Tracking and coordinating an international curation effort for the CCDS Project

The Consensus Coding Sequence (CCDS) collaboration involves curators at multiple centers with a goal of producing a conservative set of high quality, protein-coding region annotations for the human and mouse reference genome assemblies. The CCDS data set reflects a ‘gold standard’ definition of best supported protein annotations, and corresponding genes, which pass a standard series of quality assurance checks and are supported by manual curation. This data set supports use of genome annotation information by human and mouse researchers for effective experimental design, analysis and interpretation. The CCDS project consists of analysis of automated whole-genome annotation builds to identify identical CDS annotations, quality assurance testing and manual curation support. Identical CDS annotations are tracked with a CCDS identifier (ID) and any future change to the annotated CDS structure must be agreed upon by the collaborating members. CCDS curation guidelines were developed to address some aspects of curation in order to improve initial annotation consistency and to reduce time spent in discussing proposed annotation updates. Here, we present the current status of the CCDS database and details on our procedures to track and coordinate our efforts. We also present the relevant background and reasoning behind the curation standards that we have developed for CCDS database treatment of transcripts that are nonsense-mediated decay (NMD) candidates, for transcripts containing upstream open reading frames, for identifying the most likely translation start codons and for the annotation of readthrough transcripts. Examples are provided to illustrate the application of these guidelines

Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation.

The Consensus Coding Sequence (CCDS) project provides a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assembly in genome annotations produced independently by NCBI and the Ensembl group at EMBL-EBI. This dataset is the product of an international collaboration that includes NCBI, Ensembl, HUGO Gene Nomenclature Committee, Mouse Genome Informatics and University of California, Santa Cruz. Identically annotated coding regions, which are generated using an automated pipeline and pass multiple quality assurance checks, are assigned a stable and tracked identifier (CCDS ID). Additionally, coordinated manual review by expert curators from the CCDS collaboration helps in maintaining the integrity and high quality of the dataset. The CCDS data are available through an interactive web page (https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi) and an FTP site (ftp://ftp.ncbi.nlm.nih.gov/pub/CCDS/). In this paper, we outline the ongoing work, growth and stability of the CCDS dataset and provide updates on new collaboration members and new features added to the CCDS user interface. We also present expert curation scenarios, with specific examples highlighting the importance of an accurate reference genome assembly and the crucial role played by input from the research community. Nucleic Acids Res 2018 Jan 4; 46(D1):D221-D228

Recent advances in biocuration: Meeting report from the Fifth International Biocuration Conference

The 5th International Biocuration Conference brought together over 300 scientists to exchange on their work, as well as discuss issues relevant to the International Society for Biocuration’s (ISB) mission. Recurring themes this year included the creation and promotion of gold standards, the need for more ontologies, and more formal interactions with journals. The conference is an essential part of the ISB\u27s goal to support exchanges among members of the biocuration community. Next year\u27s conference will be held in Cambridge, UK, from 7 to 10 April 2013. In the meanwhile, the ISB website provides information about the society\u27s activities (http://biocurator.org), as well as related events of interest

Beyond sequencing: Re-visiting annotations for PJL as a test case

Objectives: Current developments in sequencing techniques have enabled rapid and high-throughput generation of sequence data. however, there is a growing gap between the generation of raw sequencing data and the extraction of meaningful biological information. variant annotation is a crucial step in the analysis of genome sequencing data. incorrect or incomplete annotations can cause researchers to dilute interesting variants in a pool of false positives. we require consistent, accurate and reliable annotation of variants for making diagnostic and treatment decisions. current annotation depends on the set of transcripts, and software used can be managed, with sufficient care, in the research context. careful thought needs to be given to the choice of transcript sets and software packages for variant annotation in sequencing studies. in this project, the main objective is to analyze the genetic variants observed in pakistani population data within the 1000 genomes project (1kgp).Results: We characterized only snvs and indels types of genetic variations, in total ~ 1.4 million variants. besides this, we also annotated the genetic variants with multiple annotations tools, annovar and snpeff and compared the differential results. our population-specific catalogue will enhance future studies on the functional impact at protein level

Identification of genomic features in the classification of loss- and gain-of-function mutation

BACKGROUND: Alterations of a genome can lead to changes in protein functions. Through these genetic mutations, a protein can lose its native function (loss-of-function, LoF), or it can confer a new function (gain-of-function, GoF). However, when a mutation occurs, it is difficult to determine whether it will result in a LoF or a GoF. Therefore, in this paper, we propose a study that analyzes the genomic features of LoF and GoF instances to find features that can be used to classify LoF and GoF mutations. METHODS: In order to collect experimentally verified LoF and GoF mutational information, we obtained 816 LoF mutations and 474 GoF mutations from a literature text-mining process. Next, with data-preprocessing steps, 258 LoF and 129 GoF mutations remained for a further analysis. We analyzed the properties of these LoF and GoF mutations. Among the properties, we selected features which show different tendencies between the two groups and implemented classifications using support vector machine, random forest, and linear logistic regression methods to confirm whether or not these features can identify LoF and GoF mutations. RESULTS: We analyzed the properties of the LoF and GoF mutations and identified six features which have discriminative power between LoF and GoF conditions: the reference allele, the substituted allele, mutation type, mutation impact, subcellular location, and protein domain. When using the six selected features with the random forest, support vector machine, and linear logistic regression classifiers, the result showed accuracy levels of 72.23%, 71.28%, and 70.19%, respectively. CONCLUSIONS: We analyzed LoF and GoF mutations and selected several properties which were different between the two classes. By implementing classifications with the selected features, it is demonstrated that the selected features have good discriminative power.ope

APPRIS: selecting functionally important isoforms.

APPRIS (https://appris.bioinfo.cnio.es) is a well-established database housing annotations for protein isoforms for a range of species. APPRIS selects principal isoforms based on protein structure and function features and on cross-species conservation. Most coding genes produce a single main protein isoform and the principal isoforms chosen by the APPRIS database best represent this main cellular isoform. Human genetic data, experimental protein evidence and the distribution of clinical variants all support the relevance of APPRIS principal isoforms. APPRIS annotations and principal isoforms have now been expanded to 10 model organisms. In this paper we highlight the most recent updates to the database. APPRIS annotations have been generated for two new species, cow and chicken, the protein structural information has been augmented with reliable models from the EMBL-EBI AlphaFold database, and we have substantially expanded the confirmatory proteomics evidence available for the human genome. The most significant change in APPRIS has been the implementation of TRIFID functional isoform scores. TRIFID functional scores are assigned to all splice isoforms, and APPRIS uses the TRIFID functional scores and proteomics evidence to determine principal isoforms when core methods cannot.National Human Genome Research Institute of the National Institutes of Health [2 U41 HG007234]; Spanish Ministry of Science, Innovation and Universities [PGC2018-097019-B-I00]; Carlos III Institute of Health-Fondo de Investigacion Sanitaria [PRB3 ´ (IPT17/0019––ISCIII-SGEFI/ERDF, ProteoRed]; ‘la Caixa’ Banking Foundation [HR17-00247]. Funding for open access charge: National Human Genome Research Institute.S

Annow: BLAST Based Analytical Sequence Annotation Software

As gene sequencing becomes more common the annotations that give meaning to biological data change. The large quantity of –omics data generated by these projects maintain static linkages to annotations that change as experimental evidence accumulates. The validity of data across several biological disciplines relies on the accuracy of these static linkages. This raises an informatics challenge as data sets large and small require diligent curation costing valuable resources. Annow was developed to be agile software to meet this challenge; updating data sets, while providing relevant alignment data, analysis metrics, and resource updating. Incredibly user friendly and operating offline Annow brings large data analysis capabilities to the personal computer and can update thousands of annotations in addition to more granular analysis in short time frames that are not possible with web-based solutions. The result of which is more a cost effective manner to produce reliable, accurate results applicable to any field utilizing biological data and annotations derived from gene sequencing

Identification, organisation and visualisation of complete proteomes in UniProt throughout all taxonomic ranks :|barchaea, bacteria, eukatyote and virus

Users of uniprot.org want to be able to query, retrieve and download proteome sets for an organism of their choice. They expect the data to be easily accessed, complete and up to date based on current available knowledge. UniProt release 2012_01 (25th Jan 2012) contains the proteomes of 2,923 organisms; 50% of which are bacteria, 38% viruses, 8% eukaryota and 4% archaea. Note that the term 'organism' is used in a broad sense to include subspecies, strains and isolates. Each completely sequenced organism is processed as an independent organism, hence the availability of 38 strain-specific proteomes Escherichia coli that are accessible for download. There is a project within UniProt dedicated to the mammoth task of maintaining the “Proteomes database”. This active resource is essential for UniProt to continually provide high quality proteome sets to the users. Accurate identification and incorporation of new, publically available, proteomes as well as the maintenance of existing proteomes permits sustained growth of the proteomes project. This is a huge, complicated and vital task accomplished by the activities of both curators and programmers. This thesis explains the data input and output of the proteomes database: the flow of genome project data from the nucleotide database into the proteomes database, then from each genome how a proteome is identified, augmented and made visible to uniprot.org users. Along this journey of discovery many issues arose, puzzles concerning data gathering, data integrity and also data visualisation. All were resolved and the outcome is a well-documented, actively maintained database that strives to provide optimal proteome information to its users