A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs
Abstract The human protein interaction network will offer global insights into the molecular organization of cells and provide a framework for modeling human disease, but the network's large scale demands new approaches. We report a set of 7000 physical associations among human proteins inferre...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2008-04-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.1038/msb.2008.19 |
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| _version_ | 1849225794331607040 |
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| author | Arun K Ramani Zhihua Li G Traver Hart Mark W Carlson Daniel R Boutz Edward M Marcotte |
| author_facet | Arun K Ramani Zhihua Li G Traver Hart Mark W Carlson Daniel R Boutz Edward M Marcotte |
| author_sort | Arun K Ramani |
| collection | DOAJ |
| description | Abstract The human protein interaction network will offer global insights into the molecular organization of cells and provide a framework for modeling human disease, but the network's large scale demands new approaches. We report a set of 7000 physical associations among human proteins inferred from indirect evidence: the comparison of human mRNA co‐expression patterns with those of orthologous genes in five other eukaryotes, which we demonstrate identifies proteins in the same physical complexes. To evaluate the accuracy of the predicted physical associations, we apply quantitative mass spectrometry shotgun proteomics to measure elution profiles of 3013 human proteins during native biochemical fractionation, demonstrating systematically that putative interaction partners tend to co‐sediment. We further validate uncharacterized proteins implicated by the associations in ribosome biogenesis, including WBSCR20C, associated with Williams–Beuren syndrome. This meta‐analysis therefore exploits non‐protein‐based data, but successfully predicts associations, including 5589 novel human physical protein associations, with measured accuracies of 54±10%, comparable to direct large‐scale interaction assays. The new associations’ derivation from conserved in vivo phenomena argues strongly for their biological relevance. |
| format | Article |
| id | doaj-art-c5d7a5ade6ef446ea70129876b144de1 |
| institution | Kabale University |
| issn | 1744-4292 |
| language | English |
| publishDate | 2008-04-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-c5d7a5ade6ef446ea70129876b144de12025-08-24T12:01:29ZengSpringer NatureMolecular Systems Biology1744-42922008-04-014111610.1038/msb.2008.19A map of human protein interactions derived from co‐expression of human mRNAs and their orthologsArun K Ramani0Zhihua Li1G Traver Hart2Mark W Carlson3Daniel R Boutz4Edward M Marcotte5Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of TexasCenter for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of TexasCenter for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of TexasDepartment of Biomedical Engineering, University of TexasCenter for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of TexasCenter for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of TexasAbstract The human protein interaction network will offer global insights into the molecular organization of cells and provide a framework for modeling human disease, but the network's large scale demands new approaches. We report a set of 7000 physical associations among human proteins inferred from indirect evidence: the comparison of human mRNA co‐expression patterns with those of orthologous genes in five other eukaryotes, which we demonstrate identifies proteins in the same physical complexes. To evaluate the accuracy of the predicted physical associations, we apply quantitative mass spectrometry shotgun proteomics to measure elution profiles of 3013 human proteins during native biochemical fractionation, demonstrating systematically that putative interaction partners tend to co‐sediment. We further validate uncharacterized proteins implicated by the associations in ribosome biogenesis, including WBSCR20C, associated with Williams–Beuren syndrome. This meta‐analysis therefore exploits non‐protein‐based data, but successfully predicts associations, including 5589 novel human physical protein associations, with measured accuracies of 54±10%, comparable to direct large‐scale interaction assays. The new associations’ derivation from conserved in vivo phenomena argues strongly for their biological relevance.https://doi.org/10.1038/msb.2008.19interactionsmass spectrometrynetworksproteomicssystems biology |
| spellingShingle | Arun K Ramani Zhihua Li G Traver Hart Mark W Carlson Daniel R Boutz Edward M Marcotte A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs Molecular Systems Biology interactions mass spectrometry networks proteomics systems biology |
| title | A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs |
| title_full | A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs |
| title_fullStr | A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs |
| title_full_unstemmed | A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs |
| title_short | A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs |
| title_sort | map of human protein interactions derived from co expression of human mrnas and their orthologs |
| topic | interactions mass spectrometry networks proteomics systems biology |
| url | https://doi.org/10.1038/msb.2008.19 |
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