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Aspects of the microglia transcriptome. Microglia information converted to RNA-seq outputs generates laborious integrative analyses

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Date: 21 October 2020
Time: 16:15
Location: Aula Academiegebouw Rijksuniversiteit Groningen
Address: Broerstraat 5 te Groningen
Promoter: prof.dr. H.W.G.M. Boddeke en prof.dr. B.J.L. Eggen

​Marissa Dubbelaar: Aspects of the microglia transcriptome. Microglia information converted to RNA-seq outputs generates laborious integrative analyses

Microglia play an essential role in maintaining homeostasis of the central nervous system. In this environment, microglia have a ‘surveillance’ state, the cells are stationary while their processes scan the surrounding environment for potential threats. When a threat is detected (e.g. damaged tissue, or pathogens as bacteria or viruses), microglia become ‘reactive’ and act to remove the threat.
The investigation of RNA molecules, i.e. the transcriptome, during health and pathological conditions in microglia could provide insights into the cellular conditions as development, homeostasis, stress, and diseases that are present in the central nervous system.

This thesis investigates the effect of post mortem delay in mice. Using human homologs, we found that the microglia transcriptome in both mice and human are subjected to subtle gene expression changes. Additionally, a microglia transcriptome of a non-human primate was introduced. Overlaying the macaque and mouse microglia transcriptomics profiles with human microglia led to the observation that macaque microglia are more similar to human microglia than mice microglia. Further investigation of four species resulted in the identification of genes that are evolutionarily preserved.

Furthermore, we introduce an interactive platform that consists of high impact glia studies that could be used for further exploration by other glia researchers. In summary, this thesis presents two aspects: investigation of microglia transcription profiles under specific conditions (post mortem delay, lab procedures, and bioinformatical analyses), and suggestions for collective glia platform technology which could be used in the upcoming bigdata era.


 

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