Next Article in Journal
Genome-Wide Identification of Discriminative Genetic Variations in Beef and Dairy Cattle via an Information-Theoretic Approach
Previous Article in Journal
Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker
Previous Article in Special Issue
Histone Deacetylases (HDACs): Evolution, Specificity, Role in Transcriptional Complexes, and Pharmacological Actionability
Open AccessArticle

Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms

1
Department of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia
2
Institute of Environmental and Agricultural Biology (X-BIO),Tyumen State University, 625003 Tyumen, Russia
3
Faculty of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, 141701 Moscow, Russia
4
Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
*
Author to whom correspondence should be addressed.
Genes 2020, 11(6), 677; https://doi.org/10.3390/genes11060677
Received: 30 April 2020 / Revised: 9 June 2020 / Accepted: 19 June 2020 / Published: 21 June 2020
(This article belongs to the Special Issue Evolution of Gene Regulatory Networks)
Despite tremendous efforts in genomics, transcriptomics, and proteomics communities, there is still no comprehensive data about the exact number of protein-coding genes, translated proteoforms, and their function. In addition, by now, we lack functional annotation for 1193 genes, where expression was confirmed at the proteomic level (uPE1 proteins). We re-analyzed results of AP-MS experiments from the BioPlex 2.0 database to predict functions of uPE1 proteins and their splice forms. By building a protein–protein interaction network for 12 ths. identified proteins encoded by 11 ths. genes, we were able to predict Gene Ontology categories for a total of 387 uPE1 genes. We predicted different functions for canonical and alternatively spliced forms for four uPE1 genes. In total, functional differences were revealed for 62 proteoforms encoded by 31 genes. Based on these results, it can be carefully concluded that the dynamics and versatility of the interactome is ensured by changing the dominant splice form. Overall, we propose that analysis of large-scale AP-MS experiments performed for various cell lines and under various conditions is a key to understanding the full potential of genes role in cellular processes. View Full-Text
Keywords: protein coding genes; function annotation; Gene Ontology; protein–protein interaction; splice form; proteoform; uPE1 proteins; human interactome; AP-MS; BioPlex protein coding genes; function annotation; Gene Ontology; protein–protein interaction; splice form; proteoform; uPE1 proteins; human interactome; AP-MS; BioPlex
Show Figures

Figure 1

MDPI and ACS Style

Poverennaya, E.; Kiseleva, O.; Romanova, A.; Pyatnitskiy, M. Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms. Genes 2020, 11, 677.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop