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Development and Application of Next-Generation Sequencing Methods to Profile Cellular Translational Dynamics by Sang Young Chun A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2018 Doctoral Committee: Assistant Professor Ryan E. Mills, Chair Assistant Professor Jeffrey M. Kidd Professor Mats Ljungman Professor Alexey I. Nesvizhskii Associate Professor Peter K. Todd Sang Young Chun [email protected] ORCID id: 0000-0002-4954-9446 © Sang Young Chun 2018 All Rights Reserved For my family. ii ACKNOWLEDGEMENTS Foremost, I would like to thank my advisor Ryan Mills whose guidance, support and mentorship were instrumental to my professional development. Moreover, I am deeply appreciative of his enthusiasm for video games and other esotery that provided needed respite from the stresses of research. I am especially grateful for the advice and insight provided by my committee members, Jeff Kidd, Mats Ljungman, Alexey Nesvizhskii, and Peter Todd. In addition, I would like to express my deepest gratitude to my former graduate advisors, Arul Chinnaiyan and John Kim, whose guidance and advice were critical to my early development as a graduate student. Finally, I am thankful for my past mentors, Hye Sook Kim, Susan Lyons, Duyen Dang, and Long Dang, their advice and support helped spark my interest in bioinformatics. I am indebted to the many colleagues and collaborators that I have had the privilege to work with over my graduate research career. From the Todd lab, I am grateful for the insight and expertise provided by Caitlin Rodriguez, her collaboration has informed much of my thesis. From the Chinnaiyan lab, I am especially thankful for the guidance provided by Catie Grasso, she helped me understand that efficient programming and lazy programming are often the same. I am also thankful to Mallory Freeberg from the Kim lab for her peer mentorship and support early in my graduate student career; in many ways, she served as a model for what I had aspired to achieve as a bioinformatician and student. I am also grateful for the guidance and support of Kim lab members Amelia Alessi, Allison Billi, Amanda Day, Vishal Khivansara, Arun Manoharan, Natasha Weiser, and Danny Yang. From the Mills lab, I had the distinct privilege to work alongside great iii researchers, compatriots, and friends. I would like to thank Gargi Dayama and Arthur Zhou for making clear the importance of learning to plot outside of Excel. I am thankful to Xuefang Zhao for leading the way as the first student to graduate from the lab, and her ever-present humor. I am grateful to Yifan Wang for being an inferior D.va main, and for establishing the tail end of the distribution for Mills lab time-to-doctorate. I would also like to thank Marcus Sherman for his guidance on all things Python, Alex Weber for her good-natured patience at my jokes, and Catherine Barnier for absolutely not being a Fire Noodles challenge cheater. Finally, I am thankful to have worked alongside Akima George, Nan Lin, Chen Sun, Fan Zhang, and Zhenning Zhang. I am extremely grateful for Brian Athey and his enthusiastic support over the years, as well as Margit Burmeister and Dan Burns; as a longtime student, I was able to experience firsthand how their devotion to the success of their students, like myself, led to the growth of the department to what it is today. In addition, I would like to thank Jeff de Wet for guiding my first steps as a programmer, and Julia Eussen for her tireless advocacy and enthusiasm. I would also like to take a moment to acknowledge the many friends that I made through my time at Michigan. I am especially grateful for the support of my friends Craig Biwer, Mallory Freeberg, Kathryn Iverson, Sunit Jain, Marianne Juarez, Andy Kong, Lisa LaPointe, Datta Mellacheruvu, Bryan Moyers, Arji Mufti, Lee Sam, Conner Sandefur, Avinash Shanmugam, Kraig Stevenson, Brendan Veeneman, Artur Veloso, Amanda Wilkinson, John Wilkinson, and Casey Wright. Finally, I would like to thank my friends and family, without whose love and support none of this journey would have been possible. My partners in crime, Aash Bhatt, Matthew Jonovich, Jeff Keeler, Rod Rahimi, and Andrew Woodrow. My parents John and Keum Chun, my sister Jamie Chun, and my brother Danny Chun and his wife Brandie. Most importantly, my family Erin Chun, Elijah Chun, and Eleanor Chun: thank you. iv TABLE OF CONTENTS DEDICATION ................................................................................................................................ ii ACKNOWLEDGEMENTS ........................................................................................................... iii LIST OF FIGURES ....................................................................................................................... vi LIST OF TABLES ....................................................................................................................... viii LIST OF APPENDICES ................................................................................................................ ix LIST OF ABBREVIATIONS ..........................................................................................................x ABSTRACT ................................................................................................................................. xiii CHAPTER 1: INTRODUCTION ....................................................................................................1 CHAPTER 2: SPECTRAL PROFILING OF UORF TRANSLATION IN NON- DIFFERENTIATED AND DIFFERENTIATED NEUROBLASTOMA CELLS ..................22 CHAPTER 3: TRANSLATIONAL PROFILING OF UORFS IN A CELLULAR MODEL OF NEURONAL DIFFERENTIATION .......................................................................................35 CHAPTER 4: INTEGRATED PROFILING OF CHIMERIC JUNCTIONS WITH RIBOSOME ASSOCIATED TRANSLATION IN PROSTATE CANCER ................................................72 CHAPTER 5: CONCLUDING REMARKS AND FUTURE DIRECTIONS ..............................95 APPENDICES ............................................................................................................................103 LITERATURE CITED ................................................................................................................142 v LIST OF FIGURES Figure 1.1 Gene expression and protein synthesis regulation ...................................................... 20 Figure 1.2 Adjustment of RPF alignment position ...................................................................... 21 Figure 2.1 SPECtre pipeline and tri-nucleotide periodicity ......................................................... 31 Figure 2.2 Comparative analysis of SPECtre against previously published methods ................. 32 Figure 2.3 Examples of SPECtre results and runtime comparison to RiboTaper ........................ 34 Figure 3.1 Retinoic acid treatment induces neuronal differentiation of SH-SY5Y cells ............. 59 Figure 3.2 Differential translation and translational efficiency in SH-SY5Y cells ..................... 61 Figure 3.3 Computational prediction and filtering of upstream-initiated ORFs .......................... 64 Figure 3.4 Characterization of predicted ORFs ........................................................................... 65 Figure 3.5 Validation of SPECtre scored upstream-initiated ORFs ............................................ 66 Figure 3.6 Translational efficiency of CDS with predicted uORFs ............................................. 68 Figure 3.7 Characterization of predicted ORF regulation and downstream CDS ....................... 70 Figure 4.1 Schematic of the juncRAT alignment and analytical pipeline. .................................. 86 Figure 4.2 Integrative chimeric gene fusion breakpoint alignment ............................................. 87 Figure 4.3 Paired-end library support of STAR-FUSION events ................................................ 88 Figure 4.4 Number of spanning reads by breakpoint source and profiling method ..................... 89 Figure 4.5 Coverage over the ETV1-HNRNPA2B1 breakpoint junction ................................... 90 Figure 4.6 Coverage over the TXRND1-UTP20 breakpoint junction ......................................... 91 Figure 4.7 Coverage over the ETV1-ACSL3 breakpoint junction .............................................. 92 Figure 4.8 Coverage over the CCT7-DYNC1H1 breakpoint junction ........................................ 93 Figure 4.9 Ribosome profiling validation of junction translation ................................................ 94 Figure A.1. Read length distribution of RPFs aligned to ACTB in mESC................................ 118 Figure A.2. Distribution of SPECtre scores over ACTB after weighted re-sampling ............... 119 Figure B.1 Molecular function gene set enrichment based on mRNA rank-change analysis ... 125 Figure B.2 Cellular component gene set enrichment based on mRNA rank-change analysis ... 126 Figure B.3 Enrichment of up-regulated gene sets based on DE analysis of RPF counts........... 127 Figure B.4 Enrichment of down-regulated gene sets based on DE analysis of RPF counts ...... 128 vi Figure B.5 Molecular function gene set enrichment based on translational efficiency ............. 129 Figure B.6 Cellular component gene set enrichment based on translational efficiency ............ 130 vii LIST OF TABLES Table A.1. Number of reads remaining at each stage of