Literature DB >> 18924179

A rapid approach for phenotype-screening and database independent detection of cSNP/protein polymorphism using mass accuracy precursor alignment.

Wolfgang Hoehenwarter1, Joost T van Dongen, Stefanie Wienkoop, Matthias Steinfath, Jan Hummel, Alexander Erban, Ronan Sulpice, Babette Regierer, Joachim Kopka, Peter Geigenberger, Wolfram Weckwerth.   

Abstract

The dynamics of a proteome can only be addressed with large-scale, high-throughput methods. To cope with the inherent complexity, techniques based on targeted quantification using proteotypic peptides are arising. This is an essential systems biology approach; however, for the exploratory discovery of unexpected markers, nontargeted detection of proteins, and protein modifications is indispensable. We present a rapid label-free shotgun proteomics approach that extracts relevant phenotype-specific peptide product ion spectra in an automated workflow without prior identification. These product ion spectra are subsequently sequenced with database search and de novo prediction algorithms. We analyzed six potato tuber cultivars grown on three plots of two geographically separated fields in Germany. For data mining about 1.5 million spectra from 107 analyses were aligned and statistically examined in approximately 1 day. Several cultivar-specific protein markers were detected. Based on de novo-sequencing a dominant protein polymorphism not detectable in the available EST-databases was assigned exclusively to a specific potato cultivar. The approach is applicable to organisms with unsequenced or incomplete genomes and to the automated extraction of relevant mass spectra that potentially cannot be identified by genome/EST-based search algorithms.

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Year:  2008        PMID: 18924179     DOI: 10.1002/pmic.200701047

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  19 in total

1.  Identification of metabolites related to mechanisms of resistance in barley against Fusarium graminearum, based on mass spectrometry.

Authors:  Venkatesh Bollina; Ajjamada C Kushalappa; Thin M Choo; Yves Dion; Sylvie Rioux
Journal:  Plant Mol Biol       Date:  2011-08-10       Impact factor: 4.076

2.  Precision, proteome coverage, and dynamic range of Arabidopsis proteome profiling using (15)N metabolic labeling and label-free approaches.

Authors:  Borjana Arsova; Henrik Zauber; Waltraud X Schulze
Journal:  Mol Cell Proteomics       Date:  2012-05-05       Impact factor: 5.911

3.  Performance comparison of three trypsin columns used in liquid chromatography.

Authors:  Tereza Šlechtová; Martin Gilar; Květa Kalíková; Stephanie M Moore; James W Jorgenson; Eva Tesařová
Journal:  J Chromatogr A       Date:  2017-02-14       Impact factor: 4.759

4.  Using ProtMAX to create high-mass-accuracy precursor alignments from label-free quantitative mass spectrometry data generated in shotgun proteomics experiments.

Authors:  Volker Egelhofer; Wolfgang Hoehenwarter; David Lyon; Wolfram Weckwerth; Stefanie Wienkoop
Journal:  Nat Protoc       Date:  2013-02-28       Impact factor: 13.491

5.  The time required for dormancy release in Arabidopsis is determined by DELAY OF GERMINATION1 protein levels in freshly harvested seeds.

Authors:  Kazumi Nakabayashi; Melanie Bartsch; Yong Xiang; Emma Miatton; Silke Pellengahr; Ryoichi Yano; Mitsunori Seo; Wim J J Soppe
Journal:  Plant Cell       Date:  2012-07-24       Impact factor: 11.277

6.  Metabolomics unravel contrasting effects of biodiversity on the performance of individual plant species.

Authors:  Christian Scherling; Christiane Roscher; Patrick Giavalisco; Ernst-Detlef Schulze; Wolfram Weckwerth
Journal:  PLoS One       Date:  2010-09-07       Impact factor: 3.240

7.  Enolases: storage compounds in seeds? Evidence from a proteomic comparison of zygotic and somatic embryos of Cyclamen persicum Mill.

Authors:  Christina Rode; Sébastien Gallien; Dimitri Heintz; Alain Van Dorsselaer; Hans-Peter Braun; Traud Winkelmann
Journal:  Plant Mol Biol       Date:  2011-01-20       Impact factor: 4.076

8.  Granger causality in integrated GC-MS and LC-MS metabolomics data reveals the interface of primary and secondary metabolism.

Authors:  Hannes Doerfler; David Lyon; Thomas Nägele; Xiaoliang Sun; Lena Fragner; Franz Hadacek; Volker Egelhofer; Wolfram Weckwerth
Journal:  Metabolomics       Date:  2012-10-25       Impact factor: 4.290

9.  Phytochemical composition of Potentilla anserina L. analyzed by an integrative GC-MS and LC-MS metabolomics platform.

Authors:  Angela Mari; David Lyon; Lena Fragner; Paola Montoro; Sonia Piacente; Stefanie Wienkoop; Volker Egelhofer; Wolfram Weckwerth
Journal:  Metabolomics       Date:  2012-11-17       Impact factor: 4.290

10.  Integration of metabolomic and proteomic phenotypes: analysis of data covariance dissects starch and RFO metabolism from low and high temperature compensation response in Arabidopsis thaliana.

Authors:  Stefanie Wienkoop; Katja Morgenthal; Florian Wolschin; Matthias Scholz; Joachim Selbig; Wolfram Weckwerth
Journal:  Mol Cell Proteomics       Date:  2008-04-28       Impact factor: 5.911

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