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Accurate Prediction of Protein Sequences for Proteogenomics Data Integration

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Clinical Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2420))

Abstract

This book chapter discusses proteogenomics data integration and provides an overview into the different omics layer involved in defining the proteome of a living organism. Various aspects of genome variability affecting either the sequence or abundance level of proteins are discussed in this book chapter, such as the effect of single-nucleotide variants or larger genomic structural variants on the proteome. Next, various sequencing technologies are introduced and discussed from a proteogenomics data integration perspective such as those providing short- and long-read sequencing and listing their respective advantages and shortcomings for accurate protein variant prediction using genomic/transcriptomics sequencing data. Finally, the various bioinformatics tools used to process and analyze DNA/RNA sequencing data are discussed with the ultimate goal of obtaining accurately predicted sample-specific protein sequences that can be used as a drop-in replacement in existing approaches for peptide and protein identification using popular database search engines such as MSFragger, SearchGUI/PeptideShaker.

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Acknowledgments

We thank Prof. Dr. Rainer Bischoff for his input, feedback, and discussions related to the content of this book chapter.

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Authors and Affiliations

  1. Department of Analytical Biochemistry, University of Groningen, Groningen Research Institute of Pharmacy, Groningen, The Netherlands

    Yanick Paco Hagemeijer & Peter Horvatovich

  2. European Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen, The Netherlands

    Yanick Paco Hagemeijer & Victor Guryev

Authors
  1. Yanick Paco Hagemeijer
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  2. Victor Guryev
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  3. Peter Horvatovich
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Corresponding author

Correspondence to Peter Horvatovich .

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Editors and Affiliations

  1. Proteomics Unit, Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain

    Fernando J. Corrales

  2. Proteomics Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Madrid, Spain

    Alberto Paradela

  3. Proteomics Unit, Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain

    Miguel Marcilla

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Hagemeijer, Y.P., Guryev, V., Horvatovich, P. (2022). Accurate Prediction of Protein Sequences for Proteogenomics Data Integration. In: Corrales, F.J., Paradela, A., Marcilla, M. (eds) Clinical Proteomics. Methods in Molecular Biology, vol 2420. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1936-0_18

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  • DOI: https://doi.org/10.1007/978-1-0716-1936-0_18

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1935-3

  • Online ISBN: 978-1-0716-1936-0

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