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Massachusetts Institute of Technology

Towards mapping spatial transcriptome of an entire vertebrate brain

Abstract

dc:description.abstract

Both the brain’s substantial complexity and technical challenges in monitoring and manipulating brains present challenges for understanding this essential organ. Zebrafish, for their modest brain size and transparency in the larval stage, serve as a model organism for whole-brain in vivo imaging and modeling. While calcium imaging generates substantial amounts of neural activity data, the lack of molecular information for individual neurons in a purely activity readout approach limits further biological interpretation. Recent advancements in in situ sequencing allow RNA profiling in its spatial context, which provides rich information on cell types and cell states. In this thesis, we adapted the expansion in situ sequencing(ExSeq) protocol for larval zebrafish brain slices. In brief, performing two rounds of expansion on zebrafish brain slices enabled us to obtain spatially localized sequencing readouts. This lays the foundation for mapping the spatial transcriptome of an entire vertebrate brain.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Zhang, Ruihan
Advisor dc:contributor.advisor
  • Jacobson, Joseph M.

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/141957
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/141957

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Zhang, Ruihan. Towards mapping spatial transcriptome of an entire vertebrate brain. Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/141957