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Single-cell transcriptional profiling of Huntington's disease in human and mouse models

Author(s)
Pineda, Sergio Sebastian.
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Download1227278096-MIT.pdf (13.50Mb)
Alternative title
Single-cell transcriptional profiling of HD in human and mouse models
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Manolis Kellis and Myriam Heiman.
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MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Uncovering the mechanisms that drive cell type-specific vulnerability differences in Huntington's disease (HD) is an imperative prerequisite to finding a reliable therapeutic target. The most affected regions and cell types likely possess vulnerability factors or lack protective factors possessed by other cell types that lead to their early dysfunction and enhanced loss, but such factors remain elusive. In order to characterize the cell type-specific responses induced by mutant huntingtin (mHTT), we applied single-nucleus RNA sequencing to pro- file gene expression changes in human HD and two commonly used mouse models of HD. In the process, we produced the first molecular atlas of the human neostriatum, identified new and previously unobserved cell types, and examined the molecular conservation of this brain region across species. We also developed and documented new computational methods and techniques for curating and analyzing single-cell data from post-mortem human brain samples.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020
 
Cataloged from student-submitted PDF version of thesis.
 
Includes bibliographical references (pages 45-48).
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/129176
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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