplementary Table 3). These genes, which have been preserved in paleo-duplicated locations for more than 100 Myr10,11, are more constrained than ‘average’ genes and are enriched for transcription factors and genes otherwise related to gene regulation (Supplementary Tables 3 and 4).

Sequence comparison of 31,760 Heinz 1706 genes with >5× S. pimpinellifolium read coverage in over 90% of their coding regions revealed 7,378 identical genes and 11,753 with only synonymous changes. The remaining 12,629 genes had non-synonymous changes, including gains and losses of stop codons with potential consequences for gene function (Supplementary Tables 5–7). Several pericentric regions, predicted to contain genes, are absent or polymorphic in the broader S. pimpinellifolium germplasm (Supplementary Table 8 and Supplementary Fig. 7). Within cultivated germplasm, particularly among the small-fruited cherry tomatoes, several chromosomal segments are more closely related to S. pimpinellifolium than to Heinz 1706 (Supplementary Figs 8 and 9), supporting previous observations on recent admixture of these gene pools due to breeding12. Heinz 1706 itself has been reported to carry introgressions from S. pimpinellifolium13, traces of which are detectable on chromosomes 4, 9, 11 and 12 (Supplementary Table 9).

Comparison of the tomato and grape genomes supports the hypothesis that a whole-genome triplication affecting the rosid lineage occurred in a common eudicot ancestor11 (Fig. 2a). The distribution of Ks between corresponding gene pairs in duplicated blocks suggests that one polyploidization in the solanaceous lineage preceded the rosid–asterid (tomato–grape) divergence (Supplementary Fig. 10).

Figure 2: The Solanum whole genome triplication.
Figure 2

a, Speciation and polyploidization in eudicot lineages. Confirmed whole-genome duplications and triplications are shown with annotated circles, including ‘T’ (this paper) and previously discovered events α, β, γ10,11,14. Dashed circles represent one or more suspected polyploidies reported in previous publications that need further support from genome assemblies27,28. Grey branches indicate unpublished genomes. Black and red error bars bracket indicate the likely timings of divergence of major asterid lineages and of ‘T’, respectively. The post-‘T’ subgenomes, designated T1, T2, and T3, are further detailed in Supplementary Fig. 10. b, On the basis of alignments of multiple tomato genome segments to single grape genome segments, the tomato genome is partitioned into three non-overlapping ‘subgenomes’ (T1, T2, T3), each represented by one axis in the three-dimensional plot. The ancestral gene order of each subgenome is inferred according to orthologous grape regions, with tomato chromosomal affinities shown by red (inner) bars. Segments tracing to pan-eudicot triplication (γ) are shown by green (outer) bars with colours representing the seven putative pre-γ eudicot ancestral chromosomes10, also coded ag.

Comparison with the grape genome also reveals a more recent triplication in tomato and potato. Whereas few individual tomato/potato genes remain triplicated (Supplementary Tables 10 and 11), 73% of tomato gene models are in blocks that are orthologous to one grape region, collectively covering 84% of the grape gene space. Among these grape genomic regions, 22.5% have one orthologous region in tomato, 39.9% have two, and 21.6% have three, indicating that a whole-genome triplication occurred in the Solanum lineage, followed by widespread gene loss. This triplication, also evident in potato (Supplementary Fig. 11), is estimated at 71 (±19.4) Myr on the basis of the Ks of paralogous genes (Supplementary Fig. 10), and therefore predates the 7.3 Myr tomato–potato divergence. On the basis of alignments to single grape genome segments, the tomato genome can be partitioned into three non-overlapping ‘subgenomes’ (Fig. 2b). The number of euasterid lineages that have experienced the recent triplication remains unclear and awaits complete euasterid I and II genome sequences. Ks distributions show that euasterids I and II, and indeed the rosid–asterid lineages, all diverged from common ancestry at or near the pan-eudicot triplication (Fig. 2a), suggesting that this event may have contributed to the formation of major eudicot lineages in a short period of several million years14, partially explaining the explosive radiation of angiosperm plants on Earth15.

Fleshy fruits (Supplementary Fig. 12) are an important means of attracting vertebrate frugivores for seed dispersal16. Combined orthology and synteny analyses indicate that both genome triplications added new gene family members that mediate important fruit-specific functions (Fig. 3). These include transcription factors and enzymes necessary for ethylene biosynthesis (RIN, CNR, ACS) and perception (ETR3/NR, ETR4)17, red light photoreceptors influencing fruit quality (PHYB1/PHYB2) and ethylene- and light-regulated genes mediating lycopene biosynthesis (PSY1/PSY2). Several cytochrome P450 subfamilies associated with toxic alkaloid biosynthesis show contraction or complete loss in tomato and the extant genes show negligible expression in ripe fruits (Supplementary Information section 5.4).

Figure 3: Whole-genome triplications set the stage for fruit-specific gene neofunctionalization.
Figure 3

The genes shown represent a fruit ripening control network regulated by transcription factors (MADS-RIN, CNR) necessary for production of the ripening hormone ethylene, the production of which is regulated by ACC synthase (ACS). Ethylene interacts with ethylene receptors (ETRs) to drive expression changes in output genes, including phytoene synthase (PSY), the rate-limiting step in carotenoid biosynthesis. Light, acting through phytochromes, controls fruit pigmentation through an ethylene-independent pathway. Paralogous gene pairs with different physiological roles (MADS1/RIN, PHYB1/PHYB2, ACS2/ACS6, ETR3/ETR4, PSY1/PSY2), were generated during the eudicot (γ, black circle) or the more recent Solanum (T, red circle) triplications. Complete dendrograms of the respective protein families are shown in Supplementary Figs 16 and 17.

Fruit texture has profound agronomic and sensory importance and is controlled in part by cell wall structure and composition18. More than 50 genes showing differential expression during fruit development and ripening encode proteins involved in modification of cell wall architecture (Fig. 4a and Supplementary Information section 5.7). For example, a family of xyloglucan endotransglucosylase/hydrolases (XTHs) has expanded both in the recent whole-genome triplication and through tandem duplication. One of the triplicated members, XTH10, shows differential loss between tomato and potato (Fig. 4a and Supplementary Table 12), suggesting genetically driven specialization in the remodelling of fruit cell walls.

Figure 4: The tomato genome allows systems approaches to fruit biology.
Figure 4

a, Xyloglucan transglucosylase/hydrolases (XTHs) differentially expressed between mature green and ripe fruits (Supplementary Information section 5.7). These XTH genes and many others are expressed in ripening fruits and are linked with the Solanum triplication, marked with a red circle on the phylogenetic tree. Red lines on the tree denote paralogues derived from the Solanum triplication, and blue lines are tandem duplications. b, Developmentally regulated accumulation of sRNAs mapping to the promoter region of a fruit-regulated cell wall gene (pectin acetylesterase, Solyc08g005800). Variation of abundance of sRNAs (left) and messenger RNA expression levels from the corresponding gene (right) over a tomato fruit developmental series (T1, bud; T2, flower; T3, fruit 1–3 mm; T4, fruit 5–7 mm; T5, fruit 11–13 mm; T6, fruit mature green; T7, breaker; T8, breaker + 3 days; T9, breaker + 7 days). The promoter regions are grouped in 100-nucleotide windows. For each window the size class distribution of sRNAs is shown (red, 21; green, 22; orange, 23; blue, 24). The height of the box corresponding to the first time point shows the cumulative sRNA abundance in log scale. The height of the following boxes is proportional to the log offset fold change (offset = 20) relative to the first time point. The expression profile of the mRNA is shown in log2 scale. The horizontal black line represents 1 kb of the promoter region. 0 to 12 represent arbitrary units of gene expression.

Similar to soybean and potato and in contrast to Arabidopsis, tomato sRNAs map preferentially to euchromatin (Supplementary Fig. 2). sRNAs from tomato flowers and fruits19 map to 8,416 gene promoters. Differential expression of sRNAs during fruit development is apparent for 2,687 promoters, including those of cell-wall-related genes (Fig. 4b) and occurs preferentially at key developmental transitions (for example, flower to fruit, fruit growth to fruit ripening, Supplementary Information section 2.8).

The genome sequences of tomato, S. pimpinellifolium and potato provide a starting point for comparing gene family evolution and sub-functionalization in the Solanaceae. A striking example is the SELF PRUNING (SP) gene family, which includes the homologue of Arabidopsis FT, encoding the mobile flowering signal florigen20 and its antagonist SP, encoding the orthologue of TFL1. Nearly a century ago, a spontaneous mutation in SP spawned the ‘determinate’ varieties that now dominate the tomato mechanical harvesting industry21. The genome sequence has revealed that the SP family has expanded in the Solanum lineage compared to Arabidopsis, driven by the Solanum triplication and tandem duplication (Supplementary Fig. 13). In potato, SP3D and SP6A control flowering and tuberization, respectively22, whereas SP3D in tomato, known as SINGLE FLOWER TRUSS, similarly controls flowering, but also drives heterosis for fruit yield in an epistatic relationship with SP23,24,25. Interestingly, SP6A in S. lycopersicum is inactivated by a premature stop codon, but remains functionally intact in S. pimpinellifolium. Thus, allelic variation in a subset of SP family genes has played a major role in the generation of both shared and species-specific variation in solanaceous agricultural traits.

The genome sequences of tomato and S. pimpinellifolium also provide a basis for understanding the bottlenecks that have narrowed tomato genetic diversity: the domestication of S. pimpinellifolium in the Americas, the export of a small number of genotypes to Europe in the 16th century, and the intensive breeding that followed. Charles Rick pioneered the use of trait introgression from wild tomato relatives to increase genetic diversity of cultivated tomatoes26. Introgression lines exist for seven wild tomato species, including S. pimpinellifolium, in the background of cultivated tomato. The genome sequences presented here and the availability of millions of SNPs will allow breeders to revisit this rich trait reservoir and identify domestication genes, providing biological knowledge and empowering biodiversity-based breeding.

Methods Summary

A total of 21 gigabases (Gb) of Roche/454 Titanium shotgun and mate pair reads and 3.3 Gb of Sanger paired-end reads, including 200,000 BAC and fosmid end sequence pairs, were generated from the ‘Heinz 1706’ inbred line (Supplementary Information sections 1.1–1.7), assembled using both Newbler and CABOG and integrated into a single assembly (Supplementary Information sections 1.17 and 1.18). The scaffolds were anchored using two BAC-based physical maps, one high density genetic map, overgo hybridization and genome-wide BAC FISH (Supplementary Information sections 1.8–1.16 and 1.19). Over 99.9% of BAC/fosmid end pairs mapped consistently on the assembly and over 98% of EST sequences could be aligned to the assembly (Supplementary Information section 1.20). Chloroplast genome insertions in the nuclear genome were validated using a mate pair method and the flanking regions were identified (Supplementary Information sections 1.22–1.24). Annotation was carried out using a pipeline based on EuGene that integrates de novo gene prediction, RNA-Seq alignment and rich function annotation (Supplementary Information section 2). To facilitate interspecies comparison, the potato genome was re-annotated using the same pipeline. LTR retrotransposons were detected de novo with the LTR-STRUC program and dated by the sequence divergence between left and right solo LTR (Supplementary Information section 2.10). The genome of S. pimpinellifolium was sequenced to ×40 depth using Illumina paired end reads and assembled using ABySS (Supplementary Information section 3). The tomato and potato genomes were aligned using LASTZ (Supplementary Information section 4.1). Identification of triplicated regions was done using BLASTP, in-house-generated scripts and three-way comparisons between tomato, potato and S. pimpinellifolium using MCSCAN (Supplementary Information sections 4.2–4.4). Specific gene families/groups (genes for ascorbate, carotenoid and jasmonate biosynthesis, cytochrome P450s, genes controlling cell wall architecture, hormonal and transcriptional regulators, resistance genes) were subjected to expert curation/analysis (Supplementary Information section 5). PHYML and MEGA were used to reconstruct phylogenetic trees and MCSCAN was used to infer gene collinearity (Supplementary Information section 5.2).

Accessions

Primary accessions

Data deposits

The genomic data generated by the whole project are available in GenBank as accession number AEKE00000000, and the individual chromosome sequences as numbersCM001064–CM001075. TheRNA-Seq data are available in the Sequence Read Archive under accession number SRA049915, GSE33507, SRA050797 and SRA048144. Further information on data access can be found in Supplementary Information section 2.2.

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Acknowledgements

This work was supported by: Argentina: INTA and CONICET. Belgium: Flemish Institute for Biotechnology and Ghent University. China: The State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences; Ministry of Science and Technology (2006AA10A116, 2004CB720405, 2006CB101907, 2007DFB30080) Ministry of Agriculture (‘948’ Program: 2007-Z5); National Natural Science Foundation (36171319); Postdoctoral Science Foundation (20070420446). European Union: FP6 Integrated Project EU-SOL PL 016214. France: Institute National de la Recherche Agronomique and Agence Nationale de la Recherche. Germany: the Max Planck Society. India: Department of Biotechnology, Government of India; Indian Council of Agricultural Research. Italy: Ministry of Research (FIRB-SOL, FIRB-Parallelomics, ItaLyco and GenoPOM projects); Ministry of Agriculture (Agronanotech and Biomassval projects); FILAS foundation; ENEA; CNR-ENEA project L. 191/2009. Japan: Kazusa DNA Research Institute Foundation and National Institute of Vegetable and Tea Science. Korea: KRIBB Basic Research Fund and Crop Functional Genomics Research Center (CFGC), MEST. Netherlands: Centre for BioSystems Genomics, Netherlands Organization for Scientific Research. Spain: Fundación Genoma España; Cajamar; FEPEX; Fundación Séneca; ICIA; IFAPA; Fundación Manrique de Lara; Instituto Nacional de Bioinformatica. UK: BBSRC grant BB/C509731/1; DEFRA; SEERAD. USA: NSF (DBI-0116076; DBI-0421634; DBI-0606595; IOS-0923312; DBI-0820612; DBI-0605659; DEB-0316614; DBI 0849896 and MCB 1021718); USDA (2007-02773 and 2007-35300-19739); USDA-ARS. We acknowledge the Potato Genome Sequencing Consortium for sharing data before publication; potato RNA-Seq data was provided by C. R. Buell from the NSF-funded Potato Genome Sequence and Annotation project; tomato RNA-Seq data by the USDA-funded SolCAP project, N. Sinha and J. Maloof; the Amplicon Express team for BAC pooling services; construction of the Whole Genome Profiling (WGP) physical map was supported by EnzaZaden, RijkZwaan, Vilmorin & Cie, and Takii & Co. Keygene N.V. owns patents and patent applications covering its AFLP and Whole Genome Profiling technologies; AFLP and Keygene are registered trademarks of Keygene N.V. The following individuals are also acknowledged for their contribution to the work described: J. Park, B. Wang, C. Niu, D. Liu, F. Cojutti, S. Pescarolo, A. Zambon, G. Xiao, J. Chen, J. Shi, L. Zhang, L. Zeng, M. Caccamo, D. Bolser, D. Martin, M. Gonzalez, P. A. Bedinger, P. A. Covey, P. Pachori, R. R. Pousada, S. Hakim, S. Sims, V. Cahais, W. Long, X. Zhou, Y. Lu, W. Haso, C. Lai, S. Lepp, C. Peluso, H. Teramu, H. De Jong, R. Lizarralde, E. R. May and Z. Li. M. Zabeau is thanked for his support and encouragement and S. van den Brink for her secretarial support. We dedicate this work to the late C. Rick who pioneered tomato genetics, collection of wild germplasm and the distribution of seed and knowledge.

Author information

Author notes

    • Sanghyeob Lee

    Present address: Plant Engineering Research Institute, Sejong University, Seoul, 143-747, Republic of Korea.

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  1. Kazusa DNA Research Institute, 2-6-7 Kazusa-kamatari, Kisarazu, Chiba 292-0818, Japan.

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    • , Satoshi Tabata
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  3. Amplicon Express Inc., 2345 Hopkins Court, Pullman, Washington 99163, USA.

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  4. Beijing Vegetable Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.

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  5. National Center for Gene Research, Chinese Academy of Sciences, Shanghai 200233, China.

    • Changbao Li
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  6. BGI-Shenzhen, Shenzhen 518083, China.

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  9. Centre for BioSystems Genomics, PO Box 98, 6700 AB Wageningen, The Netherlands.

    • Willem J. Stiekema
  10. Centro Nacional de Análisis Genómico (CNAG), C/ Baldiri Reixac 4, Torre I, 08028 Barcelona, Spain.

    • Paolo Ribeca
    •  & Tyler Alioto
  11. Department of Vegetable Science, College of Agronomy and Biotechnology, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China.

    • Wencai Yang
  12. Key Laboratory of Horticultural Crops Genetic Improvement of Ministry of Agriculture, Sino-Dutch Joint Lab of Horticultural Genomics Technology, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.

    • Sanwen Huang
    • , Yongchen Du
    • , Zhonghua Zhang
    • , Jianchang Gao
    • , Yanmei Guo
    • , Xiaoxuan Wang
    • , Ying Li
    •  & Jun He
  13. State Key Laboratory of Plant Genomics and National Centre for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.

    • Chuanyou Li
    • , Zhukuan Cheng
    • , Jianru Zuo
    • , Jianfeng Ren
    • , Jiuhai Zhao
    • , Liuhua Yan
    • , Hongling Jiang
    • , Bao Wang
    • , Hongshuang Li
    • , Zhenjun Li
    • , Fuyou Fu
    •  & Bingtang Chen
  14. Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China.

    • Ying Wang
  15. State Key Laboratory of Plant Cell and Chromosome Engineering and National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.

    • Hongqing Ling
  16. Laboratory of Molecular and Developmental Biology and National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100080, China.

    • Yongbiao Xue
  17. Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA.

    • Doreen Ware
    • , W. Richard McCombie
    • , Zachary B. Lippman
    • , Jer-Ming Chia
    • , Ke Jiang
    • , Shiran Pasternak
    • , Laura Gelley
    •  & Melissa Kramer
  18. Department of Biology, Colorado State University, Fort Collins, Colorado 80523, USA.

    • Lorinda K. Anderson
    • , Suzanne M. Royer
    • , Lindsay A. Shearer
    •  & Stephen M. Stack
  19. Department of Agronomy, National Taiwan University, Taipei 107, Taiwan.

    • Song-Bin Chang
  20. Department of Plant Biology, Cornell University, Ithaca, New York 14853, USA.

    • Jocelyn K. C. Rose
    • , Yimin Xu
    • , Nancy Eannetta
    • , Antonio J. Matas
    • , Ryan McQuinn
    • , Steven D. Tanksley
    •  & James J. Giovannoni
  21. Genome Bioinformatics Laboratory. Center for Genomic Regulation (CRG), University Pompeu Fabra, Barcelona 08003, Spain.

    • Francisco Camara
    •  & Roderic Guigó
  22. Department of Plant Systems Biology, VIB. Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, 9052 Gent, Belgium.

    • Stephane Rombauts
    • , Jeffrey Fawcett
    •  & Yves Van de Peer
  23. Faculty of Agriculture, The Hebrew University of Jerusalem, PO Box 12, Rehovot 76100, Israel.

    • Dani Zamir
  24. Institute of Industrial Crops, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China.

    • Chunbo Liang
  25. Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Center for Health and Environment, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany.

    • Manuel Spannagl
    • , Heidrun Gundlach
    • , Remy Bruggmann
    •  & Klaus Mayer
  26. College of Horticulture, Henan Agricultural University, Zhengzhou 450002, China.

    • Zhiqi Jia
  27. National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.

    • Junhong Zhang
    •  & Zhibiao Ye
  28. Department of Life Sciences, Imperial College London, London SW7 1AZ, UK.

    • Gerard J. Bishop
    • , Sarah Butcher
    • , Rosa Lopez-Cobollo
    • , Daniel Buchan
    • , Ioannis Filippis
    •  & James Abbott
  29. NRC on Plant Biotechnology, Indian Agricultural Research Institute, New Delhi 110 012, India.

    • Rekha Dixit
    • , Manju Singh
    • , Archana Singh
    • , Jitendra Kumar Pal
    • , Awadhesh Pandit
    • , Pradeep Kumar Singh
    • , Ajay Kumar Mahato
    • , Vivek Dogra
    • , Kishor Gaikwad
    • , Tilak Raj Sharma
    • , Trilochan Mohapatra
    •  & Nagendra Kumar Singh
  30. INRA, UR1052 Génétique et amélioration des fruits et légumes, BP 94, 84143 Monfavet Cedex, France.

    • Mathilde Causse
  31. INRA, Biologie du Fruit et Pathologie, 71 rue E. Bourleaux, 33883 Villenave d’Ornon, France.

    • Christophe Rothan
  32. Unité de Biométrie et d'Intelligence Artificielle UR 875, INRA, F-31320 Castanet-Tolosan, France.

    • Thomas Schiex
    •  & Céline Noirot
  33. INRA-CNRGV BP52627, 31326 Castanet-Tolosan, France.

    • Arnaud Bellec
    • , Hélène Berges
    •  & Sonia Vautrin
  34. Plateforme bioinformatique Genotoul, UR875 Biométrie et Intelligence Artificielle, INRA, 31326 Castanet-Tolosan, France.

    • Christophe Klopp
    •  & Jérôme Mariette
  35. Institut National Polytechnique de Toulouse - ENSAT, Université de Toulouse, Avenue de l’Agrobiopole BP 32607, 31326 Castanet-Tolosan, France.

    • Corinne Delalande
    • , Pierre Frasse
    • , Mohamed Zouine
    • , Alain Latché
    • , Christine Rousseau
    • , Farid Regad
    • , Jean-Claude Pech
    • , Murielle Philippot
    •  & Mondher Bouzayen
  36. Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV), Ciudad Politecnica de la Innovación, escalera 8E, Ingeniero Fausto Elios s/n, 46022 Valencia, Spain.

    • Pierre Pericard
    • , Sonia Osorio
    • , Asunción Fernandez del Carmen
    • , Antonio Monforte
    •  & Antonio Granell
  37. Instituto de Hortofruticultura Subtropical y Mediterránea “La Mayora”, Universidad de Malaga - Consejo Superior de Investigaciones Cientificas (IHSM-UMA-CSIC), 29750 Algarrobo-Costa (Málaga), Spain.

    • Rafael Fernandez-Muñoz
  38. Instituto de Biotecnología, PO Box 25, B1712WAA Castelar, Argentina.

    • Mariana Conte
    • , Gabriel Lichtenstein
    •  & Fernando Carrari
  39. Institute for Biomedical Technologies, National Research Council of Italy, Via F. Cervi 93, 20090 Segrate (Milano), Italy.

    • Gianluca De Bellis
    • , Fabio Fuligni
    •  & Clelia Peano
  40. Institute of Plant Genetics, Research Division Portici, National Research Council of Italy, Via Università 133, 80055 Portici (Naples), Italy.

    • Silvana Grandillo
    •  & Pasquale Termolino
  41. ENEA, Casaccia Research Center, Via Anguillarese 301, 00123 Roma, Italy.

    • Marco Pietrella
    • , Elio Fantini
    • , Giulia Falcone
    • , Alessia Fiore
    •  & Giovanni Giuliano
  42. Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33 - 56127 Pisa, Italy.

    • Marco Pietrella
  43. ENEA, Trisaia Research Center, S.S. Ionica - Km 419.5, 75026 Rotondella (Matera), Italy.

    • Loredana Lopez
    • , Paolo Facella
    • , Gaetano Perrotta
    •  & Loretta Daddiego
  44. James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK.

    • Glenn Bryan
  45. Barcelona Supercomputing Center, Nexus II Building, c/ Jordi Girona, 29, 08034 Barcelona, Spain.

    • Modesto Orozco
    • , Xavier Pastor
    •  & David Torrents
  46. Institute of Research in Biomedicine, c/ Josep Samiter 1-5, 08028 Barcelona, Spain

    • Modesto Orozco
  47. ICREA, Pg Lluís Companys, 23, 08010 Barcelona, Spain.

    • David Torrents
  48. Keygene N.V., Agro Business Park 90, 6708 PW Wageningen, The Netherlands.

    • Marco G. M. van Schriek
    • , Richard M.C. Feron
    • , Jan van Oeveren
    • , Peter de Heer
    • , Lorena daPonte
    • , Saskia Jacobs-Oomen
    • , Mike Cariaso
    • , Marcel Prins
    • , Michiel J. T. van Eijk
    • , Antoine Janssen
    • , Mark J. J. van Haaren
    • , Erwin Datema
    •  & Roeland C. H. J. van Ham
  49. Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, 305-806, Republic of Korea.

    • Sung-Hwan Jo
    • , Jungeun Kim
    • , Suk-Yoon Kwon
    • , Sangmi Kim
    • , Dal-Hoe Koo
    • , Sanghyeob Lee
    •  & Cheol-Goo Hur
  50. Life Technologies, 500 Cummings Center, Beverly, Massachusetts 01915, USA.

    • Christopher Clouser
  51. Life Technologies, 25 avenue de la Baltique, BP 96, 91943 Courtaboeuf Cedex 3, France.

    • Alain Rico
  52. Max Planck Institute for Plant Breeding Research, Carl von Linné Weg 10, 50829 Cologne, Germany.

    • Asis Hallab
    • , Christiane Gebhardt
    • , Kathrin Klee
    • , Anika Jöcker
    • , Jens Warfsmann
    •  & Ulrike Göbel
  53. School of Agriculture, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki-shi, Kanagawa 214-8571, Japan.

    • Shingo Kawamura
    •  & Kentaro Yano
  54. Department of Plant Science and Plant Pathology, Montana State University, Bozeman, Montana 59717, USA.

    • Jamie D. Sherman
  55. NARO Institute of Vegetable and Tea Science, 360 Kusawa, Ano, Tsu, Mie 514-2392, Japan.

    • Hiroyuki Fukuoka
    •  & Satomi Negoro
  56. National Institute of Plant Genome Research, New Delhi 110 067, India.

    • Sarita Bhutty
    • , Parul Chowdhury
    •  & Debasis Chattopadhyay
  57. Plant Research International, Business Unit Bioscience, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.

    • Erwin Datema
    • , Sandra Smit
    • , Elio G. W. M. Schijlen
    • , Jose van de Belt
    • , Jan C. van Haarst
    • , Sander A. Peters
    • , Marjo J. van Staveren
    • , Marleen H. C. Henkens
    • , Paul J. W. Mooyman
    • , Thamara Hesselink
    •  & Roeland C. H. J. van Ham
  58. Institute of Plant Genetic Engineering, Qingdao Agricultural University, Qingdao 266109, China.

    • Guoyong Jiang
  59. Roche Applied Science, D-82377 Penzberg, Germany.

    • Marcus Droege
  60. Seoul National University, Department of Plant Science and Plant Genomics and Breeding Institute, Seoul 151-921, Republic of Korea.

    • Doil Choi
    • , Byung-Cheol Kang
    • , Byung Dong Kim
    • , Minkyu Park
    • , Seungill Kim
    •  & Seon-In Yeom
  61. Seoul National University, Department of Agricultural Biotechnology, Seoul 151-921, Republic of Korea.

    • Yong-Hwan Lee
  62. Seoul National University, Crop Functional Genomics Center, College of Agriculture and Life Sciences, Seoul 151-921, Republic of Korea.

    • Yang-Do Choi
  63. High-Tech Research Center, Shandong Academy of Agricultural Sciences, Jinan, 250000 Shandong, China.

    • Guangcun Li
  64. Institute of Vegetables, Shandong Academy of Agricultural Sciences, Jinan, 250100 Shandong, China.

    • Jianwei Gao
  65. School of Life Sciences, Sichuan University, Chengdu, Sichuan 610064, China.

    • Yongsheng Liu
    •  & Shengxiong Huang
  66. Sistemas Genomicos, Parque Tecnológico de Valencia, Ronda G. Marconi, 6, 46980 Paterna (Valencia), Spain.

    • Victoria Fernandez-Pedrosa
    • , Carmen Collado
    •  & Sheila Zuñiga
  67. College of Horticulture, South China Agricultural University, 510642 Guangzhou, China.

    • Guoping Wang
  68. Syngenta Biotechnology, Inc. 3054 East Cornwallis Road, Research Triangle Park, North Carolina 27709 Durham, USA.

    • Rebecca Cade
    •  & Robert A. Dietrich
  69. Norwich Research Park, Norwich NR4 7UH, UK.

    • Jane Rogers
  70. Department of Botany, The Natural History Museum, Cromwell Road, London SW7 5BD, UK.

    • Sandra Knapp
  71. United States Department of Agriculture - Agricultural Research Service, Robert W. Holley Center, Tower Road, Cornell University campus, Ithaca, New York 14853, USA.

    • Zhangjun Fei
    • , Ruth A. White
    • , Theodore W. Thannhauser
    •  & James J. Giovannoni
  72. Instituto de Hortofruticultura Subtropical y Mediterranea. Departamento de Biologia Molecular y Bioquimica, 29071 Málaga, Spain.

    • Miguel Angel Botella
    •  & Louise Gilbert
  73. Centre de Regulacio Genomica, Universitat Pompeu Fabra, Dr Aiguader, 88, E-08003 Barcelona, Spain.

    • Ramon Gonzalez
  74. Arizona Genomics Institute, BIO-5 Institute for Collaborative Research, School of Plant Sciences, Thomas W. Keating Building, 1657 E. Helen Street, Tucson, Arizona 85721, USA.

    • Jose Luis Goicoechea
    • , Yeisoo Yu
    • , David Kudrna
    • , Kristi Collura
    • , Marina Wissotski
    •  & Rod Wing
  75. Crop Bioinformatics, Institute of Crop Science and Resource Conservation, University of Bonn, 53115 Bonn, Germany.

    • Heiko Schoof
  76. Department of Plant and Soil Sciences, and Delaware Biotechnology Institute, University of Delaware, Newark, Delaware 19711, USA.

    • Blake C. Meyers
    • , Aishwarya Bala Gurazada
    •  & Pamela J. Green
  77. Interdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi 110 021, India.

    • Saloni Mathur
    • , Shailendra Vyas
    • , Amolkumar U. Solanke
    • , Rahul Kumar
    • , Vikrant Gupta
    • , Arun K. Sharma
    • , Paramjit Khurana
    • , Jitendra P. Khurana
    •  & Akhilesh K. Tyagi
  78. University of East Anglia, BIO, Norwich NR4 7TJ, UK.

    • Tamas Dalmay
  79. University of East Anglia, CMP, Norwich NR4 7TJ, UK.

    • Irina Mohorianu
  80. Department of Biology and the UF Genetics Institute, Cancer and Genetics Research Complex 2033 Mowry Road, PO Box 103610, Gainesville, Florida 32610, USA.

    • Brandon Walts
    • , Srikar Chamala
    •  & W. Brad Barbazuk
  81. Plant Genome Mapping Laboratory, 111 Riverbend Road, University of Georgia, Athens, Georgia 30602, USA.

    • Jingping Li
    • , Hui Guo
    • , Tae-Ho Lee
    • , Yupeng Wang
    • , Dong Zhang
    • , Andrew H. Paterson
    • , Xiyin Wang
    •  & Haibao Tang
  82. Center for Genomics and Computational Biology, School of Life Sciences, and School of Sciences, Hebei United University, Tangshan, Hebei 063000, China.

    • Xiyin Wang
  83. J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, Maryland 20850, USA.

    • Haibao Tang
  84. University of Naples “Federico II” Department of Soil, Plant, Environmental and Animal Production Sciences, Via Universita', 100, 80055 Portici (Naples), Italy.

    • Amalia Barone
    • , Maria Luisa Chiusano
    • , Maria Raffaella Ercolano
    • , Nunzio D’Agostino
    • , Miriam Di Filippo
    • , Alessandra Traini
    • , Walter Sanseverino
    •  & Luigi Frusciante
  85. Division of Plant and Crop Sciences, University of Nottingham, Sutton Bonington, Loughborough LE12 5RD, UK.

    • Graham B. Seymour
  86. Department of Chemistry and Biochemistry, Stephenson Research and Technology Center, University of Oklahoma, Norman, Oklahoma 73019, USA.

    • Mounir Elharam
    • , Ying Fu
    • , Axin Hua
    • , Steven Kenton
    • , Jennifer Lewis
    • , Shaoping Lin
    • , Fares Najar
    • , Hongshing Lai
    • , Baifang Qin
    • , Chunmei Qu
    • , Ruihua Shi
    • , Douglas White
    • , James White
    • , Yanbo Xing
    • , Keqin Yang
    • , Jing Yi
    • , Ziyun Yao
    • , Liping Zhou
    •  & Bruce A. Roe
  87. CRIBI, University of Padua, via Ugo Bassi 58/B, 35131 Padova, Italy.

    • Alessandro Vezzi
    • , Michela D’Angelo
    • , Rosanna Zimbello
    • , Riccardo Schiavon
    • , Elisa Caniato
    • , Chiara Rigobello
    • , Davide Campagna
    • , Nicola Vitulo
    •  & Giorgio Valle
  88. Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA.

    • David R. Nelson
  89. Department of Agriculture and Environmental Sciences, University of Udine, via delle Scienze 208, 33100, Udine, Italy.

    • Emanuele De Paoli
  90. Wageningen University, Laboratory of Genetics, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.

    • Dora Szinay
    •  & Hans H. de Jong
  91. Wageningen University, Laboratory of Plant Breeding, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.

    • Dora Szinay
    • , Yuling Bai
    •  & Richard G. F. Visser
  92. Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.

    • René M. Klein Lankhorst
  93. Wellcome Trust Sanger Institute Hinxton, Cambridge CB10 1SA, UK.

    • Helen Beasley
    • , Karen McLaren
    • , Christine Nicholson
    •  & Claire Riddle
  94. Ylichron SrL, Casaccia Research Center, Via Anguillarese 301, 00123 Roma, Italy.

    • Giulio Gianese

Consortia

  1. The Tomato Genome Consortium

    Kazusa DNA Research Institute

    454 Life Sciences, a Roche company

    Amplicon Express Inc.

    Beijing Academy of Agriculture and Forestry Sciences

    BGI-Shenzhen

    BMR-Genomics SrL

    Boyce Thompson Institute for Plant Research

    Centre for BioSystems Genomics

    Centro Nacional de Análisis Genómico (CNAG)

    China Agricultural University

    Chinese Academy of Agricultural Sciences

    Chinese Academy of Sciences

    Cold Spring Harbor Laboratory and United States Department of Agriculture – Agricultural Research Service

    Colorado State University

    Cornell University

    Genome Bioinformatics Laboratory GRIB–IMIM/UPF/CRG

    Ghent University-VIB

    Hebrew University of Jerusalem

    Heilongjiang Academy of Agricultural Sciences

    Helmholtz Center for Health and Environment

    Henan Agricultural University

    Huazhong Agricultural University

    Imperial College London

    Indian Agricultural Research Institute

    INRA Avignon

    INRA Bordeaux

    INRA Toulouse

    Institut National Polytechnique de Toulouse

    Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV)

    Instituto de Hortofruticultura Subtropical y Mediterránea (IHSM-UMA-CSIC)

    Instituto Nacional de Tecnología Agropecuaría (IB-INTA) and Consejo Nacionalde Investigaciones Científicas y Técnicas (CONICET)

    Italian National Res Council, Institute for Biomedical Technologies

    Italian National Research Council, Institute of Plant Genetics, Research Division Portici

    Italian National Agency for New technologies, Energy and Sustainable Development

    James Hutton Institute

    Joint IRB-BSC program on Computational Biology

    Keygene N.V.

    Korea Research Institute of Bioscience and Biotechnology

    Life Technologies

    Max Planck Institute for Plant Breeding Research

    Meiji University

    Montana State University

    NARO Institute of Vegetable and Tea Science

    National Institute of Plant Genome Research

    Plant Research International

    Qingdao Agricultural University

    Roche Applied Science

    Seoul National University

    Shandong Academy of Agricultural Sciences

    Sichuan University

    Sistemas Genomicos

    South China Agricultural University

    Syngenta Biotechnology

    The Genome Analysis Centre

    The Natural History Museum

    United States Department of Agriculture – Agricultural Research Service, Robert W. Holley Center and Boyce Thompson Institute for Plant Research

    Universidad de Malaga-Consejo Superior de Investigaciones Cientificas

    Universitat Pompeu Fabra

    University of Arizona

    University of Bonn

    University of Delaware

    University of Delhi South Campus

    University of East Anglia, School of Biological Sciences

    University of East Anglia, School of Computing Sciences

    University of Florida

    University of Georgia

    University of Naples “Federico II”

    University of Nottingham

    University of Oklahoma

    University of Padua

    University of Tennessee Health Science Center

    University of Udine

    Wageningen University

    Wellcome Trust Sanger Institute

    Ylichron SrL

    Principal Investigators

Authors

    Contributions

    For full details of author contributions, please see the Supplementary Information.

    Competing interests

    The author declare no competing financial interests.

    Corresponding authors

    Correspondence to Dani Zamir or Giovanni Giuliano or Giovanni Giuliano.

    Supplementary information

    PDF files

    1. 1.

      Supplementary Information

      This file contains Supplementary Methods, Supplementary Results, Supplementary Figures 1-56 and additional references –see Contents for details.

    Zip files

    1. 1.

      Supplementary Tables

      This zipped excel file contains Supplementary Tables 1-78.

    2. 2.

      Supplementary Tables

      This zipped archive contains Supplementary HTM Tables 1-269. The tables can be opened by any web browser and contain additional text that can be visualized by placing the mouse over the image.

    About this article

    Publication history

    Received

    Accepted

    Published

    DOI

    https://doi.org/10.1038/nature11119

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