According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17874 proteins as PE1, having strong protein-level evidence, up 180 from 17694 one year earlier. These represent 90.4% of the 19773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.
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We appreciate the guidance from the HPP Executive Committee and the participation of all HPP investigators. We thank the UniProt groups at SIB, EBI, and PIR for providing high-quality annotations for the human proteins in UniProtKB/Swiss-Prot. The neXtProt server is hosted by VitalIT in Switzerland, ProteomeXchange and PRIDE at the European Bioinformatics Institute in Cambridge, UK, PeptideAtlas at the Institute for Systems Biology in Seattle, and MassIVE at the University of California San Diego. G.S.O. acknowledges support from National Institutes of Health grants P30ES017885-01A1 and U24CA210967; E.W.D. from National Institutes of Health grants R01GM087221, R24GM127667, U19AG023122, and from National Science Foundation grant DBI-1933311; L.L. and neXtProt from the SIB Swiss Institute of Bioinformatics; C.M.O. by Canadian Institutes of Health Research Foundation Grant 148408 and a Canada Research Chair in Protease Proteomics and Systems Biology; M.S.B. by NHMRC Project Grant APP1010303; C.L. by the Knut and Alice Wallenberg Foundation for the Human Protein Atlas; and Y.-K.P. by grants from the Korean Ministry of Health and Welfare HI13C22098 and HI16C0257.
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