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Molecular atlas of the adult mouse brain
Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-4035-5258
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Brain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain organization based on unbiased extraction of spatially-defining features. Applying whole-brain spatial transcriptomics, we captured the gene expression signatures to define the spatial organization of molecularly discrete subregions. We found that the molecular code contained sufficiently detailed information to directly deduce the complex spatial organization of the brain. This unsupervised molecular classification revealed new area- and layer-specific subregions, for example in isocortex and hippocampus, and a new division of striatum. The whole-brain molecular atlas further supports the identification of the spatial origin of single neurons using their gene expression profile, and forms the foundation to define a minimal gene set - a brain palette – that is sufficient to spatially annotate the adult brain. In summary, we have established a new molecular atlas to formally define the identity of brain regions, and a molecular code for mapping and targeting of discrete neuroanatomical domains.

Keywords [en]
spatial transcriptomics, neuroscience, brain, mouse, 3D, atlas, transcriptomics, single cell RNA-seq
National Category
Medical Biotechnology
Research subject
Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-262876DOI: 10.1101/784181OAI: oai:DiVA.org:kth-262876DiVA, id: diva2:1363008
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20191107

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-11-07Bibliographically approved
In thesis
1. Computational methods for analysis and visualization of spatially resolved transcriptomes
Open this publication in new window or tab >>Computational methods for analysis and visualization of spatially resolved transcriptomes
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Characterizing the expression level of genes (transcriptome) in cells and tis- sues is essential for understanding the biological processes of multicellular or- ganisms. RNA sequencing (RNA-seq) has gained traction in the last decade as a powerful tool that provides an accurate quantitative representation of the transcriptome in tissues. RNA-seq methods are, however, limited by the fact that they provide an average representation of the transcriptome across the tissue. Single cell RNA sequencing (scRNA-seq) provides quantitative gene expression levels of individual cells. This enables the molecular characteri- zation of cell types in health, disease and developmental tissues. However, scRNA-seq lacks the spatial context needed to understand how cells interact and their microenvironment. Current methods that provide spatially resolved gene expression levels are limited by a low throughput and the fact that the target genes must be known in advance.

Spatial Transcriptomics (ST) is a novel method that combines high-resolution imaging with high-throughput sequencing. ST provides spatially resolved gene expression levels in tissue sections. The first part of the work presented in this thesis (Papers I, II, III and IV) revolves around the ST method and the development of the computational tools required to process, analyse and visualize ST data.

Furthermore, the ST method was utilized to construct a three-dimensional (3D) molecular atlas of the adult mouse brain using 75 consecutive coronal sections (Paper V). We show that the molecular clusters obtained by unsu- pervised clustering of the atlas highly correlates with the Allen Brain Atlas. The molecular clusters provide new insights in the organization of regions like the hippocampus or the amygdala. We show that the molecular atlas can be used to spatially map single cells (scRNA-seq) onto the clusters and that only a handful of genes is required to define the brain regions at a molecular level.

Finally, the hippocampus and the olfactory bulb of transgenic mice mim- icking the Alzheimer’s disease (AD) were spatially characterized using the ST method (Paper VI). Dierential expression analysis revealed genes central in areas highly cited as important in AD including lipid metabolism, cellular bioenergetics, mitochondrial function, stress response and neurotransmission.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2019. p. 67
Series
TRITA-CBH-FOU ; 2019:54
Keywords
RNA, RNA-seq, single cell, scRNA-seq, transcriptomics, spatial transcriptomics, brain, 3D, Alzheimer’s disease
National Category
Medical and Health Sciences
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-262828 (URN)978-91-7873-335-4 (ISBN)
Public defence
2019-11-15, Air and Fire, Tomtebodavägen 23a, Solna, 10:00 (English)
Opponent
Supervisors
Note

QC 2019-10-23

Available from: 2019-10-23 Created: 2019-10-21 Last updated: 2019-10-23Bibliographically approved

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