Literature DB >> 26560066

Integrated Transcriptomic-Proteomic Analysis Using a Proteogenomic Workflow Refines Rat Genome Annotation.

Dhirendra Kumar1, Amit Kumar Yadav1, Xinying Jia2, Jason Mulvenna2, Debasis Dash3.   

Abstract

Proteogenomic re-annotation and mRNA splicing information can lead to the discovery of various protein forms for eukaryotic model organisms like rat. However, detection of novel proteoforms using mass spectrometry proteomics data remains a formidable challenge. We developed EuGenoSuite, an open source multiple algorithmic proteomic search tool and utilized it in our in-house integrated transcriptomic-proteomic pipeline to facilitate automated proteogenomic analysis. Using four proteogenomic pipelines (integrated transcriptomic-proteomic, Peppy, Enosi, and ProteoAnnotator) on publicly available RNA-sequence and MS proteomics data, we discovered 363 novel peptides in rat brain microglia representing novel proteoforms for 249 gene loci in the rat genome. These novel peptides aided in the discovery of novel exons, translation of annotated untranslated regions, pseudogenes, and splice variants for various loci; many of which have known disease associations, including neurological disorders like schizophrenia, amyotrophic lateral sclerosis, etc. Novel isoforms were also discovered for genes implicated in cardiovascular diseases and breast cancer for which rats are considered model organisms. Our integrative multi-omics data analysis not only enables the discovery of new proteoforms but also generates an improved reference for human disease studies in the rat model.
© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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Year:  2015        PMID: 26560066      PMCID: PMC4762527          DOI: 10.1074/mcp.M114.047126

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  46 in total

1.  ProteoStats--a library for estimating false discovery rates in proteomics pipelines.

Authors:  Amit Kumar Yadav; Puneet Kumar Kadimi; Dhirendra Kumar; Debasis Dash
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2.  STAR: ultrafast universal RNA-seq aligner.

Authors:  Alexander Dobin; Carrie A Davis; Felix Schlesinger; Jorg Drenkow; Chris Zaleski; Sonali Jha; Philippe Batut; Mark Chaisson; Thomas R Gingeras
Journal:  Bioinformatics       Date:  2012-10-25       Impact factor: 6.937

3.  Quantitative proteomic characterization of ethanol-responsive pathways in rat microglial cells.

Authors:  Harris Bell-Temin; Ping Zhang; Dale Chaput; Michael A King; Min You; Bin Liu; Stanley M Stevens
Journal:  J Proteome Res       Date:  2013-04-03       Impact factor: 4.466

4.  Proteoform: a single term describing protein complexity.

Authors:  Lloyd M Smith; Neil L Kelleher
Journal:  Nat Methods       Date:  2013-03       Impact factor: 28.547

5.  Proteogenomic analysis of Bradyrhizobium japonicum USDA110 using GenoSuite, an automated multi-algorithmic pipeline.

Authors:  Dhirendra Kumar; Amit Kumar Yadav; Puneet Kumar Kadimi; Shivashankar H Nagaraj; Sean M Grimmond; Debasis Dash
Journal:  Mol Cell Proteomics       Date:  2013-07-23       Impact factor: 5.911

6.  Evolutionary dynamics of gene and isoform regulation in Mammalian tissues.

Authors:  Jason Merkin; Caitlin Russell; Ping Chen; Christopher B Burge
Journal:  Science       Date:  2012-12-21       Impact factor: 47.728

7.  Peppy: proteogenomic search software.

Authors:  Brian A Risk; Wendy J Spitzer; Morgan C Giddings
Journal:  J Proteome Res       Date:  2013-05-06       Impact factor: 4.466

8.  PRIDE Inspector: a tool to visualize and validate MS proteomics data.

Authors:  Rui Wang; Antonio Fabregat; Daniel Ríos; David Ovelleiro; Joseph M Foster; Richard G Côté; Johannes Griss; Attila Csordas; Yasset Perez-Riverol; Florian Reisinger; Henning Hermjakob; Lennart Martens; Juan Antonio Vizcaíno
Journal:  Nat Biotechnol       Date:  2012-02-08       Impact factor: 54.908

9.  Widespread splicing changes in human brain development and aging.

Authors:  Pavel Mazin; Jieyi Xiong; Xiling Liu; Zheng Yan; Xiaoyu Zhang; Mingshuang Li; Liu He; Mehmet Somel; Yuan Yuan; Yi-Ping Phoebe Chen; Na Li; Yuhui Hu; Ning Fu; Zhibin Ning; Rong Zeng; Hongyi Yang; Wei Chen; Mikhail Gelfand; Philipp Khaitovich
Journal:  Mol Syst Biol       Date:  2013       Impact factor: 11.429

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Authors:  Austin M Dulak; Petar Stojanov; Shouyong Peng; Michael S Lawrence; Cameron Fox; Chip Stewart; Santhoshi Bandla; Yu Imamura; Steven E Schumacher; Erica Shefler; Aaron McKenna; Scott L Carter; Kristian Cibulskis; Andrey Sivachenko; Gordon Saksena; Douglas Voet; Alex H Ramos; Daniel Auclair; Kristin Thompson; Carrie Sougnez; Robert C Onofrio; Candace Guiducci; Rameen Beroukhim; Zhongren Zhou; Lin Lin; Jules Lin; Rishindra Reddy; Andrew Chang; Rodney Landrenau; Arjun Pennathur; Shuji Ogino; James D Luketich; Todd R Golub; Stacey B Gabriel; Eric S Lander; David G Beer; Tony E Godfrey; Gad Getz; Adam J Bass
Journal:  Nat Genet       Date:  2013-03-24       Impact factor: 38.330

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1.  Proteogenomic Analysis and Discovery of Immune Antigens in Mycobacterium vaccae.

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Journal:  Mol Cell Proteomics       Date:  2017-07-21       Impact factor: 5.911

Review 2.  A polarizing question: do M1 and M2 microglia exist?

Authors:  Richard M Ransohoff
Journal:  Nat Neurosci       Date:  2016-07-26       Impact factor: 24.884

Review 3.  Proteins and Proteoforms: New Separation Challenges.

Authors:  Fred E Regnier; JinHee Kim
Journal:  Anal Chem       Date:  2017-12-18       Impact factor: 6.986

4.  Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues.

Authors:  Shengbo Wang; David García-Seisdedos; Ananth Prakash; Deepti Jaiswal Kundu; Andrew Collins; Nancy George; Silvie Fexova; Pablo Moreno; Irene Papatheodorou; Andrew R Jones; Juan Antonio Vizcaíno
Journal:  PLoS Comput Biol       Date:  2022-06-17       Impact factor: 4.779

Review 5.  Proteotranscriptomics - A facilitator in omics research.

Authors:  Michal Levin; Falk Butter
Journal:  Comput Struct Biotechnol J       Date:  2022-07-09       Impact factor: 6.155

Review 6.  A Golden Age for Working with Public Proteomics Data.

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Journal:  Trends Biochem Sci       Date:  2017-01-22       Impact factor: 13.807

7.  Alternative splicing and translation play important roles in hypoxic germination in rice.

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8.  Fusion transcripts in normal human cortex increase with age and show distinct genomic features for single cells and tissues.

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Journal:  Sci Rep       Date:  2020-01-28       Impact factor: 4.379

9.  SWATH-MS-facilitated proteomic profiling of fruit skin between Fuji apple and a red skin bud sport mutant.

Authors:  Mo-Xian Chen; Chao Sun; Kai-Lu Zhang; Yu-Chen Song; Yuan Tian; Xi Chen; Ying-Gao Liu; Neng-Hui Ye; Jianhua Zhang; Shenchun Qu; Fu-Yuan Zhu
Journal:  BMC Plant Biol       Date:  2019-10-24       Impact factor: 4.215

Review 10.  Prospects and challenges of cancer systems medicine: from genes to disease networks.

Authors:  Mohammad Reza Karimi; Amir Hossein Karimi; Shamsozoha Abolmaali; Mehdi Sadeghi; Ulf Schmitz
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

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