Literature DB >> 30289715

ASV-ID, a Proteogenomic Workflow To Predict Candidate Protein Isoforms on the Basis of Transcript Evidence.

Seul-Ki Jeong, Chae-Yeon Kim, Young-Ki Paik.   

Abstract

One of the goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to map and characterize the functions of protein isoforms produced by alternative splicing of genes. However, identifying alternative splice variants (ASVs) via mass spectrometry remains a major challenge, because ASVs usually contain highly homologous peptide sequences. A routine protein sequence analysis suggests that more than half of the investigated proteins do not generate two or more uniquely mapping peptides that would enable their isoforms to be distinguished. Here, we develop a new proteogenomics method, named "ASV-ID" (alternative splicing variants identification), which enables identification of ASVs by using a cell type-specific protein sequence database that is supported by RNA-Seq data. Using this workflow, we identify 1935 distinct proteins under highly stringent conditions. In fact, transcript evidence on these 841 proteins helps us distinguish them from other isoforms, despite the fact that these proteins are not predicted to make 2 or more uniquely mapping peptides. We also demonstrate that ASV-ID enables detection of 19 differently expressed isoforms present in several cell lines. Thus, a new workflow using ASV-ID has the potential to map yet-to-be-identified difficult protein isoforms in a simple and robust way.

Entities:  

Keywords:  RNA-sequencing; alternative splicing variants; cell type-specific sequence database; proteogenomics

Mesh:

Substances:

Year:  2018        PMID: 30289715     DOI: 10.1021/acs.jproteome.8b00548

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  6 in total

1.  Efficient Detection of the Alternative Spliced Human Proteome Using Translatome Sequencing.

Authors:  Chun Wu; Xiaolong Lu; Shaohua Lu; Hongwei Wang; Dehua Li; Jing Zhao; Jingjie Jin; Zhenghua Sun; Qing-Yu He; Yang Chen; Gong Zhang
Journal:  Front Mol Biosci       Date:  2022-06-02

2.  Improved methods for RNAseq-based alternative splicing analysis.

Authors:  Patrick Pirrotte; Nicholas J Schork; Rebecca F Halperin; Apurva Hegde; Jessica D Lang; Elizabeth A Raupach; Christophe Legendre; Winnie S Liang; Patricia M LoRusso; Aleksandar Sekulic; Jeffrey A Sosman; Jeffrey M Trent; Sampathkumar Rangasamy
Journal:  Sci Rep       Date:  2021-05-24       Impact factor: 4.996

3.  Deep profiling and custom databases improve detection of proteoforms generated by alternative splicing.

Authors:  Laura M Agosto; Matthew R Gazzara; Caleb M Radens; Simone Sidoli; Josue Baeza; Benjamin A Garcia; Kristen W Lynch
Journal:  Genome Res       Date:  2019-11-14       Impact factor: 9.043

4.  Enhanced protein isoform characterization through long-read proteogenomics.

Authors:  Rachel M Miller; Ben T Jordan; Madison M Mehlferber; Erin D Jeffery; Christina Chatzipantsiou; Simi Kaur; Robert J Millikin; Yunxiang Dai; Simone Tiberi; Peter J Castaldi; Michael R Shortreed; Chance John Luckey; Ana Conesa; Lloyd M Smith; Anne Deslattes Mays; Gloria M Sheynkman
Journal:  Genome Biol       Date:  2022-03-03       Impact factor: 13.583

5.  Proteogenomic Analysis of Breast Cancer Transcriptomic and Proteomic Data, Using De Novo Transcript Assembly: Genome-Wide Identification of Novel Peptides and Clinical Implications.

Authors:  P S Hari; Lavanya Balakrishnan; Chaithanya Kotyada; Arivusudar Everad John; Shivani Tiwary; Nameeta Shah; Ravi Sirdeshmukh
Journal:  Mol Cell Proteomics       Date:  2022-02-26       Impact factor: 7.381

Review 6.  Uncovering the impacts of alternative splicing on the proteome with current omics techniques.

Authors:  Marina Reixachs-Solé; Eduardo Eyras
Journal:  Wiley Interdiscip Rev RNA       Date:  2022-01-03       Impact factor: 9.349

  6 in total

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