Macrophages are innate immune cells that are traditionally thought to be specialists in phagocytosis. More recent evidence suggest that macrophages reside in nearly every organ and readily adapt to local microenvironmental signals, leading to highly plastic phenotypes across and within tissues. Therefore, rather than treating it as a homogenous cell population, new studies should consider the functional heterogeneity that may exist among macrophages. A better understanding of macrophage heterogeneity can inform on potential therapeutic strategies, as macrophages play central pathological roles in numerous diseases. The emergence of high-throughput RNA profiling assays offers great potential in characterizing macrophage heterogeneity by facilitating direct comparison of gene expression profiles between different subpopulations. The introduction of single cell technology further enables the identification of new macrophage subpopulations. Given the “big data” nature of high-throughput assays, the development of novel computational algorithms and their rigorous application is crucial to gain meaningful insights from the experiments. In this thesis, we demonstrated how integrative computational analysis of bulk and single cell RNA-seq data can improve our understanding of macrophage heterogeneity across organisms and tissues. We characterized macrophage subpopulations residing in murine synovium and human pediatric livers, while assessing changes to their phenotypes under pathological conditions. We further extended the concept of cellular heterogeneity beyond macrophages, where we uncovered the existence of murine synovial monocyte populations distinct from circulation. In the last part of the thesis, we identified a major weakness in the current analytical workflow for transcriptional data and developed a web application called MAGNET, which aims to improve functional enrichment analysis for macrophage-related genomic data.

Creator

• Chen, Shang-Yang

DOI

• https://doi.org/10.21985/n2-c9md-7056

Subject

• Bioinformatics
• Biology

Language

• en

Alternate Identifier

• http://dissertations.umi.com/northwestern:16027
• etdadmin_upload_900059

Keyword

• macrophage
• bioinformatics
• NGS

Date created

• 2022-01-01

Resource type

• Dissertation

Rights statement

• In Copyright