title: A rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by direct analysis in real-time mass spectrometry.
abstract: BACKGROUND
  Efficient high throughput screening systems of useful mutants are prerequisite for study of plant functional genomics and lots of application fields. Advance in such screening tools, thanks to the development of analytic instruments. Direct analysis in real-time (DART)-mass spectrometry (MS) by ionization of complex materials at atmospheric pressure is a rapid, simple, high-resolution analytical technique. Here we describe a rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by DART-MS.
  
  
  RESULTS
  To determine whether this DART-MS combined by multivariate analysis can perform genetic discrimination based on global metabolic profiling, intact Arabidopsis thaliana mutant seeds were subjected to DART-MS without any sample preparation. Partial least squares-discriminant analysis (PLS-DA) of DART-MS spectral data from intact seeds classified 14 different lines of seeds into two distinct groups: Columbia (Col-0) and Landsberg erecta (Ler) ecotype backgrounds. A hierarchical dendrogram based on partial least squares-discriminant analysis (PLS-DA) subdivided the Col-0 ecotype into two groups: mutant lines harboring defects in the phenylpropanoid biosynthetic pathway and mutants without these defects. These results indicated that metabolic profiling with DART-MS could discriminate intact Arabidopsis seeds at least ecotype level and metabolic pathway level within same ecotype.
  
  
  CONCLUSIONS
  The described DART-MS combined by multivariate analysis allows for rapid screening and metabolic characterization of lots of Arabidopsis mutant seeds without complex metabolic preparation steps. Moreover, potential novel metabolic markers can be detected and used to clarify the genetic relationship between Arabidopsis cultivars. Furthermore this technique can be applied to predict the novel gene function of metabolic mutants regardless of morphological phenotypes.
authors.affiliation: Biological Resource Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-gu, Daejeon, 305-806, Korea.
authors.forename: Suk Weon
authors.initials: SW
authors.lastname: Kim
authors.affiliation: Division of Pharmacognosy, Kyung Hee University, 1 Hoegi dong Dongdaemun-Gu, Seoul, 130-701, Korea.
authors.forename: Hye Jin
authors.initials: HJ
authors.lastname: Kim
authors.affiliation: Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-gu, Daejeon, 305-806, Korea.
authors.forename: Jong Hyun
authors.initials: JH
authors.lastname: Kim
authors.affiliation: Biological Resource Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-gu, Daejeon, 305-806, Korea.
authors.forename: Yong Kook
authors.initials: YK
authors.lastname: Kwon
authors.affiliation: Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-gu, Daejeon, 305-806, Korea.
authors.forename: Myung Suk
authors.initials: MS
authors.lastname: Ahn
authors.affiliation: Division of Pharmacognosy, Kyung Hee University, 1 Hoegi dong Dongdaemun-Gu, Seoul, 130-701, Korea.
authors.forename: Young Pyo
authors.initials: YP
authors.lastname: Jang
authors.affiliation: Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahak-ro, Yuseong-gu, Daejeon, 305-806, Korea.
authors.forename: Jang R
authors.initials: JR
authors.lastname: Liu