Exome-based proteogenomics of HEK-293 human cell line: Coding genomic variants identified at the level of shotgun proteome

Abstract

Genomic and proteomic data were integrated into the proteogenomic workflow to identify coding genomic variants of Human Embryonic Kidney 293 (HEK-293) cell line at the proteome level. Shotgun proteome data published by Geiger et al. (2012), Chick et al. (2015), and obtained in this work for HEK-293 were searched against the customized genomic database generated using exome data published by Lin et al. (2014). Overall, 112 unique variants were identified at the proteome level out of ∼1200 coding variants annotated in the exome. Seven identified variants were shared between all the three considered proteomic datasets, and 27 variants were found in any two datasets. Some of the found variants belonged to widely known genomic polymorphisms originated from the germline, while the others were more likely resulting from somatic mutations. At least, eight of the proteins bearing amino acid variants were annotated as cancer-related ones, including p53 tumor suppressor. In all the considered shotgun datasets, the variant peptides were at the ratio of 1:2.5 less likely being identified than the wild-type ones compared with the corresponding theoretical peptides. This can be explained by the presence of the so-called "passenger" mutations in the genes, which were never expressed in HEK-293 cells. All MS data have been deposited in the ProteomeXchange with the dataset identifier PXD002613 (http://proteomecentral.proteomexchange.org/dataset/PXD002613).

Adenosine‐to‐Inosine RNA Editing in Mouse and Human Brain Proteomes

“…Manual inspection of the mass spectra of variant peptides was also performed for expert validation of findings as suggested recently . As one of the striking results obtained for the murine data, an edited peptide VTIAQGGVLP S IQAVLLPK with one acetylation site from the common histone HIST2H2AC was reported with high spectral counts.…”

Connecting Proteomics to Next‐Generation Sequencing: Proteogenomics and Its Current Applications in Biology

“…Such variants may be deleterious, and their deleteriousness can be predicted from the evolutionary conservation of homologous sequences or the structures of the encoded proteins . The sequences for such genome‐encoded variants can be obtained from exome sequencing, RNA‐Seq, or existing SNP/SNV databases. In a C‐HPP study on chromosome‐9, LC‐MS/MS and RNA‐Seq were performed on five pairs of lung adenocarcinoma tumors and adjacent non‐tumor tissues, resulting in the identification of seven unique SNPs; and four missense mutations in proteins such as LTF, HDLBP, TF, and HBD in the tumor samples .…”

Integration of large-scale multi-omic datasets: A protein-centric view

“…Such proteogenomic studies have helped to identify novel genes, splice variants, N-terminal extensions, alternative open reading frames, and short proteins in the genomes of both well-characterized and less-studied organisms [1]. Despite the initial excitement, most studies identified only a few hundred new proteins or protein variants: ~100 in the model cell line HEK-293 [28], ~300 in grapevine and monkey [29,30], ~600 in pig [31], and >800 in mosquito [32]. These relatively low numbers may be due to the limited genome coverage that proteomics provides or its bias towards high-abundance proteins, though it may also indicate that the predictive algorithms capture most of the variation, at least within the known feature space.…”