The tomato genome sequence provides insights into fleshy fruit evolution

Journal name:
Nature
Volume:
485,
Pages:
635–641
Date published:
DOI:
doi:10.1038/nature11119
Received
Accepted
Published online

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.

At a glance

Figures

  1. Tomato genome topography and synteny.
    Figure 1: Tomato genome topography and synteny.

    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 5cM 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 500kb, purple), genes (% nucleotides per 500kb, blue), chloroplast insertions; RNA-Seq reads from leaves and breaker fruits of S. lycopersicum and S. pimpinellifolium (number of reads per 500kb, green and red, respectively), microRNA genes (transcripts per million per 500kb, 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 9.8Mb, 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 Ks0.5, respectively. Green and magenta dots represent genes in collinear blocks which average 0.5<Ks1.5 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).

  2. The Solanum whole genome triplication.
    Figure 2: The Solanum whole genome triplication.

    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.

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

    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.

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

    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 1–3mm; T4, fruit 5–7mm; T5, fruit 11–13mm; T6, fruit mature green; T7, breaker; T8, breaker+3days; T9, breaker+7days). 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 1kb of the promoter region. 0 to 12 represent arbitrary units of gene expression.

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Primary accessions

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

    • Shusei Sato,
    • Satoshi Tabata,
    • Hideki Hirakawa,
    • Erika Asamizu,
    • Kenta Shirasawa,
    • Sachiko Isobe,
    • Takakazu Kaneko,
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    • Koh Aoki
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  4. Beijing Vegetable Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.

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  11. Department of Vegetable Science, College of Agronomy and Biotechnology, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China.

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  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.

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  19. Department of Agronomy, National Taiwan University, Taipei 107, Taiwan.

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  20. Department of Plant Biology, Cornell University, Ithaca, New York 14853, USA.

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

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  53. School of Agriculture, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki-shi, Kanagawa 214-8571, Japan.

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  54. Department of Plant Science and Plant Pathology, Montana State University, Bozeman, Montana 59717, USA.

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  58. Institute of Plant Genetic Engineering, Qingdao Agricultural University, Qingdao 266109, China.

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

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

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

    • Sanghyeob Lee

Consortia

  1. The Tomato Genome Consortium

  2. Kazusa DNA Research Institute

    • Shusei Sato,
    • Satoshi Tabata,
    • Hideki Hirakawa,
    • Erika Asamizu,
    • Kenta Shirasawa,
    • Sachiko Isobe,
    • Takakazu Kaneko,
    • Yasukazu Nakamura,
    • Daisuke Shibata &
    • Koh Aoki
  3. 454 Life Sciences, a Roche company

    • Michael Egholm &
    • James Knight
  4. Amplicon Express Inc.

    • Robert Bogden
  5. Beijing Academy of Agriculture and Forestry Sciences

    • Changbao Li
  6. BGI-Shenzhen

    • Yang Shuang,
    • Xun Xu,
    • Shengkai Pan,
    • Shifeng Cheng,
    • Xin Liu,
    • Yuanyuan Ren &
    • Jun Wang
  7. BMR-Genomics SrL

    • Alessandro Albiero,
    • Francesca Dal Pero &
    • Sara Todesco
  8. Boyce Thompson Institute for Plant Research

    • Joyce Van Eck,
    • Robert M. Buels,
    • Aureliano Bombarely,
    • Joseph R. Gosselin,
    • Minyun Huang,
    • Jonathan A. Leto,
    • Naama Menda,
    • Susan Strickler,
    • Linyong Mao,
    • Shan Gao,
    • Isaak Y. Tecle,
    • Thomas York,
    • Yi Zheng,
    • Julia T. Vrebalov,
    • JeMin Lee,
    • Silin Zhong &
    • Lukas A. Mueller
  9. Centre for BioSystems Genomics

    • Willem J. Stiekema
  10. Centro Nacional de Análisis Genómico (CNAG)

    • Paolo Ribeca &
    • Tyler Alioto
  11. China Agricultural University

    • Wencai Yang
  12. Chinese Academy of Agricultural Sciences

    • Sanwen Huang,
    • Yongchen Du,
    • Zhonghua Zhang,
    • Jianchang Gao,
    • Yanmei Guo,
    • Xiaoxuan Wang,
    • Ying Li &
    • Jun He
  13. Chinese Academy of Sciences

    • Chuanyou Li,
    • Zhukuan Cheng,
    • Jianru Zuo,
    • Jianfeng Ren,
    • Jiuhai Zhao,
    • Liuhua Yan,
    • Hongling Jiang,
    • Bao Wang,
    • Hongshuang Li,
    • Zhenjun Li,
    • Fuyou Fu,
    • Bingtang Chen,
    • Bin Han,
    • Qi Feng,
    • Danlin Fan,
    • Ying Wang,
    • Hongqing Ling &
    • Yongbiao Xue
  14. Cold Spring Harbor Laboratory and United States Department of Agriculture – Agricultural Research Service

    • Doreen Ware,
    • W. Richard McCombie,
    • Zachary B. Lippman,
    • Jer-Ming Chia,
    • Ke Jiang,
    • Shiran Pasternak,
    • Laura Gelley &
    • Melissa Kramer
  15. Colorado State University

    • Lorinda K. Anderson,
    • Song-Bin Chang,
    • Suzanne M. Royer,
    • Lindsay A. Shearer &
    • Stephen M. Stack
  16. Cornell University

    • Jocelyn K. C. Rose,
    • Yimin Xu,
    • Nancy Eannetta,
    • Antonio J. Matas,
    • Ryan McQuinn &
    • Steven D. Tanksley
  17. Genome Bioinformatics Laboratory GRIB–IMIM/UPF/CRG

    • Francisco Camara &
    • Roderic Guigó
  18. Ghent University-VIB

    • Stephane Rombauts,
    • Jeffrey Fawcett &
    • Yves Van de Peer
  19. Hebrew University of Jerusalem

    • Dani Zamir
  20. Heilongjiang Academy of Agricultural Sciences

    • Chunbo Liang
  21. Helmholtz Center for Health and Environment

    • Manuel Spannagl,
    • Heidrun Gundlach,
    • Remy Bruggmann &
    • Klaus Mayer
  22. Henan Agricultural University

    • Zhiqi Jia
  23. Huazhong Agricultural University

    • Junhong Zhang &
    • Zhibiao Ye
  24. Imperial College London

    • Gerard J. Bishop,
    • Sarah Butcher,
    • Rosa Lopez-Cobollo,
    • Daniel Buchan,
    • Ioannis Filippis &
    • James Abbott
  25. Indian Agricultural Research Institute

    • 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
  26. INRA Avignon

    • Mathilde Causse
  27. INRA Bordeaux

    • Christophe Rothan
  28. INRA Toulouse

    • Thomas Schiex,
    • Céline Noirot,
    • Arnaud Bellec,
    • Christophe Klopp,
    • Corinne Delalande,
    • Hélène Berges,
    • Jérôme Mariette,
    • Pierre Frasse &
    • Sonia Vautrin
  29. Institut National Polytechnique de Toulouse

    • Mohamed Zouine,
    • Alain Latché,
    • Christine Rousseau,
    • Farid Regad,
    • Jean-Claude Pech,
    • Murielle Philippot &
    • Mondher Bouzayen
  30. Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV)

    • Pierre Pericard,
    • Sonia Osorio,
    • Asunción Fernandez del Carmen,
    • Antonio Monforte &
    • Antonio Granell
  31. Instituto de Hortofruticultura Subtropical y Mediterránea (IHSM-UMA-CSIC)

    • Rafael Fernandez-Muñoz
  32. Instituto Nacional de Tecnología Agropecuaría (IB-INTA) and Consejo Nacionalde Investigaciones Científicas y Técnicas (CONICET)

    • Mariana Conte,
    • Gabriel Lichtenstein &
    • Fernando Carrari
  33. Italian National Res Council, Institute for Biomedical Technologies

    • Gianluca De Bellis,
    • Fabio Fuligni &
    • Clelia Peano
  34. Italian National Research Council, Institute of Plant Genetics, Research Division Portici

    • Silvana Grandillo &
    • Pasquale Termolino
  35. Italian National Agency for New technologies, Energy and Sustainable Development

    • Marco Pietrella,
    • Elio Fantini,
    • Giulia Falcone,
    • Alessia Fiore,
    • Giovanni Giuliano,
    • Loredana Lopez,
    • Paolo Facella,
    • Gaetano Perrotta &
    • Loretta Daddiego
  36. James Hutton Institute

    • Glenn Bryan
  37. Joint IRB-BSC program on Computational Biology

    • Modesto Orozco,
    • Xavier Pastor &
    • David Torrents
  38. Keygene N.V.

    • 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
  39. Korea Research Institute of Bioscience and Biotechnology

    • Sung-Hwan Jo,
    • Jungeun Kim,
    • Suk-Yoon Kwon,
    • Sangmi Kim,
    • Dal-Hoe Koo,
    • Sanghyeob Lee &
    • Cheol-Goo Hur
  40. Life Technologies

    • Christopher Clouser &
    • Alain Rico
  41. Max Planck Institute for Plant Breeding Research

    • Asis Hallab,
    • Christiane Gebhardt,
    • Kathrin Klee,
    • Anika Jöcker,
    • Jens Warfsmann &
    • Ulrike Göbel
  42. Meiji University

    • Shingo Kawamura &
    • Kentaro Yano
  43. Montana State University

    • Jamie D. Sherman
  44. NARO Institute of Vegetable and Tea Science

    • Hiroyuki Fukuoka &
    • Satomi Negoro
  45. National Institute of Plant Genome Research

    • Sarita Bhutty,
    • Parul Chowdhury &
    • Debasis Chattopadhyay
  46. Plant Research International

    • 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
  47. Qingdao Agricultural University

    • Guoyong Jiang
  48. Roche Applied Science

    • Marcus Droege
  49. Seoul National University

    • Doil Choi,
    • Byung-Cheol Kang,
    • Byung Dong Kim,
    • Minkyu Park,
    • Seungill Kim,
    • Seon-In Yeom,
    • Yong-Hwan Lee &
    • Yang-Do Choi
  50. Shandong Academy of Agricultural Sciences

    • Guangcun Li &
    • Jianwei Gao
  51. Sichuan University

    • Yongsheng Liu &
    • Shengxiong Huang
  52. Sistemas Genomicos

    • Victoria Fernandez-Pedrosa,
    • Carmen Collado &
    • Sheila Zuñiga
  53. South China Agricultural University

    • Guoping Wang
  54. Syngenta Biotechnology

    • Rebecca Cade &
    • Robert A. Dietrich
  55. The Genome Analysis Centre

    • Jane Rogers
  56. The Natural History Museum

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

    • Zhangjun Fei,
    • Ruth A. White,
    • Theodore W. Thannhauser &
    • James J. Giovannoni
  58. Universidad de Malaga-Consejo Superior de Investigaciones Cientificas

    • Miguel Angel Botella &
    • Louise Gilbert
  59. Universitat Pompeu Fabra

    • Ramon Gonzalez
  60. University of Arizona

    • Jose Luis Goicoechea,
    • Yeisoo Yu,
    • David Kudrna,
    • Kristi Collura,
    • Marina Wissotski &
    • Rod Wing
  61. University of Bonn

    • Heiko Schoof
  62. University of Delaware

    • Blake C. Meyers,
    • Aishwarya Bala Gurazada &
    • Pamela J. Green
  63. University of Delhi South Campus

    • Saloni Mathur,
    • Shailendra Vyas,
    • Amolkumar U. Solanke,
    • Rahul Kumar,
    • Vikrant Gupta,
    • Arun K. Sharma,
    • Paramjit Khurana,
    • Jitendra P. Khurana &
    • Akhilesh K. Tyagi
  64. University of East Anglia, School of Biological Sciences

    • Tamas Dalmay
  65. University of East Anglia, School of Computing Sciences

    • Irina Mohorianu
  66. University of Florida

    • Brandon Walts,
    • Srikar Chamala &
    • W. Brad Barbazuk
  67. University of Georgia

    • Jingping Li,
    • Hui Guo,
    • Tae-Ho Lee,
    • Yupeng Wang,
    • Dong Zhang,
    • Andrew H. Paterson,
    • Xiyin Wang &
    • Haibao Tang
  68. University of Naples “Federico II”

    • Amalia Barone,
    • Maria Luisa Chiusano,
    • Maria Raffaella Ercolano,
    • Nunzio D’Agostino,
    • Miriam Di Filippo,
    • Alessandra Traini,
    • Walter Sanseverino &
    • Luigi Frusciante
  69. University of Nottingham

    • Graham B. Seymour
  70. University of Oklahoma

    • 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
  71. University of Padua

    • Alessandro Vezzi,
    • Michela D’Angelo,
    • Rosanna Zimbello,
    • Riccardo Schiavon,
    • Elisa Caniato,
    • Chiara Rigobello,
    • Davide Campagna,
    • Nicola Vitulo &
    • Giorgio Valle
  72. University of Tennessee Health Science Center

    • David R. Nelson
  73. University of Udine

    • Emanuele De Paoli
  74. Wageningen University

    • Dora Szinay,
    • Hans H. de Jong,
    • Yuling Bai,
    • Richard G. F. Visser &
    • René M. Klein Lankhorst
  75. Wellcome Trust Sanger Institute

    • Helen Beasley,
    • Karen McLaren,
    • Christine Nicholson &
    • Claire Riddle
  76. Ylichron SrL

    • Giulio Gianese
  77. Principal Investigators

    • Shusei Sato,
    • Satoshi Tabata,
    • Lukas A. Mueller,
    • Sanwen Huang,
    • Yongchen Du,
    • Chuanyou Li,
    • Zhukuan Cheng,
    • Jianru Zuo,
    • Bin Han,
    • Ying Wang,
    • Hongqing Ling,
    • Yongbiao Xue,
    • Doreen Ware,
    • W. Richard McCombie,
    • Zachary B. Lippman,
    • Stephen M. Stack,
    • Steven D. Tanksley,
    • Yves Van de Peer,
    • Klaus Mayer,
    • Gerard J. Bishop,
    • Sarah Butcher,
    • Nagendra Kumar Singh,
    • Thomas Schiex,
    • Mondher Bouzayen,
    • Antonio Granell,
    • Fernando Carrari,
    • Gianluca De Bellis,
    • Giovanni Giuliano,
    • Glenn Bryan,
    • Michiel J. T. van Eijk,
    • Hiroyuki Fukuoka,
    • Debasis Chattopadhyay,
    • Roeland C. H. J. van Ham,
    • Doil Choi,
    • Jane Rogers,
    • Zhangjun Fei,
    • James J. Giovannoni,
    • Rod Wing,
    • Heiko Schoof,
    • Blake C. Meyers,
    • Jitendra P. Khurana,
    • Akhilesh K. Tyagi,
    • Tamas Dalmay,
    • Andrew H. Paterson,
    • Xiyin Wang,
    • Luigi Frusciante,
    • Graham B. Seymour,
    • Bruce A. Roe,
    • Giorgio Valle,
    • Hans H. de Jong &
    • René M. Klein Lankhorst

Contributions

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

Competing financial interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to:

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.

Author details

    Supplementary information

    PDF files

    1. Supplementary Information (16.4M)

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

    Zip files

    1. Supplementary Tables (28.7M)

      This zipped excel file contains Supplementary Tables 1-78.

    2. Supplementary Tables (250K)

      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.

    Additional data