UNIVERSITY OF CALIFORNIA Los Angeles Computational tools for the analysis of high-throughput genome-scale sequence data A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Molecular Biology by David Adrian Lopez, Jr. 2016 © Copyright by David Adrian Lopez, Jr. 2016 ABSTRACT OF THE DISSERTATION Computational tools for the analysis of high-throughput genome-scale sequence data by David Adrian Lopez, Jr. Doctor of Philosophy in Molecular Biology University of California, Los Angeles, 2016 Professor Matteo Pellegrini, Chair As high-throughput sequence data becomes increasingly used in a variety of fields, there is a growing need for computational tools that facilitate analyzing and interpreting the sequence data to extract biological meaning. To date, several computational tools have been developed to analyze raw and processed sequence data in a number of contexts. However, many of these tools primarily focus on well-studied, reference organisms, and in some cases, such as the visualization of molecular signatures in expression data, there is a scarcity or complete absence of tools. Furthermore, the compendium of genome-scale data in publicly accessible databases can be leveraged to inform new studies. The focus of this dissertation is the development of computational tools and methods to analyze high-throughput genome-scale sequence data, as well as applications in mammalian, algal, and bacterial systems. Chapter 1 introduces the challenges of analyzing high-throughput sequence data. Chapter 2 presents the Signature Visualization Tool (SaVanT), a framework to visualize molecular signatures in user- ii generated expression data on a sample-by-sample basis. This chapter demonstrates that SaVanT can use immune activation signatures to distinguish patients with different types of acute infections (influenza A and bacterial pneumonia), and determine the primary cell types underlying different leukemias (acute myeloid and acute lymphoblastic) and skin disorders. Chapter 3 describes the Algal Functional Annotation Tool, which biologically interprets large gene lists, such as those derived from differential expression experiments. This tool integrates data from several pathway, ontology, and protein domain databases and performs enrichment testing on gene lists for several algal genomes. Chapter 4 describes a survey of the Chlamydomonas reinhardtii transcriptome and methylome across various stages of its sexual life cycle. This chapter discusses the identification and function of 361 gamete-specific and 627 zygote-specific genes, the first base-resolution methylation map of C. reinhardtii, and the changes in chloroplast methylation throughout key stages of its life cycle. Chapter 5 presents a comparative genomics approach to identifying previously uncharacterized bacterial microcompartment (BMC) proteins. Based on genomic proximity of genes in 131 fully-sequenced bacterial genomes, this chapter describes new putative microcompartments and their function. iii The dissertation of David Adrian Lopez, Jr. is approved. Jason Ernst Eleazar Eskin Sabeeha Merchant Todd O. Yeates Matteo Pellegrini, Committee Chair University of California, Los Angeles 2016 iv DEDICATION This thesis is dedicated to my family, for their constant love, support, and encouragement without which this work would not have been possible v TABLE OF CONTENTS Abstract of the dissertation ii Committee page iv Dedication page v Acknowledgments vii Vita viii Chapter 1: Computational methods and tools to analyze high-throughput 1 sequence data References 5 Chapter 2: SaVanT -- a web-based tool for the sample-level visualization 7 of molecular signatures in gene expression profiles (Lopez et al., In Preparation) 8 References 27 Chapter 3: Algal Functional Annotation Tool – a web-based analysis suite 30 to functionally interpret large gene lists using integrated annotation and expression data (Lopez et al., BMC Bioinformatics 2011) 31 References 39 Chapter 4: Dynamic changes in the transcriptome and methylome of 41 Chlamydomonas reinhardtii throughout its life cycle (Lopez et al., Plant Physiology 2015) 42 References 53 Chapter 5: Using comparative genomics to uncover new kinds of 56 protein-based metabolic organelles in bacteria (Jorda, Lopez et al., Protein Science 2013) 57 References 70 vi ACKNOWLEDGMENTS Firstly, I thank my mentor, Matteo Pellegrini, for igniting the spark and for providing an environment of academic freedom, trust, and support to carry out my research projects. His approaches to research have been inspirational and have taught me how to frame and pursue scientific questions. A special thanks to my committee members – Jason Ernst, Eleazar Eskin, Sabeeha Merchant, and Todd Yeates – for their constant guidance. In particular, I appreciate the years of collaboration and for pointing me toward several fellowship and training opportunities. I also thank Tama Hasson for encouraging me to continue my studies, as well as providing extensive mentorship and support throughout my undergraduate career and the graduate school application process. The staff of the Undergraduate Research Center played a critical role in my success as an early researcher. I am thankful to all of the members of the Pellegrini lab for the countless ideas, discussions, and fun times. I’d like to especially thank Shawn Cokus for his mentorship throughout my graduate career. The work in this dissertation would not have been possible without many, many collaborators. In particular, I’d like to thank Mark Hildebrand, Jesse Traller, James Umen, Takashi Hamaji, and Robert Modlin. My funding sources have been instrumental in giving me the freedom to explore my research interests. I want to thank the Genome Analysis Training Program, the Eugene V. Cota Robles Fellowship, as well as the Fred and Judith Eiseling Doctoral Fellowship for funding the work throughout my graduate career. Finally, but certainly not least, I’d like to thank my family for their love and support throughout the years. The emotional, financial, and intellectual support of my parents – David and Leticia Lopez – enabled me to take the path that has led me here. Their encouragement, compassion, and example have helped in ways I cannot describe in words. I thank my brother, Andy Lopez, for always encouraging me and being my ally. I also thank Leyla Naimi for the years of support and for being by my side to share all the wonderful memories. I couldn’t have done it without all of you. vii VITA EDUCATION University of California, Los Angeles Los Angeles, CA Ph.D. Candidate, Molecular, Cell, and Developmental Biology 2011-2016 Advisor: Matteo Pellegrini B.S., Molecular, Cell, and Developmental Biology 2006-2011 GRANTS AND AWARDS Fred Eiserling and Judith Lengyel Doctoral Fellowship 2014-2016 University of California, Los Angeles Human Genetics Genome Analysis Training Grant 2013-2015 National Institutes of Health (NIH) Training Grant (T32) Eugene V. Cota-Robles Fellowship 2011-2012 University of California, Los Angeles PUBLICATIONS Lopez D., Hamaji T., Kropat J., De Hoff P., Morselli M., Rubbi L., Fitz-Gibbon S., Gallaher S.D., Merchant S.S., Umen J., Pellegrini M. (2015). Dynamic changes in the transcriptome and methylome of Chlamydomonas reinhardtii throughout its life cycle. Plant Phys. 169(4):2730-2743. Orozco L.D., Morselli M., Rubbi L., Guo W., Go J., Shi H., Lopez D., Furlotte N.A., Bennett B.J., Farber C.R., Ghazalpour A., Zhang M.Q., Bahous R., Rozen R., Lusis A.J., Pellegrini M. (2015). Epigenome-wide association of liver methylation patterns and complex metabolic traits in mice. Cell Metabolism. 21(6):905-917. Inkeles M.S., Scumpia P.O., Swindell W.R., Lopez D., Teles R.M., Graeber T.G., Meller S., Homey B., Elder J.T., Gilliet M., Modlin R.L., Pellegrini M. (2015). Comparison of molecular signatures from multiple skin diseases identifies mechanisms of immunopathogenesis. Journal of Investigative Dermatology. 135(1):151-159. Chen P.Y., Montanini B., Liao W.W., Morselli M., Jaroszewicz A., Lopez D., Ottonello S., Pellegrini M. (2014). A comprehensive resource of genomic, epigenomic and transcriptomic sequencing data for the black truffle Tuber melanosporum. Gigascience. 3:25. viii Montanini B., Chen P.Y., Morselli M., Jaroszewicz A., Lopez D., Martin F., Ottonello S., Pellegrini M. (2014) Non-exhaustive DNA methylation mediated transposon silencing in the black truffle genome, a complex fungal genome with massive repeat element content. Genome Biology. 15:411 Jorda J.*, Lopez D.*, Wheatley N.M., Yeates T.O. (2013). Using comparative genomics to uncover new kinds of protein-based metabolic organelles in bacteria. Protein Science. 22(2):179-95. Molnár I., Lopez D., Wisecaver J.H., Devarenne T.P., Weiss T.L., Pellegrini M., Hackett J.D. (2012). Bio- crude transcriptomics: Gene discovery and metabolic network reconstruction for the biosynthesis of the terpenome of the hydrocarbon oil-producing green alga, Botryococcus braunii race B (Showa). BMC Genomics. 13:576. Chodavarapu R.K., Feng S., Ding B., Simon S.A., Lopez D., Jia Y., Wang G.L., Meyers B.C., Jacobsen S.E., Pellegrini M. (2012). Transcriptome and methylome interactions in rice hybrids. Proc Natl Acad Sci. 109(30):12040-5. Lopez D., Casero D., Cokus S.J., Merchant S.S., Pellegrini M. (2011). Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data. BMC Bioinformatics. 12:282. * Authors contributed equally CONFERENCES AND