Web-based digital gene expression atlases for the mouse

Big data and experimental biology: the complementary roles of hypothesis-led and blue skies research

JEB has broadened its scope to include non-hypothesis-led research. In this Perspective, based on our lab's lived experience, I argue that this is excellent news, because truly novel insights can occur from 'blue skies' idea-led experiments. Hypothesis-led and hypothesis-free experimentation are not philosophically antagonistic; rather, the latter can provide a short-cut to an unbiased view of organism function, and is intrinsically hypothesis generating. Insights derived from hypothesis-free research are commonly obtained by the generation and analysis of big datasets - for example, by genetic screens - or from omics-led approaches (notably transcriptomics). Furthermore, meta-analyses of existing datasets can also provide a lower-cost means to formulating new hypotheses, specifically if researchers take advantage of the FAIR principles (findability, accessibility, interoperability and reusability) to access relevant, publicly available datasets. The broadened scope will thus bring new, original work and novel insights to our journal, by expanding the range of fundamental questions that can be asked.

Genome-wide identification of disease-causing copy number variations in 450 individuals with anorectal malformations

Anorectal malformations (ARM) represent a spectrum of rare malformations originating from a perturbated development of the embryonic hindgut. Approximately 60% occur as a part of a defined genetic syndrome or within the spectrum of additional congenital anomalies. Rare copy number variations (CNVs) have been associated with both syndromic and non-syndromic forms. The present study represents the largest study to date to explore the contribution of CNVs to the expression of ARMs. SNP-array-based molecular karyotyping was applied in 450 individuals with ARM and 4392 healthy controls. CNVs were identified from raw intensity data using PennCNV. Overlapping CNVs between cases and controls were discarded. Remaining CNVs were filtered using a stringent filter algorithm of nine filter steps. Prioritized CNVs were confirmed using qPCR. Filtering prioritized and qPCR confirmed four microscopic chromosomal anomalies and nine submicroscopic CNVs comprising seven microdeletions (del2p13.2, del4p16.2, del7q31.33, del9p24.1, del16q12.1, del18q32, del22q11.21) and two microduplications (dup2p13.2, dup17q12) in 14 individuals (12 singletons and one affected sib-pair). Within these CNVs, based on their embryonic expression data and function, we suggest FOXK2, LPP, and SALL3 as putative candidate genes. Overall, our CNV analysis identified putative microscopic and submicroscopic chromosomal rearrangements in 3% of cases. Functional characterization and re-sequencing of suggested candidate genes is warranted.

Analysis of Uncharacterized mKiaa1211 Expression during Mouse Development and Cardiovascular Morphogenesis

Mammalian Kiaa1211 and Kiaa1211-like are a homologous pair of uncharacterized, highly conserved genes cloned from fetal and adult brain cDNA libraries. Herein we map the in utero spatiotemporal expression of mKiaa1211 and mKiaa1211L mRNA and their expression patterns in postnatal testis, skin, gastrointestinal, and adipose progenitor tissues. Significantly, mKiaa1211 is present throughout the early stages of mouse heart development, particularly in the second heart field (SHF) lineage as it differentiates from mesenchymal cells into cardiomyocytes. We also show that mKiaa1211 is expressed within several early neuronal tissues destined to give rise to central, peripheral, and sympathetic nervous system structures. Expression profiling revealed that the paralog mKiaa1211L is not expressed during the normal developmental process and that mKiaa1211 expression was noticeably absent from most adult terminally differentiated tissues. Finally, we confirm that a previously uncharacterized CRISPR/CAS-generated mKiaa1211 mouse mutant allele is hypomorphic.

Comparing the Expression of Genes Related to Serotonin (5-HT) in C57BL/6J Mice and Humans Based on Data Available at the Allen Mouse Brain Atlas and Allen Human Brain Atlas

Brain atlases are tools based on comprehensive studies used to locate biological characteristics (structures, connections, proteins, and gene expression) in different regions of the brain. These atlases have been disseminated to the point where tools have been created to store, manage, and share the information they contain. This study used the data published by the Allen Mouse Brain Atlas (2004) for mice (C57BL/6J) and Allen Human Brain Atlas (2010) for humans (6 donors) to compare the expression of serotonin-related genes. Genes of interest were searched for manually in each case (in situ hybridization for mice and microarrays for humans), normalized expression data (z-scores) were extracted, and the results were graphed. Despite the differences in methodology, quantification, and subjects used in the process, a high degree of similarity was found between expression data. Here we compare expression in a way that allows the use of translational research methods to infer and validate knowledge. This type of study allows part of the relationship between structures and functions to be identified, by examining expression patterns and comparing levels of expression in different states, anatomical correlations, and phenotypes between different species. The study concludes by discussing the importance of knowing, managing, and disseminating comprehensive, open-access studies in neuroscience.

Self-organized developmental patterning and differentiation in cerebral organoids

Cerebral organoids recapitulate human brain development at a considerable level of detail, even in the absence of externally added signaling factors. The patterning events driving this self-organization are currently unknown. Here, we examine the developmental and differentiative capacity of cerebral organoids. Focusing on forebrain regions, we demonstrate the presence of a variety of discrete ventral and dorsal regions. Clearing and subsequent 3D reconstruction of entire organoids reveal that many of these regions are interconnected, suggesting that the entire range of dorso-ventral identities can be generated within continuous neuroepithelia. Consistent with this, we demonstrate the presence of forebrain organizing centers that express secreted growth factors, which may be involved in dorso-ventral patterning within organoids. Furthermore, we demonstrate the timed generation of neurons with mature morphologies, as well as the subsequent generation of astrocytes and oligodendrocytes. Our work provides the methodology and quality criteria for phenotypic analysis of brain organoids and shows that the spatial and temporal patterning events governing human brain development can be recapitulated in vitro.

Leveraging Online Resources to Prioritize Candidate Genes for Functional Analyses: Using the Fetal Testis as a Test Case

With each new microarray or RNA-seq experiment, massive quantities of transcriptomic information are generated with the purpose to produce a list of candidate genes for functional analyses. Yet an effective strategy remains elusive to prioritize the genes on these candidate lists. In this review, we outline a prioritizing strategy by taking a step back from the bench and leveraging the rich range of public databases. This in silico approach provides an economical, less biased, and more effective solution. We discuss the publicly available online resources that can be used to answer a range of questions about a gene. Is the gene of interest expressed in the system of interest (using expression databases)? Where else is this gene expressed (using added-value transcriptomic resources)? What pathways and processes is the gene involved in (using enriched gene pathway analysis and mouse knockout databases)? Is this gene correlated with human diseases (using human disease variant databases)? Using mouse fetal testis as an example, our strategies identified 298 genes annotated as expressed in the fetal testis. We cross-referenced these genes to existing microarray data and narrowed the list down to cell-type-specific candidates (35 for Sertoli cells, 11 for Leydig cells, and 25 for germ cells). Our strategies can be customized so that they allow researchers to effectively and confidently prioritize genes for functional analysis.

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from “data-to-knowledge-to-innovation,” a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ (geneanalytics.genecards.org), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®—the human gene database; the MalaCards—the human diseases database; and the PathCards—the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®—the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene–tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell “cards” in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics, and others yet to emerge on the postgenomics horizon.

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.

Dysplastic spondylolysis is caused by mutations in the diastrophic dysplasia sulfate transporter gene

Spondylolysis is a fracture in part of the vertebra with a reported prevalence of about 3-6% in the general population. Genetic etiology of this disorder remains unknown. The present study was aimed at identifying genomic mutations in patients with dysplastic spondylolysis as well as the potential pathogenesis of the abnormalities. Whole-exome sequencing and functional analysis were performed for patients with spondylolysis. We identified a novel heterozygous mutation (c.2286A > T; p.D673V) in the sulfate transporter gene SLC26A2 in five affected subjects of a Chinese family. Two additional mutations (e.g., c.1922A > G; p.H641R and g.18654T > C in the intron 1) in the gene were identified by screening a cohort of 30 unrelated patients with the disease. In situ hybridization analysis showed that SLC26A2 is abundantly expressed in the lumbosacral spine of the mouse embryo at day 14.5. Sulfate uptake activities in CHO cells transfected with mutant SLC26A2 were dramatically reduced compared with the wild type, confirming the pathogenicity of the two missense mutations. Further analysis of the gene-disease network revealed a convergent pathogenic network for the development of lumbosacral spine. To our knowledge, our findings provide the first identification of autosomal dominant SLC26A2 mutations in patients with dysplastic spondylolysis, suggesting a new clinical entity in the pathogenesis of chondrodysplasia involving lumbosacral spine. The analysis of the gene-disease network may shed new light on the study of patients with dysplastic spondylolysis and spondylolisthesis as well as high-risk individuals who are asymptomatic.

Subcellular localization of K+ channels in mammalian brain neurons: remarkable precision in the midst of extraordinary complexity

Potassium channels (KChs) are the most diverse ion channels, in part due to extensive combinatorial assembly of a large number of principal and auxiliary subunits into an assortment of KCh complexes. Their structural and functional diversity allows KChs to play diverse roles in neuronal function. Localization of KChs within specialized neuronal compartments defines their physiological role and also fundamentally impacts their activity, due to localized exposure to diverse cellular determinants of channel function. Recent studies in mammalian brain reveal an exquisite refinement of KCh subcellular localization. This includes axonal KChs at the initial segment, and near/within nodes of Ranvier and presynaptic terminals, dendritic KChs found at sites reflecting specific synaptic input, and KChs defining novel neuronal compartments. Painting the remarkable diversity of KChs onto the complex architecture of mammalian neurons creates an elegant picture of electrical signal processing underlying the sophisticated function of individual neuronal compartments, and ultimately neurotransmission and behavior.

Genome-wide RNA Tomography in the zebrafish embryo

Advancing our understanding of embryonic development is heavily dependent on identification of novel pathways or regulators. Although genome-wide techniques such as RNA sequencing are ideally suited for discovering novel candidate genes, they are unable to yield spatially resolved information in embryos or tissues. Microscopy-based approaches, using in situ hybridization, for example, can provide spatial information about gene expression, but are limited to analyzing one or a few genes at a time. Here, we present a method where we combine traditional histological techniques with low-input RNA sequencing and mathematical image reconstruction to generate a high-resolution genome-wide 3D atlas of gene expression in the zebrafish embryo at three developmental stages. Importantly, our technique enables searching for genes that are expressed in specific spatial patterns without manual image annotation. We envision broad applicability of RNA tomography as an accurate and sensitive approach for spatially resolved transcriptomics in whole embryos and dissected organs.

Integrated annotation and analysis of in situ hybridization images using the ImAnno system: application to the ear and sensory organs of the fetal mouse

An in situ hybridization (ISH) study was performed on 2000 murine genes representing around 10% of the protein-coding genes present in the mouse genome using data generated by the EURExpress consortium. This study was carried out in 25 tissues of late gestation embryos (E14.5), with a special emphasis on the developing ear and on five distinct developing sensory organs, including the cochlea, the vestibular receptors, the sensory retina, the olfactory organ, and the vibrissae follicles. The results obtained from an analysis of more than 11,000 micrographs have been integrated in a newly developed knowledgebase, called ImAnno. In addition to managing the multilevel micrograph annotations performed by human experts, ImAnno provides public access to various integrated databases and tools. Thus, it facilitates the analysis of complex ISH gene expression patterns, as well as functional annotation and interaction of gene sets. It also provides direct links to human pathways and diseases. Hierarchical clustering of expression patterns in the 25 tissues revealed three main branches corresponding to tissues with common functions and/or embryonic origins. To illustrate the integrative power of ImAnno, we explored the expression, function and disease traits of the sensory epithelia of the five presumptive sensory organs. The study identified 623 genes (out of 2000) concomitantly expressed in the five embryonic epithelia, among which many (∼12%) were involved in human disorders. Finally, various multilevel interaction networks were characterized, highlighting differential functional enrichments of directly or indirectly interacting genes. These analyses exemplify an under-represention of "sensory" functions in the sensory gene set suggests that E14.5 is a pivotal stage between the developmental stage and the functional phase that will be fully reached only after birth.

A lacZ reporter gene expression atlas for 313 adult KOMP mutant mouse lines

Expression of the bacterial beta-galactosidase reporter gene (lacZ) in the vector used for the Knockout Mouse Project (KOMP) is driven by the endogenous promoter of the target gene. In tissues from KOMP mice, histochemical staining for LacZ enzyme activity can be used to determine gene expression patterns. With this technique, we have produced a comprehensive resource of gene expression using both whole mount (WM) and frozen section (FS) LacZ staining in 313 unique KOMP mutant mouse lines. Of these, ∼80% of mutants showed specific staining in one or more tissues, while ∼20% showed no specific staining, ∼13% had staining in only one tissue, and ∼25% had staining in >6 tissues. The highest frequency of specific staining occurred in the brain (∼50%), male gonads (42%), and kidney (39%). The WM method was useful for rapidly identifying whole organ and some substructure staining, while the FS method often revealed substructure and cellular staining specificity. Both staining methods had >90% repeatability in biological replicates. Nonspecific LacZ staining occurs in some tissues due to the presence of bacteria or endogenous enzyme activity. However, this can be effectively distinguished from reporter gene activity by the combination of the WM and FS methods. After careful annotation, LacZ staining patterns in a high percentage of mutants revealed a unique structure-function not previously reported for many of these genes. The validation of methods for LacZ staining, annotation, and expression analysis reported here provides unique insights into the function of genes for which little is currently known.

Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology

[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.

The tissue-specific transcriptomic landscape of the mid-gestational mouse embryo

Differential gene expression is a prerequisite for the formation of multiple cell types from the fertilized egg during embryogenesis. Understanding the gene regulatory networks controlling cellular differentiation requires the identification of crucial differentially expressed control genes and, ideally, the determination of the complete transcriptomes of each individual cell type. Here, we have analyzed the transcriptomes of six major tissues dissected from mid-gestational (TS12) mouse embryos. Approximately one billion reads derived by RNA-seq analysis provided extended transcript lengths, novel first exons and alternative transcripts of known genes. We have identified 1375 genes showing tissue-specific expression, providing gene signatures for each of the six tissues. In addition, we have identified 1403 novel putative long noncoding RNA gene loci, 439 of which show differential expression. Our analysis provides the first complete transcriptome data for the mouse embryo. It offers a rich data source for the analysis of individual genes and gene regulatory networks controlling mid-gestational development.

LifeMap Discovery™: the embryonic development, stem cells, and regenerative medicine research portal

LifeMap Discovery™ provides investigators with an integrated database of embryonic development, stem cell biology and regenerative medicine. The hand-curated reconstruction of cell ontology with stem cell biology; including molecular, cellular, anatomical and disease-related information, provides efficient and easy-to-use, searchable research tools. The database collates in vivo and in vitro gene expression and guides translation from in vitro data to the clinical utility, and thus can be utilized as a powerful tool for research and discovery in stem cell biology, developmental biology, disease mechanisms and therapeutic discovery. LifeMap Discovery is freely available to academic nonprofit institutions at http://discovery.lifemapsc.com.

Tools, methods, and applications for optophysiology in neuroscience

The advent of optogenetics and genetically encoded photosensors has provided neuroscience researchers with a wealth of new tools and methods for examining and manipulating neuronal function in vivo. There exists now a wide range of experimentally validated protein tools capable of modifying cellular function, including light-gated ion channels, recombinant light-gated G protein-coupled receptors, and even neurotransmitter receptors modified with tethered photo-switchable ligands. A large number of genetically encoded protein sensors have also been developed to optically track cellular activity in real time, including membrane-voltage-sensitive fluorophores and fluorescent calcium and pH indicators. The development of techniques for controlled expression of these proteins has also increased their utility by allowing the study of specific populations of cells. Additionally, recent advances in optics technology have enabled both activation and observation of target proteins with high spatiotemporal fidelity. In combination, these methods have great potential in the study of neural circuits and networks, behavior, animal models of disease, as well as in high-throughput ex vivo studies. This review collects some of these new tools and methods and surveys several current and future applications of the evolving field of optophysiology.

METscout: a pathfinder exploring the landscape of metabolites, enzymes and transporters

METscout (http://metscout.mpg.de) brings together metabolism and gene expression landscapes. It is a MySQL relational database linking biochemical pathway information with 3D patterns of gene expression determined by robotic in situ hybridization in the E14.5 mouse embryo. The sites of expression of ∼1500 metabolic enzymes and of ∼350 solute carriers (SLCs) were included and are accessible as single cell resolution images and in the form of semi-quantitative image abstractions. METscout provides several graphical web-interfaces allowing navigation through complex anatomical and metabolic information. Specifically, the database shows where in the organism each of the many metabolic reactions take place and where SLCs transport metabolites. To link enzymatic reactions and transport, the KEGG metabolic reaction network was extended to include metabolite transport. This network in conjunction with spatial expression pattern of the network genes allows for a tracing of metabolic reactions and transport processes across the entire body of the embryo.