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dc.contributor.advisorMehmet Fatih Yanik.en_US
dc.contributor.authorWu, Yuelong, Ph. D. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.date.accessioned2018-02-16T20:04:42Z
dc.date.available2018-02-16T20:04:42Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/113760
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.en_US
dc.descriptionPage 150 blank. Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 133-145).en_US
dc.description.abstractThe information processing capability of the brain is realized by a complex network of neuron subtypes, whose identities, locations, and connections are precisely controlled by the expression of specific sets of genes. Disruptions in the delicate spatiotemporal patterns of gene expression underlie many neurological disorders. Zebrafish, a unique model organism for high-throughput applications, have become increasingly popular for neuroscience research because of its small size and optical transparency of its brain. However, current phenotypic analysis of zebrafish relies heavily on qualitative methods such as crude visual examination. Additionally, the speed of phenotyping zebrafish lines is currently significantly behind the rate of generation of new mutant lines. There is a pressing need for a high-throughput tool that can quantitatively characterize zebrafish phenotypes in detail. In this thesis, an optical projection tomography system has been developed to rapidly image brain-specific gene expression patterns in 3D at cellular resolution. Then registration algorithms and a collection of high-content analysis techniques-including correlation analysis, voxel-wise significance testing, and colocalization clustering-are applied to the reconstructed 3D dataset to automatically detect phenotypic changes. The system has been used to screen full brain phenotype at cellular resolution in a well-studied mutant line tofm808 with a point mutation at the fezf2 gene, a conserved master regulator that plays an important role in neurogenesis and neuronal subtype specification. The analysis successfully detects both monoaminergic diencephalic phenotypes, which have been extensively discussed in the literature, and novel telencephalic phenotypes that were previously overlooked. The telencephalic phenotypes, which include glutamatergic defects in the pallium (the closest counterpart of the neocortex in fish), reveal unexpected parallels between the fezf2 functions in zebrafish and mammals, opening up new opportunities for discovery.en_US
dc.description.statementofresponsibilityby Yuelong Wu.en_US
dc.format.extent150 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.titleRapid 3D characterization of whole vertebrate brain at cellular resolutionen_US
dc.title.alternativeRapid three-D characterization of whole vertebrate brain at cellular resolutionen_US
dc.title.alternativeRapid three-dimensional characterization of whole vertebrate brain at cellular resolutionen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc1022268167en_US


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