Ascidians belong to the tunicates, the sister group of vertebrates and are recognized model organisms in the field of embryonic development, regeneration and stem cells. ANISEED is the main information system in the field of ascidian developmental biology. This article reports the development of the system since its initial publication in 2010. Over the past five years, we refactored the system from an initial custom schema to an extended version of the Chado schema and redesigned all user and back end interfaces. This new architecture was used to improve and enrich the description of Ciona intestinalis embryonic development, based on an improved genome assembly and gene model set, refined functional gene annotation, and anatomical ontologies, and a new collection of full ORF cDNAs. The genomes of nine ascidian species have been sequenced since the release of the C. intestinalis genome. In ANISEED 2015, all nine new ascidian species can be explored via dedicated genome browsers, and searched by Blast. In addition, ANISEED provides full functional gene annotation, anatomical ontologies and some gene expression data for the six species with highest quality genomes. ANISEED is publicly available at: http://www.aniseed.cnrs.fr.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is an expertly curated database of literature-derived functional information for the model organism budding yeast, Saccharomyces cerevisiae. SGD constantly strives to synergize new types of experimental data and bioinformatics predictions with existing data, and to organize them into a comprehensive and up-to-date information resource. The primary mission of SGD is to facilitate research into the biology of yeast and to provide this wealth of information to advance, in many ways, research on other organisms, even those as evolutionarily distant as humans. To build such a bridge between biological kingdoms, SGD is curating data regarding yeast-human complementation, in which a human gene can successfully replace the function of a yeast gene, and/or vice versa. These data are manually curated from published literature, made available for download, and incorporated into a variety of analysis tools provided by SGD.

WormBase (http://www.wormbase.org/) is a highly curated resource dedicated to supporting research using the model organism Caenorhabditis elegans. With an electronic history predating the World Wide Web, WormBase contains information ranging from the sequence and phenotype of individual alleles to genome-wide studies generated using next-generation sequencing technologies. In recent years, we have expanded the contents to include data on additional nematodes of agricultural and medical significance, bringing the knowledge of C. elegans to bear on these systems and providing support for underserved research communities. Manual curation of the primary literature remains a central focus of the WormBase project, providing users with reliable, up-to-date and highly cross-linked information. In this update, we describe efforts to organize the original atomized and highly contextualized curated data into integrated syntheses of discrete biological topics. Next, we discuss our experiences coping with the vast increase in available genome sequences made possible through next-generation sequencing platforms. Finally, we describe some of the features and tools of the new WormBase Web site that help users better find and explore data of interest.

Xenbase (www.xenbase.org) is a model organism database integrating a diverse array of biological and genomic data on the frogs, Xenopus laevis and Xenopus (Silurana) tropicalis. Data is collected from other databases, high-throughput screens and the scientific literature and integrated into a number of database modules covering subjects such as community, literature, gene and genomic analysis. Gene pages are automatically assembled from data piped from the Entrez Gene, Gurdon Institute, JGI, Metazome, MGI, OMIM, PubMed, Unigene, Zfin, commercial suppliers and others. These data are then supplemented with in-house annotation. Xenbase has implemented the Gbrowse genome browser and also provides a BLAST service that allows users to specifically search either laevis or tropicalis DNA or protein targets. A table of Xenopus gene synonyms has been implemented and allows the genome, genes, publications and high-throughput gene expression data to be seamlessly integrated with other Xenopus data and to external database resources, making the wealth of developmental and functional data from the frog available to the broader research community.

The Nucleic Acids Research Molecular Biology Database Collection is a public online resource that lists the databases described in this and previous issues of Nucleic Acids Research together with other databases of value to the biologist and available throughout the world. All databases included in this Collection are freely available to the public. The 2005 update includes 719 databases, 171 more than the 2004 one. The databases are organized in a hierarchical classification that simplifies the process of finding the right database for any given task. The growing number of databases related to immunology, plant and organelle research have been accommodated by separating them into three new categories. The database summaries provide brief descriptions of the databases, contact details, appropriate references and acknowledgements. The online summaries also serve as a venue for the maintainers of each database to introduce database updates and other improvements in the scope and tools. These updates are particularly important for those databases that have not been described in print in the recent past. The database list and summaries are available online at the Nucleic Acids Research web site, http://nar.oupjournals.org/.

X-inactive-specific transcript (Xist) is a long noncoding RNA (lncRNA) essential for inactivating one of the two X chromosomes in mammalian females. Random X chromosome inactivation is mediated by Xist RNA expressed from the inactive X chromosome. We found that Xist RNA is unspliced in naïve embryonic stem (ES) cells. Upon differentiation, Xist splicing becomes efficient across all exons independent of transcription, suggesting interdependent or coordinated removal of Xist introns. In female cells with mutated polypyrimidine tract binding protein 1 (Ptbp1), differentiation fails to substantially upregulate mature Xist RNA because of a defect in Xist splicing. We further found both Xist129 and XistCAS RNA are unspliced in Mus musculus 129SvJ/Mus castaneous (CAS) hybrid female ES cells. Upon differentiation, Xist129 exhibits a higher splicing efficiency than XistCAS, likely contributing to preferential inhibition of the X129 chromosome. Single cell analysis shows that the allelic choice of Xist splicing is linked to the inactive X chromosome. We conclude post-transcriptional control of Xist RNA splicing is an essential regulatory step of Xist induction. Our studies shed light on the developmental roles of splicing for nuclear-retained Xist lncRNA and suggest inefficient Xist splicing is an additional fail-safe mechanism to prevent Xist activity in ES cells.

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.

miRNet is an easy-to-use, web-based platform designed to help elucidate microRNA (miRNA) functions by integrating users' data with existing knowledge via network-based visual analytics. Since its first release in 2016, miRNet has been accessed by >20 000 researchers worldwide, with ∼100 users on a daily basis. While version 1.0 was focused primarily on miRNA-target gene interactions, it has become clear that in order to obtain a global view of miRNA functions, it is necessary to bring other important players into the context during analysis. Driven by this concept, in miRNet version 2.0, we have (i) added support for transcription factors (TFs) and single nucleotide polymorphisms (SNPs) that affect miRNAs, miRNA-binding sites or target genes, whilst also greatly increased (>5-fold) the underlying knowledgebases of miRNAs, ncRNAs and disease associations; (ii) implemented new functions to allow creation and visual exploration of multipartite networks, with enhanced support for in situ functional analysis and (iii) revamped the web interface, optimized the workflow, and introduced microservices and web application programming interface (API) to sustain high-performance, real-time data analysis. The underlying R package is also released in tandem with version 2.0 to allow more flexible data analysis for R programmers. The miRNet 2.0 website is freely available at https://www.mirnet.ca.

The 20th annual Database Issue of Nucleic Acids Research includes 176 articles, half of which describe new online molecular biology databases and the other half provide updates on the databases previously featured in NAR and other journals. This year's highlights include two databases of DNA repeat elements; several databases of transcriptional factors and transcriptional factor-binding sites; databases on various aspects of protein structure and protein-protein interactions; databases for metagenomic and rRNA sequence analysis; and four databases specifically dedicated to Escherichia coli. The increased emphasis on using the genome data to improve human health is reflected in the development of the databases of genomic structural variation (NCBI's dbVar and EBI's DGVa), the NIH Genetic Testing Registry and several other databases centered on the genetic basis of human disease, potential drugs, their targets and the mechanisms of protein-ligand binding. Two new databases present genomic and RNAseq data for monkeys, providing wealth of data on our closest relatives for comparative genomics purposes. The NAR online Molecular Biology Database Collection, available at http://www.oxfordjournals.org/nar/database/a/, has been updated and currently lists 1512 online databases. The full content of the Database Issue is freely available online on the Nucleic Acids Research website (http://nar.oxfordjournals.org/).

To ensure error-free duplication of all (epi)genetic information once per cell cycle, DNA replication follows a cell type and developmental stage specific spatio-temporal program. Here, we analyze the spatio-temporal DNA replication progression in (un)differentiated mouse embryonic stem (mES) cells. Whereas telomeres replicate throughout S-phase, we observe mid S-phase replication of (peri)centromeric heterochromatin in mES cells, which switches to late S-phase replication upon differentiation. This replication timing reversal correlates with and depends on an increase in condensation and a decrease in acetylation of chromatin. We further find synchronous duplication of the Y chromosome, marking the end of S-phase, irrespectively of the pluripotency state. Using a combination of single-molecule and super-resolution microscopy, we measure molecular properties of the mES cell replicon, the number of replication foci active in parallel and their spatial clustering. We conclude that each replication nanofocus in mES cells corresponds to an individual replicon, with up to one quarter representing unidirectional forks. Furthermore, with molecular combing and genome-wide origin mapping analyses, we find that mES cells activate twice as many origins spaced at half the distance than somatic cells. Altogether, our results highlight fundamental developmental differences on progression of genome replication and origin activation in pluripotent cells.

The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.

During its life cycle, Trypanosoma brucei shuttles between a mammalian host and the tsetse fly vector. In the mammalian host, immune evasion of T. brucei bloodstream form (BSF) cells relies on antigenic variation, which includes monoallelic expression and periodic switching of variant surface glycoprotein (VSG) genes. The active VSG is transcribed from only 1 of the 15 subtelomeric expression sites (ESs). During differentiation from BSF to the insect-resident procyclic form (PCF), the active ES is transcriptionally silenced. We used mass spectrometry-based interactomics to determine the composition of telomere protein complexes in T. brucei BSF and PCF stages to learn more about the structure and functions of telomeres in trypanosomes. Our data suggest a different telomere complex composition in the two forms of the parasite. One of the novel telomere-associated proteins, TelAP1, forms a complex with telomeric proteins TbTRF, TbRAP1 and TbTIF2 and influences ES silencing kinetics during developmental differentiation.

We report the development of OikoBase (http://oikoarrays.biology.uiowa.edu/Oiko/), a tiling array-based genome browser resource for Oikopleura dioica, a metazoan belonging to the urochordates, the closest extant group to vertebrates. OikoBase facilitates retrieval and mining of a variety of useful genomics information. First, it includes a genome browser which interrogates 1260 genomic sequence scaffolds and features gene, transcript and CDS annotation tracks. Second, we annotated gene models with gene ontology (GO) terms and InterPro domains which are directly accessible in the browser with links to their entries in the GO (http://www.geneontology.org/) and InterPro (http://www.ebi.ac.uk/interpro/) databases, and we provide transcript and peptide links for sequence downloads. Third, we introduce the transcriptomics of a comprehensive set of developmental stages of O. dioica at high resolution and provide downloadable gene expression data for all developmental stages. Fourth, we incorporate a BLAST tool to identify homologs of genes and proteins. Finally, we include a tutorial that describes how to use OikoBase as well as a link to detailed methods, explaining the data generation and analysis pipeline. OikoBase will provide a valuable resource for research in chordate development, genome evolution and plasticity and the molecular ecology of this important marine planktonic organism.

Tet enzymes (Tet1/2/3) oxidize 5-methylcytosine to promote DNA demethylation and partner with chromatin modifiers to regulate gene expression. Tet1 is highly expressed in embryonic stem cells (ESCs), but its enzymatic and non-enzymatic roles in gene regulation are not dissected. We have generated Tet1 catalytically inactive (Tet1m/m) and knockout (Tet1-/-) ESCs and mice to study these functions. Loss of Tet1, but not loss of its catalytic activity, caused aberrant upregulation of bivalent (H3K4me3+; H3K27me3+) developmental genes, leading to defects in differentiation. Wild-type and catalytic-mutant Tet1 occupied similar genomic loci which overlapped with H3K27 tri-methyltransferase PRC2 and the deacetylase complex Sin3a at promoters of bivalent genes and with the helicase Chd4 at active genes. Loss of Tet1, but not loss of its catalytic activity, impaired enrichment of PRC2 and Sin3a at bivalent promoters leading to reduced H3K27 trimethylation and deacetylation, respectively, in absence of any changes in DNA methylation. Tet1-/-, but not Tet1m/m, embryos expressed higher levels of Gata6 and were developmentally delayed. Thus, the critical functions of Tet1 in ESCs and early development are mediated through its non-catalytic roles in regulating H3K27 modifications to silence developmental genes, and are more important than its catalytic functions in DNA demethylation.

Enhancers are distal cis-regulatory elements that modulate gene expression. They are depleted of nucleosomes and enriched in specific histone modifications; thus, calling DNase-seq and histone mark ChIP-seq peaks can predict enhancers. We evaluated nine peak-calling algorithms for predicting enhancers validated by transgenic mouse assays. DNase and H3K27ac peaks were consistently more predictive than H3K4me1/2/3 and H3K9ac peaks. DFilter and Hotspot2 were the best DNase peak callers, while HOMER, MUSIC, MACS2, DFilter and F-seq were the best H3K27ac peak callers. We observed that the differential DNase or H3K27ac signals between two distant tissues increased the area under the precision-recall curve (PR-AUC) of DNase peaks by 17.5-166.7% and that of H3K27ac peaks by 7.1-22.2%. We further improved this differential signal method using multiple contrast tissues. Evaluated using a blind test, the differential H3K27ac signal method substantially improved PR-AUC from 0.48 to 0.75 for predicting heart enhancers. We further validated our approach using postnatal retina and cerebral cortex enhancers identified by massively parallel reporter assays, and observed improvements for both tissues. In summary, we compared nine peak callers and devised a superior method for predicting tissue-specific mouse developmental enhancers by reranking the called peaks.

Hydroxamate-based lysine deacetylase inhibitors (KDACis) are approved for clinical use against certain cancers. However, intrinsic and acquired resistance presents a major problem. Treatment of cells with hydroxamates such as trichostatin A (TSA) leads to rapid preferential acetylation of histone H3 already trimethylated on lysine 4 (H3K4me3), although the importance of this H3K4me3-directed acetylation in the biological consequences of KDACi treatment is not known. We address this utilizing Dictyostelium discoideum strains lacking H3K4me3 due to disruption of the gene encoding the Set1 methyltransferase or mutations in endogenous H3 genes. Loss of H3K4me3 confers resistance to TSA-induced developmental inhibition and delays accumulation of H3K9Ac and H3K14Ac. H3K4me3-directed H3Ac is mediated by Sgf29, a subunit of the SAGA acetyltransferase complex that interacts with H3K4me3 via a tandem tudor domain (TTD). We identify an Sgf29 orthologue in Dictyostelium with a TTD that specifically recognizes the H3K4me3 modification. Disruption of the gene encoding Sgf29 delays accumulation of H3K9Ac and abrogates H3K4me3-directed H3Ac. Either loss or overexpression of Sgf29 confers developmental resistance to TSA. Our results demonstrate that rapid acetylation of H3K4me3 histones regulates developmental sensitivity to TSA. Levels of H3K4me3 or Sgf29 will provide useful biomarkers for sensitivity to this class of chemotherapeutic drug.

Predictive toxicology using stem cells or their derived tissues has gained increasing importance in biomedical and pharmaceutical research. Here, we show that toxicity category prediction by support vector machines (SVMs), which uses qRT-PCR data from 20 categorized chemicals based on a human embryonic stem cell (hESC) system, is improved by the adoption of gene networks, in which network edge weights are added as feature vectors when noisy qRT-PCR data fail to make accurate predictions. The accuracies of our system were 97.5-100% for three toxicity categories: neurotoxins (NTs), genotoxic carcinogens (GCs) and non-genotoxic carcinogens (NGCs). For two uncategorized chemicals, bisphenol-A and permethrin, our system yielded reasonable results: bisphenol-A was categorized as an NGC, and permethrin was categorized as an NT; both predictions were supported by recently published papers. Our study has two important features: (i) as the first study to employ gene networks without using conventional quantitative structure-activity relationships (QSARs) as input data for SVMs to analyze toxicogenomics data in an hESC validation system, it uses additional information of gene-to-gene interactions to significantly increase prediction accuracies for noisy gene expression data; and (ii) using only undifferentiated hESCs, our study has considerable potential to predict late-onset chemical toxicities, including abnormalities that occur during embryonic development.

Single transcription factors (TFs) regulate multiple developmental pathways, but the underlying mechanisms remain unclear. Here, we quantitatively characterized the genome-wide occupancy profiles of BLIMP1, a key transcriptional regulator for diverse developmental processes, during the development of three germ-layer derivatives (photoreceptor precursors, embryonic intestinal epithelium and plasmablasts) and the germ cell lineage (primordial germ cells). We identified BLIMP1-binding sites shared among multiple developmental processes, and such sites were highly occupied by BLIMP1 with a stringent recognition motif and were located predominantly in promoter proximities. A subset of bindings common to all the lineages exhibited a new, strong recognition sequence, a GGGAAA repeat. Paradoxically, however, the shared/common bindings had only a slight impact on the associated gene expression. In contrast, BLIMP1 occupied more distal sites in a cell type-specific manner; despite lower occupancy and flexible sequence recognitions, such bindings contributed effectively to the repression of the associated genes. Recognition motifs of other key TFs in BLIMP1-binding sites had little impact on the expression-level changes. These findings suggest that the shared/common sites might serve as potential reservoirs of BLIMP1 that functions at the specific sites, providing the foundation for a unified understanding of the genome regulation by BLIMP1, and, possibly, TFs in general.

The Deciphering the Mechanisms of Developmental Disorders (DMDD) consortium is a research programme set up to identify genes in the mouse, which if mutated (or knocked-out) result in embryonic lethality when homozygous, and initiate the study of why disruption of their function has such profound effects on embryo development and survival. The project uses a combination of comprehensive high resolution 3D imaging and tissue histology to identify abnormalities in embryo and placental structures of embryonic lethal lines. The image data we have collected and the phenotypes scored are freely available through the project website (http://dmdd.org.uk). In this article we describe the web interface to the images that allows the embryo data to be viewed at full resolution in different planes, discuss how to search the database for a phenotype, and our approach to organising the data for an embryo and a mutant line so it is easy to comprehend and intuitive to navigate.

Echinobase (www.echinobase.org) is a third generation web resource supporting genomic research on echinoderms. The new version was built by cloning the mature Xenopus model organism knowledgebase, Xenbase, refactoring data ingestion pipelines and modifying the user interface to adapt to multispecies echinoderm content. This approach leveraged over 15 years of previous database and web application development to generate a new fully featured informatics resource in a single year. In addition to the software stack, Echinobase uses the private cloud and physical hosts that support Xenbase. Echinobase currently supports six echinoderm species, focused on those used for genomics, developmental biology and gene regulatory network analyses. Over 38 000 gene pages, 18 000 publications, new improved genome assemblies, JBrowse genome browser and BLAST + services are available and supported by the development of a new echinoderm anatomical ontology, uniformly applied formal gene nomenclature, and consistent orthology predictions. A novel feature of Echinobase is integrating support for multiple, disparate species. New genomes from the diverse echinoderm phylum will be added and supported as data becomes available. The common code development design of the integrated knowledgebases ensures parallel improvements as each resource evolves. This approach is widely applicable for developing new model organism informatics resources.