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Metabolomics

, Volume 11, Issue 2, pp 261–270 | Cite as

Assessing metabolomic and chemical diversity of a soybean lineage representing 35 years of breeding

  • Miyako Kusano
  • Ivan BaxterEmail author
  • Atsushi Fukushima
  • Akira Oikawa
  • Yozo Okazaki
  • Ryo Nakabayashi
  • Denise J. Bouvrette
  • Frederic Achard
  • Andrew R. Jakubowski
  • Joan M. Ballam
  • Jonathan R. Phillips
  • Angela H. Culler
  • Kazuki SaitoEmail author
  • George G. HarriganEmail author
Original Article

Abstract

Information on crop genotype- and phenotype-metabolite associations can be of value to trait development as well as to food security and safety. The unique study presented here assessed seed metabolomic and ionomic diversity in a soybean lineage representing ~35 years of breeding (launch years 1972–2008) and increasing yield potential. Selected varieties included six conventional and three genetically modified (GM) glyphosate-tolerant lines. A metabolomics approach utilizing capillary electrophoresis (CE)-time-of-flight-mass spectrometry (TOF-MS), gas chromatography (GC)-TOF-MS and liquid chromatography (LC)-quadrupole (q)-TOFMS resulted in measurement of a total of 732 annotated peaks. Ionomics through inductively-coupled plasma (ICP)-MS profiled twenty mineral elements. Orthogonal partial least squares-discriminant analysis (OPLS-DA) of the seed data successfully differentiated newer higher-yielding soybean from earlier lower-yielding accessions at both field sites. This result reflected genetic fingerprinting data that demonstrated a similar distinction between the newer and older soybean. Correlation analysis also revealed associations between yield data and specific metabolites. There were no clear metabolic differences between the conventional and GM lines. Overall, observations of metabolic and genetic differences between older and newer soybean varieties provided novel and significant information on the impact of varietal development on biochemical variability. Proposed applications of omics in food and feed safety assessments will need to consider that GM is not a major source of metabolite variability and that trait development in crops will, of necessity, be associated with biochemical variation.

Keywords

Soybean (Glycine max) breeding Food safety Metabolomics Ionomics 

Notes

Acknowledgements

We are very grateful for the agronomic support provided by Matt Culler of Monsanto. Genetic fingerprint analyses were conducted within the Molecular Breeding Technology group at Monsanto. The excellent logistical support provided by James McCarter and his sample management team was also critical to the success of this experiment. We are indebted to Nordine Cheikh for his support and encouragement and to Mark Leibman and John Vicini for helpful comments on the manuscript. We also thank Tomoko Nishizawa, Makoto Kobayashi, Ryosuke Sasaki, and Koji Takano (RIKEN) for their technical assistance in the study. This research was also supported by the Japan Advanced Plant Science Network.

Supplementary material

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Miyako Kusano
    • 1
  • Ivan Baxter
    • 2
    Email author
  • Atsushi Fukushima
    • 1
  • Akira Oikawa
    • 1
  • Yozo Okazaki
    • 1
  • Ryo Nakabayashi
    • 1
  • Denise J. Bouvrette
    • 3
  • Frederic Achard
    • 3
  • Andrew R. Jakubowski
    • 3
  • Joan M. Ballam
    • 3
  • Jonathan R. Phillips
    • 3
  • Angela H. Culler
    • 3
  • Kazuki Saito
    • 1
    • 4
    Email author
  • George G. Harrigan
    • 3
    Email author
  1. 1.RIKEN Center for Sustainable Resource ScienceYokohamaJapan
  2. 2.Agricultural Research Service Plant Genetics Research Unit, Donald Danforth Plant Science CenterUnited States Department of AgricultureSt. LouisUSA
  3. 3.Monsanto CompanySt. LouisUSA
  4. 4.Graduate School of Pharmaceutical ScienceChiba UniversityChibaJapan

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