Wholemount immunohistochemistry for revealing complex brain topography

The repeated and well-understood cellular architecture of the cerebellum make it an ideal model system for exploring brain topography. Underlying its relatively uniform cytoarchitecture is a complex array of parasagittal domains of gene and protein expression. The molecular compartmentalization of the cerebellum is mirrored by the anatomical and functional organization of afferent fibers. To fully appreciate the complexity of cerebellar organization we previously refined a wholemount staining approach for high throughput analysis of patterning defects in the mouse cerebellum. This protocol describes in detail the reagents, tools, and practical steps that are useful to successfully reveal protein expression patterns in the adult mouse cerebellum by using wholemount immunostaining. The steps highlighted here demonstrate the utility of this method using the expression of zebrinII/aldolaseC as an example of how the fine topography of the brain can be revealed in its native three-dimensional conformation. Also described are adaptations to the protocol that allow for the visualization of protein expression in afferent projections and large cerebella for comparative studies of molecular topography. To illustrate these applications, data from afferent staining of the rat cerebellum are included.     

Automated pipeline for atlas-based annotation of gene expression patterns: Application to postnatal day 7 mouse brain

Massive amounts of image data have been collected and continue to be generated for representing cellular gene expression throughout the mouse brain. Critical to exploiting this key effort of the post-genomic era is the ability to place these data into a common spatial reference that enables rapid interactive queries, analysis, data sharing, and visualization. In this paper, we present a set of automated protocols for generating and annotating gene expression patterns suitable for the establishment of a database. The steps include imaging tissue slices, detecting cellular gene expression levels, spatial registration with an atlas, and textual annotation. Using high-throughput in situ hybridization to generate serial sets of tissues displaying gene expression, this process was applied toward the establishment of a database representing over 200 genes in the postnatal day 7 mouse brain. These data using this protocol are now well-suited for interactive comparisons, analysis, queries, and visualization.     

Study of gene function based on spatial co-expression in a high-resolution mouse brain atlas

Background  

The Allen Brain Atlas (ABA) project systematically profiles three-dimensional high-resolution gene expression in postnatal mouse brains for thousands of genes. By unveiling gene behaviors at both the cellular and molecular levels, ABA is becoming a unique and comprehensive neuroscience data source for decoding enigmatic biological processes in the brain. Given the unprecedented volume and complexity of the in situ hybridization image data, data mining in this area is extremely challenging. Currently, the ABA database mainly serves as an online reference for visual inspection of individual genes; the underlying rich information of this large data set is yet to be explored by novel computational tools. In this proof-of-concept study, we studied the hypothesis that genes sharing similar three-dimensional expression profiles in the mouse brain are likely to share similar biological functions.     

High-resolution gene expression atlases for adult and developing mouse brain and spinal cord

Knowledge of the structure, genetics, circuits, and physiological properties of the mammalian brain in both normal and pathological states is ever increasing as research labs worldwide probe the various aspects of brain function. Until recently, however, comprehensive cataloging of gene expression across the central nervous system has been lacking. The Allen Institute for Brain Science, as part of its mission to propel neuroscience research, has completed several large gene-mapping projects in mouse, nonhuman primate, and human brain, producing informative online public resources and tools. Here we present the Allen Mouse Brain Atlas, covering ~20,000 genes throughout the adult mouse brain; the Allen Developing Mouse Brain Atlas, detailing expression of approximately 2,000 important developmental genes across seven embryonic and postnatal stages of brain growth; and the Allen Spinal Cord Atlas, revealing expression for ~20,000 genes in the adult and neonatal mouse spinal cords. Integrated data-mining tools, including reference atlases, informatics analyses, and 3-D viewers, are described. For these massive-scale projects, high-throughput industrial techniques were developed to standardize and reliably repeat experimental goals. To verify consistency and accuracy, a detailed analysis of the 1,000 most viewed genes for the adult mouse brain (according to website page views) was performed by comparing our data with peer-reviewed literature and other databases. We show that our data are highly consistent with independent sources and provide a comprehensive compendium of information and tools used by thousands of researchers each month. All data and tools are freely available via the Allen Brain Atlas portal (www.brain-map.org).     

Mathematical characterization of three-dimensional gene expression patterns

MOTIVATION: The importance of a systematic methodology for the mathematical characterization of three-dimensional gene expression patterns in embryonic development. METHODS: By combining lacunarity and multiscale fractal dimension analyses with computer-based methods of three-dimensional reconstruction, it becomes possible to extract new information from in situ hybridization studies. Lacunarity and fractality are appropriate measures for the cloud-like gene activation signals in embryonic tissues. The newly introduced multiscale method provides a natural extension of the fractal dimension concept, being capable of characterizing the fractality of geometrical patterns in terms of spatial scale. This tool can be systematically applied to three-dimensional patterns of gene expression. RESULTS: Applications are illustrated using the three-dimensional expression patterns of the myogenic marker gene Myf5 in a series of differentiating somites of a mouse embryo.     

Gene Class expression: analysis tool of Gene Ontology terms with gene expression data

Serial analysis of gene expression (SAGE) technology produces large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in these gene sets. We present an interactive web-based tool, called Gene Class, which allows functional annotation of SAGE data using the Gene Ontology (GO) database. This tool performs searches in the GO database for each SAGE tag, making associations in the selected GO category for a level selected in the hierarchy. This system provides user-friendly data navigation and visualization for mapping SAGE data onto the gene ontology structure. This tool also provides graphical visualization of the percentage of SAGE tags in each GO category, along with confidence intervals and hypothesis testing.     

Enrichment of ultraconserved elements among genomic imbalances causing mental delay and congenital anomalies

Background

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required.

Results

We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms.

Conclusions

The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.     

The microarray explorer tool for data mining of cDNA microarrays: application for the mammary gland

The Microarray Explorer (MAExplorer) is a versatile Java-based data mining bioinformatic tool for analyzing quantitative cDNA expression profiles across multiple microarray platforms and DNA labeling systems. It may be run as either a stand-alone application or as a Web browser applet over the Internet. With this program it is possible to (i) analyze the expression of individual genes, (ii) analyze the expression of gene families and clusters, (iii) compare expression patterns and (iv) directly access other genomic databases for clones of interest. Data may be downloaded as required from a Web server or in the case of the stand-alone version, reside on the user’s computer. Analyses are performed in real-time and may be viewed and directly manipulated in images, reports, scatter plots, histograms, expression profile plots and cluster analyses plots. A key feature is the clone data filter for constraining a working set of clones to those passing a variety of user-specified logical and statistical tests. Reports may be generated with hypertext Web access to UniGene, GenBank and other Internet databases for sets of clones found to be of interest. Users may save their explorations on the Web server or local computer and later recall or share them with other scientists in this groupware Web environment. The emphasis on direct manipulation of clones and sets of clones in graphics and tables provides a high level of interaction with the data, making it easier for investigators to test ideas when looking for patterns. We have used the MAExplorer to profile gene expression patterns of 1500 duplicated genes isolated from mouse mammary tissue. We have identified genes that are preferentially expressed during pregnancy and during lactation. One gene we identified, carbonic anhydrase III, is highly expressed in mammary tissue from virgin and pregnant mice and in gene knock-out mice with underdeveloped mammary epithelium. Other genes, which include those encoding milk proteins, are preferentially expressed during lactation. MAExplorer may be accessed at http://www.lecb.ncifcrf.gov.MAExplorer.     

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.