The Zebrafish Information Network (ZFIN): the zebrafish model organism database

Sprague, Judy

doi:10.1093/nar/gkg027

Cited by 123 publications

(96 citation statements)

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“…To analyse its potential regulatory inputs, we scanned for conserved TF-binding sites using the alignment tool MultiTF at ECR browser 46 . The resulting list of putative regulators (Supplementary Table 4) was further filtered to examine their reported developmental expression patterns in The Zebrafish Model Organism Database 47 . This approach revealed a number of TFs expressed in the retinal tissue, such as vsx2, crx, brca or pbx.…”

Section: Resultsmentioning

confidence: 99%

“…To scan for conserved TF DNAbinding sites within the H6_10137 sequence, we used Mulan alignments and multiTF search tools, available at the ECR browser (http://ecrbrowser.dcode.org/ ) 67 . The expression pattern of the transcriptional regulators potentially binding the identified motifs was analysed in the ZFIN database (http://zfin.org/) 47 . ClustalX 2.0 (ref.…”

Section: Methodsmentioning

confidence: 99%

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Analysis of opo cis-regulatory landscape uncovers Vsx2 requirement in early eye morphogenesis

et al. 2015

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The self-organized morphogenesis of the vertebrate optic cup entails coupling the activation of the retinal gene regulatory network to the constriction-driven infolding of the retinal epithelium. Yet the genetic mechanisms underlying this coordination remain largely unexplored. Through phylogenetic footprinting and transgenesis in zebrafish, here we examine the cis-regulatory landscape of opo, an endocytosis regulator essential for eye morphogenesis. Among the different conserved enhancers identified, we isolate a single retina-specific element (H6_10137) and show that its activity depends on binding sites for the retinal determinant Vsx2. Gain-and loss-of-function experiments and ChIP analyses reveal that Vsx2 regulates opo expression through direct binding to this retinal enhancer. Furthermore, we show that vsx2 knockdown impairs the primary optic cup folding. These data support a model by which vsx2, operating through the effector gene opo, acts as a central transcriptional node that coordinates neural retina patterning and optic cup invagination in zebrafish.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Analysis of opo cis-regulatory landscape uncovers Vsx2 requirement in early eye morphogenesis

et al. 2015

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“…For example, in model organism specific databases ZFin (Sprague et al, 2003), Wormbase (Rogers et al, 2008), MEPD (Henrich et al, 2005), Geisha (Bell et al, 2004;Darnell et al, 2007), GXD (Ringwald et al, 1997;Smith et al, 2007), BDGP (Tomancak et al, 2007), and Xenbase (Bowes et al, 2008), and across multiple species in VisiGene (Kuhn et al, 2007), 4DX-press (Haudry et al, 2008), and quickImage (Gilchrist et al, 2008). The general areas of bioimage informatics and related topics are covered in a recent review (Peng, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Anatomy-based annotation is exemplified in zebrafish by the heroic efforts of Bernard Thisse and others, visualized through the Zfin database (Sprague et al, 2003), and a similar approach has been used both for mouse brains in the Allen Brain Atlas (Lein et al, 2007) and for fruit fly embryos in the BDGP database (Tomancak et al, 2007). This is essentially a manual annotation process.…”

Section: Introductionmentioning

confidence: 99%

Database of queryable gene expression patterns for Xenopus

Gilchrist

Christensen

Bronchain

et al. 2009

Developmental Dynamics

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The precise localization of gene expression within the developing embryo, and how it changes over time, is one of the most important sources of information for elucidating gene function. As a searchable resource, this information has up until now been largely inaccessible to the Xenopus community. Here, we present a new database of Xenopus gene expression patterns, queryable by specific location or region in the embryo. Pattern matching can be driven either from an existing in situ image, or from a user-defined pattern based on development stage schematic diagrams. The data are derived from the work of a group of 21 Xenopus researchers over a period of 4 days. We used a novel, rapid manual annotation tool, XenMARK, which exploits the ability of the human brain to make the necessary distortions in transferring data from the in situ images to the standard schematic geometry.

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“…105 As for the terms and structures involving taxonomic rank and hierarchy, we referred to the 106 Vertebrate Taxonomy Ontology (VTO) (Midford et al, 2013) and imported several of its major classes 107 (with subclasses and all the annotations) in order to demonstrate the functionality of the FO. We also 108 considered biodiversity standard such as the Darwin Core (Wieczorek et al, 2012), and other related 109 ontologies such as the Zebrafish Information Network (ZFIN) (Sprague, 2003), as the references for the FO 110 vocabulary creation. As an example, we imported the class "Chordata" and all of the subclasses for the 111 genus Rastrelliger and Chiloscyllium from the VTO, and reused the terms "Location" and "Taxon" from 112 Darwin Core in our FO.…”

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confidence: 99%

Fish Ontology framework for taxonomy-based fish recognition

Ali

Khan

Then

et al. 2017

Preprint

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Life science ontologies play an important role in semantic web. In the fish and fisheries research field, it is imperative to have an ontology that can automatically provide information for biological objects annotations and links to relevant data pieces. As such, we introduce the Fish Ontology (FO), an automated classification architecture of existing fish taxa which provides taxonomic information of unknown fish based on metadata restrictions. It is designed to support knowledge discovery, providing semantic annotation of fish and fisheries resources, data integration, and information retrieval. The automated classification for unknown specimen is a feature not existing in other known ontologies covering fish species profiling and fisheries data. Examples of automated classification for major groups of fish are demonstrated, showing the inferred information by introducing several restrictions at the species or specimen level. The current version of FO has 1830 classes, includes widely used fisheries terminology, and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish species globally, the FO will be an indispensable tool for fish scientists and other interested users. 15 Life science ontologies play an important role in semantic web. In the fish and fisheries research field, it 16 is imperative to have an ontology that can automatically provide information for biological objects 17 annotations and links to relevant data pieces. As such, we introduce the Fish Ontology (FO), an automated 18 classification architecture of existing fish taxa which provides taxonomic information of unknown fish 19 based on metadata restrictions. It is designed to support knowledge discovery, providing semantic 20 annotation of fish and fisheries resources, data integration, and information retrieval. The automated 21 classification for unknown specimen is a feature not existing in other known ontologies covering fish 22 species profiling and fisheries data. Examples of automated classification for major groups of fish are 23 demonstrated, showing the inferred information by introducing several restrictions at the species or 24 specimen level. The current version of FO has 1830 classes, includes widely used fisheries terminology, 25 and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish 26 species globally, the FO will be an indispensable tool for fish scientists and other interested users. 28 INTRODUCTION29 Increasing amount of data produced by a single species has made it harder for fish researchers to manage 30 and provide fish data in a single database. Moreover, the high demand of having related data (metadata) 31 for a single species have encourage researchers to find an alternative for the current database set. Since 32 the arrival of computational automation, it is impractical to generate species data based on human 33 observation (Perez & Benjamins, 1999). The semantic web technology provides a promising platform for 34 biodiversity r...

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The Zebrafish Information Network (ZFIN): the zebrafish model organism database

Cited by 123 publications

References 1 publication

Analysis of opo cis-regulatory landscape uncovers Vsx2 requirement in early eye morphogenesis

Analysis of opo cis-regulatory landscape uncovers Vsx2 requirement in early eye morphogenesis

Database of queryable gene expression patterns for Xenopus

Fish Ontology framework for taxonomy-based fish recognition

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