Objective Epigenetic mechanisms, including DNA methylation (DNAm), have been proposed to play a key role in Crohn’s disease (CD) pathogenesis. However, the specific cell types and pathways affected as well as their potential impact on disease phenotype and outcome remain unknown. We set out to investigate the role of intestinal epithelial DNAm in CD pathogenesis. Design We generated 312 intestinal epithelial organoids (IEOs) from mucosal biopsies of 168 patients with CD (n=72), UC (n=23) and healthy controls (n=73). We performed genome-wide molecular profiling including DNAm, bulk as well as single-cell RNA sequencing. Organoids were subjected to gene editing and the functional consequences of DNAm changes evaluated using an organoid-lymphocyte coculture and a nucleotide-binding oligomerisation domain, leucine-rich repeat and CARD domain containing 5 (NLRC5) dextran sulphate sodium (DSS) colitis knock-out mouse model. Results We identified highly stable, CD-associated loss of DNAm at major histocompatibility complex (MHC) class 1 loci including NLRC5 and cognate gene upregulation. Single-cell RNA sequencing of primary mucosal tissue and IEOs confirmed the role of NLRC5 as transcriptional transactivator in the intestinal epithelium. Increased mucosal MHC-I and NLRC5 expression in adult and paediatric patients with CD was validated in additional cohorts and the functional role of MHC-I highlighted by demonstrating a relative protection from DSS-mediated mucosal inflammation in NLRC5-deficient mice. MHC-I DNAm in IEOs showed a significant correlation with CD disease phenotype and outcomes. Application of machine learning approaches enabled the development of a disease prognostic epigenetic molecular signature. Conclusions Our study has identified epigenetically regulated intestinal epithelial MHC-I as a novel mechanism in CD pathogenesis.

Ensembl (https://www.ensembl.org) is unique in its flexible infrastructure for access to genomic data and annotation. It has been designed to efficiently deliver annotation at scale for all eukaryotic life, and it also provides deep comprehensive annotation for key species. Genomes representing a greater diversity of species are increasingly being sequenced. In response, we have focussed our recent efforts on expediting the annotation of new assemblies. Here, we report the release of the greatest annual number of newly annotated genomes in the history of Ensembl via our dedicated Ensembl Rapid Release platform (http://rapid.ensembl.org). We have also developed a new method to generate comparative analyses at scale for these assemblies and, for the first time, we have annotated non-vertebrate eukaryotes. Meanwhile, we continually improve, extend and update the annotation for our high-value reference vertebrate genomes and report the details here. We have a range of specific software tools for specific tasks, such as the Ensembl Variant Effect Predictor (VEP) and the newly developed interface for the Variant Recoder. All Ensembl data, software and tools are freely available for download and are accessible programmatically.

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC.

The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser; the first virus to be encompassed within the Ensembl platform. This resource incorporates a new Ensembl gene set, multiple variant sets, and annotation from several relevant resources aligned to the reference SARS-CoV-2 assembly. Since the first release in May 2020, the content has been regularly updated using our new rapid release workflow, and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.

ABSTRACTBackground & AimsHuman intestinal epithelial organoids (IEO) are a powerful tool to model major aspects of intestinal development, health and diseases, as patient derived cultures retain many features found in-vivo. A necessary aspect of the organoid model is the requirement to expand cultures in-vitro through several rounds of passaging. This is of concern, as the passaging of cells has been shown to affect cell morphology, ploidy, and function. In this study, we address concerns around long term passaging of IEO to better characterise and define effects on cell morphology and function.MethodsHere we have analysed 173 human IEO from two sampling sites, terminal ileum and sigmoid colon and examined the effect of culture duration on DNA methylation (DNAm), gene expression and cellular function including their response to proinflammatory cytokines and in-vitro cell differentiation.ResultsOur analyses revealed a major effect of culture duration on DNAm, leading to significant changes at 61,337 loci representing approximately 8% of all CpGs tested. Although global cellular functions such as gut segment-specific gene expression remained stable, a subset of methylation changes correlated with altered gene expression at baseline as well as in response to inflammatory cytokine exposure and in-vitro differentiation. Importantly, epigenetic changes were found to be enriched in genomic regions associated with colonic cancer and distant to the site of replication indicating similarities to malignant transformation.ConclusionsOur study reveals culture-associated epigenetic, transcriptomic and functional changes in human mucosa derived IEO and highlights the importance of considering passage number as a potentially confounding factor.SynopsisThis work describes cell culture induced changes to DNA methylation, gene expression and cellular function in human IEO. Globally organoids lost DNA methylation with time in culture while DNA methylation also became generally more variable. This work suggests a shifted epigenetic profile in organoids cultured long-term.

Background: Many types of data from genomic analyses can be represented as genomic tracks, i.e. features linked to the genomic coordinates of a reference genome. Examples of such data are epigenetic DNA methylation data, ChIP-seq peaks, germline or somatic DNA variants, as well as RNA-seq expression levels. Researchers often face difficulties in locating, accessing and combining relevant tracks from external sources, as well as locating the raw data, reducing the value of the generated information. Description of work: We propose to advance the application of FAIR data principles (Findable, Accessible, Interoperable, and Reusable) to produce searchable metadata for genomic tracks. Findability and Accessibility of metadata can then be ensured by a track search service that integrates globally identifiable metadata from various track hubs in the Track Hub Registry and other relevant repositories. Interoperability and Reusability need to be ensured by the specification and implementation of a basic set of recommendations for metadata. We have tested this concept by developing such a specification in a JSON Schema, called FAIRtracks, and have integrated it into a novel track search service, called TrackFind. We demonstrate practical usage by importing datasets through TrackFind into existing examples of relevant analytical tools for genomic tracks: EPICO and the GSuite HyperBrowser. Conclusion: We here provide a first iteration of a draft standard for genomic track metadata, as well as the accompanying software ecosystem. It can easily be adapted or extended to future needs of the research community regarding data, methods and tools, balancing the requirements of both data submitters and analytical end-users.

The Ensembl project (https://www ensembl org) annotates genomes and disseminates genomic data for vertebrate species We create detailed and comprehensive annotation of gene structures, regulatory elements and variants, and enable comparative genomics by inferring the evolutionary history of genes and genomes Our integrated genomic data are made available in a variety of ways, including genome browsers, search interfaces, specialist tools such as the Ensembl Variant Effect Predictor, download files and programmatic interfaces Here, we present recent Ensembl developments including two new website portals Ensembl Rapid Release (http://rapid ensembl org) is designed to provide core tools and services for genomes as soon as possible and has been deployed to support large biodiversity sequencing projects Our SARS-CoV-2 genome browser (https://covid-19 ensembl org) integrates our own annotation with publicly available genomic data from numerous sources to facilitate the use of genomics in the international scientific response to the COVID-19 pandemic We also report on other updates to our annotation resources, tools and services All Ensembl data and software are freely available without restriction

The Sequence Ontology (SO) is a structured, controlled vocabulary that provides terms and definitions for genomic annotation. The Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC) initiative has gathered input from many groups of researchers, including the SO, the Gene Ontology (GO), and gene regulation experts, with the goal of curating information about how gene expression is regulated at the molecular level. Here we discuss recent updates to the SO reflecting current knowledge. We have developed more accurate human-readable terms (also known as classes), including new definitions, and relationships related to the expression of genes. New findings continue to give us insight into the biology of gene regulation, including the order of events, and participants in those events. These updates to the SO support logical reasoning with the current understanding of gene expression regulation at the molecular level.

Background: Many types of data from genomic analyses can be represented as genomic tracks, i.e. features linked to the genomic coordinates of a reference genome. Examples of such data are epigenetic DNA methylation data, ChIP-seq peaks, germline or somatic DNA variants, as well as RNA-seq expression levels. Researchers often face difficulties in locating, accessing and combining relevant tracks from external sources, as well as locating the raw data, reducing the value of the generated information. Description of work: We propose to advance the application of FAIR data principles (Findable, Accessible, Interoperable, and Reusable) to produce searchable metadata for genomic tracks. Findability and Accessibility of metadata can then be ensured by a track search service that integrates globally identifiable metadata from various track hubs in the Track Hub Registry and other relevant repositories. Interoperability and Reusability need to be ensured by the specification and implementation of a basic set of recommendations for metadata. We have tested this concept by developing such a specification in a JSON Schema, called FAIRtracks, and have integrated it into a novel track search service, called TrackFind. We demonstrate practical usage by importing datasets through TrackFind into existing examples of relevant analytical tools for genomic tracks: EPICO and the GSuite HyperBrowser. Conclusion: We here provide a first iteration of a draft standard for genomic track metadata, as well as the accompanying software ecosystem. It can easily be adapted or extended to future needs of the research community regarding data, methods and tools, balancing the requirements of both data submitters and analytical end-users.

Abstract 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. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue ( https://www.ebi.ac.uk/eqtl ), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

The Functional Annotation of ANimal Genomes (FAANG) project is a worldwide coordinated action creating high-quality functional annotation of farmed and companion animal genomes. The generation of a rich genome-to-phenome resource and supporting informatic infrastructure advances the scope of comparative genomics and furthers the understanding of functional elements. The project also provides terrestrial and aquatic animal agriculture community powerful resources for supporting improvements to farmed animal production, disease resistance, and genetic diversity. The FAANG Data Portal ( https://data.faang.org ) ensures Findable, Accessible, Interoperable and Reusable (FAIR) open access to the wealth of sample, sequencing, and analysis data produced by an ever-growing number of FAANG consortia. It is developed and maintained by the FAANG Data Coordination Centre (DCC) at the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI). FAANG projects produce a standardised set of multi-omic assays with resulting data placed into a range of specialised open data archives. To ensure this data is easily findable and accessible by the community, the portal automatically identifies and collates all submitted FAANG data into a single easily searchable resource. The Data Portal supports direct download from the multiple underlying archives to enable seamless access to all FAANG data from within the portal itself. The portal provides a range of predefined filters, powerful predictive search, and a catalogue of sampling and analysis protocols and automatically identifies publications associated with any dataset. To ensure all FAANG data submissions are high-quality, the portal includes powerful contextual metadata validation and data submissions brokering to the underlying EMBL-EBI archives. The portal will incorporate extensive new technical infrastructure to effectively deliver and standardise FAANG's shift to single-cellomics, cell atlases, pangenomes, and novel phenotypic prediction models. The Data Portal plays a key role for FAANG by supporting high-quality functional annotation of animal genomes, through open FAIR sharing of data, complete with standardised rich metadata. Future Data Portal features developed by the DCC will support new technological developments for continued improvement for FAANG projects.

The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidatecis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression(1). The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community. The authors summarize the history of the ENCODE Project, the achievements of ENCODE 1 and ENCODE 2, and how the new data generated and analysed in ENCODE 3 complement the previous phases.

The Ensembl (https://www.ensembl.org) is a system for generating and distributing genome annotation such as genes, variation, regulation and comparative genomics across the vertebrate subphylum and key model organisms. The Ensembl annotation pipeline is capable of integrating experimental and reference data from multiple providers into a single integrated resource. Here, we present 94 newly annotated and re-annotated genomes, bringing the total number of genomes offered by Ensembl to 227. This represents the single largest expansion of the resource since its inception. We also detail our continued efforts to improve human annotation, developments in our epigenome analysis and display, a new tool for imputing causal genes from genome-wide association studies and visualisation of variation within a 3D protein model. Finally, we present information on our new website. Both software and data are made available without restriction via our website, online tools platform and programmatic interfaces (available under an Apache 2.0 license) and data updates made available four times a year.

Our understanding of the human genome has continuously expanded since its draft publication in 2001. Over the years, novel assays have allowed us to progressively overlay layers of knowledge above the raw sequence of A’s, T’s, G’s, and C’s. The reference human genome sequence is now a complex knowledge base maintained under the shared stewardship of multiple specialist communities. Its complexity stems from the fact that it is simultaneously a template for transcription, a record of evolution, a vehicle for genetics, and a functional molecule. In short, the human genome serves as a frame of reference at the intersection of a diversity of scientific fields. In recent years, the progressive fall in sequencing costs has given increasing importance to the quality of the human reference genome, as hundreds of thousands of individuals are being sequenced yearly, often for clinical applications. Also, novel sequencing-based assays shed light on novel functions of the genome, especially with respect to gene expression regulation. Keeping the human genome annotation up to date and accurate is therefore an ongoing partnership between reference annotation projects and the greater community worldwide.

Background Many types of data from genomic analyses can be represented as genomic tracks, i.e. features linked to the genomic coordinates of a reference genome. Examples of such data are epigenetic DNA methylation data, ChIP-seq peaks, germline or somatic DNA variants, or RNA-seq expression levels. Researchers often face difficulties in locating, accessing and combining relevant tracks from external sources, as well as locating the raw data, reducing the value of the generated information. FAIRtracks software ecosystem We have, as an output of the ELIXIR Implementation Study "FAIRification of Genomic Tracks", developed a basic set of recommendations for genomic track metadata together with an implementation called FAIRtracks in the form of a JSON Schema. We propose FAIRtracks as a draft standard for genomic track metadata in order to advance the application of FAIR data principles (Findable, Accessible, Interoperable, and Reusable). We have demonstrated practical usage of this approach by designing a software ecosystem around the FAIRtracks draft standard, integrating globally identifiable metadata from various track hubs in the Track Hub Registry and other relevant repositories into a novel track search service, called TrackFind. The software ecosystem also includes the FAIRtracks augmentation service, which assists metadata producers by automatically augmenting minimal machine-readable metadata with their human-readable counterparts, as well as the FAIRtracks validation service, which extends basic JSON Schema validation to include FAIR-related features (global identifiers, ontology terms, and object references). Finally, we have implemented track metadata search and import functionality into relevant analytical tools: EPICO and the GSuite HyperBrowser. For an overview of the FAIRtracks software ecosystem, please visit: http://fairtracks.github.io/ Example FAIRtracks JSON document - augmented The "Example FAIRtracks JSON document - augmented" is generated as part of the build process of the FAIRtracks draft standard JSON Schema (source code: https://github.com/fairtracks/fairtracks_standard/). The example FAIRtracks document contains a small selection of tracks and objects from the ENCODE project metadata (https://www.encodeproject.org/), adapted to align with the FAIRtracks draft standard. In addition to being available in the above-mentioned GitHub repository, the "Example FAIRtracks JSON document - augmented" is also published here on Zenodo in order for the document to be globally uniquely identifiable by a Digital Object Identifier (DOI).

Abstract Background & Aims Gene expression patterns of CD8+ T cells have been reported to correlate with clinical outcomes of adults with inflammatory bowel diseases (IBD). We aimed at validating these findings in independent patient cohorts. Methods We obtained peripheral blood samples from 112 children with a new diagnosis of IBD (71 with Crohn’s disease and 41 with ulcerative colitis) and 19 children without IBD (controls) and recorded medical information on disease activity and outcomes. CD8+ T cells were isolated from blood samples by magnetic bead sorting at the point of diagnosis and during the course of disease. Genome-wide transcription (n=192) and DNA methylation (n=66) profiles were generated using Affymetrix and Illumina arrays, respectively. Publicly available transcriptomes and DNA methylomes of CD8+ T cells from three adult patient cohorts with and without IBD were included in data analyses. Results Previously reported CD8+ T cell prognostic expression and exhaustion signatures were only found in the original adult IBD patient cohort. These signatures could not be detected either in a pediatric, or in a second adult IBD cohort. In contrast, an association between CD8+ T cell gene expression with age and sex was detected across all three cohorts. CD8+ gene transcription was clearly associated with IBD in the two cohorts that included non-IBD controls. Lastly, DNA methylation profiles of CD8+ T cells from children with Crohn’s disease correlated with age but not with disease outcome. Conclusions We were unable to validate previously reported findings of an association between CD8+ T cell gene transcription and disease outcome in IBD. Our findings reveal the challenges of developing prognostic biomarkers for patients with IBD and the importance of their validation in large, independent cohorts before clinical application.

MOTIVATION:Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data.RESULTS:We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource.AVAILABILITY AND IMPLEMENTATION:The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io.

Motivation: Compared to traditional haploid reference genomes, graph genomes are an efficient and compact data structure for storing multiple genomic sequences, for storing polymorphisms or for mapping sequencing reads with greater sensitivity. Further, graphs are well-studied computer science objects that can be efficiently analyzed. However, their adoption in genomic research is slow, in part because of the cognitive difficulty in interpreting graphs. Results: We present an intuitive graphical representation for graph genomes that re-uses well-honed techniques developed to display public transport networks, and demonstrate it as a web tool.