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Understanding Cellular Specialization Through Functional Genomics Understanding Cellular Specialization Through Functional Genomics The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Nelms, Bradlee. 2015. Understanding Cellular Specialization Through Functional Genomics. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:23845458 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Understanding Cellular Specialization through Functional Genomics A dissertation presented by Bradlee Nelms to The Committee on Higher Degrees in Biophysics in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Biophysics Harvard University Cambridge, Massachusetts August 2015 © 2015 – Bradlee Nelms All rights reserved. Thesis advisor: Dr. Wayne Lencer Bradlee Nelms Understanding Cellular Specialization through Functional Genomics Abstract The human body is composed of hundreds of specialized cell types, each fulfilling distinct functions that are together essential for normal tissue homeostasis. This thesis is aimed at identifying genes that contribute to to cell type-specific functions, with major projects focused on (1) a specialized epithelial transport pathway called transcytosis and (2) the challenge of measuring cell type-specific gene expression. In both projects, we applied high-throughput methods to narrow down from the ~25,000 protein coding genes to distinguish the subset that contribute to specialized cellular functions. Common themes include the development of enabling technology and the value of integrating diverse genomic datasets. The results described here implicate new genes in cell type-specific processes and provide a starting place for subsequent investigation into the individual genes and pathways. In the first project, we performed an RNA interference (RNAi) screen to identify genes necessary for receptor-mediated transcytosis, a specialized endosomal pathway in epithelial cells. We developed high-throughput assays to measure the transcytosis of immunoglobulin G (IgG) across cultured epithelial cells in conjunction with gene knockdown. Then we selected a set of 582 candidate genes to screen using a combination of literature review and integrated high-throughput evidence, including iii expression data, proteomics, and domain annotation. We knocked-down each of these candidates in parallel and identified many reagents that interfered with transcytosis. In small-scale validation assays, we confirmed a reproducible decrease in transcytosis after knocking down 7 genes with multiple independent reagents (7 confirmed out of 8 genes tested). The validated hits included genes with an established role in related pathways, such as EXOC2 and PARD6B, and genes that have not been implicated in epithelial trafficking before, such as LEPROT, VPS13C, and ARMT. In the second project, we developed an approach to identify genes expressed selectively in specific cell types, using a computational algorithm that searches thousands of microarrays for genes with a similar expression profile to known cell type-specific markers. Our method, CellMapper, is accurate without the need for cell isolation and can be applied to any cell type where at least one cell-specific marker gene is known. We demonstrated the approach for 30 diverse cell types, many of which have not been isolated for expression analysis in humans before. Furthermore, we explored the applicability of our method to infer causal relationships in genome-wide association studies (GWAS) and to investigate the transcriptional identity of a poorly understood cell type, enteric glia. We provided a user-friendly R implementation that will enable researchers from systems biology, molecular biology of disease, and population genetics to identify cellular localization of genes of interest or to expand the catalog of known marker genes for difficult-to-isolate cell types. iv Table of Contents Preface...............................................................................................................................1 I. An RNAi Screen for Factors that Regulate Membrane Transport in Polarized Epithelia...5 1. Endosomal Specialization in Polarized Epithelia.............................................................6 1.0 Introduction...............................................................................................................6 1.1 FcRn-mediated transcytosis as a model system.......................................................7 1.2 Trafficking routes and sorting stations in polarized epithelia.....................................8 1.3 Molecular reactions in endosome trafficking...........................................................10 2. Identifying Genes that Direct IgG Transport Across Polarized Epithelial Cells..............15 2.0 Introduction.............................................................................................................15 2.1 Developing an assay of receptor-mediated transcytosis compatible with high- throughput screening (HTS).........................................................................................16 2.2 esiRNA library design and construction..................................................................20 2.3 RNAi screen...........................................................................................................23 2.4 Confirmation Screen and Small-Scale Validation Assays........................................31 II. Computational Tools to Predict Cell Type-Specific Gene Expression............................34 3. Estimating Cell Type-Specific Gene Expression through Computational Deconvolution ......................................................................................................................................... 35 v 3.0 Introduction.............................................................................................................35 3.1 Experimental approaches.......................................................................................36 3.2 Computational approaches.....................................................................................38 4. Design and Validation of the CellMapper Algorithm......................................................41 4.0 Introduction.............................................................................................................41 4.1 Development of CellMapper...................................................................................43 4.2 CellMapper can distinguish cell type-specific expression signatures from whole tissue microarray data..................................................................................................52 4.3 Discussion..............................................................................................................63 5. Applications of CellMapper...........................................................................................65 5.1 Prioritizing candidate genes in human disease loci.................................................65 5.2 Transcriptional identity of enteric glia......................................................................71 III. Appendix...................................................................................................................... 79 A. Details of Normalization and Analysis for RNAi Screen................................................80 B. Comparing CellMapper to Other Approaches...............................................................84 References.......................................................................................................................90 vi Acknowledgements I would first like to thank my advisor, Dr. Wayne Lencer, for his constant support and encouragement during my time in graduate school. Wayne has given me a remarkable amount of freedom to drive my own research projects, along with the guidance to insure that these projects were successful. I remember several years back when I approached Wayne with an idea to computationally predict which genes were broadly expressed in simple epithelial cells. Rather than persuade me against a project that was outside of his experience, he discussed the objectives and challenges with me and then put me in touch with two great collaborators – Drs. Curtis Huttenhower and Levi Waldron. With Wayne's guidance, this simple idea has since developed into an exciting paper, and left me with experience in bioinformatics and statistics that will be invaluable as I move into the next phase of academia. During graduate school, I have become fascinated with plant biology – due to the fundamental importance our green brethren have on human health and global sustainability – and I plan to move into plant research during my post- doctoral fellowship. Wayne has been an amazing mentor as I consider this next stage in my life: sharing the lessons he learned as his own diverse career path took him refugee camps in Cambodia to research labs in Boston, sending me to a national conference in plant biology to learn more about research in plants, and aiding in innumerable ways as I conducted my job search in a new field. I am leaving graduate school with a tough choice to make between several strong
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