GENCODE 2025: reference gene annotation for human and mouse.

GENCODE produces comprehensive reference gene annotation for human and mouse. Entering its twentieth year, the project remains highly active as new technologies and methodologies allow us to catalog the genome at ever-increasing granularity. In particular, long-read transcriptome sequencing enables us to identify large numbers of missing transcripts and to substantially improve existing models, and our long non-coding RNA catalogs have undergone a dramatic expansion and reconfiguration as a result.

GENCODE: reference annotation for the human and mouse genomes in 2023.

GENCODE produces high quality gene and transcript annotation for the human and mouse genomes. All GENCODE annotation is supported by experimental data and serves as a reference for genome biology and clinical genomics. The GENCODE consortium generates targeted experimental data, develops bioinformatic tools and carries out analyses that, along with externally produced data and methods, support the identification and annotation of transcript structures and the determination of their function.

GENCODE 2021.

The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics. GENCODE annotation processes make use of primary data and bioinformatic tools and analysis generated both within the consortium and externally to support the creation of transcript structures and the determination of their function. Here, we present improvements to our annotation infrastructure, bioinformatics tools, and analysis, and the advances they support in the annotation of the human and mouse genomes including: the completion of first pass manual annotation for the mouse reference genome; targeted improvements to the annotation of genes associated with SARS-CoV-2 infection; collaborative projects to achieve convergence across reference annotation databases for the annotation of human and mouse protein-coding genes; and the first GENCODE manually supervised automated annotation of lncRNAs.

Mining Social Media Data to Study the Consequences of Dementia Diagnosis on Caregivers and Relatives.

Introduction: Caregivers for people with dementia face a number of challenges such as changing family relationships, social isolation, or financial difficulties. Internet usage and social media are increasingly being recognised as resources to increase support and general public health.

Objective: Using automated analysis, the aim of this study was to explore (i) the age and sex of people who post to the social media forum Reddit about dementia diagnoses, (ii) the affected person and their diagnosis, (iii) which subreddits authors are posting to, (iv) the types of messages posted, and (v) the content of these posts.

GENCODE reference annotation for the human and mouse genomes.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation.

Automated PDF highlighting to support faster curation of literature for Parkinson's and Alzheimer's disease.

Unlabelled: Neurodegenerative disorders such as Parkinson's and Alzheimer's disease are devastating and costly illnesses, a source of major global burden. In order to provide successful interventions for patients and reduce costs, both causes and pathological processes need to be understood. The ApiNATOMY project aims to contribute to our understanding of neurodegenerative disorders by manually curating and abstracting data from the vast body of literature amassed on these illnesses.

Characterisation of mental health conditions in social media using Informed Deep Learning.

The number of people affected by mental illness is on the increase and with it the burden on health and social care use, as well as the loss of both productivity and quality-adjusted life-years. Natural language processing of electronic health records is increasingly used to study mental health conditions and risk behaviours on a large scale. However, narrative notes written by clinicians do not capture first-hand the patients' own experiences, and only record cross-sectional, professional impressions at the point of care.

Analysis of diagnoses extracted from electronic health records in a large mental health case register.

The UK government has recently recognised the need to improve mental health services in the country. Electronic health records provide a rich source of patient data which could help policymakers to better understand needs of the service users. The main objective of this study is to unveil statistics of diagnoses recorded in the Case Register of the South London and Maudsley NHS Foundation Trust, one of the largest mental health providers in the UK and Europe serving a source population of over 1.

Comparative analysis of the transcriptome across distant species.

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly.

Characterizing genetic variants for clinical action.

Genome-wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data.

Ensembl 2014.

Ensembl (http://www.ensembl.org) creates tools and data resources to facilitate genomic analysis in chordate species with an emphasis on human, major vertebrate model organisms and farm animals.

The zebrafish reference genome sequence and its relationship to the human genome.

Zebrafish have become a popular organism for the study of vertebrate gene function. The virtually transparent embryos of this species, and the ability to accelerate genetic studies by gene knockdown or overexpression, have led to the widespread use of zebrafish in the detailed investigation of vertebrate gene function and increasingly, the study of human genetic disease. However, for effective modelling of human genetic disease it is important to understand the extent to which zebrafish genes and gene structures are related to orthologous human genes.

Ensembl 2013.

The Ensembl project (http://www.ensembl.org) provides genome information for sequenced chordate genomes with a particular focus on human, mouse, zebrafish and rat.

Ensembl 2012.

The Ensembl project (http://www.ensembl.org) provides genome resources for chordate genomes with a particular focus on human genome data as well as data for key model organisms such as mouse, rat and zebrafish.

Dalliance: interactive genome viewing on the web.

Summary: Dalliance is a new genome viewer which offers a high level of interactivity while running within a web browser. All data is fetched using the established distributed annotation system (DAS) protocol, making it easy to customize the browser and add extra data.

Availability And Implementation: Dalliance runs entirely within your web browser, and relies on existing DAS server infrastructure.

Ensembl 2011.

The Ensembl project (http://www.ensembl.org) seeks to enable genomic science by providing high quality, integrated annotation on chordate and selected eukaryotic genomes within a consistent and accessible infrastructure.

iMotifs: an integrated sequence motif visualization and analysis environment.

Motivation: Short sequence motifs are an important class of models in molecular biology, used most commonly for describing transcription factor binding site specificity patterns. High-throughput methods have been recently developed for detecting regulatory factor binding sites in vivo and in vitro and consequently high-quality binding site motif data are becoming available for increasing number of organisms and regulatory factors. Development of intuitive tools for the study of sequence motifs is therefore important.

Ensembl's 10th year.

Ensembl (http://www.ensembl.org) integrates genomic information for a comprehensive set of chordate genomes with a particular focus on resources for human, mouse, rat, zebrafish and other high-value sequenced genomes.

The Protein Feature Ontology: a tool for the unification of protein feature annotations.

Motivation: The advent of sequencing and structural genomics projects has provided a dramatic boost in the number of uncharacterized protein structures and sequences. Consequently, many computational tools have been developed to help elucidate protein function. However, such services are spread throughout the world, often with standalone web pages.

Integrating biological data--the Distributed Annotation System.

Background: The Distributed Annotation System (DAS) is a widely adopted protocol for dynamically integrating a wide range of biological data from geographically diverse sources. DAS continues to expand its applicability and evolve in response to new challenges facing integrative bioinformatics.

Results: Here we describe the various infrastructure components of DAS and present a new extended version of the DAS specification.

A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis.

DNA methylation is an indispensible epigenetic modification required for regulating the expression of mammalian genomes. Immunoprecipitation-based methods for DNA methylome analysis are rapidly shifting the bottleneck in this field from data generation to data analysis, necessitating the development of better analytical tools. In particular, an inability to estimate absolute methylation levels remains a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling.

An integrated resource for genome-wide identification and analysis of human tissue-specific differentially methylated regions (tDMRs).

We report a novel resource (methylation profiles of DNA, or mPod) for human genome-wide tissue-specific DNA methylation profiles. mPod consists of three fully integrated parts, genome-wide DNA methylation reference profiles of 13 normal somatic tissues, placenta, sperm, and an immortalized cell line, a visualization tool that has been integrated with the Ensembl genome browser and a new algorithm for the analysis of immunoprecipitation-based DNA methylation profiles. We demonstrate the utility of our resource by identifying the first comprehensive genome-wide set of tissue-specific differentially methylated regions (tDMRs) that may play a role in cellular identity and the regulation of tissue-specific genome function.

Data growth and its impact on the SCOP database: new developments.

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. The SCOP hierarchy comprises the following levels: Species, Protein, Family, Superfamily, Fold and Class. While keeping the original classification scheme intact, we have changed the production of SCOP in order to cope with a rapid growth of new structural data and to facilitate the discovery of new protein relationships.

Integrating sequence and structural biology with DAS.

Background: The Distributed Annotation System (DAS) is a network protocol for exchanging biological data. It is frequently used to share annotations of genomes and protein sequence.

Results: Here we present several extensions to the current DAS 1.