The Zebrafish Information Network (ZFIN): a resource for genetic, genomic and developmental research

The Zebrafish Information Network, ZFIN, is a WWW community resource of zebrafish genetic, genomic and developmental research information (http://zfin.org). ZFIN provides an anatomical atlas and dictionary, developmental staging criteria, research methods, pathology information and a link to the ZFIN relational database (http://zfin. org/ZFIN/). The database, built on a relational, object-oriented model, provides integrated information about mutants, genes, genetic markers, mapping panels, publications and contact information for the zebrafish research community. The database is populated with curated published data, user submitted data and large dataset uploads. A broad range of data types including text, images, graphical representations and genetic maps supports the data. ZFIN incorporates links to other genomic resources that provide sequence and ortholog data. Zebrafish nomenclature guidelines and an automated registration mechanism for new names are provided. Extensive usability testing has resulted in an easy to learn and use forms interface with complex searching capabilities.     

A curated gene list for expanding the horizons of pigmentation biology

Over the past century, studies of human pigmentary disorders along with mouse and zebrafish models have shed light on the many cellular functions associated with visible pigment phenotypes. This has led to numerous genes annotated with the ontology term “pigmentation” in independent human, mouse, and zebrafish databases. Comparisons among these datasets revealed that each is individually incomplete in documenting all genes involved in integument‐based pigmentation phenotypes. Additionally, each database contained inherent species‐specific biases in data annotation, and the term “pigmentation” did not solely reflect integument pigmentation phenotypes. This review presents a comprehensive, cross‐species list of 650 genes involved in pigmentation phenotypes that was compiled with extensive manual curation of genes annotated in OMIM, MGI, ZFIN, and GO. The resulting cross‐species list of genes both intrinsic and extrinsic to integument pigment cells provides a valuable tool that can be used to expand our knowledge of complex, pigmentation‐associated pathways.     

Gramene: development and integration of trait and gene ontologies for rice

Gramene (http://www.gramene.org/) is a comparative genome database for cereal crops and a community resource for rice. We are populating and curating Gramene with annotated rice (Oryza sativa) genomic sequence data and associated biological information including molecular markers, mutants, phenotypes, polymorphisms and Quantitative Trait Loci (QTL). In order to support queries across various data sets as well as across external databases, Gramene will employ three related controlled vocabularies. The specific goal of Gramene is, first to provide a Trait Ontology (TO) that can be used across the cereal crops to facilitate phenotypic comparisons both within and between the genera. Second, a vocabulary for plant anatomy terms, the Plant Ontology (PO) will facilitate the curation of morphological and anatomical feature information with respect to expression, localization of genes and gene products and the affected plant parts in a phenotype. The TO and PO are both in the early stages of development in collaboration with the International Rice Research Institute, TAIR and MaizeDB as part of the Plant Ontology Consortium. Finally, as part of another consortium comprising macromolecular databases from other model organisms, the Gene Ontology Consortium, we are annotating the confirmed and predicted protein entries from rice using both electronic and manual curation.     

Zebrafish information network,the knowledgebase for Danio rerio research

The Zebrafish Information Network (zfin.org) is the central repository for Danio rerio genetic and genomic data. The Zebrafish Information Network has served the zebrafish research community since 1994, expertly curating, integrating, and displaying zebrafish data. Key data types available at the Zebrafish Information Network include, but are not limited to, genes, alleles, human disease models, gene expression, phenotype, and gene function. The Zebrafish Information Network makes zebrafish research data Findable, Accessible, Interoperable, and Reusable through nomenclature, curatorial and annotation activities, web interfaces, and data downloads. Recently, the Zebrafish Information Network and 6 other model organism knowledgebases have collaborated to form the Alliance of Genome Resources, aiming to develop sustainable genome information resources that enable the use of model organisms to understand the genetic and genomic basis of human biology and disease. Here, we provide an overview of the data available at the Zebrafish Information Network including recent updates to the gene page to provide access to single-cell RNA sequencing data, links to Alliance web pages, ribbon diagrams to summarize the biological systems and Gene Ontology terms that have annotations, and data integration with the Alliance of Genome Resources.     

Validation of Zebrafish （Danio redo） Reference Genes for Quantitative Real-time RT-PCR Normalization

The normalization of quantitative real time RT-PCR （qRT-PCR） is important to obtain accurate gene expression data. The most common method for qRT-PCR normalization is to use reference, or housekeeping genes. However, there is emerging evidence that even reference genes can be regulated under different conditions, qRT-PCR has only recently been used in terms of zebrafish gene expression studies and there is no validated set of reference genes. This study characterizes the expression of nine possible reference genes during zebrafish embryonic development and in a zebrafish tissue panel. All nine reference genes exhibited variable expression. The fl-actin, EFlot and Rpll3ot genes comprise a validated reference gene panel for zebrafish developmental time course studies, and the EF1 or, Rpll3α and 18S rRNA genes are more suitable as a reference gene panel for zebrafish tissue analysis. Importantly, the zebrafish GAPDH gene appears unsuitable as reference gene for both types of studies.     

More than a decade of developmental gene expression atlases: where are we now?

To unravel regulatory networks of genes functioning during embryonic development, information on in situ gene expression is required. Enormous amounts of such data are available in literature, where each paper reports on a limited number of genes and developmental stages. The best way to make these data accessible is via spatio-temporal gene expression atlases. Eleven atlases, describing developing vertebrates and covering at least 100 genes, were reviewed. This review focuses on: (i) the used anatomical framework, (ii) the handling of input data and (iii) the retrieval of information. Our aim is to provide insights into both the possibilities of the atlases, as well as to describe what more than a decade of developmental gene expression atlases can teach us about the requirements of the design of the ‘ideal atlas’. This review shows that most ingredients needed to develop the ideal atlas are already applied to some extent in at least one of the discussed atlases. A review of these atlases shows that the ideal atlas should be based on a spatial framework, i.e. a series of 3D reference models, which is anatomically annotated using an ontology with sufficient resolution, both for relations as well as for anatomical terms.     

Expanding the annotation of zebrafish microRNAs based on small RNA sequencing

MicroRNAs (miRs) are short non-coding RNAs that fine-tune the regulation of gene expression to coordinate a wide range of biological processes. Because of their role in the regulation of gene expression, miRs are essential players in development by acting on cell fate determination and progression towards cell differentiation and are increasingly relevant to human health and disease. Although the zebrafish Danio rerio is a major model for studies of development, genetics, physiology, evolution, and human biology, the annotation of zebrafish miR-producing genes remains limited. In the present work, we report deep sequencing data of zebrafish small RNAs from brain, heart, testis, and ovary. Results provide evidence for the expression of 56 un-annotated mir genes and 248 un-annotated mature strands, increasing the number of zebrafish mir genes over those already deposited in miRBase by 16% and the number of mature sequences by 63%. We also describe the existence of three pairs of mirror-mir genes and two mirtron genes, genetic features previously undescribed in non-mammalian vertebrates. This report provides information that substantially increases our knowledge of the zebrafish miRNome and will benefit the entire miR community.     

Automatic,context-specific generation of Gene Ontology slims

Background  

The use of ontologies to control vocabulary and structure annotation has added value to genome-scale data, and contributed to the capture and re-use of knowledge across research domains. Gene Ontology (GO) is widely used to capture detailed expert knowledge in genomic-scale datasets and as a consequence has grown to contain many terms, making it unwieldy for many applications. To increase its ease of manipulation and efficiency of use, subsets called GO slims are often created by collapsing terms upward into more general, high-level terms relevant to a particular context. Creation of a GO slim currently requires manipulation and editing of GO by an expert (or community) familiar with both the ontology and the biological context. Decisions about which terms to include are necessarily subjective, and the creation process itself and subsequent curation are time-consuming and largely manual.     

The SOFG Anatomy Entry List (SAEL): an annotation tool for functional genomics data

A great deal of data in functional genomics studies needs to be annotated with low-resolution anatomical terms. For example, gene expression assays based on manually dissected samples (microarray, SAGE, etc.) need high-level anatomical terms to describe sample origin. First-pass annotation in high-throughput assays (e.g. large-scale in situ gene expression screens or phenotype screens) and bibliographic applications, such as selection of keywords, would also benefit from a minimum set of standard anatomical terms. Although only simple terms are required, the researcher faces serious practical problems of inconsistency and confusion, given the different aims and the range of complexity of existing anatomy ontologies. A Standards and Ontologies for Functional Genomics (SOFG) group therefore initiated discussions between several of the major anatomical ontologies for higher vertebrates. As we report here, one result of these discussions is a simple, accessible, controlled vocabulary of gross anatomical terms, the SOFG Anatomy Entry List (SAEL). The SAEL is available from http://www.sofg.org and is intended as a resource for biologists, curators, bioinformaticians and developers of software supporting functional genomics. It can be used directly for annotation in the contexts described above. Importantly, each term is linked to the corresponding term in each of the major anatomy ontologies. Where the simple list does not provide enough detail or sophistication, therefore, the researcher can use the SAEL to choose the appropriate ontology and move directly to the relevant term as an entry point. The SAEL links will also be used to support computational access to the respective ontologies.     

New data and collaborations at the Saccharomyces Genome Database: updated reference genome,alleles, and the Alliance of Genome Resources

Saccharomyces cerevisiae is used to provide fundamental understanding of eukaryotic genetics, gene product function, and cellular biological processes. Saccharomyces Genome Database (SGD) has been supporting the yeast research community since 1993, serving as its de facto hub. Over the years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation, and developed various tools and methods for analysis and curation of a variety of emerging data types. More recently, SGD and six other model organism focused knowledgebases have come together to create the Alliance of Genome Resources to develop sustainable genome information resources that promote and support the use of various model organisms to understand the genetic and genomic bases of human biology and disease. Here we describe recent activities at SGD, including the latest reference genome annotation update, the development of a curation system for mutant alleles, and new pages addressing homology across model organisms as well as the use of yeast to study human disease.     

Expression of the dnmt3 genes in zebrafish development: similarity to Dnmt3a and Dnmt3b

The zebrafish differs from mammals in that they have six dnmt3 genes as opposed to the two that can produce a catalytically active protein in mammals. Zebrafish also do not show evidence of genomic imprinting and lack the Dnmt3l gene necessary to that process in mammals. As such, they offer a unique opportunity to compare the two genetic situations in order to define the roles of the multiple genes in developmental gene methylation. To this end, we have analyzed the developmental expression of the six dnmt3 genes in zebrafish and find that they fall into two distinct patterns. The expression patterns of the dnmt6 and dnmt8 genes, which more closely resemble the mammalian Dnmt3a gene in sequence, also show an expression pattern that is more similar to the expression of Dnmt3a rather than Dnmt3b. Conversely, the other four dnmt3 genes in zebrafish (dnmt3, dnmt4, dnmt5, and dnmt7) show an expression pattern that is more similar to Dnmt3b. The dnmt6 and dnmt8 genes are also expressed in the adult zebrafish and in the brain in particular. In situ expression analyses show that the dnmt6 and/or dnmt8 genes also show tissue-specific differences in expression with those two genes being more ubiquitously expressed in the developing zebrafish than the other dnmt3 genes. Although differences in dnmt3 function may exist between mammals and fish, our results showing similar expression patterns between the genes in fish and mammals suggest that the six dnmt3 genes in the zebrafish may be analogous to the two Dnmt3 genes in mammals.     

Ageing genetic signature of hypersomatotropism

Acromegaly is a pathological condition that is caused by over-secretion of growth hormone (GH) and develops primarily from a pituitary adenoma. Excess GH exposure over a prolonged period of time leads to a wide range of systemic manifestations and comorbidities. Studying the effect of excess GH on the cellular level could help to understand the underlying causes of acromegaly health complications and comorbidities. In our previous publications, we have shown that excess GH reduces body side population (SP) stem cells and induces signs of premature ageing in an acromegaly zebrafish model. Here, we study acromegaly ageing in greater depth at the level of gene expression. We investigated whether acromegaly induces an ageing genetic signature in different organs. Using the GenAge database, our acromegaly model showed a significant enrichment of ageing genetic datasets in the muscle but not in other organs. Likewise, the hierarchical clustering of wild type (WT), acromegaly and aged RNA data from various organs revealed the similarity of gene expression profiles between the acromegaly and the aged muscles. We therefore identified overlapping differentially expressed genes (DEGs) in different organs between acromegaly and aged zebrafish. Importantly, about half of the muscle, liver and brain acromegaly DEGs overlapped with aged zebrafish DEGs. Interestingly, overlapping was observed in the same way; acromegaly-up DEGs overlapped with aged zebrafish up DEGs, not down DEGs, and vice versa. We then identified the biological functions of overlapping DEGs. Enrichment database analysis and gene ontology showed that most overlapping muscle genes were involved in ageing metabolism, while overlapping liver DEGs were involved in metabolic pathways, response to hypoxia and endoplasmic reticulum stress. Thus, this study provides a full ageing genetic signature of acromegaly at the gene expression level.