Literature DB >> 25266668

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

Xiaojing Wang1, Qi Liu, Bing Zhang.   

Abstract

RNA sequencing (RNA-Seq) and MS-based shotgun proteomics are powerful high-throughput technologies for identifying and quantifying RNA transcripts and proteins, respectively. With the increasing affordability of these technologies, many projects have started to apply both to the same samples to achieve a more comprehensive understanding of biological systems. A major analytical challenge for such integrative projects is how to effectively leverage the complementary nature of RNA-Seq and shotgun proteomics data. RNA-Seq provides comprehensive information on mRNA abundance, alternative splicing, nucleotide variation, and structure alteration. Sample-specific protein databases derived from RNA-Seq data can better approximate the real protein pools in cell and tissue samples and thus improve protein identification. Meanwhile, proteomics data provide essential confirmation of the validity and functional relevance of novel findings from RNA-Seq data. At the quantitative level, mRNA and protein levels are only modestly correlated, suggesting strong involvement of posttranscriptional regulation in controlling gene expression. Here, we review recent studies at the interface of RNA-Seq and proteomics data. We discuss goals, accomplishments, and challenges in RNA-Seq-based proteogenomics. We also examine the current status and future potential of parallel transcriptome and proteome quantification in revealing posttranscriptional regulatory mechanisms.
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Data integration; Posttranscriptional regulation; Proteogenomics; Proteomics; RNA-Seq

Mesh:

Substances:

Year:  2014        PMID: 25266668      PMCID: PMC4270470          DOI: 10.1002/pmic.201400184

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


  86 in total

1.  Protein expression regulation under oxidative stress.

Authors:  Christine Vogel; Gustavo Monteiro Silva; Edward M Marcotte
Journal:  Mol Cell Proteomics       Date:  2011-09-20       Impact factor: 5.911

Review 2.  Global signatures of protein and mRNA expression levels.

Authors:  Raquel de Sousa Abreu; Luiz O Penalva; Edward M Marcotte; Christine Vogel
Journal:  Mol Biosyst       Date:  2009-10-01

3.  Proteogenomic database construction driven from large scale RNA-seq data.

Authors:  Sunghee Woo; Seong Won Cha; Gennifer Merrihew; Yupeng He; Natalie Castellana; Clark Guest; Michael MacCoss; Vineet Bafna
Journal:  J Proteome Res       Date:  2013-07-17       Impact factor: 4.466

4.  Omics evidence: single nucleotide variants transmissions on chromosome 20 in liver cancer cell lines.

Authors:  Quanhui Wang; Bo Wen; Tong Wang; Zhongwei Xu; Xuefei Yin; Shaohang Xu; Zhe Ren; Guixue Hou; Ruo Zhou; Haiyi Zhao; Jin Zi; Shenyan Zhang; Huan Gao; Xiaomin Lou; Haidan Sun; Qiang Feng; Cheng Chang; Peibin Qin; Chengpu Zhang; Ning Li; Yunping Zhu; Wei Gu; Jiayong Zhong; Gong Zhang; Pengyuan Yang; Guoquan Yan; Huali Shen; Xiaohui Liu; Haojie Lu; Fan Zhong; Qing-Yu He; Ping Xu; Liang Lin; Siqi Liu
Journal:  J Proteome Res       Date:  2013-12-05       Impact factor: 4.466

5.  De novo derivation of proteomes from transcriptomes for transcript and protein identification.

Authors:  Vanessa C Evans; Gary Barker; Kate J Heesom; Jun Fan; Conrad Bessant; David A Matthews
Journal:  Nat Methods       Date:  2012-11-11       Impact factor: 28.547

6.  The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq data: a preliminary assessment.

Authors:  Kang Ning; Alexey I Nesvizhskii
Journal:  BMC Bioinformatics       Date:  2010-12-14       Impact factor: 3.169

7.  Proteogenomic analysis of pathogenic yeast Cryptococcus neoformans using high resolution mass spectrometry.

Authors:  Lakshmi Dhevi Nagarajha Selvan; Jyothi Embekkat Kaviyil; Raja Sekhar Nirujogi; Babylakshmi Muthusamy; Vinuth N Puttamallesh; Tejaswini Subbannayya; Nazia Syed; Aneesha Radhakrishnan; Dhanashree S Kelkar; Sartaj Ahmad; Sneha M Pinto; Praveen Kumar; Anil K Madugundu; Bipin Nair; Aditi Chatterjee; Akhilesh Pandey; Raju Ravikumar; Harsha Gowda; Thottethodi Subrahmanya Keshava Prasad
Journal:  Clin Proteomics       Date:  2014-02-03       Impact factor: 3.988

8.  Enhanced whole genome sequence and annotation of Clostridium stercorarium DSM8532T using RNA-seq transcriptomics and high-throughput proteomics.

Authors:  John J Schellenberg; Tobin J Verbeke; Peter McQueen; Oleg V Krokhin; Xiangli Zhang; Graham Alvare; Brian Fristensky; Gerhard G Thallinger; Bernard Henrissat; John A Wilkins; David B Levin; Richard Sparling
Journal:  BMC Genomics       Date:  2014-07-07       Impact factor: 3.969

9.  Determinants of protein abundance and translation efficiency in S. cerevisiae.

Authors:  Tamir Tuller; Martin Kupiec; Eytan Ruppin
Journal:  PLoS Comput Biol       Date:  2007-12       Impact factor: 4.475

10.  Transcript level and sequence determinants of protein abundance and noise in Escherichia coli.

Authors:  Joao C Guimaraes; Miguel Rocha; Adam P Arkin
Journal:  Nucleic Acids Res       Date:  2014-02-07       Impact factor: 16.971

View more
  32 in total

1.  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

Review 2.  Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases.

Authors:  Yan V Sun; Yi-Juan Hu
Journal:  Adv Genet       Date:  2016-01-25       Impact factor: 1.944

3.  Slowed decay of mRNAs enhances platelet specific translation.

Authors:  Eric W Mills; Rachel Green; Nicholas T Ingolia
Journal:  Blood       Date:  2017-02-17       Impact factor: 22.113

Review 4.  Methods, Tools and Current Perspectives in Proteogenomics.

Authors:  Kelly V Ruggles; Karsten Krug; Xiaojing Wang; Karl R Clauser; Jing Wang; Samuel H Payne; David Fenyö; Bing Zhang; D R Mani
Journal:  Mol Cell Proteomics       Date:  2017-04-29       Impact factor: 5.911

5.  Human Leukocyte Antigen (HLA) Peptides Derived from Tumor Antigens Induced by Inhibition of DNA Methylation for Development of Drug-facilitated Immunotherapy.

Authors:  Bracha Shraibman; Dganit Melamed Kadosh; Eilon Barnea; Arie Admon
Journal:  Mol Cell Proteomics       Date:  2016-07-13       Impact factor: 5.911

Review 6.  Algorithms and design strategies towards automated glycoproteomics analysis.

Authors:  Han Hu; Kshitij Khatri; Joseph Zaia
Journal:  Mass Spectrom Rev       Date:  2016-01-04       Impact factor: 10.946

7.  Membrane Proteomic Insights into the Physiology and Taxonomy of an Oleaginous Green Microalga.

Authors:  Adriana Garibay-Hernández; Bronwyn J Barkla; Rosario Vera-Estrella; Alfredo Martinez; Omar Pantoja
Journal:  Plant Physiol       Date:  2016-11-08       Impact factor: 8.340

Review 8.  Application of targeted mass spectrometry in bottom-up proteomics for systems biology research.

Authors:  Nathan P Manes; Aleksandra Nita-Lazar
Journal:  J Proteomics       Date:  2018-02-13       Impact factor: 4.044

Review 9.  Proteogenomics from a bioinformatics angle: A growing field.

Authors:  Gerben Menschaert; David Fenyö
Journal:  Mass Spectrom Rev       Date:  2015-12-15       Impact factor: 10.946

10.  Multi-omics integration reveals the hepatoprotective mechanisms of ursolic acid intake against chronic alcohol consumption.

Authors:  Xin Yan; Xiaoyun Liu; Yu Wang; Xueyang Ren; Jiamu Ma; Ruolan Song; Xiuhuan Wang; Ying Dong; Qiqi Fan; Jing Wei; Axiang Yu; Hong Sui; Gaimei She
Journal:  Eur J Nutr       Date:  2021-07-02       Impact factor: 5.614

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.