Literature DB >> 22593724

Pair-wise multicomparison and OPLS analyses of cold-acclimation phases in Siberian spruce.

Liudmila Shiryaeva, Henrik Antti, Wolfgang P Schröder, Richard Strimbeck, Anton S Shiriaev.   

Abstract

Analysis of metabolomics data often goes beyond the task of discovering biomarkers and can be aimed at recovering other important characteristics of observed metabolomic changes. In this paper we explore different methods to detect the presence of distinctive phases in seasonal-responsive changes of metabolomic patterns of Siberian spruce (Picea obovata) during cold acclimation occurred in the period from mid-August to January. Multivariate analysis, specifically orthogonal projection to latent structures discriminant analysis (OPLS-DA), identified time points where the metabolomic patterns underwent substantial modifications as a whole, revealing four distinctive phases during acclimation. This conclusion was re-examined by a univariate analysis consisting of multiple pair-wise comparisons to identify homogeneity intervals for each metabolite. These tests complemented OPLS-DA, clarifying biological interpretation of the classification: about 60% of metabolites found responsive to the cold stress indeed changed at one or more of the time points predicted by OPLS-DA. However, the univariate approach did not support the proposed division of the acclimation period into four phases: less than 10% of metabolites altered during the acclimation had homogeneous levels predicted by OPLS-DA. This demonstrates that coupling the classification found by OPLS-DA and the analysis of dynamics of individual metabolites obtained by pair-wise multicomparisons reveals a more correct characterization of biochemical processes in freezing tolerant trees and leads to interpretations that cannot be deduced by either method alone. The combined analysis can be used in other 'omics'-studies, where response factors have a causal dependence (like the time in the present work) and pair-wise multicomparisons are not conservative. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0304-5) contains supplementary material, which is available to authorized users.

Entities:  

Year:  2011        PMID: 22593724      PMCID: PMC3337411          DOI: 10.1007/s11306-011-0304-5

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


  15 in total

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3.  High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses.

Authors:  Pär Jonsson; Annika I Johansson; Jonas Gullberg; Johan Trygg; Jiye A; Bjørn Grung; Stefan Marklund; Michael Sjöström; Henrik Antti; Thomas Moritz
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Review 4.  Plant metabolomics: towards biological function and mechanism.

Authors:  Nicolas Schauer; Alisdair R Fernie
Journal:  Trends Plant Sci       Date:  2006-09-01       Impact factor: 18.313

5.  Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models.

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Journal:  Anal Chem       Date:  2007-11-21       Impact factor: 6.986

6.  Metabolic phenotyping in health and disease.

Authors:  Elaine Holmes; Ian D Wilson; Jeremy K Nicholson
Journal:  Cell       Date:  2008-09-05       Impact factor: 41.582

Review 7.  Visualization of omics data for systems biology.

Authors:  Nils Gehlenborg; Seán I O'Donoghue; Nitin S Baliga; Alexander Goesmann; Matthew A Hibbs; Hiroaki Kitano; Oliver Kohlbacher; Heiko Neuweger; Reinhard Schneider; Dan Tenenbaum; Anne-Claude Gavin
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Review 8.  Exploring disease through metabolomics.

Authors:  Nawaporn Vinayavekhin; Edwin A Homan; Alan Saghatelian
Journal:  ACS Chem Biol       Date:  2010-01-15       Impact factor: 5.100

9.  Design of experiments: an efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry.

Authors:  Jonas Gullberg; Pär Jonsson; Anders Nordström; Michael Sjöström; Thomas Moritz
Journal:  Anal Biochem       Date:  2004-08-15       Impact factor: 3.365

10.  Dynamics of low-temperature acclimation in temperate and boreal conifer foliage in a mild winter climate.

Authors:  G Richard Strimbeck; Trygve D Kjellsen; Paul G Schaberg; Paula F Murakami
Journal:  Tree Physiol       Date:  2008-09       Impact factor: 4.196

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  4 in total

1.  Metabolite changes in conifer buds and needles during forced bud break in Norway spruce (Picea abies) and European silver fir (Abies alba).

Authors:  Priyanka Dhuli; Jens Rohloff; G Richard Strimbeck
Journal:  Front Plant Sci       Date:  2014-12-11       Impact factor: 5.753

2.  Protein expression in tension wood formation monitored at high tissue resolution in Populus.

Authors:  Joakim Bygdell; Vaibhav Srivastava; Ogonna Obudulu; Manoj K Srivastava; Robert Nilsson; Björn Sundberg; Johan Trygg; Ewa J Mellerowicz; Gunnar Wingsle
Journal:  J Exp Bot       Date:  2017-06-15       Impact factor: 6.992

3.  Multivariate statistical models of metabolomic data reveals different metabolite distribution patterns in isonitrosoacetophenone-elicited Nicotiana tabacum and Sorghum bicolor cells.

Authors:  Ntakadzeni E Madala; Lizelle A Piater; Paul A Steenkamp; Ian A Dubery
Journal:  Springerplus       Date:  2014-05-20

4.  Selected Plant Metabolites Involved in Oxidation-Reduction Processes during Bud Dormancy and Ontogenetic Development in Sweet Cherry Buds (Prunus avium L.).

Authors:  Susanne Baldermann; Thomas Homann; Susanne Neugart; Frank-M Chmielewski; Klaus-Peter Götz; Kristin Gödeke; Gerd Huschek; Getrud E Morlock; Harshadrai M Rawel
Journal:  Molecules       Date:  2018-05-17       Impact factor: 4.411

  4 in total

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