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Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms
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 wa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350264/ https://www.ncbi.nlm.nih.gov/pubmed/32575886 http://dx.doi.org/10.3390/genes11060677 |
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author | Poverennaya, Ekaterina Kiseleva, Olga Romanova, Anastasia Pyatnitskiy, Mikhail |
author_facet | Poverennaya, Ekaterina Kiseleva, Olga Romanova, Anastasia Pyatnitskiy, Mikhail |
author_sort | Poverennaya, Ekaterina |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7350264 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73502642020-07-22 Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms Poverennaya, Ekaterina Kiseleva, Olga Romanova, Anastasia Pyatnitskiy, Mikhail Genes (Basel) Article 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. MDPI 2020-06-21 /pmc/articles/PMC7350264/ /pubmed/32575886 http://dx.doi.org/10.3390/genes11060677 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Poverennaya, Ekaterina Kiseleva, Olga Romanova, Anastasia Pyatnitskiy, Mikhail Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms |
title | Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms |
title_full | Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms |
title_fullStr | Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms |
title_full_unstemmed | Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms |
title_short | Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms |
title_sort | predicting functions of uncharacterized human proteins: from canonical to proteoforms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350264/ https://www.ncbi.nlm.nih.gov/pubmed/32575886 http://dx.doi.org/10.3390/genes11060677 |
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