Literature DB >> 26147403

Combinations of the Ghd7, Ghd8 and Hd1 genes largely define the ecogeographical adaptation and yield potential of cultivated rice.

Jia Zhang1, Xiangchun Zhou1, Wenhao Yan1, Zhanyi Zhang1, Li Lu1, Zhongmin Han1, Hu Zhao1, Haiyang Liu1, Pan Song1, Yong Hu1, Guojing Shen1, Qin He1, Sibin Guo2, Guoqing Gao2, Gongwei Wang1, Yongzhong Xing1.   

Abstract

Rice cultivars have been adapted to favorable ecological regions and cropping seasons. Although several heading date genes have separately made contributions to this adaptation, the roles of gene combinations are still unclear. We employed a map-based cloning approach to isolate a heading date gene, which coordinated the interaction between Ghd7 and Ghd8 to greatly delay rice heading. We resequenced these three genes in a germplasm collection to analyze natural variation. Map-based cloning demonstrated that the gene largely affecting the interaction between Ghd7 and Ghd8 was Hd1. Natural variation analysis showed that a combination of loss-of-function alleles of Ghd7, Ghd8 and Hd1 contributes to the expansion of rice cultivars to higher latitudes; by contrast, a combination of pre-existing strong alleles of Ghd7, Ghd8 and functional Hd1 (referred as SSF) is exclusively found where ancestral Asian cultivars originated. Other combinations have comparatively larger favorable ecological scopes and acceptable grain yield. Our results indicate that the combinations of Ghd7, Ghd8 and Hd1 largely define the ecogeographical adaptation and yield potential in rice cultivars. Breeding varieties with the SSF combination are recommended for tropical regions to fully utilize available energy and light resources and thus produce greater yields.
© 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Entities:  

Keywords:  Oryza rufipogon; Oryza sativa; combinations; ecogeographical adaptation; grain yield; heading date; natural variation

Mesh:

Substances:

Year:  2015        PMID: 26147403     DOI: 10.1111/nph.13538

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  38 in total

1.  Integrated analysis of phenome, genome, and transcriptome of hybrid rice uncovered multiple heterosis-related loci for yield increase.

Authors:  Dayong Li; Zhiyuan Huang; Shuhui Song; Yeyun Xin; Donghai Mao; Qiming Lv; Ming Zhou; Dongmei Tian; Mingfeng Tang; Qi Wu; Xue Liu; Tingting Chen; Xianwei Song; Xiqin Fu; Bingran Zhao; Chengzhi Liang; Aihong Li; Guozhen Liu; Shigui Li; Songnian Hu; Xiaofeng Cao; Jun Yu; Longping Yuan; Caiyan Chen; Lihuang Zhu
Journal:  Proc Natl Acad Sci U S A       Date:  2016-09-23       Impact factor: 11.205

2.  Structural Insight into DNA Recognition by CCT/NF-YB/YC Complexes in Plant Photoperiodic Flowering.

Authors:  Cuicui Shen; Haiyang Liu; Zeyuan Guan; Junjie Yan; Ting Zheng; Wenhao Yan; Changyin Wu; Qifa Zhang; Ping Yin; Yongzhong Xing
Journal:  Plant Cell       Date:  2020-08-25       Impact factor: 11.277

Review 3.  Rice functional genomics: decades' efforts and roads ahead.

Authors:  Rongzhi Chen; Yiwen Deng; Yanglin Ding; Jingxin Guo; Jie Qiu; Bing Wang; Changsheng Wang; Yongyao Xie; Zhihua Zhang; Jiaxin Chen; Letian Chen; Chengcai Chu; Guangcun He; Zuhua He; Xuehui Huang; Yongzhong Xing; Shuhua Yang; Daoxin Xie; Yaoguang Liu; Jiayang Li
Journal:  Sci China Life Sci       Date:  2021-12-07       Impact factor: 6.038

4.  Genome-wide identification and function characterization of GATA transcription factors during development and in response to abiotic stresses and hormone treatments in pepper.

Authors:  Chuying Yu; Ning Li; Yanxu Yin; Fei Wang; Shenghua Gao; Chunhai Jiao; Minghua Yao
Journal:  J Appl Genet       Date:  2021-02-24       Impact factor: 3.240

5.  Genome-Wide Association Studies Reveal the Genetic Basis of Ionomic Variation in Rice.

Authors:  Meng Yang; Kai Lu; Fang-Jie Zhao; Weibo Xie; Priya Ramakrishna; Guangyuan Wang; Qingqing Du; Limin Liang; Cuiju Sun; Hu Zhao; Zhanyi Zhang; Zonghao Liu; Jingjing Tian; Xin-Yuan Huang; Wensheng Wang; Huaxia Dong; Jintao Hu; Luchang Ming; Yongzhong Xing; Gongwei Wang; Jinhua Xiao; David E Salt; Xingming Lian
Journal:  Plant Cell       Date:  2018-10-29       Impact factor: 11.277

6.  Assessment of the effect of ten heading time genes on reproductive transition and yield components in rice using a CRISPR/Cas9 system.

Authors:  Yue Cui; Mengmeng Zhu; Zhengjin Xu; Quan Xu
Journal:  Theor Appl Genet       Date:  2019-03-19       Impact factor: 5.699

7.  Bin-based genome-wide association analyses improve power and resolution in QTL mapping and identify favorable alleles from multiple parents in a four-way MAGIC rice population.

Authors:  Zhongmin Han; Gang Hu; Hua Liu; Famao Liang; Lin Yang; Hu Zhao; Qinghua Zhang; Zhixin Li; Qifa Zhang; Yongzhong Xing
Journal:  Theor Appl Genet       Date:  2019-09-23       Impact factor: 5.699

8.  Genetic architecture of subspecies divergence in trace mineral accumulation and elemental correlations in the rice grain.

Authors:  Yongjun Tan; Liang Sun; Qingnan Song; Donghai Mao; Jieqiang Zhou; Youru Jiang; Jiurong Wang; Tony Fan; Qihong Zhu; Daoyou Huang; Han Xiao; Caiyan Chen
Journal:  Theor Appl Genet       Date:  2019-11-16       Impact factor: 5.699

9.  Lessons from natural variations: artificially induced heading date variations for improvement of regional adaptation in rice.

Authors:  Yong Hu; Shuangle Li; Yongzhong Xing
Journal:  Theor Appl Genet       Date:  2018-10-31       Impact factor: 5.699

10.  QTL mapping of domestication and diversifying selection related traits in round-fruited semi-wild Xishuangbanna cucumber (Cucumis sativus L. var. xishuangbannanesis).

Authors:  Yupeng Pan; Shuping Qu; Kailiang Bo; Meiling Gao; Kristin R Haider; Yiqun Weng
Journal:  Theor Appl Genet       Date:  2017-04-24       Impact factor: 5.699

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.