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Validating amino acid variants in proteogenomics using sequence coverage by multiple reads

View ORCID ProfileL.I. Levitsky, View ORCID ProfileK.G. Kuznetsova, View ORCID ProfileA.A. Kliuchnikova, View ORCID ProfileI.Y. Ilina, View ORCID ProfileA.O. Goncharov, View ORCID ProfileA.A. Lobas, View ORCID ProfileM.V. Ivanov, View ORCID ProfileV.N. Lazarev, View ORCID ProfileR.H. Ziganshin, View ORCID ProfileM.V. Gorshkov, View ORCID ProfileS.A. Moshkovskii
doi: https://doi.org/10.1101/2022.01.08.475497
L.I. Levitsky
1V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow, 119334, Russia
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K.G. Kuznetsova
2Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow, 119435, Russia
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A.A. Kliuchnikova
2Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow, 119435, Russia
3Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow, 117997, Russia
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I.Y. Ilina
2Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow, 119435, Russia
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A.O. Goncharov
2Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow, 119435, Russia
3Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow, 117997, Russia
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A.A. Lobas
1V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow, 119334, Russia
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M.V. Ivanov
1V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow, 119334, Russia
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V.N. Lazarev
2Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow, 119435, Russia
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R.H. Ziganshin
4Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya, Moscow, 117997, Russia
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M.V. Gorshkov
1V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow, 119334, Russia
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S.A. Moshkovskii
2Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow, 119435, Russia
3Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow, 117997, Russia
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  • For correspondence: smosh@mail.ru
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Abstract

Mass spectrometry-based proteome analysis usually implies matching mass spectra of proteolytic peptides to amino acid sequences predicted from nucleic acid sequences. At the same time, due to the stochastic nature of the method when it comes to proteome-wide analysis, in which only a fraction of peptides are selected for sequencing, the completeness of protein sequence identification is undermined. Likewise, the reliability of peptide variant identification in proteogenomic studies is suffering. We propose a way to interpret shotgun proteomics results, specifically in data-dependent acquisition mode, as protein sequence coverage by multiple reads, just as it is done in the field of nucleic acid sequencing for the calling of single nucleotide variants. Multiple reads for each position in a sequence could be provided by overlapping distinct peptides, thus, confirming the presence of certain amino acid residues in the overlapping stretch with much lower false discovery rate than conventional 1%. The source of overlapping distinct peptides are, first, miscleaved tryptic peptides in combination with their properly cleaved counterparts, and, second, peptides generated by several proteases with different specificities after the same specimen is subject to parallel digestion and analyzed separately. We illustrate this approach using publicly available multiprotease proteomic datasets and our own data generated for HEK-293 cell line digests obtained using trypsin, LysC and GluC proteases. From 5000 to 8000 protein groups are identified for each digest corresponding to up to 30% of the whole proteome coverage. Most of this coverage was provided by a single read, while up to 7% of the observed protein sequences were covered two-fold and more. The proteogenomic analysis of HEK-293 cell line revealed 36 peptide variants associated with SNP, seven of which were supported by multiple reads. The efficiency of the multiple reads approach depends strongly on the depth of proteome analysis, the digesting features such as the level of miscleavages, and will increase with the number of different proteases used in parallel proteome digestion.

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Competing Interest Statement

The authors have declared no competing interest.

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Posted January 11, 2022.
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Validating amino acid variants in proteogenomics using sequence coverage by multiple reads
L.I. Levitsky, K.G. Kuznetsova, A.A. Kliuchnikova, I.Y. Ilina, A.O. Goncharov, A.A. Lobas, M.V. Ivanov, V.N. Lazarev, R.H. Ziganshin, M.V. Gorshkov, S.A. Moshkovskii
bioRxiv 2022.01.08.475497; doi: https://doi.org/10.1101/2022.01.08.475497
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Validating amino acid variants in proteogenomics using sequence coverage by multiple reads
L.I. Levitsky, K.G. Kuznetsova, A.A. Kliuchnikova, I.Y. Ilina, A.O. Goncharov, A.A. Lobas, M.V. Ivanov, V.N. Lazarev, R.H. Ziganshin, M.V. Gorshkov, S.A. Moshkovskii
bioRxiv 2022.01.08.475497; doi: https://doi.org/10.1101/2022.01.08.475497

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