The UniProt website has been augmented with new data visualizations for the subcellular localization of proteins as well as their structure and interactions. The proteins expressed in a cell at any moment of time determine its function, its topology, how it reacts to changes in environment and ultimately its longevity and well-being.
Improvements in experimental techniques are providing ever deeper information on the structure and function of individual proteins, whilst large-scale sequencing efforts are driving increased coverage of the complete proteomes of the breadth of organisms that populate the tree of life. Our challenge is to capture the growing depth and breadth of information and make it easily available and interpretable to our users. Improved metagenomic assembly and binning tools are resulting in an increasing number of high-quality metagenomic assembled genomes MAGs being represented in the database.
Additionally, we provide the UniRef databases that cluster sequence sets at various levels of sequence identity and the UniProt Archive UniParc that delivers a complete set of known sequences, including historical obsolete sequence. We describe the major developments that we have made since our last update published in this journal in 1 with a focus on how we are positioning the UniProt database to address the challenges of the increased volume of sequence data entering the database.
Taxa may be specifically targeted by curators to fill gaps in the taxonomic space and additional proteome import can be requested by individual users. We continue to see exponential growth in many of our datasets, see Figure 1. We are managing this growth by a number of processes. Most critically, a redundancy removal process was first introduced in As can be seen in Figure 1 , the redundancy reduction both greatly reduced the size of UniProtKB as well as made its growth more scalable.
Recently, we have added virus Reference Proteomes described below to this list. The growth of Reference Proteome sets is shown in Figure 2. Growth of the total number of Complete Proteomes and Reference Proteomes since The QfO reference proteomes datasets are a compiled subset of the UniProt reference proteomes, comprising well-annotated model organisms and organisms of interest for biomedical research and phylogeny, with the intention to provide broad coverage of the tree of life whilst maintaining a low number of proteomes for the benchmark.
To this end, a gene-centric pipeline has been developed and enhanced over the past year by UniProt. In the last release for QfO in April, the number of species increased from 66 to 78 comprising 1,, non-redundant protein sequences 48 Eukaryotes and 30 bacteria-archaea. At the time of our previous publication, the number of virus Reference Proteomes in UniProtKB stood at —practically an order of magnitude less than the number of known viral species which stands at according to the International Committee on Taxonomy of Viruses, or ICTV.
To improve Reference Proteome Coverage of viruses in UniProt we have undertaken a concerted effort to curate Complete Proteomes and to use these as input for the computational selection of Reference Proteomes.
Computational clustering of this enhanced viral Complete Proteome set 13 produced 5, viral Reference Proteomes. Note that redundancy removal procedures are not currently applied to viruses, due to the challenges posed by the high number of variants in the small genomes of these species.
Technological advances have enabled the sequencing of the genetic material from all the microorganisms in a particular environment without the cultivation of any of the community members.
The existing data input pipeline is currently based on those submissions to the INSDC which fulfil certain threshold criteria but future plans are to move to using the EBI Metagenomics resource, MGnify 14 , as the main source of metagenome derived assemblies.
We will include only those MAGs that show a high level of completeness and a low level of contamination. Expert curation of the literature is critically important to the UniProt databases. Expert curation is labour intensive, with curators assimilating and evaluating multiple lines of evidence from the text and figures of relevant publications, but this has repeatedly proven to be the most efficient method of extracting all relevant data from a paper.
An example of this is PLC1 UniProtKB:Q , a member of the phosphoinositide phospholipase C family InterPro:IPR in which the existence of an asparagine residue in the active site instead of the conserved histidine residue suggests a non-catalytic role for this protein.
This task can be difficult, as our knowledge of protein function continues to evolve and finer grained experimental techniques provide new knowledge that may appear to contradict previous observations. The modification acts as a key regulator of mRNA stability: methylation is completed upon the release of mRNA into the nucleoplasm and affects various processes, such as mRNA stability, processing, translation efficiency and editing.
The enzymes that catalyse this process were believed to have been fully characterized some years ago, but more recent data has changed our understanding of how these molecules work.
Both proteins are members of the MT-A70 family and are classified as S-adenosyl-L-methionine-dependent methyltransferases by sequence prediction resources. Methyltransferase activity has been reported for both Subsequent structural studies have now shown that that only one protein, METTL3, constitutes the catalytic subunit 20— The other subunit, METTL14, has a degenerate active site that is unable to accommodate donor and acceptor substrates and plays a non-catalytic role in maintaining complex integrity and substrate RNA binding WTAP appears to serve as a regulatory subunit.
Future plans for the manual curation activities in UniProtKB include the development of mechanisms to identify and highlight contradictory information in existing protein entries in order to improve rigor and reproducibility. This example also illustrates the collaborative nature of the UniProt Consortium in that the molecular interactions involved have also been added to the IMEx Consortium www.
New terms were added to the GO to enable this and others were updated. InterPro is used to classify sequences at superfamily, family and subfamily levels and to predict the occurrence of functional domains and important sites. These prediction systems can annotate protein properties such as protein names, function, catalytic activity, pathway membership and subcellular location, along with sequence-specific information, such as the positions of post-translational modifications and active sites.
We continue to increase the number of Rules used for annotation and this has now grown to over in total as shown in Figure 4. ProteinExistence is the numerical value describing the evidence for the existence of the protein. SequenceVersion is the version number of the sequence.
ClusterName is the name of the UniRef cluster. See also: Related questions from our FAQ. You are using a version of browser that may not display all the features of this website. Please consider upgrading your browser. Basket 0. Your basket is currently empty. Please consider upgrading your browser. Your basket is currently empty.
UniParc The UniProt Archive UniParc is a comprehensive and non-redundant database that contains most of the publicly available protein sequences in the world. The UniProt Archive UniParc is a comprehensive and non-redundant database that contains most of the publicly available protein sequences in the world.
Proteins may exist in different source databases and in multiple copies in the same database. UniParc avoided such redundancy by storing each unique sequence only once and giving it a stable and unique identifier UPI making it possible to identify the same protein from different source databases. A UPI is never removed, changed or reassigned. UniParc contains only protein sequences. All other information about the protein must be retrieved from the source databases using the database cross-references.
UniParc tracks sequence changes in the source databases and archives the history of all changes.
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