Candidate gene prioritization based on spatially mapped gene expression: an application to XLMR

Motivation: The identification of genes involved in specific phenotypes, such as human hereditary diseases, often requires the time-consuming and expensive examination of a large number of positional candidates selected by genome-wide techniques such as linkage analysis and association studies. Even considering the positive impact of next-generation sequencing technologies, the prioritization of these positional candidates may be an important step for disease-gene identification

Digital Atlases as a Framework for Data Sharing

Digital brain atlases are useful as references, analytical tools, and as a data integration framework. As a result, they and their supporting tools are being recognized as potentially useful resources in the movement toward data sharing. Several projects are connecting infrastructure to these tools which facilitate sharing, managing, and retrieving data of different types, scale, and even location. With these in place, we have the ability to combine, analyze, and interpret these data in a manner not previously possible, opening the door to examine issues in new and exciting ways, and potentially leading to speedier discovery of answers as well as new questions about the brain. Here we discuss recent efforts in the use of digital mouse atlases for data sharing

Constructive connectomics: How neuronal axons get from here to there using gene-expression maps derived from their family trees

During brain development, billions of axons must navigate over multiple spatial scales to reach specific neuronal targets, and so build the processing circuits that generate the intelligent behavior of animals. However, the limited information capacity of the zygotic genome puts a strong constraint on how, and which, axonal routes can be encoded. We propose and validate a mechanism of development that can provide an efficient encoding of this global wiring task. The key principle, confirmed through simulation, is that basic constraints on mitoses of neural stem cells—that mitotic daughters have similar gene expression to their parent and do not stray far from one another—induce a global hierarchical map of nested regions, each marked by the expression profile of its common progenitor population. Thus, a traversal of the lineal hierarchy generates a systematic sequence of expression profiles that traces a staged route, which growth cones can follow to their remote targets. We have analyzed gene expression data of developing and adult mouse brains published by the Allen Institute for Brain Science, and found them consistent with our simulations: gene expression indeed partitions the brain into a global spatial hierarchy of nested contiguous regions that is stable at least from embryonic day 11.5 to postnatal day 56. We use this experimental data to demonstrate that our axonal guidance algorithm is able to robustly extend arbors over long distances to specific targets, and that these connections result in a qualitatively plausible connectome. We conclude that, paradoxically, cell division may be the key to uniting the neurons of the brain

Development of a New Tool for 3D Modeling for Regenerative Medicine

The effectiveness of therapeutic treatment based on regenerative medicine for degenerative diseases (i.e., neurodegenerative or cardiac diseases) requires tools allowing the visualization and analysis of the three-dimensional (3D) distribution of target drugs within the tissue. Here, we present a new computational procedure able to overcome the limitations of visual analysis emerging by the examination of a molecular signal within images of serial tissue/organ sections by using the conventional techniques. Together with the 3D anatomical reconstitution of the tissue/organ, our framework allows the detection of signals of different origins (e.g., marked generic molecules, colorimetric, or fluorimetric substrates for enzymes; microRNA; recombinant protein). Remarkably, the application does not require the employment of specific tracking reagents for the imaging analysis. We report two different representative applications: the first shows the reconstruction of a 3D model of mouse brain with the analysis of the distribution of the β-Galactosidase, the second shows the reconstruction of a 3D mouse heart with the measurement of the cardiac volume

Development of On-Tissue Mass Spectrometric Strategies for Protein Identification, Quantification and Mapping

Résumé : L’imagerie par spectrométrie de masse est une technique sans marquage permettant la détection et la localisation de protéines à partir de coupes de tissus. Afin de répondre à des problématiques biologiques, le nombre de protéines identifiées doit être amélioré. Une stratégie consiste à réaliser une micro-jonction liquide sur des régions particulières des coupes de tissus afin d’extraire les peptides issus de la digestion in situ des protéines. Plus de 1500 protéines ont identifié sur une zone de 650µm, correspondant à environ 1900 cellules. Une corrélation entre ces données avec celles générées par MSI a augmenté le nombre de protéines localisées. Afin d’obtenir dans le même temps, la localisation et l’identification de protéines, une méthode consiste à réaliser la microdissection de l’ensemble de la coupe après l’avoir déposée sur une lame recouverte de prafilm. Parafilm-Assisted Microdissection (PAM) a également été appliquée à l’étude de l'expression différentielle de protéines dans des tumeurs de prostate. Les résultats identifiés glutamate oxaloacétate transférase 2 (GOT2) en tant que biomarqueur de protéine candidate impliquée dans le métabolisme du glucose, en plus de celles qui ont déjà été indiqué précédemment. Réunis ensemble, ces méthodes MS d'analyses directes fournissent un moyen robuste d’étude de protéines dans leur état natif afin de fournir des indications sur leur rôle dans des systèmes biologiques. // Abstract : Mass spectrometry-based methods for direct tissue analysis, such as MS imaging, are label-free techniques that permit the detection and localization of proteins on tissue sections. There is a need to improve the number of protein identifications in these techniques for them to comprehensively address biological questions. One strategy to obtain high protein IDs is to realize liquid microjunction on localized regions of tissue sections to extract peptides from the in situ digestion of proteins. More than 1500 proteins were identified in a 650μm spot, corresponding to about 1900 cells. Matching these IDs with those from MSI increased the number of localized proteins. In order to achieve simultaneous identification and localization of proteins, a method consisting of microdissecting entire tissue sections mounted on parafilmcovered slides was developed. Spectral counting was then used to quantify identified proteins, and the values were used to generate images. Parafilm-Assisted Microdissection (PAM) was also used to examine the differential expression of proteins on prostate tumors. Results identified glutamate oxaloacetate transferase 2 (GOT2) as a candidate protein biomarker involved in glucose metabolism, in addition to those that have already been reported previously. Taken together, these direct MS analysis methods provide a robust means of analyzing proteins in their native state and are expected to provide insights to their role in biological systems

Virtual light fields for global illumination in computer graphics

This thesis presents novel techniques for the generation and real-time rendering of globally illuminated environments with surfaces described by arbitrary materials. Real-time rendering of globally illuminated virtual environments has for a long time been an elusive goal. Many techniques have been developed which can compute still images with full global illumination and this is still an area of active flourishing research. Other techniques have only dealt with certain aspects of global illumination in order to speed up computation and thus rendering. These include radiosity, ray-tracing and hybrid methods. Radiosity due to its view independent nature can easily be rendered in real-time after pre-computing and storing the energy equilibrium. Ray-tracing however is view-dependent and requires substantial computational resources in order to run in real-time. Attempts at providing full global illumination at interactive rates include caching methods, fast rendering from photon maps, light fields, brute force ray-tracing and GPU accelerated methods. Currently, these methods either only apply to special cases, are incomplete exhibiting poor image quality and/or scale badly such that only modest scenes can be rendered in real-time with current hardware. The techniques developed in this thesis extend upon earlier research and provide a novel, comprehensive framework for storing global illumination in a data structure - the Virtual Light Field - that is suitable for real-time rendering. The techniques trade off rapid rendering for memory usage and precompute time. The main weaknesses of the VLF method are targeted in this thesis. It is the expensive pre-compute stage with best-case O(N^2) performance, where N is the number of faces, which make the light propagation unpractical for all but simple scenes. This is analysed and greatly superior alternatives are presented and evaluated in terms of efficiency and error. Several orders of magnitude improvement in computational efficiency is achieved over the original VLF method. A novel propagation algorithm running entirely on the Graphics Processing Unit (GPU) is presented. It is incremental in that it can resolve visibility along a set of parallel rays in O(N) time and can produce a virtual light field for a moderately complex scene (tens of thousands of faces), with complex illumination stored in millions of elements, in minutes and for simple scenes in seconds. It is approximate but gracefully converges to a correct solution; a linear increase in resolution results in a linear increase in computation time. Finally a GPU rendering technique is presented which can render from Virtual Light Fields at real-time frame rates in high resolution VR presentation devices such as the CAVETM

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 2

Proceedings of the workshop are presented. The mission of the conference was to transfer advanced technologies developed by the Federal government, its contractors, and other high-tech organizations to U.S. industries for their use in developing new or improved products and processes. Volume two presents papers on the following topics: materials science, robotics, test and measurement, advanced manufacturing, artificial intelligence, biotechnology, electronics, and software engineering

Using an Atlas-Based Approach in the Analysis of Gene Expression Maps Obtained by Voxelation

Part 8: First Workshop on Algorithms for Data and Text Mining in Bioinformatics (WADTMB 2012)International audienceThe integration of gene expression datasets with gene function information provides valuable insights in unraveling the molecular mechanisms of the brain. In this paper, gene expression maps, acquired by the technique of voxelation, are analyzed using an atlas-based framework and the extracted spatial information is employed to organize genes in significant clusters. Moreover, gene function enrichment analysis of clusters enables exploring the relationships among brain regions, gene expressions and gene functions. Our work confirms the hypothesis that genes of similar spatial expression patterns display similar functions indicating that our methodology could assist in the functional identification of unannotated genes