The gene expression database for mouse development (GXD): putting developmental expression information at your fingertips

PvGeneExpDB: An integrative gene expression database for in-depth understanding on the Pacific white shrimp (Litopenaeus vannamei)

The Pacific white shrimp (Litopenaeus vannamei) is a high-valued economic farming species. With the development of high-throughput sequencing technology, cumulative large-scale transcriptomic studies have been revealing molecular landscape of various biological conditions including genetic selection, breeding, evolution, disease landscape, etc. However, no single experiment or databases allow thorough investigations of transcriptomic dynamics for these progressions. Meanwhile, the available datasets are often scattered and lack management. Here, we have established PvGeneExpDB, the first gene expression database for L. vannamei (www.bio-marine-scau.com/pv_ex/), which encompasses gene expression profiles, differential expression, and co-expression analyses under various biological conditions. Based on the analyses of 7 datasets, which include 53 samples with accurate and detailed records, PvGeneExpDB identifies 20,599 novel transcripts, shows expression profiles of a total of 20,817 genes, and implements Gene Ontology (GO) reconstruction of 76.7 % of these genes. Besides, 26 co-expressed groups were first identified by large-scale, cross-sample Weighted Gene Co-expression Network Analysis (WGCNA). By integrating the gene expression data in the database, our goal is to deepen the biological understanding of L. vannamei.

Mouse Genome Informatics: an integrated knowledgebase system for the laboratory mouse

Mouse Genome Informatics (MGI) is a federation of expertly curated information resources designed to support experimental and computational investigations into genetic and genomic aspects of human biology and disease using the laboratory mouse as a model system. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are core MGI databases that share data and system architecture. MGI serves as the central community resource of integrated information about mouse genome features, variation, expression, gene function, phenotype, and human disease models acquired from peer-reviewed publications, author submissions, and major bioinformatics resources. To facilitate integration and standardization of data, biocuration scientists annotate using terms from controlled metadata vocabularies and biological ontologies (e.g. Mammalian Phenotype Ontology, Mouse Developmental Anatomy, Disease Ontology, Gene Ontology, etc.), and by applying international community standards for gene, allele, and mouse strain nomenclature. MGI serves basic scientists, translational researchers, and data scientists by providing access to FAIR-compliant data in both human-readable and compute-ready formats. The MGI resource is accessible at https://informatics.jax.org. Here, we present an overview of the core data types represented in MGI and highlight recent enhancements to the resource with a focus on new data and functionality for MGD and GXD.

Skeletal Muscle's Role in Prenatal Inter-organ Communication: A Phenogenomic Study with Qualitative Citation Analysis

Gene targeting in mice allows for a complete elimination of skeletal (striated or voluntary) musculature in the body, from the beginning of its development, resulting in our ability to study the consequences of this ablation on other organs. Here I focus on the relationship between the muscle and lung, motor neurons, skeleton, and special senses. Since the inception of my independent laboratory, in 2000, with my team, we published more than 30 papers (and a book chapter), nearly 400 pages of data, on these specific relationships. Here I trace, using Web of Science, nearly 600 citations of this work, to understand its impact. The current report contains a summary of our work and its impact, NCBI's Gene Expression Omnibus accession numbers of all our microarray data, and three clear future directions doable by anyone using our publicly available data. Together, this effort furthers our understanding of inter-organ communication during prenatal development.

The mouse Gene Expression Database (GXD): 2021 update

The Gene Expression Database (GXD; www.informatics.jax.org/expression.shtml) is an extensive and well-curated community resource of mouse developmental gene expression information. For many years, GXD has collected and integrated data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot, and western blot experiments through curation of the scientific literature and by collaborations with large-scale expression projects. Since our last report in 2019, we have continued to acquire these classical types of expression data; developed a searchable index of RNA-Seq and microarray experiments that allows users to quickly and reliably find specific mouse expression studies in ArrayExpress (https://www.ebi.ac.uk/arrayexpress/) and GEO (https://www.ncbi.nlm.nih.gov/geo/); and expanded GXD to include RNA-Seq data. Uniformly processed RNA-Seq data are imported from the EBI Expression Atlas and then integrated with the other types of expression data in GXD, and with the genetic, functional, phenotypic and disease-related information in Mouse Genome Informatics (MGI). This integration has made the RNA-Seq data accessible via GXD’s enhanced searching and filtering capabilities. Further, we have embedded the Morpheus heat map utility into the GXD user interface to provide additional tools for display and analysis of RNA-Seq data, including heat map visualization, sorting, filtering, hierarchical clustering, nearest neighbors analysis and visual enrichment.

The mouse Gene Expression Database (GXD): 2019 update

The mouse Gene Expression Database (GXD) is an extensive, well-curated community resource freely available at www.informatics.jax.org/expression.shtml. Covering all developmental stages, GXD includes data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments in wild-type and mutant mice. GXD's gene expression information is integrated with the other data in Mouse Genome Informatics and interconnected with other databases, placing these data in the larger biological and biomedical context. Since the last report, the ability of GXD to provide insights into the molecular mechanisms of development and disease has been greatly enhanced by the addition of new data and by the implementation of new web features. These include: improvements to the Differential Gene Expression Data Search, facilitating searches for genes that have been shown to be exclusively expressed in a specified structure and/or developmental stage; an enhanced anatomy browser that now provides access to expression data and phenotype data for a given anatomical structure; direct access to the wild-type gene expression data for the tissues affected in a specific mutant; and a comparison matrix that juxtaposes tissues where a gene is normally expressed against tissues, where mutations in that gene cause abnormalities.

Evolving Role of RING1 and YY1 Binding Protein in the Regulation of Germ-Cell-Specific Transcription

Separation of germline cells from somatic lineages is one of the earliest decisions of embryogenesis. Genes expressed in germline cells include apoptotic and meiotic factors, which are not transcribed in the soma normally, but a number of testis-specific genes are active in numerous cancer types. During germ cell development, germ-cell-specific genes can be regulated by specific transcription factors, retinoic acid signaling and multimeric protein complexes. Non-canonical polycomb repressive complexes, like ncPRC1.6, play a critical role in the regulation of the activity of germ-cell-specific genes. RING1 and YY1 binding protein (RYBP) is one of the core members of the ncPRC1.6. Surprisingly, the role of Rybp in germ cell differentiation has not been defined yet. This review is focusing on the possible role of Rybp in this process. By analyzing whole-genome transcriptome alterations of the Rybp^-/- embryonic stem (ES) cells and correlating this data with experimentally identified binding sites of ncPRC1.6 subunits and retinoic acid receptors in ES cells, we propose a model how germ-cell-specific transcription can be governed by an RYBP centered regulatory network, underlining the possible role of RYBP in germ cell differentiation and tumorigenesis.

Developmental biology of the meninges

The meninges are membranous layers surrounding the central nervous system. In the head, the meninges lie between the brain and the skull, and interact closely with both during development. The cranial meninges originate from a mesenchymal sheath on the surface of the developing brain, called primary meninx, and undergo differentiation into three layers with distinct histological characteristics: the dura mater, the arachnoid mater, and the pia mater. While genetic regulation of meningeal development is still poorly understood, mouse mutants and other models with meningeal defects have demonstrated the importance of the meninges to normal development of the calvaria and the brain. For the calvaria, the interactions with the meninges are necessary for the progression of calvarial osteogenesis during early development. In later stages, the meninges control the patterning of the skull and the fate of the sutures. For the brain, the meninges regulate diverse processes including cell survival, cell migration, generation of neurons from progenitors, and vascularization. Also, the meninges serve as a stem cell niche for the brain in the postnatal life. Given these important roles of the meninges, further investigation into the molecular mechanisms underlying meningeal development can provide novel insights into the coordinated development of the head.

Searching the Mouse Genome Informatics (MGI) Resources for Information on Mouse Biology from Genotype to Phenotype

The Mouse Genome Informatics (MGI) resource provides the research community with access to information on the genetics, genomics, and biology of the laboratory mouse. Core data in MGI include gene characterization and function, phenotype and disease model descriptions, DNA and protein sequence data, gene expression data, vertebrate homologies, SNPs, mapping data, and links to other bioinformatics databases. Semantic integration is supported through the use of standardized nomenclature, and through the use of controlled vocabularies such as the mouse Anatomical Dictionary, the Mammalian Phenotype Ontology, and the Gene Ontologies. MGI extracts and organizes data from primary literature. MGI data are shared with and widely displayed from other bioinformatics resources. The database is updated weekly with curated annotations, and regularly adds new datasets and features. This unit provides a guide to using the MGI bioinformatics resource. © 2016 by John Wiley & Sons, Inc.

The mouse Gene Expression Database (GXD): 2017 update

The Gene Expression Database (GXD; www.informatics.jax.org/expression.shtml) is an extensive and well-curated community resource of mouse developmental expression information. Through curation of the scientific literature and by collaborations with large-scale expression projects, GXD collects and integrates data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments. Expression data from both wild-type and mutant mice are included. The expression data are combined with genetic and phenotypic data in Mouse Genome Informatics (MGI) and made readily accessible to many types of database searches. At present, GXD includes over 1.5 million expression results and more than 300 000 images, all annotated with detailed and standardized metadata. Since our last report in 2014, we have added a large amount of data, we have enhanced data and database infrastructure, and we have implemented many new search and display features. Interface enhancements include: a new Mouse Developmental Anatomy Browser; interactive tissue-by-developmental stage and tissue-by-gene matrix views; capabilities to filter and sort expression data summaries; a batch search utility; gene-based expression overviews; and links to expression data from other species.

Representation of anatomy in online atlases and databases: a survey and collection of patterns for interface design

BACKGROUND

A large number of online atlases and databases have been developed to mange the rapidly growing amount of data describing embryogenesis. As these community resources continue to evolve, it is important to understand how representations of anatomy can facilitate the sharing and integration of data. In addition, attention to the design of the interfaces is critical to make online resources useful and usable.

RESULTS

I first present a survey of online atlases and gene expression resources for model organisms, with a focus on methods of semantic and spatial representation of anatomy. A total of 14 anatomical atlases and 21 gene expression resources are included. This survey demonstrates how choices in semantic representation, in the form of ontologies, can enhance interface search functions and provide links between relevant information. This survey also reviews methods for spatially representing anatomy in online resources. I then provide a collection of patterns for interface design based on the atlases and databases surveyed. These patterns include methods for displaying graphics, integrating semantic and spatial representations, organizing information, and querying databases to find genes expressed in anatomical structures.

CONCLUSIONS

This collection of patterns for interface design will assist biologists and software developers in planning the interfaces of new atlases and databases or enhancing existing ones. They also show the benefits of standardizing semantic and spatial representations of anatomy by demonstrating how interfaces can use standardization to provide enhanced functionality.

Characterization of the hypothalamic transcriptome in response to food deprivation reveals global changes in long noncoding RNA, and cell cycle response genes

The hypothalamus integrates energy balance information from the periphery using different neuronal subtypes within each of the hypothalamic areas. However, the effects of prandial state on global mRNA, microRNA and long noncoding (lnc) RNA expression within the whole hypothalamus are largely unknown. In this study, mice were given either a 24-h fast, or ad libitum access to food. RNA samples were analyzed by microarray, and then a subset was confirmed using quantitative real-time PCR (QPCR). A total of 540 mRNAs were either up- or down-regulated with food deprivation. Since gene ontology enrichment analyses identified several categories of mRNAs related to cell cycle processes, ten cell-cycle-related genes were further analyzed using QPCR with six confirmed to be significantly up-regulated and one down-regulated in response to 24-h fasting. While 22 independent microRNAs were differentially expressed by microarray, secondary analysis by QPCR failed to confirm significant changes with fasting. There were 622 lncRNAs identified as differentially expressed, and of three tested by QPCR, two were confirmed. Overall, this is the first time that expression of hypothalamic lncRNAs has been shown to be responsive to food deprivation. In addition, this study is the first to identify a list of lncRNAs with high expression in RNA extracted from hypothalamus. Individual contributions from specific miRNA, lncRNA and mRNAs to the food deprivation response can now be further studied at the physiological and biochemical levels.

The mouse gene expression database: New features and how to use them effectively

The Gene Expression Database (GXD) is an extensive and freely available community resource of mouse developmental expression data. GXD curates and integrates expression data from the literature, via electronic data submissions, and by collaborations with large-scale projects. As an integral component of the Mouse Genome Informatics Resource, GXD combines expression data with genetic, functional, phenotypic, and disease-related data, and provides tools for the research community to search for and analyze expression data in this larger context. Recent enhancements include: an interactive browser to navigate the mouse developmental anatomy and find expression data for specific anatomical structures; the capability to search for expression data of genes located in specific genomic regions, supporting the identification of disease candidate genes; a summary displaying all the expression images that meet specified search criteria; interactive matrix views that provide overviews of spatio-temporal expression patterns (Tissue × Stage Matrix) and enable the comparison of expression patterns between genes (Tissue × Gene Matrix); data zoom and filter utilities to iteratively refine summary displays and data sets; and gene-based links to expression data from other model organisms, such as chicken, Xenopus, and zebrafish, fostering comparative expression analysis for species that are highly relevant for developmental research.

GXD: a community resource of mouse Gene Expression Data

The Gene Expression Database (GXD) is an extensive, easily searchable, and freely available database of mouse gene expression information (www.informatics.jax.org/expression.shtml). GXD was developed to foster progress toward understanding the molecular basis of human development and disease. GXD contains information about when and where genes are expressed in different tissues in the mouse, especially during the embryonic period. GXD collects different types of expression data from wild-type and mutant mice, including RNA in situ hybridization, immunohistochemistry, RT-PCR, and northern and western blot results. The GXD curators read the scientific literature and enter the expression data from those papers into the database. GXD also acquires expression data directly from researchers, including groups doing large-scale expression studies. GXD currently contains nearly 1.5 million expression results for over 13,900 genes. In addition, it has over 265,000 images of expression data, allowing users to retrieve the primary data and interpret it themselves. By being an integral part of the larger Mouse Genome Informatics (MGI) resource, GXD’s expression data are combined with other genetic, functional, phenotypic, and disease-oriented data. This allows GXD to provide tools for researchers to evaluate expression data in the larger context, search by a wide variety of biologically and biomedically relevant parameters, and discover new data connections to help in the design of new experiments. Thus, GXD can provide researchers with critical insights into the functions of genes and the molecular mechanisms of development, differentiation, and disease.

High-throughput screening of mouse gene knockouts identifies established and novel skeletal phenotypes

Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening (HTS) data for 3 762 distinct global gene knockout (KO) mouse lines with viable adult homozygous mice generated using either gene-trap or homologous recombination technologies. Bone mass was determined from DEXA scans of male and female mice at 14 weeks of age and by microCT analyses of bones from male mice at 16 weeks of age. Wild-type (WT) cagemates/littermates were examined for each gene KO. Lethality was observed in an additional 850 KO lines. Since primary HTS are susceptible to false positive findings, additional cohorts of mice from KO lines with intriguing HTS bone data were examined. Aging, ovariectomy, histomorphometry and bone strength studies were performed and possible non-skeletal phenotypes were explored. Together, these screens identified multiple genes affecting bone mass: 23 previously reported genes (Calcr, Cebpb, Crtap, Dcstamp, Dkk1, Duoxa2, Enpp1, Fgf23, Kiss1/Kiss1r, Kl (Klotho), Lrp5, Mstn, Neo1, Npr2, Ostm1, Postn, Sfrp4, Slc30a5, Slc39a13, Sost, Sumf1, Src, Wnt10b), five novel genes extensively characterized (Cldn18, Fam20c, Lrrk1, Sgpl1, Wnt16), five novel genes with preliminary characterization (Agpat2, Rassf5, Slc10a7, Slc26a7, Slc30a10) and three novel undisclosed genes coding for potential osteoporosis drug targets.