Literature DB >> 24290761

Quantitative and qualitative proteome characteristics extracted from in-depth integrated genomics and proteomics analysis.

Teck Yew Low1, Sebastiaan van Heesch2, Henk van den Toorn1, Piero Giansanti1, Alba Cristobal1, Pim Toonen2, Sebastian Schafer3, Norbert Hübner4, Bas van Breukelen1, Shabaz Mohammed1, Edwin Cuppen5, Albert J R Heck6, Victor Guryev2.   

Abstract

Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and posttranscriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We obtained peptide evidence for 26,463 rat liver proteins. We validated 1,195 gene predictions, 83 splice events, 126 proteins with nonsynonymous variants, and 20 isoforms with nonsynonymous RNA editing. Quantitative RNA sequencing and proteomics data correlate highly between strains but poorly among each other, indicating extensive nongenetic regulation. Our multilevel analysis identified a genomic variant in the promoter of the most differentially expressed gene Cyp17a1, a previously reported top hit in genome-wide association studies for human hypertension, as a potential contributor to the hypertension phenotype in SHR rats. These results demonstrate the power of and need for integrative analysis for understanding genetic control of molecular dynamics and phenotypic diversity in a system-wide manner.
Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 24290761     DOI: 10.1016/j.celrep.2013.10.041

Source DB:  PubMed          Journal:  Cell Rep            Impact factor:   9.423


  55 in total

1.  A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites.

Authors:  Alexander Koch; Daria Gawron; Sandra Steyaert; Elvis Ndah; Jeroen Crappé; Sarah De Keulenaer; Ellen De Meester; Ming Ma; Ben Shen; Kris Gevaert; Wim Van Criekinge; Petra Van Damme; Gerben Menschaert
Journal:  Proteomics       Date:  2014-10-02       Impact factor: 3.984

2.  Multi-omics Comparative Analysis Reveals Multiple Layers of Host Signaling Pathway Regulation by the Gut Microbiota.

Authors:  Nathan P Manes; Natalia Shulzhenko; Arthur G Nuccio; Sara Azeem; Andrey Morgun; Aleksandra Nita-Lazar
Journal:  mSystems       Date:  2017-10-24       Impact factor: 6.496

3.  Deep proteomics of the Xenopus laevis egg using an mRNA-derived reference database.

Authors:  Martin Wühr; Robert M Freeman; Marc Presler; Marko E Horb; Leonid Peshkin; Steven Gygi; Marc W Kirschner
Journal:  Curr Biol       Date:  2014-06-19       Impact factor: 10.834

4.  Multi-omic data analysis using Galaxy.

Authors:  Jorrit Boekel; John M Chilton; Ira R Cooke; Peter L Horvatovich; Pratik D Jagtap; Lukas Käll; Janne Lehtiö; Pieter Lukasse; Perry D Moerland; Timothy J Griffin
Journal:  Nat Biotechnol       Date:  2015-02       Impact factor: 54.908

5.  PRIME-XS, a European infrastructure for proteomics.

Authors:  Reinout Raijmakers; Jesper V Olsen; Ruedi Aebersold; Albert J R Heck
Journal:  Mol Cell Proteomics       Date:  2014-06-23       Impact factor: 5.911

6.  Disclosure of selective advantages in the "modern" sublineage of the Mycobacterium tuberculosis Beijing genotype family by quantitative proteomics.

Authors:  Jeroen de Keijzer; Petra E de Haas; Arnoud H de Ru; Peter A van Veelen; Dick van Soolingen
Journal:  Mol Cell Proteomics       Date:  2014-07-14       Impact factor: 5.911

7.  Leveraging the complementary nature of RNA-Seq and shotgun proteomics data.

Authors:  Xiaojing Wang; Qi Liu; Bing Zhang
Journal:  Proteomics       Date:  2014-11-17       Impact factor: 3.984

Review 8.  The emergence of proteome-wide technologies: systematic analysis of proteins comes of age.

Authors:  Michal Breker; Maya Schuldiner
Journal:  Nat Rev Mol Cell Biol       Date:  2014-06-18       Impact factor: 94.444

9.  Mass-spectrometry-based draft of the human proteome.

Authors:  Mathias Wilhelm; Judith Schlegl; Hannes Hahne; Amin Moghaddas Gholami; Marcus Lieberenz; Mikhail M Savitski; Emanuel Ziegler; Lars Butzmann; Siegfried Gessulat; Harald Marx; Toby Mathieson; Simone Lemeer; Karsten Schnatbaum; Ulf Reimer; Holger Wenschuh; Martin Mollenhauer; Julia Slotta-Huspenina; Joos-Hendrik Boese; Marcus Bantscheff; Anja Gerstmair; Franz Faerber; Bernhard Kuster
Journal:  Nature       Date:  2014-05-29       Impact factor: 49.962

Review 10.  Rat models of human diseases and related phenotypes: a systematic inventory of the causative genes.

Authors:  Claude Szpirer
Journal:  J Biomed Sci       Date:  2020-08-02       Impact factor: 8.410

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