Literature DB >> 23400830

Three genetic systems controlling growth, development and productivity of rice (Oryza sativa L.): a reevaluation of the 'Green Revolution'.

Fan Zhang1, Yun-Zhu Jiang, Si-Bin Yu, J Ali, A H Paterson, G S Khush, Jian-Long Xu, Yong-Ming Gao, Bin-Ying Fu, R Lafitte, Zhi-Kang Li.   

Abstract

The Green Revolution (GR-I) included worldwide adoption of semi-dwarf rice cultivars (SRCs) with mutant alleles at GA20ox2 or SD1 encoding gibberellin 20-oxidase. Two series of experiments were conducted to characterize the pleiotropic effects of SD1 and its relationships with large numbers of QTLs affecting rice growth, development and productivity. The pleiotropic effects of SD1 in the IR64 genetic background for increased height, root length/mass and grain weight, and for reduced spikelet fertility and delayed heading were first demonstrated using large populations derived from near isogenic IR64 lines of SD1. In the second set of experiments, QTLs controlling nine growth and yield traits were characterized using a new molecular quantitative genetics model and the phenotypic data of the well-known IR64/Azucena DH population evaluated across 11 environments, which revealed three genetic systems: the SD1-mediated, SD1-repressed and SD1-independent pathways that control rice growth, development and productivity. The SD1-mediated system comprised 43 functional genetic units (FGUs) controlled by GA. The SD1-repressed system was the alternative one comprising 38 FGUs that were only expressed in the mutant sd1 backgrounds. The SD1-independent one comprised 64 FGUs that were independent of SD1. GR-I resulted from the overall differences between the former two systems in the three aspects: (1) trait/environment-specific contributions; (2) distribution of favorable alleles for increased productivity in the parents; and (3) different responses to (fertilizer) inputs. Our results suggest that at 71.4 % of the detected loci, a QTL resulted from the difference between a functional allele and a loss-of-function mutant, whereas at the remaining 28.6 % of loci, from two functional alleles with differentiated effects. Our results suggest two general strategies to achieve GR-II (1) by further exploiting the genetic potential of the SD1-repressed and SD1-independent pathways and (2) by restoring the SD1-mediated pathways, or 'back to the nature' to fully exploit the genetic diversity of those loci in the SD1-mediated pathways which are virtually inaccessible to most rice-breeding programs worldwide that are exclusively based on sd1.

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Year:  2013        PMID: 23400830     DOI: 10.1007/s00122-012-2033-1

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  28 in total

1.  Green revolution: a mutant gibberellin-synthesis gene in rice.

Authors:  A Sasaki; M Ashikari; M Ueguchi-Tanaka; H Itoh; A Nishimura; D Swapan; K Ishiyama; T Saito; M Kobayashi; G S Khush; H Kitano; M Matsuoka
Journal:  Nature       Date:  2002-04-18       Impact factor: 49.962

2.  QTL x environment interactions in rice. I. heading date and plant height.

Authors:  Z K Li; S B Yu; H R Lafitte; N Huang; B Courtois; S Hittalmani; C H M Vijayakumar; G F Liu; G C Wang; H E Shashidhar; J Y Zhuang; K L Zheng; V P Singh; J S Sidhu; S Srivantaneeyakul; G S Khush
Journal:  Theor Appl Genet       Date:  2003-09-05       Impact factor: 5.699

3.  Different plant hormones regulate similar processes through largely nonoverlapping transcriptional responses.

Authors:  Jennifer L Nemhauser; Fangxin Hong; Joanne Chory
Journal:  Cell       Date:  2006-08-11       Impact factor: 41.582

4.  Paleo-Green Revolution for rice.

Authors:  Andrew H Paterson; Zhi-Kang Li
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-21       Impact factor: 11.205

Review 5.  Gibberellins: perception, transduction and responses.

Authors:  R Hooley
Journal:  Plant Mol Biol       Date:  1994-12       Impact factor: 4.076

6.  Heterosis in rice seedlings: its relationship to gibberellin content and expression of gibberellin metabolism and signaling genes.

Authors:  Qian Ma; Peter Hedden; Qifa Zhang
Journal:  Plant Physiol       Date:  2011-06-21       Impact factor: 8.340

Review 7.  Gibberellin metabolism: new insights revealed by the genes.

Authors:  P Hedden; A L Phillips
Journal:  Trends Plant Sci       Date:  2000-12       Impact factor: 18.313

8.  Dissecting genetic networks underlying complex phenotypes: the theoretical framework.

Authors:  Fan Zhang; Hu-Qu Zhai; Andrew H Paterson; Jian-Long Xu; Yong-Ming Gao; Tian-Qing Zheng; Rong-Ling Wu; Bin-Ying Fu; Jauhar Ali; Zhi-Kang Li
Journal:  PLoS One       Date:  2011-01-20       Impact factor: 3.240

9.  New approach for rice improvement using a pleiotropic QTL gene for lodging resistance and yield.

Authors:  Taiichiro Ookawa; Tokunori Hobo; Masahiro Yano; Kazumasa Murata; Tsuyu Ando; Hiroko Miura; Kenji Asano; Yusuke Ochiai; Mayuko Ikeda; Ryoichi Nishitani; Takeshi Ebitani; Hidenobu Ozaki; Enrique R Angeles; Tadashi Hirasawa; Makoto Matsuoka
Journal:  Nat Commun       Date:  2010-11-30       Impact factor: 14.919

Review 10.  The genes of the Green Revolution.

Authors:  Peter Hedden
Journal:  Trends Genet       Date:  2003-01       Impact factor: 11.639

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  8 in total

1.  Map-Based Cloning of Seed Dormancy1-2 Identified a Gibberellin Synthesis Gene Regulating the Development of Endosperm-Imposed Dormancy in Rice.

Authors:  Heng Ye; Jiuhuan Feng; Lihua Zhang; Jinfeng Zhang; Muhamad S Mispan; Zhuanqin Cao; Donn H Beighley; Jianchang Yang; Xing-You Gu
Journal:  Plant Physiol       Date:  2015-09-15       Impact factor: 8.340

2.  Genomic Architecture of Yield Performance of an Elite Rice Hybrid Revealed by its Derived Recombinant Inbred Line and Their Backcross Hybrid Populations.

Authors:  Fan Zhang; Conghe Zhang; Xiuqin Zhao; Shuangbing Zhu; Kai Chen; Guixiang Zhou; Zhichao Wu; Min Li; Tianqing Zheng; Wensheng Wang; Zhi Yan; Qinyong Fei; Zhikang Li; Jinjie Chen; Jianlong Xu
Journal:  Rice (N Y)       Date:  2022-10-01       Impact factor: 5.638

3.  Traditional rice landraces in Lei-Qiong area of South China tolerate salt stress with strong antioxidant activity.

Authors:  Yan Hu; Yongxiang Huang; Shuangxi Zhou; Yueqin Zhang; Risheng Cheng; Jianfu Guo; Yu Ling
Journal:  Plant Signal Behav       Date:  2020-03-17

4.  SS1 (NAL1)- and SS2-Mediated Genetic Networks Underlying Source-Sink and Yield Traits in Rice (Oryza sativa L.).

Authors:  Jian-Long Xu; Yun Wang; Fan Zhang; Yuan Wu; Tian-Qing Zheng; Yong-Hong Wang; Xiu-Qin Zhao; Yan-Ru Cui; Kai Chen; Qiang Zhang; Hong-Xuan Lin; Jia-Yang Li; Zhi-Kang Li
Journal:  PLoS One       Date:  2015-07-10       Impact factor: 3.240

5.  Identification of QTLs for yield-related traits in RILs derived from the cross between pLIA-1 carrying Oryza longistaminata chromosome segments and Norin 18 in rice.

Authors:  Emily Gichuhi; Eiko Himi; Hidekazu Takahashi; Sinhao Zhu; Kazuyuki Doi; Kazuo Tsugane; Masahiko Maekawa
Journal:  Breed Sci       Date:  2016-11-02       Impact factor: 2.086

6.  Identification and Validation of Aerobic Adaptation QTLs in Upland Rice.

Authors:  Peng Xu; Jun Yang; Zhenbing Ma; Diqiu Yu; Jiawu Zhou; Dayun Tao; Zichao Li
Journal:  Life (Basel)       Date:  2020-05-14

7.  A Genetic Network Underlying Rhizome Development in Oryza longistaminata.

Authors:  Wenfei Li; Shilai Zhang; Guangfu Huang; Liyu Huang; Jing Zhang; Zheng Li; Fengyi Hu
Journal:  Front Plant Sci       Date:  2022-04-05       Impact factor: 6.627

8.  Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population.

Authors:  Kurniawan R Trijatmiko; Joko Prasetiyono; Michael J Thomson; Casiana M Vera Cruz; Sugiono Moeljopawiro; Andy Pereira
Journal:  Mol Breed       Date:  2014-06-29       Impact factor: 2.589

  8 in total

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