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dc.contributor.authorKustatscher, G
dc.contributor.authorGrabowski, P
dc.contributor.authorSchrader, TA
dc.contributor.authorPassmore, JB
dc.contributor.authorSchrader, M
dc.contributor.authorRappsilber, J
dc.date.accessioned2019-07-16T13:58:11Z
dc.date.issued2019-11-04
dc.description.abstractThe 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.sponsorshipBiotechnology & Biological Sciences Research Council (BBSRC)en_GB
dc.description.sponsorshipEuropean Commissionen_GB
dc.identifier.citationVol. 37, pp. 1361–1371en_GB
dc.identifier.doi10.1038/s41587-019-0298-5
dc.identifier.grantnumberBB/R016844/1en_GB
dc.identifier.grantnumber812968en_GB
dc.identifier.urihttp://hdl.handle.net/10871/38001
dc.language.isoenen_GB
dc.publisherNature Researchen_GB
dc.relation.urlhttps://github.com/Rappsilber-Laboratory/ProteomeHD
dc.relation.urlhttps://github.com/Rappsilber-Laboratory/treeClust-benchmarking
dc.relation.urlhttp://proteomecentral.proteomexchange.org/cgi/GetDataset
dc.rights.embargoreasonUnder 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.titleCo-regulation map of the human proteome enables identification of protein functionsen_GB
dc.typeArticleen_GB
dc.date.available2019-07-16T13:58:11Z
dc.identifier.issn1087-0156
dc.descriptionThis is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recorden_GB
dc.descriptionData 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.descriptionCode 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.descriptionNote that the title of the AAM is different from the published version
dc.identifier.journalNature Biotechnologyen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2019-09-27
exeter.funder::Biotechnology & Biological Sciences Research Council (BBSRC)en_GB
exeter.funder::Biotechnology & Biological Sciences Research Council (BBSRC)en_GB
exeter.funder::European Commissionen_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2019-07-08
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-07-16T13:49:05Z
refterms.versionFCDAM
refterms.panelAen_GB


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