A transcriptome atlas of the mouse brain at cellular resolution

Museum of spatial transcriptomics

The function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors, depends on the spatial organization of their cells. In the past decade, high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage spatial gene expression data to identify genes with spatial patterns and to delineate neighborhoods within tissues. To comprehensively document spatial gene expression technologies and data-analysis methods, we present a curated review of literature on spatial transcriptomics dating back to 1987, along with a thorough analysis of trends in the field, such as usage of experimental techniques, species, tissues studied, and computational approaches used. Our Review places current methods in a historical context, and we derive insights about the field that can guide current research strategies. A companion supplement offers a more detailed look at the technologies and methods analyzed: https://pachterlab.github.io/LP_2021/ .

Modeling Down syndrome in animals from the early stage to the 4.0 models and next

The genotype-phenotype relationship and the physiopathology of Down Syndrome (DS) have been explored in the last 20 years with more and more relevant mouse models. From the early age of transgenesis to the new CRISPR/CAS9-derived chromosomal engineering and the transchromosomic technologies, mouse models have been key to identify homologous genes or entire regions homologous to the human chromosome 21 that are necessary or sufficient to induce DS features, to investigate the complexity of the genetic interactions that are involved in DS and to explore therapeutic strategies. In this review we report the new developments made, how genomic data and new genetic tools have deeply changed our way of making models, extended our panel of animal models, and increased our understanding of the neurobiology of the disease. But even if we have made an incredible progress which promises to make DS a curable condition, we are facing new research challenges to nurture our knowledge of DS pathophysiology as a neurodevelopmental disorder with many comorbidities during ageing.

VEGF receptor-2/neuropilin 1 trans-complex formation between endothelial and tumor cells is an independent predictor of pancreatic cancer survival

Unstable and dysfunctional tumor vasculature promotes cancer progression and spread. Signal transduction by the pro‐angiogenic vascular endothelial growth factor (VEGF) receptor‐2 (VEGFR2) is modulated by VEGFA‐dependent complex formation with neuropilin 1 (NRP1). NRP1 expressed on tumor cells can form VEGFR2/NRP1 trans‐complexes between tumor cells and endothelial cells which arrests VEGFR2 on the endothelial surface, thus interfering with productive VEGFR2 signaling. In mouse fibrosarcoma, VEGFR2/NRP1 trans‐complexes correlated with reduced tumor vessel branching and reduced tumor cell proliferation. Pancreatic ductal adenocarcinoma (PDAC) strongly expressed NRP1 on both tumor cells and endothelial cells, in contrast to other common cancer forms. Using proximity ligation assay, VEGFR2/NRP1 trans‐complexes were identified in human PDAC tumor tissue, and its presence was associated with reduced tumor vessel branching, reduced tumor cell proliferation, and improved patient survival after adjusting for other known survival predictors. We conclude that VEGFR2/NRP1 trans‐complex formation is an independent predictor of PDAC patient survival. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Multifunctional Activity-Based Protein Profiling of the Developing Lung

Lung diseases and disorders are a leading cause of death among infants. Many of these diseases and disorders are caused by premature birth and underdeveloped lungs. In addition to developmentally related disorders, the lungs are exposed to a variety of environmental contaminants and xenobiotics upon birth that can cause breathing issues and are progenitors of cancer. In order to gain a deeper understanding of the developing lung, we applied an activity-based chemoproteomics approach for the functional characterization of the xenometabolizing cytochrome P450 enzymes, active ATP and nucleotide binding enzymes, and serine hydrolases using a suite of activity-based probes (ABPs). We detected P450 activity primarily in the postnatal lung; using our ATP-ABP, we characterized a wide range of ATPases and other active nucleotide- and nucleic acid-binding enzymes involved in multiple facets of cellular metabolism throughout development. ATP-ABP targets include kinases, phosphatases, NAD- and FAD-dependent enzymes, RNA/DNA helicases, and others. The serine hydrolase-targeting probe detected changes in the activities of several proteases during the course of lung development, yielding insights into protein turnover at different stages of development. Select activity-based probe targets were then correlated with RNA in situ hybridization analyses of lung tissue sections.

LungMAP: The Molecular Atlas of Lung Development Program

The National Heart, Lung, and Blood Institute is funding an effort to create a molecular atlas of the developing lung (LungMAP) to serve as a research resource and public education tool. The lung is a complex organ with lengthy development time driven by interactive gene networks and dynamic cross talk among multiple cell types to control and coordinate lineage specification, cell proliferation, differentiation, migration, morphogenesis, and injury repair. A better understanding of the processes that regulate lung development, particularly alveologenesis, will have a significant impact on survival rates for premature infants born with incomplete lung development and will facilitate lung injury repair and regeneration in adults. A consortium of four research centers, a data coordinating center, and a human tissue repository provides high-quality molecular data of developing human and mouse lungs. LungMAP includes mouse and human data for cross correlation of developmental processes across species. LungMAP is generating foundational data and analysis, creating a web portal for presentation of results and public sharing of data sets, establishing a repository of young human lung tissues obtained through organ donor organizations, and developing a comprehensive lung ontology that incorporates the latest findings of the consortium. The LungMAP website (www.lungmap.net) currently contains more than 6,000 high-resolution lung images and transcriptomic, proteomic, and lipidomic human and mouse data and provides scientific information to stimulate interest in research careers for young audiences. This paper presents a brief description of research conducted by the consortium, database, and portal development and upcoming features that will enhance the LungMAP experience for a community of users.

A digital atlas of ion channel expression patterns in the two-week-old rat brain

The approximately 350 ion channels encoded by the mammalian genome are a main pillar of the nervous system. We have determined the expression pattern of 320 channels in the two-week-old (P14) rat brain by means of non-radioactive robotic in situ hybridization. Optimized methods were developed and implemented to generate stringently coronal brain sections. The use of standardized methods permits a direct comparison of expression patterns across the entire ion channel expression pattern data set and facilitates recognizing ion channel co-expression. All expression data are made publically available at the Genepaint.org database. Inwardly rectifying potassium channels (Kir, encoded by the Kcnj genes) regulate a broad spectrum of physiological processes. Kcnj channel expression patterns generated in the present study were fitted with a deformable subdivision mesh atlas produced for the P14 rat brain. This co-registration, when combined with numerical quantification of expression strengths, allowed for semi-quantitative automated annotation of expression patterns as well as comparisons among and between Kcnj subfamilies. The expression patterns of Kcnj channel were also cross validated against previously published expression patterns of Kcnj channel genes.

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.

Garbage in, garbage out: a critical evaluation of strategies used for validation of immunohistochemical biomarkers

The use of immunohistochemistry (IHC) in clinical cohorts is of paramount importance in determining the utility of a biomarker in clinical practice. A major bottleneck in translating a biomarker from bench-to-bedside is the lack of well characterized, specific antibodies suitable for IHC. Despite the widespread use of IHC as a biomarker validation tool, no universally accepted standardization guidelines have been developed to determine the applicability of particular antibodies for IHC prior to its use. In this review, we discuss the technical challenges faced by the use of immunohistochemical biomarkers and rigorously explore classical and emerging antibody validation technologies. Based on our review of these technologies, we provide strict criteria for the pragmatic validation of antibodies for use in immunohistochemical assays.

Tissue microarrays: fast-tracking protein expression at the cellular level

Tissue microarrays maximize returns in cellular pathology whilst minimizing the use of cells and tissues. They are made by arraying cores of tissue taken from multiple donor blocks into a single recipient block. Accordingly, the histology and pathology of several hundred tissues can be represented in one tissue microarray that, when stained by immunohistochemistry, provides comprehensive topographic information on protein expression. Used with complimentary techniques, such as complementary DNA microarray analysis, tissue microarrays are providing valuable data for the identification of new markers of disease and assisting in the discovery of therapeutic targets. They are also leading a revolution in cellular pathology as high-throughput technology is introduced to maximize the information provided.

An efficient algorithm for mapping imaging data to 3D unstructured grids in computational biomechanics

Geometries for organ scale and multiscale simulations of organ function are now routinely derived from imaging data. However, medical images may also contain spatially heterogeneous information other than geometry that are relevant to such simulations either as initial conditions or in the form of model parameters. In this manuscript, we present an algorithm for the efficient and robust mapping of such data to imaging-based unstructured polyhedral grids in parallel. We then illustrate the application of our mapping algorithm to three different mapping problems: (i) the mapping of MRI diffusion tensor data to an unstructured ventricular grid; (ii) the mapping of serial cyrosection histology data to an unstructured mouse brain grid; and (iii) the mapping of computed tomography-derived volumetric strain data to an unstructured multiscale lung grid. Execution times and parallel performance are reported for each case.

Web-based digital gene expression atlases for the mouse

Over the past 15 years the publicly available mouse gene expression data determined by in situ hybridization have dramatically increased in scope and spatiotemporal resolution. As a consequence of resources and tools available in the post-genomic era, full transcriptomes in the mouse brain and in the mouse embryo can be studied. Here we introduce and discuss seven current databases (MAMEP, EMBRYS, GenePaint, EURExpress, EuReGene, BGEM, and GENSAT) that grant access to large collections of expression data in mouse. We review the experimental focus, coverage, data assessment, and annotation for each of these databases and the implementation of analytic tools and links to other relevant databases. We provide a user-oriented summary of how to interrogate each database.

Scalable in situ hybridization on tissue arrays for validation of novel cancer and tissue-specific biomarkers

Tissue localization of gene expression is increasingly important for accurate interpretation of large scale datasets from expression and mutational analyses. To this end, we have (1) developed a robust and scalable procedure for generation of mRNA hybridization probes, providing >95% first-pass success rate in probe generation to any human target gene and (2) adopted an automated staining procedure for analyses of formalin-fixed paraffin-embedded tissues and tissue microarrays. The in situ mRNA and protein expression patterns for genes with known as well as unknown tissue expression patterns were analyzed in normal and malignant tissues to assess procedure specificity and whether in situ hybridization can be used for validating novel antibodies. We demonstrate concordance between in situ transcript and protein expression patterns of the well-known pathology biomarkers KRT17, CHGA, MKI67, PECAM1 and VIL1, and provide independent validation for novel antibodies to the biomarkers BRD1, EZH2, JUP and SATB2. The present study provides a foundation for comprehensive in situ gene set or transcriptome analyses of human normal and tumor tissues.

Atlas-guided correction of brain histology distortion

Histological tissue preparation stages (e.g., cutting, sectioning, etc.) often introduce tissue distortions that prevent a smooth 3D reconstruction from being built. In this paper, we propose a method to correct histology distortions by running a piecewise registration scheme. It takes the information of several consecutive slices in a neighborhood into account. In order to achieve an accurate anatomic presentation, we run the method iteratively with the assistance from a pre-segmented brain atlas. The registration parameters are optimized to accommodate different brain sub-regions, e.g., cerebellum, hippocampus, etc. The results are evaluated by both visual and quantitative approaches. The proposed method has been proved to be robust enough for reconstructing an accurate and smooth mouse brain volume.

Markov Random Field-based Fitting of a Subdivision-based Geometric Atlas

An accurate labeling of a multi-part, complex anatomical structure (e.g., brain) is required in order to compare data across images for spatial analysis. It can be achieved by fitting an object-specific geometric atlas that is constructed using a partitioned, high-resolution deformable mesh and tagging each of its polygons with a region label. Subdivision meshes have been used to construct such an atlas because they can provide a compact representation of a partitioned, multi-resolution, object-specific mesh structure using only a few control points. However, automated fitting of a subdivision mesh-based geometric atlas to an anatomical structure in an image is a difficult problem and has not been sufficiently addressed. In this paper, we propose a novel Markov Random Field-based method for fitting a planar, multi-part subdivision mesh to anatomical data. The optimal fitting of the atlas is obtained by determining the optimal locations of the control points. We also tackle the problem of landmark matching in tandem with atlas fitting by constructing a single graphical model to impose pose-invariant, landmark-based geometric constraints on atlas deformation. The atlas deformation is also governed by additional constraints imposed by the mesh's geometric properties and the object boundary. We demonstrate the potential of the proposed method on the difficult problem of segmenting a mouse brain and its interior regions in gene expression images which exhibit large intensity and shape variability. We obtain promising results when compared with manual annotations and prior methods.

Landmark/Image-based Deformable Registration of Gene Expression Data

Analysis of gene expression patterns in brain images obtained from high-throughput in situ hybridization requires accurate and consistent annotations of anatomical regions/subregions. Such annotations are obtained by mapping an anatomical atlas onto the gene expression images through intensity- and/or landmark-based registration methods or deformable model-based segmentation methods. Due to the complex appearance of the gene expression images, these approaches require a pre-processing step to determine landmark correspondences in order to incorporate landmark-based geometric constraints. In this paper, we propose a novel method for landmark-constrained, intensity-based registration without determining landmark correspondences a priori. The proposed method performs dense image registration and identifies the landmark correspondences, simultaneously, using a single higher-order Markov Random Field model. In addition, a machine learning technique is used to improve the discriminating properties of local descriptors for landmark matching by projecting them in a Hamming space of lower dimension. We qualitatively show that our method achieves promising results and also compares well, quantitatively, with the expert's annotations, outperforming previous methods.

A high-resolution anatomical atlas of the transcriptome in the mouse embryo

The manuscript describes the “digital transcriptome atlas” of the developing mouse embryo, a powerful resource to determine co-expression of genes, to identify cell populations and lineages and to identify functional associations between genes relevant to development and disease.

Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org), consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease.

In situ hybridization (ISH) can be used to visualize gene expression in cells and tissues in their native context. High-throughput ISH using nonradioactive RNA probes allowed the Eurexpress consortium to generate a comprehensive, interactive, and freely accessible digital gene expression atlas, the Eurexpress transcriptome atlas (http://www.eurexpress.org), of the E14.5 mouse embryo. Expression data for over 15,000 genes were annotated for hundreds of anatomical structures, thus allowing us to systematically identify tissue-specific and tissue-overlapping gene networks. We illustrate the value of the Eurexpress atlas by finding novel regional subdivisions in the developing brain. We also use the transcriptome atlas to allocate specific components of the complex Wnt signaling pathway to kidney development, and we identify regionally expressed genes in liver that may be markers of hematopoietic stem cell differentiation.

Comparison of an expanded ataxia interactome with patient medical records reveals a relationship between macular degeneration and ataxia

Spinocerebellar ataxias 6 and 7 (SCA6 and SCA7) are neurodegenerative disorders caused by expansion of CAG repeats encoding polyglutamine (polyQ) tracts in CACNA1A, the alpha1A subunit of the P/Q-type calcium channel, and ataxin-7 (ATXN7), a component of a chromatin-remodeling complex, respectively. We hypothesized that finding new protein partners for ATXN7 and CACNA1A would provide insight into the biology of their respective diseases and their relationship to other ataxia-causing proteins. We identified 118 protein interactions for CACNA1A and ATXN7 linking them to other ataxia-causing proteins and the ataxia network. To begin to understand the biological relevance of these protein interactions within the ataxia network, we used OMIM to identify diseases associated with the expanded ataxia network. We then used Medicare patient records to determine if any of these diseases co-occur with hereditary ataxia. We found that patients with ataxia are at 3.03-fold greater risk of these diseases than Medicare patients overall. One of the diseases comorbid with ataxia is macular degeneration (MD). The ataxia network is significantly (P= 7.37 × 10⁻⁵) enriched for proteins that interact with known MD-causing proteins, forming a MD subnetwork. We found that at least two of the proteins in the MD subnetwork have altered expression in the retina of Ataxin-7^266Q/+ mice suggesting an in vivo functional relationship with ATXN7. Together these data reveal novel protein interactions and suggest potential pathways that can contribute to the pathophysiology of ataxia, MD, and diseases comorbid with ataxia.

A semiautomated approach for artefact removal in serial tissue cryosections

Thinly sliced serial tissue sections of an organ can be imaged using optical microscopy at a resolution detailing individual cells. When the tissue sections are first subjected to in situ hybridization or immunohistochemistry, these data sets can be analysed for changes in gene expression and gene products. Such spatial information is important for understanding the functional effects of experimental or environmental challenges to the organism. However, a critical step in analysing these data sets is mitigating artefacts that result from the preparation of the tissue sections. In this paper, we describe an automated method with manual validation tools that together enable detecting and addressing artefacts including dust particles and air bubbles.

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.

Atoh1-lineal neurons are required for hearing and for the survival of neurons in the spiral ganglion and brainstem accessory auditory nuclei

Atoh1 is a basic helix-loop-helix transcription factor necessary for the specification of inner ear hair cells and central auditory system neurons derived from the rhombic lip. We used the Cre-loxP system and two Cre-driver lines (Egr2(Cre) and Hoxb1(Cre)) to delete Atoh1 from different regions of the cochlear nucleus (CN) and accessory auditory nuclei (AAN). Adult Atoh1-conditional knock-out mice (Atoh1(CKO)) are behaviorally deaf, have diminished auditory brainstem evoked responses, and have disrupted CN and AAN morphology and connectivity. In addition, Egr2; Atoh1(CKO) mice lose spiral ganglion neurons in the cochlea and AAN neurons during the first 3 d of life, revealing a novel critical period in the development of these neurons. These new mouse models of predominantly central deafness illuminate the importance of the CN for support of a subset of peripheral and central auditory neurons.

Subdivision meshes for organizing spatial biomedical data

As biomedical images and volumes are being collected at an increasing speed, there is a growing demand for efficient means to organize spatial information for comparative analysis. In many scenarios, such as determining gene expression patterns by in situ hybridization, the images are collected from multiple subjects over a common anatomical region, such as the brain. A fundamental challenge in comparing spatial data from different images is how to account for the shape variations among subjects, which make direct image-to-image comparisons meaningless. In this paper, we describe subdivision meshes as a geometric means to efficiently organize 2D images and 3D volumes collected from different subjects for comparison. The key advantages of a subdivision mesh for this purpose are its light-weight geometric structure and its explicit modeling of anatomical boundaries, which enable efficient and accurate registration. The multi-resolution structure of a subdivision mesh also allows development of fast comparison algorithms among registered images and volumes.

Traumatic brain injury alters expression of hippocampal microRNAs: potential regulators of multiple pathophysiological processes

Multiple cellular, molecular, and biochemical changes contribute to outcome after traumatic brain injury (TBI). MicroRNAs (miRNAs) are known to influence many important cellular processes, including proliferation, apoptosis, neurogenesis, angiogenesis, and morphogenesis, all processes that are involved in TBI pathophysiology. However, it has not yet been determined whether miRNA expression is altered after TBI. In the present study, we used a microarray platform to examine changes in the hippocampal expression levels of 444 verified rodent miRNAs at 3 and 24 hr after controlled cortical impact injury. Our analysis found 50 miRNAs exhibited decreased expression levels and 35 miRNAs exhibited increased expression levels in the hippocampus after injury. We extended the microarray findings using quantitative polymerase chain reaction analysis for a subset of the miRNAs with altered expression levels (miR-107, -130a, -223, -292-5p, -433-3p, -451, -541, and -711). Bioinformatic analysis of the predicted targets for this panel of miRNAs revealed an overrepresentation of proteins involved in several biological processes and functions known to be initiated after injury, including signal transduction, transcriptional regulation, proliferation, and differentiation. Our results indicate that multiple protein targets and biological processes involved in TBI pathophysiology may be regulated by miRNAs.

Expression patterns of the aquaporin gene family during renal development: influence of genetic variability

High-throughput analyses have shown that aquaporins (AQPs) belong to a cluster of genes that are differentially expressed during kidney organogenesis. However, the spatiotemporal expression patterns of the AQP gene family during tubular maturation and the potential influence of genetic variation on these patterns and on water handling remain unknown. We investigated the expression patterns of all AQP isoforms in fetal (E13.5 to E18.5), postnatal (P1 to P28), and adult (9 weeks) kidneys of inbred (C57BL/6J) and outbred (CD-1) mice. Using quantitative polymerase chain reaction (PCR), we evidenced two mRNA patterns during tubular maturation in C57 mice. The AQPs 1-7-11 showed an early (from E14.5) and progressive increase to adult levels, similar to the mRNA pattern observed for proximal tubule markers (Megalin, NaPi-IIa, OAT1) and reflecting the continuous increase in renal cortical structures during development. By contrast, AQPs 2-3-4 showed a later (E15.5) and more abrupt increase, with transient postnatal overexpression. Most AQP genes were expressed earlier and/or stronger in maturing CD-1 kidneys. Furthermore, adult CD-1 kidneys expressed more AQP2 in the collecting ducts, which was reflected by a significant delay in excreting a water load. The expression patterns of proximal vs. distal AQPs and the earlier expression in the CD-1 strain were confirmed by immunoblotting and immunostaining. These data (1) substantiate the clustering of important genes during tubular maturation and (2) demonstrate that genetic variability influences the regulation of the AQP gene family during tubular maturation and water handling by the mature kidney.

Mouse models of MeCP2 disorders share gene expression changes in the cerebellum and hypothalamus

A group of post-natal neurodevelopmental disorders collectively referred to as MeCP2 disorders are caused by aberrations in the gene encoding methyl-CpG-binding protein 2 (MECP2). Loss of MeCP2 function causes Rett syndrome (RTT), whereas increased copy number of the gene causes MECP2 duplication or triplication syndromes. MeCP2 acts as a transcriptional repressor, however the gene expression changes observed in the hypothalamus of MeCP2 disorder mouse models suggest that MeCP2 can also upregulate gene expression, given that the majority of genes are downregulated upon loss of MeCP2 and upregulated in its presence. To determine if this dual role of MeCP2 extends beyond the hypothalamus, we studied gene expression patterns in the cerebellum of Mecp2-null and MECP2-Tg mice, modeling RTT and MECP2 duplication syndrome, respectively. We found that abnormal MeCP2 dosage causes alterations in the expression of hundreds of genes in the cerebellum. The majority of genes were upregulated in MECP2-Tg mice and downregulated in Mecp2-null mice, consistent with a role for MeCP2 as a modulator that can both increase and decrease gene expression. Interestingly, many of the genes altered in the cerebellum, particularly those increased by the presence of MeCP2 and decreased in its absence, were similarly altered in the hypothalamus. Our data suggest that either gain or loss of MeCP2 results in gene expression changes in multiple brain regions and that some of these changes are global. Further delineation of the expression pattern of MeCP2 target genes throughout the brain might identify subsets of genes that are more amenable to manipulation, and can thus be used to modulate some of the disease phenotypes.

Identification and subclassification of new Atoh1 derived cell populations during mouse spinal cord development

At spinal levels, sensory information pertaining to body positioning (proprioception) is relayed to the cerebellum by the spinocerebellar tracts (SCTs). In the past we revealed the basic helix-loop-helix transcription factor Atoh1 (Math1) to be important for establishing Dorsal Progenitor 1 (DP1) commissural interneurons, which comprise a subset of proprioceptive interneurons. Given there exists multiple subdivisions of the SCT we asked whether Atoh1 may also play a role in specifying other cell types in the spinal cord. Here, we reveal the generation of at least three DP1 derived interneuron populations that reside at spatially restricted positions along the rostral-caudal axis. Each of these cell populations expresses distinct markers and anatomically coincides with the cell bodies of the various subdivisions of the SCT. In addition, we found that as development proceeds (e.g. by E13.5) Atoh1 expression becomes apparent in the dorsal midline in the region of the roof plate (RP). Interestingly, we find that cells derived from Atoh1 expressing RP progenitors express SSEA-1, and in the absence of Atoh1 these progenitors become SOX9 positive. Altogether we reveal the existence of multiple Atoh1 dependent cell types in the spinal cord, and uncover a novel progenitor domain that arises late in development.

Deletion of Mecp2 in Sim1-expressing neurons reveals a critical role for MeCP2 in feeding behavior, aggression, and the response to stress

Rett Syndrome (RTT) is an autism spectrum disorder caused by mutations in the X-linked gene encoding methyl-CpG binding protein 2 (MeCP2). In order to map the neuroanatomic origins of the complex neuropsychiatric behaviors observed in patients with RTT and to uncover endogenous functions of MeCP2 in the hypothalamus, we removed Mecp2 from Sim1-expressing neurons in the hypothalamus using Cre-loxP technology. Loss of MeCP2 in Sim1-expressing neurons resulted in mice that recapitulated the abnormal physiological stress response that is seen upon MeCP2 dysfunction in the entire brain. Surprisingly, we also uncovered a role for MeCP2 in the regulation of social and feeding behaviors since the Mecp2 conditional knockout (CKO) mice were aggressive, hyperphagic, and obese. This study demonstrates that deleting Mecp2 in a defined brain region is an excellent approach to map the neuronal origins of complex behaviors and provides new insight about the function of MeCP2 in specific neurons.

Transcriptome analysis identifies genes with enriched expression in the mouse central extended amygdala

The central extended amygdala (EAc) is an ensemble of highly interconnected limbic structures of the anterior brain, and forms a cellular continuum including the bed nucleus of the stria terminalis (BNST), the central nucleus of the amygdala (CeA) and the nucleus accumbens shell (AcbSh). This neural network is a key site for interactions between brain reward and stress systems, and has been implicated in several aspects of drug abuse. In order to increase our understanding of EAc function at the molecular level, we undertook a genome-wide screen (Affymetrix) to identify genes whose expression is enriched in the mouse EAc. We focused on the less-well known BNST-CeA areas of the EAc, and identified 121 genes that exhibit more than twofold higher expression level in the EAc compared with whole brain. Among these, 43 genes have never been described to be expressed in the EAc. We mapped these genes throughout the brain, using non-radioactive in situ hybridization, and identified eight genes with a unique and distinct rostro-caudal expression pattern along AcbSh, BNST and CeA. Q-PCR analysis performed in brain and peripheral organ tissues indicated that, with the exception of one (Spata13), all these genes are predominantly expressed in brain. These genes encode signaling proteins (Adora2, GPR88, Arpp21 and Rem2), a transcription factor (Limh6) or proteins of unknown function (Rik130, Spata13 and Wfs1). The identification of genes with enriched expression expands our knowledge of EAc at a molecular level, and provides useful information to toward genetic manipulations within the EAc.

Bone morphogenetic proteins, eye patterning, and retinocollicular map formation in the mouse

Patterning events during early eye formation determine retinal cell fate and can dictate the behavior of retinal ganglion cell (RGC) axons as they navigate toward central brain targets. The temporally and spatially regulated expression of bone morphogenetic proteins (BMPs) and their receptors in the retina are thought to play a key role in this process, initiating gene expression cascades that distinguish different regions of the retina, particularly along the dorsoventral axis. Here, we examine the role of BMP and a potential downstream effector, EphB, in retinotopic map formation in the lateral geniculate nucleus (LGN) and superior colliculus (SC). RGC axon behaviors during retinotopic map formation in wild-type mice are compared with those in several strains of mice with engineered defects of BMP and EphB signaling. Normal RGC axon sorting produces axon order in the optic tract that reflects the dorsoventral position of the parent RGCs in the eye. A dramatic consequence of disrupting BMP signaling is a missorting of RGC axons as they exit the optic chiasm. This sorting is not dependent on EphB. When BMP signaling in the developing eye is genetically modified, RGC order in the optic tract and targeting in the LGN and SC are correspondingly disrupted. These experiments show that BMP signaling regulates dorsoventral RGC cell fate, RGC axon behavior in the ascending optic tract, and retinotopic map formation in the LGN and SC through mechanisms that are in part distinct from EphB signaling in the LGN and SC.

Organization of the pronephric kidney revealed by large-scale gene expression mapping

Gene expression mapping reveals 8 functionally distinct domains in the Xenopus pronephros. Interestingly, no structure equivalent to the mammalian collecting duct is identified.

Background

The pronephros, the simplest form of a vertebrate excretory organ, has recently become an important model of vertebrate kidney organogenesis. Here, we elucidated the nephron organization of the Xenopus pronephros and determined the similarities in segmentation with the metanephros, the adult kidney of mammals.

Results

We performed large-scale gene expression mapping of terminal differentiation markers to identify gene expression patterns that define distinct domains of the pronephric kidney. We analyzed the expression of over 240 genes, which included members of the solute carrier, claudin, and aquaporin gene families, as well as selected ion channels. The obtained expression patterns were deposited in the searchable European Renal Genome Project Xenopus Gene Expression Database. We found that 112 genes exhibited highly regionalized expression patterns that were adequate to define the segmental organization of the pronephric nephron. Eight functionally distinct domains were discovered that shared significant analogies in gene expression with the mammalian metanephric nephron. We therefore propose a new nomenclature, which is in line with the mammalian one. The Xenopus pronephric nephron is composed of four basic domains: proximal tubule, intermediate tubule, distal tubule, and connecting tubule. Each tubule may be further subdivided into distinct segments. Finally, we also provide compelling evidence that the expression of key genes underlying inherited renal diseases in humans has been evolutionarily conserved down to the level of the pronephric kidney.

Conclusion

The present study validates the Xenopus pronephros as a genuine model that may be used to elucidate the molecular basis of nephron segmentation and human renal disease.

Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering

Background

Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular level resolution. Projects creating gene expression atlases at unprecedented scales for the embryonic fruit fly as well as the embryonic and adult mouse already involve the analysis of hundreds of thousands of high resolution experimental images mapping mRNA expression patterns. Challenges include accurate registration of highly deformed tissues, associating cells with known anatomical regions, and identifying groups of genes whose expression is coordinately regulated with respect to both concentration and spatial location. Solutions to these and other challenges will lead to a richer understanding of the complex system aspects of gene regulation in heterogeneous tissue.

Results

We present an end-to-end approach for processing raw in situ expression imagery and performing subsequent analysis. We use a non-linear, information theoretic based image registration technique specifically adapted for mapping expression images to anatomical annotations and a method for extracting expression information within an anatomical region. Our method consists of coarse registration, fine registration, and expression feature extraction steps. From this we obtain a matrix for expression characteristics with rows corresponding to genes and columns corresponding to anatomical sub-structures. We perform matrix block cluster analysis using a novel row-column mixture model and we relate clustered patterns to Gene Ontology (GO) annotations.

Conclusion

Resulting registrations suggest that our method is robust over intensity levels and shape variations in ISH imagery. Functional enrichment studies from both simple analysis and block clustering indicate that gene relationships consistent with biological knowledge of neuronal gene functions can be extracted from large ISH image databases such as the Allen Brain Atlas [1] and the Max-Planck Institute [2] using our method. While we focus here on imagery and experiments of the mouse brain our approach should be applicable to a variety of in situ experiments.

MCAM: a database to accelerate the identification of functional cell adhesion molecules

In the post-genomic era, computational identification of cell adhesion molecules (CAMs) becomes important in defining new targets for diagnosis and treatment of various diseases including cancer. Lack of a comprehensive CAM-specific database restricts our ability to identify and characterize novel CAMs. Therefore, we developed a comprehensive mammalian cell adhesion molecule (MCAM) database. The current version is an interactive Web-based database, which provides the resources needed to search mouse, human and rat-specific CAMs and their sequence information and characteristics such as gene functions and virtual gene expression patterns in normal and tumor tissues as well as cell lines. Moreover, the MCAM database can be used for various bioinformatics and biological analyses including identifying CAMs involved in cell-cell interactions and homing of lymphocytes, hematopoietic stem cells and malignant cells to specific organs using data from high-throughput experiments. Furthermore, the database can also be used for training and testing existing transmembrane (TM) topology prediction methods specifically for CAM sequences. The database is freely available online at http://app1.unmc.edu/mcam.

Regulatory pathway analysis by high-throughput in situ hybridization

Automated in situ hybridization enables the construction of comprehensive atlases of gene expression patterns in mammals. Such atlases can become Web-searchable digital expression maps of individual genes and thus offer an entryway to elucidate genetic interactions and signaling pathways. Towards this end, an atlas housing ∼1,000 spatial gene expression patterns of the midgestation mouse embryo was generated. Patterns were textually annotated using a controlled vocabulary comprising >90 anatomical features. Hierarchical clustering of annotations was carried out using distance scores calculated from the similarity between pairs of patterns across all anatomical structures. This process ordered hundreds of complex expression patterns into a matrix that reflects the embryonic architecture and the relatedness of patterns of expression. Clustering yielded 12 distinct groups of expression patterns. Because of the similarity of expression patterns within a group, members of each group may be components of regulatory cascades. We focused on the group containing Pax6, an evolutionary conserved transcriptional master mediator of development. Seventeen of the 82 genes in this group showed a change of expression in the developing neocortex of Pax6-deficient embryos. Electromobility shift assays were used to test for the presence of Pax6-paired domain binding sites. This led to the identification of 12 genes not previously known as potential targets of Pax6 regulation. These findings suggest that cluster analysis of annotated gene expression patterns obtained by automated in situ hybridization is a novel approach for identifying components of signaling cascades.

Signaling pathways drive biological processes with high specificity. Reductionist approaches such as mutagenesis provide one strategy to identity components of pathways. We used high throughput in situ hybridization to systematically map the spatiotemporal expression pattern of ∼1,000 developmental genes in the mouse embryo. The rich information collectively contained in these patterns was captured in annotation tables that were systematically mined using hierarchical clustering, resulting in 12 groups of genes with related expression patterns. We show that this process generates biologically meaningful, high-content information. The expression pattern of developmental master regulator Pax6 is found in a cluster together with that of 81 other genes. The paired DNA binding domain of Pax6 can bind to regulatory sequences in 14 of the 81 genes. We also found that the expression pattern of all these 14 genes is up- or downregulated in Pax6 mutant mice. These results emphasize that determining the expression pattern of many genes in a systematic way followed by an application of integrative tools leads to the identification of novel candidate components of signaling pathways. More generally, when complemented with appropriate data-mining strategies, transcriptome-scale in situ hybridization can be turned into a powerful instrument for systems biology.

The E-protein Tcf4 interacts with Math1 to regulate differentiation of a specific subset of neuronal progenitors

Proneural factors represent <10 transcriptional regulators required for specifying all of the different neurons of the mammalian nervous system. The mechanisms by which such a small number of factors creates this diversity are still unknown. We propose that proteins interacting with proneural factors confer such specificity. To test this hypothesis we isolated proteins that interact with Math1, a proneural transcription factor essential for the establishment of a neural progenitor population (rhombic lip) that gives rise to multiple hindbrain structures and identified the E-protein Tcf4. Interestingly, haploinsufficiency of TCF4 causes the Pitt-Hopkins mental retardation syndrome, underscoring the important role for this protein in neural development. To investigate the functional relevance of the Math1/Tcf4 interaction in vivo, we studied Tcf4(-/-) mice and found that they have disrupted pontine nucleus development. Surprisingly, this selective deficit occurs without affecting other rhombic lip-derived nuclei, despite expression of Math1 and Tcf4 throughout the rhombic lip. Importantly, deletion of any of the other E-protein-encoding genes does not have detectable effects on Math1-dependent neurons, suggesting a specialized role for Tcf4 in distinct neural progenitors. Our findings provide the first in vivo evidence for an exclusive function of dimers formed between a proneural basic helix-loop-helix factor and a specific E-protein, offering insight about the mechanisms underlying transcriptional programs that regulate development of the mammalian nervous system.

Automated characterization of gene expression patterns with an atlas of the mouse brain

A spatio-temporal map of gene activity in the brain would be an important contribution to the understanding of brain development, disease, and function. Such a resource is now possible using high-throughput in situ hybridization, a method for transcriptome-wide acquisition of cellular resolution gene expression patterns in serial tissue sections. However, querying an enormous quantity of image data requires computational methods for describing and organizing gene expression patterns in a consistent manner. In addressing this, we have developed procedures for automated annotation of gene expression patterns in the postnatal mouse brain.

Learning-based segmentation framework for tissue images containing gene expression data

Associating specific gene activity with functional locations in the brain results in a greater understanding of the role of the gene. To perform such an association for the more than 20 000 genes in the mammalian genome, reliable automated methods that characterize the distribution of gene expression in relation to a standard anatomical model are required. In this paper, we propose a new automatic method that results in the segmentation of gene expression images into distinct anatomical regions in which the expression can be quantified and compared with other images. Our contribution is a novel hybrid atlas that utilizes a statistical shape model based on a subdivision mesh, texture differentiation at region boundaries, and features of anatomical landmarks to delineate boundaries of anatomical regions in gene expression images. This atlas, which provides a common coordinate system for internal brain data, is being used to create a searchable database of gene expression patterns in the adult mouse brain. Our framework annotates the images about four times faster and has achieved a median spatial overlap of up to 0.92 compared with expert segmentation in 64 images tested. This tool is intended to help scientists interpret large-scale gene expression patterns more efficiently.

Identification of novel striatal genes by expression profiling in adult mouse brain

Large-scale transcriptome analysis in the brain is a powerful approach to identify novel genes of potential interest toward understanding cerebral organization and function. We utilized the microarray technology to measure expression levels of about 24,000 genes and expressed sequence tags in mouse hippocampus, frontal cortex and striatum. Using expression profile obtained from whole brain as a reference, we categorized the genes into groups of genes either enriched in, or restricted to, one of the three areas of interest. We found enriched genes for each target area. Further, we identified 14 genes in the category of genes restricted to the striatum, among which were the orphan G protein-coupled receptor GPR88 and retinoic acid receptor-beta. These two genes were already reported to be selectively expressed in the striatum, thus validating our experimental approach. We selected 6 striatal-restricted genes, as well as 10 striatal-enriched candidates, that were previously undescribed. We analyzed their expression by in situ hybridization analysis in the brain, and quantitative RT-PCR in both brain and peripheral organs. Two of these unknown genes displayed a notable expression pattern. The striatal-restricted gene H3076B11 shows uniform expression throughout and uniquely in the striatum, representing a genuine striatal marker. The striatal-enriched gene 4833421E05Rik is preferentially expressed in the rostral striatum, and is also abundant in kidney, liver and lung. These two genes may contribute to some of the many striatal-controlled behaviors, including initiation of movement, habit formation, or reward and motivation.

NeuroTerrain--a client-server system for browsing 3D biomedical image data sets

Background

Three dimensional biomedical image sets are becoming ubiquitous, along with the canonical atlases providing the necessary spatial context for analysis. To make full use of these 3D image sets, one must be able to present views for 2D display, either surface renderings or 2D cross-sections through the data. Typical display software is limited to presentations along one of the three orthogonal anatomical axes (coronal, horizontal, or sagittal). However, data sets precisely oriented along the major axes are rare. To make fullest use of these datasets, one must reasonably match the atlas' orientation; this involves resampling the atlas in planes matched to the data set. Traditionally, this requires the atlas and browser reside on the user's desktop; unfortunately, in addition to being monolithic programs, these tools often require substantial local resources. In this article, we describe a network-capable, client-server framework to slice and visualize 3D atlases at off-axis angles, along with an open client architecture and development kit to support integration into complex data analysis environments.

Results

Here we describe the basic architecture of a client-server 3D visualization system, consisting of a thin Java client built on a development kit, and a computationally robust, high-performance server written in ANSI C++. The Java client components (NetOStat) support arbitrary-angle viewing and run on readily available desktop computers running Mac OS X, Windows XP, or Linux as a downloadable Java Application. Using the NeuroTerrain Software Development Kit (NT-SDK), sophisticated atlas browsing can be added to any Java-compatible application requiring as little as 50 lines of Java glue code, thus making it eminently re-useable and much more accessible to programmers building more complex, biomedical data analysis tools. The NT-SDK separates the interactive GUI components from the server control and monitoring, so as to support development of non-interactive applications. The server implementation takes full advantage of data center's high-performance hardware, where it can be co-localized with centrally-located, 3D dataset repositories, extending access to the researcher community throughout the Internet.

Conclusion

The combination of an optimized server and modular, platform-independent client provides an ideal environment for viewing complex 3D biomedical datasets, taking full advantage of high-performance servers to prepare images and subsets of associated meta-data for viewing, as well as the graphical capabilities in Java to actually display the data.

Neuroproteomics - the tasks lying ahead

The brain is unquestionably the most fascinating organ. Despite tremendous progress, current knowledge falls short of being able to explain its function. An emerging approach toward improved understanding of the molecular mechanisms underlying brain function is neuroproteomics. Today's neuroscientists have access to a battery of versatile technologies both in transcriptomics and proteomics. The challenge is to choose the right strategy in order to generate new hypotheses on how the brain works. The goal of this review is therefore two-fold: first we recall the bewildering cellular, molecular, and functional complexity in the brain, as this knowledge is fundamental to any study design. In fact, an impressive complexity on the molecular level has recently re-emerged as a central theme in large-scale analyses. Then we review transcriptomics and proteomics technologies, as both are complementary. Finally, we comment on the most widely used proteomics techniques and their respective strengths and drawbacks. We conclude that for the time being, neuroproteomics should focus on its strengths, namely the identification of posttranslational modifications and protein-protein interactions, as well as the characterization of highly purified subproteomes. For global expression profiling, emphasis should be put on further development to significantly increase coverage.

Analysing the developing brain transcriptome with the GenePaint platform

We discuss technical means by which the complexity of gene and protein signalling cascades can be projected onto the complex structure of the mammalian brain. We argue that this requires both robotics and novel computational tools to register images of gene expression, annotate expression patterns and quantify gene expression. When sufficiently enriched and detailed, such gene expression/neuroanatomical atlases are hypothesis-generating tools and contain in themselves much of the information needed to investigate function in normal and genetically or otherwise modified brains. To be successful and useful, data-rich and comprehensive gene expression/neuroanatomical atlases have to be web accessible and structured in a way that allows the application of data exploration and mining tools.

Hybrid segmentation framework for tissue images containing gene expression data

Associating specific gene activity with functional locations in the brain results in a greater understanding of the role of the gene. To perform such an association for the over 20,000 genes in the mammalian genome, reliable automated methods that characterize the distribution of gene expression in relation to a standard anatomical model are required. In this work, we propose a new automatic method that results in the segmentation of gene expression images into distinct anatomical regions in which the expression can be quantified and compared with other images. Our method utilizes shape models from training images, texture differentiation at region boundaries, and features of anatomical landmarks, to deform a subdivision mesh-based atlas to fit gene expression images. The subdivision mesh provides a common coordinate system for internal brain data through which gene expression patterns can be compared across images. The automated large-scale annotation will help scientists interpret gene expression patterns at cellular resolution more efficiently.

Neural lineages of the Drosophila brain: a three-dimensional digital atlas of the pattern of lineage location and projection at the late larval stage

The late larval brain consists of embryonically produced primary neurons forming a deep core cortex, surrounded at the surface by approximately 100 secondary lineages. Each secondary lineage forms a tract (secondary lineage tract) with an invariant and characteristic trajectory. Within the neuropile, tracts of neighboring lineages bundle together to form secondary tract systems. In this paper, we visualized secondary lineages by the global marker BP106 (neurotactin), as well as green fluorescent protein-labeled clones and thereby establish a comprehensive digital atlas of secondary lineages. The information contained in this atlas is the location of the lineage within the cortex, the neuropile compartment contacted by the lineage tract, and the projection pattern of the lineage tract within the neuropile. We have digitally mapped the expression pattern of three genes, sine oculis, period, and engrailed into the lineage atlas. The atlas will enable us and others to analyze the phenotype of mutant clones in the larval brain. Mutant clones can only be interpreted if the corresponding wild-type clone is well characterized, and our lineage atlas, which visualizes all wild-type lineages, will provide this information. Secondly, secondary lineage tracts form a scaffold of connections in the neuropile that foreshadows adult nerve connections. Thus, starting from the larval atlas and proceeding forward through pupal development, one will be able to reconstruct adult brain connectivity at a high level of resolution. Third, the atlas can serve as a repository for genes expressed in lineage-specific patterns.

Dynamic expression of retinoic acid-synthesizing and -metabolizing enzymes in the developing mouse inner ear

Retinoic acid signaling plays essential roles in morphogenesis and neural development through transcriptional regulation of downstream target genes. It is believed that the balance between the activities of synthesizing and metabolizing enzymes determines the amount of active retinoic acid to which a developing tissue is exposed. In this study, we investigated spatiotemporal expression patterns of four synthesizing enzymes, the retinaldehyde dehydrogenases 1, 2, 3, and 4 (Raldh1, Raldh2, Raldh3, and Raldh4) and two metabolizing enzymes (Cyp26A1 and Cyp26B1) in the embryonic and postnatal mouse inner ear by using quantitative reverse transcriptase polymerase chain reaction (RT-PCR), in situ hybridization, and Western blot analysis. Quantitative RT-PCR analysis and Western blot data revealed that the expression of CYP26s was much higher than that of Raldhs at early embryonic ages but that Cyp26 expression was downregulated during embryonic development. Conversely, the expression levels of Raldh2 and -3 increased during development and were significantly higher than the Cyp26 levels at postnatal day 20. At this age, Raldh3 was expressed predominantly in the cochlea, whereas Raldh2 was present in the vestibular end organ. At early embryonic stages, as observed by in situ hybridization, the synthesizing enzymes were expressed only in the dorsoventral epithelium of the otocyst, whereas the metabolizing enzymes were present mainly in mesenchymal cells surrounding the otic epithelium. At later stages, Raldh2, Raldh3, and Cyp26B1 were confined to the stria vascularis, spiral ganglion, and supporting cells in the cochlear and vestibular epithelia, respectively. The downregulation of Cyp26s and the upregulation of Raldhs after birth during inner ear maturation suggest tissue changes in the sensitivity to retinoic acid concentrations.

Visualization, reconstruction, and integration of neuronal structures in digital brain atlases

Brain atlases are used in neuroanatomy to define the spatial layout of neuronal structures. Their digital variant can serve as a database and common reference frame for integrating data from different biological experiments. This article presents an overview of methods for three-dimensional visualization of neuroanatomical image data, reconstructing neuronal structures from image data, creating digital brain atlases, and registering data in an atlas. This enables analysis of spatial relations between individual structures imaged in different experiments as well as between these structures and the atlas.

3D volume reconstruction of a mouse brain from histological sections using warp filtering

Sectioning tissues for optical microscopy often introduces upon the resulting sections distortions that make 3D reconstruction difficult. Here we present an automatic method for producing a smooth 3D volume from distorted 2D sections in the absence of any undistorted references. The method is based on pairwise elastic image warps between successive tissue sections, which can be computed by 2D image registration. Using a Gaussian filter, an average warp is computed for each section from the pairwise warps in a group of its neighboring sections. The average warps deform each section to match its neighboring sections, thus creating a smooth volume where corresponding features on successive sections lie close to each other. The proposed method can be used with any existing 2D image registration method for 3D reconstruction. In particular, we present a novel image warping algorithm based on dynamic programming that extends Dynamic Time Warping in 1D speech recognition to compute pairwise warps between high-resolution 2D images. The warping algorithm efficiently computes a restricted class of 2D local deformations that are characteristic between successive tissue sections. Finally, a validation framework is proposed and applied to evaluate the quality of reconstruction using both real sections and a synthetic volume.

Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment

We report a global proteomic approach for analyzing brain tissue and for the first time a comprehensive characterization of the whole mouse brain proteome. Preparation of the whole brain sample incorporated a highly efficient cysteinyl-peptide enrichment (CPE) technique to complement a global enzymatic digestion method. Both the global and the cysteinyl-enriched peptide samples were analyzed by SCX fractionation coupled with reversed phase LC-MS/MS analysis. A total of 48,328 different peptides were confidently identified (>98% confidence level), covering 7792 nonredundant proteins ( approximately 34% of the predicted mouse proteome). A total of 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide and the global peptide samples, respectively, corresponding to 25% and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. The identified proteins provide a broad representation of the mouse proteome with little bias evident due to protein pI, molecular weight, and/or cellular localization. Approximately 26% of the identified proteins with gene ontology (GO) annotations were membrane proteins, with 1447 proteins predicted to have transmembrane domains, and many of the membrane proteins were found to be involved in transport and cell signaling. The MS/MS spectrum count information for the identified proteins was used to provide a measure of relative protein abundances. The mouse brain peptide/protein database generated from this study represents the most comprehensive proteome coverage for the mammalian brain to date, and the basis for future quantitative brain proteomic studies using mouse models. The proteomic approach presented here may have broad applications for rapid proteomic analyses of various mouse models of human brain diseases.