Large-Scale Mass Spectrometric Detection of Variant Peptides Resulting from Nonsynonymous Nucleotide Differences

Abstract

Each individual carries thousands of non-synonymous single nucleotide variants (nsSNVs) in their genome, each corresponding to a single amino acid polymorphism (SAP) in the encoded proteins. It is important to be able to directly detect and quantify these variations at the protein level in order to study post-transcriptional regulation, differential allelic expression, and other important biological processes. However, such variant peptides are not generally detected in standard proteomic analyses, due to their absence from the generic databases that are employed for mass spectrometry searching. Here, we extend previous work that demonstrated the use of customized SAP databases constructed from sample-matched RNA-Seq data. We collected deep coverage RNA-Seq data from the Jurkat cell line, compiled the set of nsSNVs that are expressed, used this information to construct a customized SAP database, and searched it against deep coverage shotgun MS data obtained from the same sample. This approach enabled detection of 421 SAP peptides mapping to 395 nsSNVs. We compared these peptides to peptides identified from a large generic search database containing all known nsSNVs (dbSNP) and found that more than 70% of the SAP peptides from this dbSNP-derived search were not supported by the RNA-Seq data, and thus are likely false positives. Next, we increased the SAP coverage from the RNA-Seq derived database by utilizing multiple protease digestions, thereby increasing variant detection to 695 SAP peptides mapping to 504 nsSNV sites. These detected SAP peptides corresponded to moderate to high abundance transcripts (30+ transcripts per million, TPM). The SAP peptides included 192 allelic pairs; the relative expression levels of the two alleles were evaluated for 51 of those pairs, and found to be comparable in all cases.

Single Amino Acid Variant Profiles of Subpopulations in the MCF-7 Breast Cancer Cell Line

“…21 Sheynkman et al also developed a customized SAP database from sample-matched RNA-Seq data and were able to detect 695 SAP peptides mapping to 504 nsSNV sites from their mass spec data. 22 However, this strategy depends on an RNA-seq database for a specific sample and for a highly heterogeneous tumor or a cell line that has been passaged an unknown number of times, this database may not be transferable in terms of the expressed mutations.…”

Human Proteomic Variation Revealed by Combining RNA-Seq Proteogenomics and Global Post-Translational Modification (G-PTM) Search Strategy

“…The SAV and NSJ databases were produced and appended to the reference proteome in UniProt XML format to create a sample-specific database for each cell line. For the present work, we adapted and combined scripts from the works by Sheynkman et al 6,7,9 to develop software named SampleSpecificDBGenerator used to perform this process. This program and source code can be obtained at .…”

“…This specific version was used to maintain consistency with previous studies on these workflows. 7,9 …”

Full-length mRNA sequencing uncovers a widespread coupling between transcription and mRNA processing

“…20). Presence of SAS events without knowledge of their existence through sample-specific protein database can either lead to mismatch or failure to detect peptides using general annotations such as Gencode 43 . This is more prominent for sample-specific differential expression of paralogous genes (Supplementary Fig.…”