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Validating Amino Acid Variants in Proteogenomics Using Sequence Coverage by Multiple Reads.

Lev I LevitskyKsenia G KuznetsovaAnna A KliuchnikovaIrina Y IlinaAnton O GoncharovAnna A LobasMikhail V GorshkovVassili N LazarevRustam H ZiganshinMikhail V GorshkovSergei A Moshkovskii
Published in: Journal of proteome research (2022)
Mass spectrometry-based proteome analysis implies matching the mass spectra of proteolytic peptides to amino acid sequences predicted from genomic sequences. Reliability of peptide variant identification in proteogenomic studies is often lacking. We propose a way to interpret shotgun proteomics results, specifically in the data-dependent acquisition mode, as protein sequence coverage by multiple reads as it is done in nucleic acid sequencing for calling of single nucleotide variants. Multiple reads for each sequence position could be provided by overlapping distinct peptides, thus confirming the presence of certain amino acid residues in the overlapping stretch with a lower false discovery rate. Overlapping distinct peptides originate from miscleaved tryptic peptides in combination with their properly cleaved counterparts and from peptides generated by multiple proteases after the same specimen is subject to parallel digestion and analyzed separately. We illustrate this approach using publicly available multiprotease data sets and our own data generated for the HEK-293 cell line digests obtained using trypsin, LysC, and GluC proteases. Totally, up to 30% of the whole proteome was covered by tryptic peptides with up to 7% covered twofold and more. The proteogenomic analysis of the HEK-293 cell line revealed 36 single amino acid variants, seven of which were supported by multiple reads.
Keyphrases
  • amino acid
  • mass spectrometry
  • copy number
  • electronic health record
  • nucleic acid
  • big data
  • single cell
  • small molecule
  • healthcare
  • high throughput
  • ms ms
  • data analysis
  • deep learning