Literature DB >> 24259710

Genetic analysis of the metabolome exemplified using a rice population.

Liang Gong1, Wei Chen, Yanqiang Gao, Xianqing Liu, Hongyan Zhang, Caiguo Xu, Sibin Yu, Qifa Zhang, Jie Luo.   

Abstract

Plant metabolites are crucial for both plant life and human nutrition. Despite recent advance in metabolomics, the genetic control of plant metabolome remains largely unknown. Here, we performed a genetic analysis of the rice metabolome that provided over 2,800 highly resolved metabolic quantitative trait loci for 900 metabolites. Distinct and overlapping accumulation patterns of metabolites were observed and complex genetic regulation of metabolism was revealed in two different tissues. We associated 24 candidate genes to various metabolic quantitative trait loci by data mining, including ones regulating important morphological traits and biological processes. The corresponding pathways were reconstructed by updating in vivo functions of previously identified and newly assigned genes. This study demonstrated a powerful tool and provided a vast amount of high-quality data for understanding the plasticity of plant metabolome, which may help bridge the gap between the genome and phenome.

Entities:  

Keywords:  Oryza sativa; gene function; metabolic profiling; recombinant inbred line

Mesh:

Substances:

Year:  2013        PMID: 24259710      PMCID: PMC3864304          DOI: 10.1073/pnas.1319681110

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  41 in total

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Journal:  Plant Physiol       Date:  2010-07-20       Impact factor: 8.340

Review 2.  Metabolomics for functional genomics, systems biology, and biotechnology.

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Journal:  Annu Rev Plant Biol       Date:  2010       Impact factor: 26.379

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Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-14       Impact factor: 11.205

4.  Detection and identification of 700 drugs by multi-target screening with a 3200 Q TRAP LC-MS/MS system and library searching.

Authors:  S Dresen; N Ferreirós; H Gnann; R Zimmermann; W Weinmann
Journal:  Anal Bioanal Chem       Date:  2010-02-03       Impact factor: 4.142

5.  Molecular characterization of flavonoid malonyltransferase from Oryza sativa.

Authors:  Dea Hwan Kim; Seong Kyong Kim; Jeong-Ho Kim; Bong-Gyu Kim; Joong-Hoon Ahn
Journal:  Plant Physiol Biochem       Date:  2009-08-27       Impact factor: 4.270

6.  Biochemical networks and epistasis shape the Arabidopsis thaliana metabolome.

Authors:  Heather C Rowe; Bjarne Gram Hansen; Barbara Ann Halkier; Daniel J Kliebenstein
Journal:  Plant Cell       Date:  2008-05-30       Impact factor: 11.277

7.  Four glucosyltransferases from rice: cDNA cloning, expression, and characterization.

Authors:  Jae Hyung Ko; Bong Gyu Kim; Jeong Ho Kim; Hojung Kim; Chae Eun Lim; Jun Lim; Chan Lee; Yoongho Lim; Joong-Hoon Ahn
Journal:  J Plant Physiol       Date:  2007-03-23       Impact factor: 3.549

8.  Starch as a major integrator in the regulation of plant growth.

Authors:  Ronan Sulpice; Eva-Theresa Pyl; Hirofumi Ishihara; Sandra Trenkamp; Matthias Steinfath; Hanna Witucka-Wall; Yves Gibon; Björn Usadel; Fabien Poree; Maria Conceição Piques; Maria Von Korff; Marie Caroline Steinhauser; Joost J B Keurentjes; Manuela Guenther; Melanie Hoehne; Joachim Selbig; Alisdair R Fernie; Thomas Altmann; Mark Stitt
Journal:  Proc Natl Acad Sci U S A       Date:  2009-06-08       Impact factor: 11.205

9.  Functional characterization of key structural genes in rice flavonoid biosynthesis.

Authors:  Chun Hat Shih; Hung Chu; Lee Kwan Tang; Wataru Sakamoto; Masahiko Maekawa; Ivan K Chu; Mingfu Wang; Clive Lo
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10.  The C-glycosylation of flavonoids in cereals.

Authors:  Melissa Brazier-Hicks; Kathryn M Evans; Markus C Gershater; Horst Puschmann; Patrick G Steel; Robert Edwards
Journal:  J Biol Chem       Date:  2009-05-01       Impact factor: 5.157

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  65 in total

1.  Integrative Approaches to Enhance Understanding of Plant Metabolic Pathway Structure and Regulation.

Authors:  Takayuki Tohge; Federico Scossa; Alisdair R Fernie
Journal:  Plant Physiol       Date:  2015-09-14       Impact factor: 8.340

2.  Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights.

Authors:  Nicole E Soltis; Daniel J Kliebenstein
Journal:  Plant Physiol       Date:  2015-08-13       Impact factor: 8.340

3.  Rethinking Mass Spectrometry-Based Small Molecule Identification Strategies in Metabolomics.

Authors:  Fumio Matsuda
Journal:  Mass Spectrom (Tokyo)       Date:  2014-08-16

4.  Evolutionary Metabolomics Identifies Substantial Metabolic Divergence between Maize and Its Wild Ancestor, Teosinte.

Authors:  Guanghui Xu; Jingjing Cao; Xufeng Wang; Qiuyue Chen; Weiwei Jin; Zhen Li; Feng Tian
Journal:  Plant Cell       Date:  2019-06-21       Impact factor: 11.277

5.  Evolutionarily Distinct BAHD N-Acyltransferases Are Responsible for Natural Variation of Aromatic Amine Conjugates in Rice.

Authors:  Meng Peng; Yanqiang Gao; Wei Chen; Wensheng Wang; Shuangqian Shen; Jian Shi; Cheng Wang; Yu Zhang; Li Zou; Shouchuang Wang; Jian Wan; Xianqing Liu; Liang Gong; Jie Luo
Journal:  Plant Cell       Date:  2016-06-27       Impact factor: 11.277

Review 6.  Prospects of breeding high-quality rice using post-genomic tools.

Authors:  Roslen Anacleto; Rosa Paula Cuevas; Rosario Jimenez; Cindy Llorente; Eero Nissila; Robert Henry; Nese Sreenivasulu
Journal:  Theor Appl Genet       Date:  2015-05-21       Impact factor: 5.699

7.  Identification of optimal prediction models using multi-omic data for selecting hybrid rice.

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Journal:  Heredity (Edinb)       Date:  2019-03-25       Impact factor: 3.821

Review 8.  Crop metabolomics: from diagnostics to assisted breeding.

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Journal:  Metabolomics       Date:  2018-11-03       Impact factor: 4.290

Review 9.  Augmentation of crop productivity through interventions of omics technologies in India: challenges and opportunities.

Authors:  Rajesh Kumar Pathak; Mamta Baunthiyal; Dinesh Pandey; Anil Kumar
Journal:  3 Biotech       Date:  2018-10-19       Impact factor: 2.406

10.  Incorporation of parental phenotypic data into multi-omic models improves prediction of yield-related traits in hybrid rice.

Authors:  Yang Xu; Yue Zhao; Xin Wang; Ying Ma; Pengcheng Li; Zefeng Yang; Xuecai Zhang; Chenwu Xu; Shizhong Xu
Journal:  Plant Biotechnol J       Date:  2020-09-02       Impact factor: 9.803

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