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PMID: 24861081 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

Metabolic variation between japonica and indica rice cultivars as revealed by non-targeted metabolomics.

Scientific reports ·Vol. 4 ·2014-05-27 ·Pages 5067

Hu C, Shi J, Quan S, Cui B, Kleessen S, Nikoloski Z, Tohge T, Alexander D, Guo L, Lin H, Wang J, Cui X, Rao J, Luo Q, Zhao X, Fernie AR, Zhang D

Abstract

Seed metabolites are critically important both for plant development and human nutrition; however, the natural variation in their levels remains poorly characterized. Here we profiled 121 metabolites in mature seeds of a wide panel Oryza sativa japonica and indica cultivars, revealing correlations between the metabolic phenotype and geographic origin of the rice seeds. Moreover, japonica and indica subspecies differed significantly not only in the relative abundances of metabolites but also in their corresponding metabolic association networks. These findings provide important insights into metabolic adaptation in rice subgroups, bridging the gap between genome and phenome, and facilitating the identification of genetic control of metabolic properties that can serve as a basis for the future improvement of rice quality via metabolic engineering.

MeSH Terms
Crops, Agricultural Genetic Variation Humans Metabolic Engineering Metabolomics Oryza/genetics,metabolism Seeds/genetics,metabolism
Authors & Affiliations
17 authors, click to expand affiliations / ORCID
Hu Chaoyang
1] National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China [2].
Shi Jianxin
1] National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China [2].
Quan Sheng
1] National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China [2].
Cui Bo
National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
Kleessen Sabrina
Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany.
Nikoloski Zoran
Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany.
Tohge Takayuki
Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany.
Alexander Danny
Metabolon Inc., Durham, North Carolina 27713, USA.
Guo Lining
Metabolon Inc., Durham, North Carolina 27713, USA.
Lin Hong
National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
Wang Jing
National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
Cui Xiao
National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
Rao Jun
National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
Luo Qian
National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
Zhao Xiangxiang
Jiangsu Key Laboratory for Eco-Agricultural Biotechnology around Hongze Lake, Huaiyin Normal University, Huaian, Jiangsu, 223300, China.
Fernie Alisdair R
Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany.
Zhang Dabing
National Center for Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
References (50)
50 references, click to expand
  1. Network analysis: tackling complex data to study plant metabolism.
    Trends Biotechnol. 2013 Jan;31(1):29-36 PMID: 23245943
  2. Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems.
    Anal Chem. 2009 Aug 15;81(16):6656-67 PMID: 19624122
  3. Not just a grain of rice: the quest for quality.
    Trends Plant Sci. 2009 Mar;14(3):133-9 PMID: 19230745
  4. Origin, dispersal, cultivation and variation of rice.
    Plant Mol Biol. 1997 Sep;35(1-2):25-34 PMID: 9291957
  5. Assessment of genetically modified soybean in relation to natural variation in the soybean seed metabolome.
    Sci Rep. 2013 Oct 30;3:3082 PMID: 24170158
  6. Untargeted metabolomic profiling as an evaluative tool of fenofibrate-induced toxicology in Fischer 344 male rats.
    Toxicol Pathol. 2009 Jun;37(4):521-35 PMID: 19458390
  7. The SMALL AND ROUND SEED1 (SRS1/DEP2) gene is involved in the regulation of seed size in rice.
    Genes Genet Syst. 2010;85(5):327-39 PMID: 21317545
  8. Metabolomic and functional genomic analyses reveal varietal differences in bioactive compounds of cooked rice.
    PLoS One. 2010 Sep 23;5(9):e12915 PMID: 20886119
  9. Vitamin B6: a long known compound of surprising complexity.
    Molecules. 2009 Jan 12;14(1):329-51 PMID: 19145213
  10. Combining genome-wide association mapping and transcriptional networks to identify novel genes controlling glucosinolates in Arabidopsis thaliana.
    PLoS Biol. 2011 Aug;9(8):e1001125 PMID: 21857804
  11. Gene expression profiles deciphering rice phenotypic variation between Nipponbare (Japonica) and 93-11 (Indica) during oxidative stress.
    PLoS One. 2010 Jan 08;5(1):e8632 PMID: 20072620
  12. Carbohydrate availability affects growth and metabolism in peach fruit.
    Physiol Plant. 2008 Jun;133(2):229-41 PMID: 18298408
  13. A genome-wide association study of seed protein and oil content in soybean.
    BMC Genomics. 2014 Jan 02;15:1 PMID: 24382143
  14. Reconfiguration of the achene and receptacle metabolic networks during strawberry fruit development.
    Plant Physiol. 2008 Oct;148(2):730-50 PMID: 18715960
  15. Contribution of the GABA shunt to hypoxia-induced alanine accumulation in roots of Arabidopsis thaliana.
    Plant Cell Physiol. 2008 Jan;49(1):92-102 PMID: 18077464
  16. Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels.
    Nat Genet. 2013 Jan;45(1):43-50 PMID: 23242369
  17. A review of phytate, iron, zinc, and calcium concentrations in plant-based complementary foods used in low-income countries and implications for bioavailability.
    Food Nutr Bull. 2010 Jun;31(2 Suppl):S134-46 PMID: 20715598
  18. What does Arabidopsis natural variation teach us (and does not teach us) about adaptation in plants?
    Curr Opin Plant Biol. 2011 Jun;14(3):225-31 PMID: 21536479
  19. Natural variation in maize aphid resistance is associated with 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one glucoside methyltransferase activity.
    Plant Cell. 2013 Jun;25(6):2341-55 PMID: 23898034
  20. Application of a metabolomic method combining one-dimensional and two-dimensional gas chromatography-time-of-flight/mass spectrometry to metabolic phenotyping of natural variants in rice.
    J Chromatogr B Analyt Technol Biomed Life Sci. 2007 Aug;855(1):71-9 PMID: 17556050
  21. Comparing nitrate storage and remobilization in two rice cultivars that differ in their nitrogen use efficiency.
    J Exp Bot. 2007;58(7):1729-40 PMID: 17351248
  22. Genome-wide association study and pathway-level analysis of tocochromanol levels in maize grain.
    G3 (Bethesda). 2013 Aug 07;3(8):1287-99 PMID: 23733887
  23. Genome-wide association studies of 14 agronomic traits in rice landraces.
    Nat Genet. 2010 Nov;42(11):961-7 PMID: 20972439
  24. Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement.
    Nat Biotechnol. 2006 Apr;24(4):447-54 PMID: 16531992
  25. Genome-wide analysis of branched-chain amino acid levels in Arabidopsis seeds.
    Plant Cell. 2013 Dec;25(12):4827-43 PMID: 24368787
  26. Ascorbate and glutathione: the heart of the redox hub.
    Plant Physiol. 2011 Jan;155(1):2-18 PMID: 21205630
  27. Specific roles of alpha- and gamma-tocopherol in abiotic stress responses of transgenic tobacco.
    Plant Physiol. 2007 Apr;143(4):1720-38 PMID: 17293434
  28. Improving the content of essential amino acids in crop plants: goals and opportunities.
    Plant Physiol. 2008 Jul;147(3):954-61 PMID: 18612072
  29. Dissection of genotype-phenotype associations in rice grains using metabolome quantitative trait loci analysis.
    Plant J. 2012 May;70(4):624-36 PMID: 22229385
  30. The origin and evolution of fragrance in rice (Oryza sativa L.).
    Proc Natl Acad Sci U S A. 2009 Aug 25;106(34):14444-9 PMID: 19706531
  31. Iron fortification of rice seeds through activation of the nicotianamine synthase gene.
    Proc Natl Acad Sci U S A. 2009 Dec 22;106(51):22014-9 PMID: 20080803
  32. Metabolite profiling and quantitative genetics of natural variation for flavonoids in Arabidopsis.
    J Exp Bot. 2012 Jun;63(10):3749-64 PMID: 22442426
  33. Data integration through proximity-based networks provides biological principles of organization across scales.
    Plant Cell. 2013 Jun;25(6):1917-27 PMID: 23749845
  34. Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize.
    Proc Natl Acad Sci U S A. 2012 Jun 5;109(23):8872-7 PMID: 22615396
  35. Reactive electrophilic oxylipins: pattern recognition and signalling.
    Phytochemistry. 2009 Sep;70(13-14):1511-21 PMID: 19555983
  36. Free amino acid profiles suggest a possible role for asparagine in the control of storage-product accumulation in developing seeds of low- and high-protein soybean lines.
    J Exp Bot. 2005 Jul;56(417):1951-63 PMID: 15911557
  37. Oxylipins produced by the 9-lipoxygenase pathway in Arabidopsis regulate lateral root development and defense responses through a specific signaling cascade.
    Plant Cell. 2007 Mar;19(3):831-46 PMID: 17369372
  38. Detection and localization of markers of oxidative stress by in situ methods: application in the study of Alzheimer disease.
    Methods Mol Biol. 2010;610:419-34 PMID: 20013193
  39. Molecular evidence for a single evolutionary origin of domesticated rice.
    Proc Natl Acad Sci U S A. 2011 May 17;108(20):8351-6 PMID: 21536870
  40. A map of rice genome variation reveals the origin of cultivated rice.
    Nature. 2012 Oct 25;490(7421):497-501 PMID: 23034647
  41. Bioengineering nitrogen acquisition in rice: can novel initiatives in rice genomics and physiology contribute to global food security?
    Bioessays. 2004 Jun;26(6):683-92 PMID: 15170866
  42. Mode of inheritance of primary metabolic traits in tomato.
    Plant Cell. 2008 Mar;20(3):509-23 PMID: 18364465
  43. Oxylipin profile and antioxidant status of potato tubers during extended storage at room temperature.
    Plant Physiol Biochem. 2008 Dec;46(12):1077-84 PMID: 18930658
  44. Use of proteomics to understand seed development in rice.
    Proteomics. 2013 Jun;13(12-13):1784-800 PMID: 23483697
  45. Deciphering transcriptional and metabolic networks associated with lysine metabolism during Arabidopsis seed development.
    Plant Physiol. 2009 Dec;151(4):2058-72 PMID: 19783646
  46. Genetic architecture of maize kernel composition in the nested association mapping and inbred association panels.
    Plant Physiol. 2012 Feb;158(2):824-34 PMID: 22135431
  47. The lasso method for variable selection in the Cox model.
    Stat Med. 1997 Feb 28;16(4):385-95 PMID: 9044528
  48. Metabolic profiling of a mapping population exposes new insights in the regulation of seed metabolism and seed, fruit, and plant relations.
    PLoS Genet. 2012;8(3):e1002612 PMID: 22479206
  49. Structured patterns in geographic variability of metabolic phenotypes in Arabidopsis thaliana.
    Nat Commun. 2012;3:1319 PMID: 23271653
  50. Understanding the evolution of defense metabolites in Arabidopsis thaliana using genome-wide association mapping.
    Genetics. 2010 Jul;185(3):991-1007 PMID: 19737743
Article Info
Journal
Scientific reports
Abbr.
Sci Rep
ISSN
2045-2322
DOI
10.1038/srep05067
Published
2014-05-27
Epub
2014-00-27
Pages
5067
Language
English
Region
England
NLM ID
101563288
PMCID
PMC5381408
Subset
IM
External Links
PubMed source DOI: 10.1038/srep05067 PMC Full Text View journal details
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