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Active Centers of Excellence in Genomic Science AwardsCenter for Genomic Experimentation and ComputationP50 HG002370
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This Center of Excellence in Genomic Science (CEGS) assembles a multidisciplinary group of investigators to develop innovative technologies with the goal of imaging and mutating every developmentally important vertebrate gene. Novel "in toto imaging" tools make it possible to use a systems-based approach for analysis of gene function in developing vertebrate embryos in real time and space. These tools can digitize in vivo data in a systematic, high-throughput, and quantitative fashion. Combining in toto imaging with novel gene traps permits a means to rapidly screen for developmentally relevant expression patterns, followed by the ability to immediately mutagenize genes of interest. Initially, key technologies will be developed and tested in the zebrafish embryo due to its transparency and the ability to obtain rapid feedback. Once validated, these techniques will be applied to an amniote, the avian embryo, due to several advantages including accessibility and similarity to human embryogenesis. Finally, to monitor alterations in gene expression in normal and mutant embryos, we will develop new techniques for in situ hybridization that permit simultaneous analysis of multiple marker genes in a sensitive and potentially quantitative manner. Our goal is to combine real time analysis of gene expression on a genome-wide scale coupled with the ability to mutate genes of interest and examine global alterations in gene expression as a result of gene loss. Much of the value will come from the development of new and broadly applicable technologies. In contrast to a typical technology development grant, however, there will be experimental fruit emerging from at least two vertebrate systems (zebrafish and avian). The following aims will be pursued: Specific Aim 1: Real-time "in toto" image analysis of reporter gene expression; Specific Aim 2: Comprehensive spatiotemporal analysis of gene function of the developing vertebrate embryo using the FlipTrap approach for gene trapping; Specific Aim 3: Design of quantitative, multiplexed 'hybridization chain reaction' (HCR) amplifiers for in vivo imaging with active background suppression; Specific Aim 4: Data analysis and integration of data sets to produce a "digital" fish and a "digital" bird. The technologies and the resulting atlases will be made broadly available via electronic publication.
Center Web Site: California Institute of Technology Center of Excellence in Genomic Science
Summary CRISP Record [crisp.cit.nih.gov]
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We propose here the Molecular and Genomic Imaging Center (MGIC) in response to a biomedical-community-wide need for flexible, cost-effective, high-resolution technology to identify and characterize variation in biological systems at the level of genomes and transcriptomes. We plan to help meet this need by developing the polymerase colony, or polony, technology. Polonies represent a highly parallel method of nucleic acid analysis that is realistic, close-at-hand, modular, and versatile. The primary mission of the MGIC is to efficiently integrate a diverse set of contributions from technology developers into a robust platform that can be smoothly disseminated to a variety of users with specialized clinical and biological interests. These are the main aims: (1) Polymerase DNA colonies (polonies) and Fluorescent In Situ Sequencing (FISSEQ) will be reliably obtained from millions of polonies in a parallel fashion to enable biological applications including resequencing of microbial & human genomes and mRNA abundance measurements by counting of short mRNA-derived tags. We will improve immobilization (including beads), amplification (PCR & isothermal methods), nucleotide chemistry (including reversible terminators), libraries & robust automation. (2) Most mammalian mRNAs undergo alternative splicing, which is challenging for array-based analyses. "Single molecule" RNA analyses enable monitoring of combinations of alternatively spliced exons. We will develop assays for human Tau, CD44 and other complex splicing patterns. This aim focuses on temporal profiling for bulk cell samples. (3) Applications to several biomedical problems will benefit from the parallel analysis of many individual cells. Protocols for analyzing DNA and RNA from single cells and in situ are crucial. Specifically, assays are needed for protocadherin gene splice variant distributions in individual mouse neuronal cells and differentiating embryonic stem cells, and pathways controlling rat adult hepatic stem cell asymmetric kinetics. Identification of single stranded segments of 'immortal' DNA in these cells will be attempted. (4) We will develop robust, open-source, and user-friendly computational tools enabling polony data acquisition, optimization of component technologies, sequences from the digitally-captured images, analysis of multiple short overlapping sequences, digital statistical error models required for quantitation, and compelling systems models focusing on correlations of comprehensively evaluated splice variant levels within pathways.
Center Web Site: Molecular and Genomic Imaging Center
Summary CRISP Record [crisp.cit.nih.gov]
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Epigenetics is the study of information within the cell that is heritable during cell division, but does not lie within the DNA sequence itself. Epigenetics has been largely ignored in human genomic science, although there is reason to believe that common human diseases may be related to epigenetic modifiers. Except for cancer genetics, where one can compare the disease to normal tissue from the same individual, there have been no systematic approaches toward identifying the epigenetic basis of common human disease, and indeed the human genome project is essentially devoid of any epigenetic information to date. Our goal is to develop the tools and paradigms for the nascent area of medical epigenetics, including epigenome discovery, its quantitative analysis, and its application to medicine. The first aim is to begin to develop high throughput tools for epigenome analysis, high throughput approaches to allele-specific gene expression and methylation analysis, and computational approaches to identifying epigenetic marks through comparative sequencing. The second aim is to develop a novel field of quantitative epigenetics, including a novel epigenetic transmission test, an innovative approach to quantitative epigenotype-quantitative phenotype association, and a new approach to genetic linkage in which the epigenotype is treated mathematically as a quantitative phenotype to identify conventional genetic variants that influence epigenetic phenomena. The third aim is to begin to apply these tools to the epigenetics of common human disease, using epidemiological approaches that interface between these quantitative epigenetic tools and two defined populations: a large Icelandic population that will allow assessment of stability of epigenetic marks over time; and autism patients to test evidence of epigenetic effects on specific gene regions. The investigators all have a strong record of past and recent accomplishments in genetics and genomics, including technical novelty, and we have already united in significant ways in preparing this proposal. Finally, we have taken a highly innovative approach to the Minority Action Plan, developed for recruiting gifted minority children through the Center for Talented Youth at Johns Hopkins, and providing longitudinal training opportunities in genomic science through college. We believe our Center will have a major impact in genomic science in providing a foundation for this novel, important, and exciting field.
Center Web Site: Center of Excellence in Genomic Science at Johns Hopkins
Summary CRISP Record [crisp.cit.nih.gov]
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The long-term goal of this project is to understand the genomic mechanisms that generate phenotypic diversity in vertebrates. Rapid progress in genomics has provided nearly complete sequences for several organisms. Comparative analysis suggests many fundamental pathways and gene networks are conserved between organisms. And yet, the morphology, physiology, and behavior of different species are obviously and profoundly different. What are the mechanisms that generate these key differences? Are unique traits controlled by few or many genetic changes? What kinds of changes? Are there particular genes and mechanisms that are used repeatedly when organisms adapt to new environments? Can better understanding of these mechanisms help explain dramatic differences in disease susceptibility that also exist between groups? The Stanford CEGS will use an innovative combination of approaches in fish, mice, and humans to identify the molecular basis of major phenotypic change in natural populations of vertebrates. Specific aims include: 1) cross stickleback fish and develop a genome wide map of the chromosomes, genes, and mutations that control a broad range of new morphological, physiological, and behavioral traits in natural environments; 2) test which population genetic measures provide the most reliable "signatures of selection" surrounding genes that are known to have served as the basis of parallel adaptive change in many different natural populations around the world; 3) assemble the stickleback proto Y chromosome and test whether either sex or autosomal rearrangements play an important role in generating phenotypic diversity, or are enriched in genomic regions that control phenotypic change; 4) test whether particular genes and mechanisms are used repeatedly to control phenotypic change in many different vertebrates. Preliminary data suggests that mechanisms identified as the basis of adaptive change in natural fish populations may be broadly predictive of adaptive mechanisms across a surprisingly large range of animals, including humans. Genetic regions hypothesized to be under selection in humans will be compared to genetic regions under selection in fish. Regions predicted to play an important role in natural human variation and disease susceptibility will be modeled in mice, generating new model systems for confirming functional variants predicted from human population genetics and comparative genomics.
Center Web Site: Stanford Genome Evolution Center
Summary CRISP Record [crisp.cit.nih.gov]
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Increasingly, it is becoming apparent that understanding, predicting, and diagnosing disease states is confounded by the inherent heterogeneity of in situ cell populations. This variation in cell fate can be dramatic, for instance, one cell living while an adjacent cell dies. Thus, in order to understand fundamental pathways involved in disease states, it is necessary to link preexisting cell state to cell fate in the disease process at the individual cell level. The Microscale Life Sciences Center (MLSC) at the University of Washington is focused on solving this problem, by developing cutting-edge microscale technology for high throughput genomic-level and multi-parameter single-cell analysis, and applying that technology to fundamental problems of biology and health. Our vision is to address pathways to disease states directly at the individual cell level, at increasing levels of complexity that progressively move to an in vivo understanding of disease. We propose to apply MLSC technological innovations to questions that focus on the balance between cell proliferation and cell death. The top three killers in the United States, cancer, heart disease and stroke, all involve an imbalance in this cellular decision-making process. Because of intrinsic cellular heterogeneity in the live/die decision, this fundamental cellular biology problem is an example of one for which analysis of individual cells is essential for developing the link between genomics, cell function, and disease. The specific systems to be studied are proinflammatory cell death (pyroptosis) in a mouse macrophage model, and neoplastic progression in the Barrett's Esophagus (BE) precancerous model. In each case, diagnostic signatures for specific cell states will be determined by measuring both physiological (cell cycle, ploidy, respiration rate, membrane potential) and genomic (gene expression profiles by single-cell proteomics, qRT-PCR and transcriptomics; LOH by LATE-PCR) parameters. These will then be correlated with cell fate via the same sets of measurements after a challenge is administered, for instance, a cell death stimulus for pyroptosis or a predisposing risk factor challenge (acid reflux) for BE. Ultimately, time series will be taken to map out the pathways that underlie the live/die decision.
Finally, this information will be used as a platform to define cell-cell interactions at the single-cell level, to move information on disease pathways towards greater in vivo relevance. New technology will be developed and integrated into the existing MLSC Living Cell Analysis cassette system to support these ambitious biological goals including 1) automated systems for cell placement, off-chip device interconnects, and high throughput data analysis with user friendly interfaces; 2) new optical and electronic sensors based on a new detection platform, new dyes and nanowires; and 3) new micromodules for single-cell qRT-PCR, LATE-PCR for LOH including single-cell pyrosequencing, on-chip single-cell proteomics, and single-cell transcriptomics using barcoded nanobeads.
Collaborating Institutions: Fred Hutchison Cancer Research Center, Seattle, Wash. Brandeis University, Waltham, Mass.; University of Washington, Seattle, Wash.
Center Web Site: Microscale Life Sciences Center
Summary CRISP Record [crisp.cit.nih.gov]
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We propose to establish a center to build genomic DNA arrays and develop novel technologies that will use these arrays for the large-scale functional analysis of the human genome. 0.3-1.4 kb fragments of nonrepetitive DNA from each of chromosomes 22, 21, 20, 19,7, 17, and perhaps the X chromosome will be prepared by PCR and attached to microscope slides. The arrays will be used to develop technologies for the large-scale mapping of 1) Transcribed sequences. 2) Binding sites of chromosomal proteins. 3) Origins of replication. 4) Genetic mutation and variation. A web-accessible database will be constructed to house the information generated in this study; data from other studies will also be integrated into the database. The arrays and technologies will be made available throughout both the Yale University and the larger scientific community. They will be integrated into our training programs for postdoctoral fellows, graduate students and undergraduates at Yale. We expect these procedures to be applicable to the analysis of the entire human genome and the genomes of many other organisms.
Center Web Site: Yale University Center for Excellence in Genomic Science
Summary CRISP Record [crisp.cit.nih.gov]
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Genetic differences between individuals can greatly influence their susceptibility to disease. The information originating from the Human Genome Project (HGP), including the genome sequence and its annotation, together with projects such as the HapMap and the Human Cancer Genome Project (HCGP) have greatly accelerated our ability to find genetic variants and associate genes with a wide range of human diseases. Despite these advances, linking individual genes and their variations to disease remains a daunting challenge. Even where a causal variant has been identified, the biological insight that must precede a strategy for therapeutic intervention has generally been slow in coming. The primary reason for this is that the phenotypic effects of functional sequence variants are mediated by a dynamic network of gene products and metabolites, which exhibit emergent properties that cannot be understood one gene at a time. Our central hypothesis is that both human genetic variations and pathogens such as viruses influence local and global properties of networks to induce "disease states." Therefore, we propose a general approach to understanding cellular networks based on environmental and genetic perturbations of network structure and readout of the effects using interactome mapping, proteomic analysis, and transcriptional profiling. We have chosen a defined model system with a variety of disease outcomes: viral infection. We will explore the concept that one must understand changes in complex cellular networks to fully understand the link between genotype, environment, and phenotype. We will integrate observations from network-level perturbations caused by particular viruses together with genome-wide human variation datasets for related human diseases with the goal of developing general principles for data integration and network prediction, instantiation of these in open-source software tools, and development of testable hypotheses that can be used to assess the value of our methods. Our plans to achieve these goals are summarized in the following specific aims: 1. Profile all viral-host protein-protein interactions for a group of viruses with related biological properties. 2. Profile the perturbations that viral proteins induce on the transcriptome of their host cells. 3. Combine the resulting interaction and perturbation data to derive cellular network-based models. 4. Use the developed models to interpret genome-wide genetic variations observed in human disease, 5. Integrate the bioinformatics resources developed by the various CCSG members within a Bioinformatics Core for data management and dissemination. 6. Building on existing education and outreach programs, we plan to develop a genomic and network centered educational program, with particular emphasis on providing access for underrepresented minorities to internships, workshop and scientific meetings.
Center Web Site: Center for Cancer Systems Biology (CCSB) Center of Excellence in Genomic Science [cegs.ccsb.dfci.harvard.edu]
Summary CRISP Record [crisp.cit.nih.gov]
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Recent studies have indicated that human genetic variation has a "haplotype block structure" such that each chromosome can be decomposed into large blocks with strong linkage disequilibrium (LD) and relatively few haplotypes, separated by short regions of extensive recombination. The primary objective of this application is to study the biological significance of the observed haplotype structure and the practical implications of such haplotype structure for the mapping of genes responsible for human disease. To achieve this objective, we take an inter-disciplinary approach involving molecular biologists, population geneticists, genetic epidemiologists, statisticians, computer scientists, and mathematicians. We achieve the objective through five inter-related specific aims: (1) Develop efficient algorithms to improve the accuracy of polymorphism detection by both DNA sequencing and hybridization chips; (2) Develop efficient computational algorithms for haplotype block partitions and tag SNP selection; (3) Investigate the correspondence between the observed blocks and experimentally determined (primarily through genotyping of single sperm) rates of recombination; (4) Explore population genetics models of haplotype evolution that include alternative reasons for the presence of haplotype structure; and (5) Study the implications of haplotype block structure for association studies of both quantitative and qualitative traits, and develop novel statistical methods for association studies based on haplotype structure. We will validate and apply the newly developed methods on data from a variety of sources, both public and private. In addition to the scientific aims, we will train scientists in interdisciplinary, quantitative approaches to analyzing genomic polymorphism data, and in bioinformatics more generally. The need for such training is clear. We have a strong record of training in computational biology, and believe that we can provide a unique learning environment.
Center Web Site: The USC Center of Excellence in Genomic Science
Summary CRISP Record [crisp.cit.nih.gov]
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Last Reviewed: April 28, 2008
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