dc.contributor.author | Kustatscher, G | |
dc.contributor.author | Grabowski, P | |
dc.contributor.author | Schrader, TA | |
dc.contributor.author | Passmore, JB | |
dc.contributor.author | Schrader, M | |
dc.contributor.author | Rappsilber, J | |
dc.date.accessioned | 2019-07-16T13:58:11Z | |
dc.date.issued | 2019-11-04 | |
dc.description.abstract | The annotation of protein function is a longstanding challenge of cell biology that
suffers from the sheer magnitude of the task. Here we present ProteomeHD, which
documents the response of 10,323 human proteins to 294 biological perturbations,
measured by isotope-labelling mass spectrometry. We reveal functional associations
between human proteins using the treeClust machine learning algorithm, which we
show to improve protein co-regulation analysis due to robust selectivity for close
linear relationships. Our co-regulation map identifies a functional context for many
uncharacterized proteins, including microproteins that are difficult to study with
traditional methods. Co-regulation also captures relationships between proteins
which do not physically interact or co-localize. For example, co-regulation of the
peroxisomal membrane protein PEX11β with mitochondrial respiration factors led us
to discover a novel organelle interface between peroxisomes and mitochondria in
mammalian cells. The co-regulation map can be explored at www.proteomeHD.net . | en_GB |
dc.description.sponsorship | Biotechnology & Biological Sciences Research Council (BBSRC) | en_GB |
dc.description.sponsorship | European Commission | en_GB |
dc.identifier.citation | Vol. 37, pp. 1361–1371 | en_GB |
dc.identifier.doi | 10.1038/s41587-019-0298-5 | |
dc.identifier.grantnumber | BB/R016844/1 | en_GB |
dc.identifier.grantnumber | 812968 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/38001 | |
dc.language.iso | en | en_GB |
dc.publisher | Nature Research | en_GB |
dc.relation.url | https://github.com/Rappsilber-Laboratory/ProteomeHD | |
dc.relation.url | https://github.com/Rappsilber-Laboratory/treeClust-benchmarking | |
dc.relation.url | http://proteomecentral.proteomexchange.org/cgi/GetDataset | |
dc.rights.embargoreason | Under embargo until 4 May 2020 in compliance with publisher policy | en_GB |
dc.rights | © The Author(s), under exclusive licence to Springer Nature America, Inc. 2019 | |
dc.title | Co-regulation map of the human proteome enables identification of protein functions | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-07-16T13:58:11Z | |
dc.identifier.issn | 1087-0156 | |
dc.description | This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record | en_GB |
dc.description | Data availability:
All mass spectrometry raw files generated in-house have been deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository36 with the dataset identifier PXD008888. The co-regulation map is hosted on our website at www.proteomeHD.net, and pair-wise co-regulation scores are available through STRING (https://string-db.org). A network of the top 0.5% co-regulated protein pairs can be explored interactively on NDEx (https://doi.org/10.18119/N9N30Q). | |
dc.description | Code availability:
Data analysis was performed in R 3.5.1. R scripts and input files required to reproduce the results of this manuscript are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/ProteomeHD. R scripts related specifically to the benchmarking of the treeClust algorithm using synthetic data are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/treeClust-benchmarking. The R package data.table was used for fast data processing. Figures were prepared using ggplot2, gridExtra, cowplot and viridis. | |
dc.description | Note that the title of the AAM is different from the published version | |
dc.identifier.journal | Nature Biotechnology | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
dcterms.dateAccepted | 2019-09-27 | |
exeter.funder | ::Biotechnology & Biological Sciences Research Council (BBSRC) | en_GB |
exeter.funder | ::Biotechnology & Biological Sciences Research Council (BBSRC) | en_GB |
exeter.funder | ::European Commission | en_GB |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-07-08 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-07-16T13:49:05Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-05-03T23:00:00Z | |
refterms.panel | A | en_GB |