Identification of cell type-specific marker genes and pathways in the mouse brain
No Thumbnail Available
Journal Title
Journal ISSN
Volume Title
School of Science |
Master's thesis
Checking the digitized thesis and permission for publishing
Instructions for the author
Instructions for the author
Author
Date
2013
Department
Major/Subject
Informaatiotekniikka
Mcode
T-61
Degree programme
Language
en
Pages
136
Series
Abstract
Gene expression profiling techniques such as RNA sequencing has greatly contributed to our understanding of physiological and disease processes in the brain. When applied to cellular complex brain tissue samples, these techniques do not account for cell type specific expression changes and the underlying biological pathways of cell types. Aberrations in cell type gene expression patterns have been documented in brain diseases· such as depression, schizophrenia, Alzheimer's among others. Therefore, gene expression at cell type resolution might be critical to understand disease processes and biological pathways. In the recent years, several cell isolation techniques such as such as laser capture micro-dissection and fluorescence-activated cell sorting have been coupled with microarrays for this purpose. However, these methods are technically highly challenging, time-and resource consuming and may be limited because of potential isolation artefacts, mRNA length and abundance biases. For these combined technical issues, gene expression profiling with tissue samples is still the most widely applied approach in brain. In this study, we aim at establishing a transcriptome database for gene expression profiles and identify marker genes that are devoid of these biases, from mouse derived in vitro oligodendrocytes, microglia, astrocytes and neurons. To this end, a modified deep sequencing method that enriches for 3' mRNA reads was used for expression profiling. This study identified numerous cell type-specific gene markers that can potentially be used to characterize cell types and even estimate the proportion of cell types in tissue samples. Additionally, a novel strategy based on RNA abundance to compare the pathway enrichment between the cell types was developed and pathways that are particularly enriched in individual cell types were identified. Thus, this transcriptome database of digital RNA sequencing data generated for the major cell types of the brain can be used as reference information for cell type specific gene expression profiles to overcome some limitations of expression studies from brain tissues.Description
Supervisor
Rousu, Juho|Lundeberg, JoakimThesis advisor
Rossner, MoritzKeywords
transcriptome, cell types, gene markers, pathways, RNA seq
