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      The quest for tolerant varieties: the importance of integrating “omics” techniques to phenotyping

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          Abstract

          The primary objective of crop breeding is to improve yield and/or harvest quality while minimizing inputs. Global climate change and the increase in world population are significant challenges for agriculture and call for further improvements to crops and the development of new tools for research. Significant progress has been made in the molecular and genetic analysis of model plants. However, is science generating false expectations? Are ‘omic techniques generating valuable information that can be translated into the field? The exploration of crop biodiversity and the correlation of cellular responses to stress tolerance at the plant level is currently a challenge. This viewpoint reviews concisely the problems one encounters when working on a crop and provides an outline of possible workflows when initiating cellular phenotyping via “-omic” techniques (transcriptomics, proteomics, metabolomics).

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          Most cited references94

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          Correlation between protein and mRNA abundance in yeast.

          We have determined the relationship between mRNA and protein expression levels for selected genes expressed in the yeast Saccharomyces cerevisiae growing at mid-log phase. The proteins contained in total yeast cell lysate were separated by high-resolution two-dimensional (2D) gel electrophoresis. Over 150 protein spots were excised and identified by capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein spots were quantified by metabolic labeling and scintillation counting. Corresponding mRNA levels were calculated from serial analysis of gene expression (SAGE) frequency tables (V. E. Velculescu, L. Zhang, W. Zhou, J. Vogelstein, M. A. Basrai, D. E. Bassett, Jr., P. Hieter, B. Vogelstein, and K. W. Kinzler, Cell 88:243-251, 1997). We found that the correlation between mRNA and protein levels was insufficient to predict protein expression levels from quantitative mRNA data. Indeed, for some genes, while the mRNA levels were of the same value the protein levels varied by more than 20-fold. Conversely, invariant steady-state levels of certain proteins were observed with respective mRNA transcript levels that varied by as much as 30-fold. Another interesting observation is that codon bias is not a predictor of either protein or mRNA levels. Our results clearly delineate the technical boundaries of current approaches for quantitative analysis of protein expression and reveal that simple deduction from mRNA transcript analysis is insufficient.
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            Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics.

            Selected reaction monitoring on a triple quadrupole mass spectrometer is currently experiencing a renaissance within the proteomics community for its, as yet, unparalleled ability to characterize and quantify a set of proteins reproducibly, completely, and with high sensitivity. Given the immense benefit that high resolution and accurate mass instruments have brought to the discovery proteomics field, we wondered if highly accurate mass measurement capabilities could be leveraged to provide benefits in the targeted proteomics domain as well. Here, we propose a new targeted proteomics paradigm centered on the use of next generation, quadrupole-equipped high resolution and accurate mass instruments: parallel reaction monitoring (PRM). In PRM, the third quadrupole of a triple quadrupole is substituted with a high resolution and accurate mass mass analyzer to permit the parallel detection of all target product ions in one, concerted high resolution mass analysis. We detail the analytical performance of the PRM method, using a quadrupole-equipped bench-top Orbitrap MS, and draw a performance comparison to selected reaction monitoring in terms of run-to-run reproducibility, dynamic range, and measurement accuracy. In addition to requiring minimal upfront method development and facilitating automated data analysis, PRM yielded quantitative data over a wider dynamic range than selected reaction monitoring in the presence of a yeast background matrix because of PRM's high selectivity in the mass-to-charge domain. With achievable linearity over the quantifiable dynamic range found to be statistically equal between the two methods, our investigation suggests that PRM will be a promising new addition to the quantitative proteomics toolbox.
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              Research on plant abiotic stress responses in the post-genome era: past, present and future.

              Understanding abiotic stress responses in plants is an important and challenging topic in plant research. Physiological and molecular biological analyses have allowed us to draw a picture of abiotic stress responses in various plants, and determination of the Arabidopsis genome sequence has had a great impact on this research field. The availability of the complete genome sequence has facilitated access to essential information for all genes, e.g. gene products and their function, transcript levels, putative cis-regulatory elements, and alternative splicing patterns. These data have been obtained from comprehensive transcriptome analyses and studies using full-length cDNA collections and T-DNA- or transposon-tagged mutant lines, which were also enhanced by genome sequence information. Moreover, studies on novel regulatory mechanisms involving use of small RNA molecules, chromatin modulation and genomic DNA modification have enabled us to recognize that plants have evolved complicated and sophisticated systems in response to complex abiotic stresses. Integrated data obtained with various 'omics' approaches have provided a more comprehensive picture of abiotic stress responses. In addition, research on stress responses in various plant species other than Arabidopsis has increased our knowledge regarding the mechanisms of plant stress tolerance in nature. Based on this progress, improvements in crop stress tolerance have been attempted by means of gene transfer and marker-assisted breeding. In this review, we summarize recent progress in abiotic stress studies, especially in the post-genomic era, and offer new perspectives on research directions for the next decade.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                09 July 2015
                2015
                : 6
                : 448
                Affiliations
                [1] 1Department Génétique Quantitative et Évolution, Le Moulon INRA, CNRS, AgroParisTech, Plateforme PAPPSO, Université Paris-Sud , Gif-sur-Yvette, France
                [2] 2Department of Ecogenomics and Systems Biology, University of Vienna , Vienna, Austria
                [3] 3Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology , Belvaux, Luxembourg
                [4] 4Instituto de Tecnologia Química e Biológica, New University of Lisbon , Oeiras, Portugal
                [5] 5Faculdade de Ciências e Tecnologia, New University of Lisbon , Caparica, Portugal
                [6] 6Department of Sciences et Technologies, CNRS/Université Lille , Villeneuve d’Ascq, France
                [7] 7Department of Biosystems, University of Leuven , Leuven, Belgium
                [8] 8SYBIOMA, University of Leuven , Leuven, Belgium
                Author notes

                Edited by: Jesus V. J. Novo, University of Cordoba, Spain

                Reviewed by: Ján A. Miernyk, University of Missouri, USA; Borjana Arsova, Université de Liège, Belgium

                *Correspondence: Sebastien Carpentier, SYBIOMA, University of Leuven, Willem de Croylaan 42, Box 2455, 3001 Leuven, Belgium, sebastien.carpentier@ 123456biw.kuleuven.be

                This article was submitted to Plant Proteomics, a section of the journal Frontiers in Plant Science.

                Article
                10.3389/fpls.2015.00448
                4496562
                58fc863a-6013-4254-a395-0c5c2a719f15
                Copyright © 2015 Zivy, Wienkoop, Renaut, Pinheiro, Goulas and Carpentier.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 13 March 2015
                : 31 May 2015
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 110, Pages: 11, Words: 10315
                Funding
                Funded by: Action to organize meetings and disseminate
                Categories
                Plant Science
                Review

                Plant science & Botany
                proteomics,data integration and computational methods,phenotype,omics-technologies,crop improvement

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