The rubber tree genome reveals new insights into rubber production and species adaptation

Tang Chaorong, Yang Meng, Fang Yongjun, Luo Yingfeng, Gao Shenghan, Xiao Xiaohu, An Zewei, Zhou Binhui, Zhang Bing, Tan Xinyu, Yeang Hoong Yeet, Qin Yunxia, Yang Jianghua, Lin Qiang, Mei Hailiang, Montoro Pascal, Long Xiangyu, Qi Jiyan, Hua Yuwei, He Zilong, Sun Min, Li Wenjie, Zeng Xia, Cheng Han, Liu Ying, Yang Jin, Tian Weimin, Zhuang Nansheng, Zeng Rizhong, Li Dejun, He Peng, Li Zhe, Zou Zhi, Li Shuangli, Li Chenji, Wang Jixiang, Wei Dong, Lai Chao-Qiang, Luo Wei, Yu Jun, Hu Songnian, Huang Huasun. 2016. The rubber tree genome reveals new insights into rubber production and species adaptation. Nature Plants, 10 p.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
Published version - Anglais
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Abstract : The Para rubber tree (Hevea brasiliensis) is an economically important tropical tree species that produces natural rubber, an essential industrial raw material. Here we present a high-quality genome assembly of this species (1.37 Gb, scaffold N50 = 1.28 Mb) that covers 93.8% of the genome (1.47 Gb) and harbours 43,792 predicted protein-coding genes. A striking expansion of the REF/SRPP (rubber elongation factor/small rubber particle protein) gene family and its divergence into several laticifer-specific isoforms seem crucial for rubber biosynthesis. The REF/SRPP family has isoforms with sizes similar to or larger than SRPP1 (204 amino acids) in 17 other plants examined, but no isoforms with similar sizes to REF1 (138 amino acids), the predominant molecular variant. A pivotal point in Hevea evolution was the emergence of REF1, which is located on the surface of large rubber particles that account for 93% of rubber in the latex (despite constituting only 6% of total rubber particles, large and small). The stringent control of ethylene synthesis under active ethylene signalling and response in laticifers resolves a longstanding mystery of ethylene stimulation in rubber production. Our study, which includes the re-sequencing of five other Hevea cultivars and extensive RNA-seq data, provides a valuable resource for functional genomics and tools for breeding elite Hevea cultivars. The rubber tree (Hevea brasiliensis, hereafter referred to as Hevea) is a member of the spurge family (Euphorbiaceae), along with several other economically important species such as cassava (Manihot esculenta) and the castor oil plant (Ricinus communis). Natural rubber (cis-1, 4-polyisoprene) makes up about one-third of the volume of latex that is essentially cytoplasm of the articulated laticifers in Hevea. The latex is extracted by tapping the bark, a non-destructive method of harvesting that facilitates continual production. As an industrial commodity, natural rubber is an elastomer with physical and chemical properties that cannot be fully matched by synthetic rubber1. In contrast to synthetics, the production of natural rubber is sustainable and environment friendly2. The commercial cultivation of Hevea, a native to the Amazon Basin, began in 1896 on a plantation scale in Malaya (now Malaysia) and expanded to other Southeast Asian countries that lead in world natural rubber production today3. Decades of selective breeding have resulted in a gradual improvement in rubber productivity, from 650 kg ha–1 derived from unselected seedlings during the 1920s to 2,500 kg ha–1 yielded by elite cultivars by the 1990s4. Nevertheless, the field production achieved so far is still well below the theoretical yield of 7,000–12,000 kg ha–1, as has been suggested for the rubber tree5. Meanwhile, conventional rubber breeding has been stagnating in the introduction of high-yield cultivars. The reasons include a narrow genetic basis for exploiting breeding potential and difficulty in introducing wild germplasms because of the genetic burden in removing unfavourable alleles6. The incorporation of marker-assisted selection and transgenic techniques offers promise to improve breeding efficiency for latex yield, and sequencing of the Hevea genome would uncover even more avenues leading to this end. The first draft Hevea genome was released by a Malaysian team7 that was participant to the recent boom in transcriptomic and proteomic studies of the species8,9,10,11. However, its low sequence coverage (∼13×) and a lack of large insert libraries (such as fosmid- or BAC-based clone libraries) have limited the success of genome assembly (a scaffold N50 size of 2,972 bp), precluding its application for furthering quality research in the field. Here, we report a high-quality genome assembly of Hevea Reyan7-33-97, an elite cultivar widely planted in China12,13 based on sequence data from both whole-genome shotgun (WGS) and pooled BAC clones. This assembly contains 7,453 scaffolds (N50 = 1.28 Mb), has a length of 1.37 Gb and covers ∼94% of the predicted genome size (1.46 Gb). Together with analysis of data from re-sequencing five other cultivars and comprehensive transcriptomic surveys, we aim to obtain new insights into the physiology of laticifers and molecular details of rubber biosynthesis, especially in relation to ethylene-stimulated rubber production. (Résumé d'auteur)

Mots-clés Agrovoc : Hevea brasiliensis, Caoutchouc, Génome, Protéine, Expression des gènes, Composition chimique, Acide aminé, Éthylène, Biosynthèse, Synthèse protéique, génomique, Manihot esculenta

Mots-clés géographiques Agrovoc : Malaisie, Asie du Sud-Est

Mots-clés libres : Hevea brasiliensis, Rubber, Genome, Genomics, Transcriptome, Transcriptomics, Ethylene, Rubber biosynthesis

Classification Agris : F30 - Plant genetics and breeding
F60 - Plant physiology and biochemistry

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Tang Chaorong, CATAS (CHN)
  • Yang Meng, Chinese Academy of Sciences (CHN)
  • Fang Yongjun, CATAS (CHN)
  • Luo Yingfeng, Chinese Academy of Sciences (CHN)
  • Gao Shenghan, Chinese Academy of Sciences (CHN)
  • Xiao Xiaohu, CATAS (CHN)
  • An Zewei, CATAS (CHN)
  • Zhou Binhui, CATAS (CHN)
  • Zhang Bing, Chinese Academy of Sciences (CHN)
  • Tan Xinyu, Chinese Academy of Sciences (CHN)
  • Yeang Hoong Yeet, MRB (MYS)
  • Qin Yunxia, CATAS (CHN)
  • Yang Jianghua, CATAS (CHN)
  • Lin Qiang, Chinese Academy of Sciences (CHN)
  • Mei Hailiang, Chinese Academy of Sciences (CHN)
  • Montoro Pascal, CIRAD-BIOS-UMR AGAP (FRA)
  • Long Xiangyu, CATAS (CHN)
  • Qi Jiyan, CATAS (CHN)
  • Hua Yuwei, CATAS (CHN)
  • He Zilong, Chinese Academy of Sciences (CHN)
  • Sun Min, Chinese Academy of Sciences (CHN)
  • Li Wenjie, Chinese Academy of Sciences (CHN)
  • Zeng Xia, CATAS (CHN)
  • Cheng Han, CATAS (CHN)
  • Liu Ying, Chinese Academy of Sciences (CHN)
  • Yang Jin, Chinese Academy of Sciences (CHN)
  • Tian Weimin, Chinese Academy of Sciences (CHN)
  • Zhuang Nansheng, Hainan University (CHN)
  • Zeng Rizhong, CATAS (CHN)
  • Li Dejun, CATAS (CHN)
  • He Peng, CATAS (CHN)
  • Li Zhe, CATAS (CHN)
  • Zou Zhi, CATAS (CHN)
  • Li Shuangli, Chinese Academy of Sciences (CHN)
  • Li Chenji, Chinese Academy of Sciences (CHN)
  • Wang Jixiang, Chinese Academy of Sciences (CHN)
  • Wei Dong, Chinese Academy of Sciences (CHN)
  • Lai Chao-Qiang, Tufts University (USA)
  • Luo Wei, CATAS (CHN)
  • Yu Jun, Chinese Academy of Sciences (CHN)
  • Hu Songnian, Chinese Academy of Sciences (CHN)
  • Huang Huasun, CATAS (CHN)

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