Eukaryotic Plant Pathogen Detection Through High Throughput Dna/Rna Sequencing Data Analysis
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EUKARYOTIC PLANT PATHOGEN DETECTION THROUGH HIGH THROUGHPUT DNA/RNA SEQUENCING DATA ANALYSIS By ANDRES S. ESPINDOLA Bachelor of Science in Biotechnology Engineering Escuela Politécnica del Ejército Quito, Ecuador 2009 Master of Science in Entomology and Plant Pathology Oklahoma State University Stillwater, Oklahoma 2013 Submitted to the Faculty of the Graduate College of the Oklahoma State University in partial fulfillment of the requirements for the Degree of DOCTOR OF PHILOSOPHY December, 2016 EUKARYOTIC PLANT PATHOGEN DETECTION THROUGH HIGH THROUGHPUT DNA/RNA SEQUENCING DATA ANALYSIS Thesis Approved: Dr. Carla Garzon Thesis Adviser Dr. William Schneider Dr. Stephen Marek Dr. Hassan Melouk ii ACKNOWLEDGEMENTS I would like to express my sincere gratitude to all the people who made possible the completion of my thesis research. Most importantly to my advisor Dr. Carla Garzon for her continuous support, guidance and motivation. She was a great support throughout my PhD. research and thesis writing. I would like to express my deepest gratitude to the members of my advisory committee: Dr. William Schneider, Dr. Stephen Maren and Dr. Hassan Melouk, for their guidance, insightful comments and encouragement. I want to thank the Department of Entomology and Plant Pathology at Oklahoma State University for keeping an excellent environment for the students and professors. This is a great advantage that has helped me to succeed on my research and thesis writing. Thanks to my fellow lab-mates for keeping a competitive and at the same time very friendly environment full of enriching discussions and productive working hours. I would like to thank my wife Patricia Acurio, who has been extremely helpful throughout my PhD., her support, patience, love and encouragement were crucial to succeed completing my degree. Last but not least, I would like to thank my parents, Isabel Camacho & Edison Espindola and my sister, Carolina Espindola for their support and encouragement that helped me to stay strong and productive during this important stage of my life. iii Acknowledgements reflect the views of the author and are not endorsed by committee members or Oklahoma State University. Name: ANDRES SEBASTIAN ESPINDOLA CAMACHO Date of Degree: DECEMBER, 2016 Title of Study: EUKARYOTIC PLANT PATHOGEN DETECTION THROUGH HIGH THROUGHPUT DNA/RNA SEQUENCING DATA ANALYSIS Major Field: PLANT PATHOLOGY Abstract: Plant pathogen detection is crucial for developing appropriate management techniques. A variety of tools are available for rapid plant pathogen detection. Most tools rely on unique features of the pathogen to detect its presence. Immunoassays rely on unique proteins while genetic approaches rely on unique DNA signatures. However, most of these tools can detect a limited number of pathogens at once. E-probe Diagnostics Nucleic acid Analysis (EDNA) is a bioinformatic tool originally designed as a theoretical approach to detect multiple plant pathogens at once. EDNA uses metagenomic databases and bioinformatics to infer the presence/absence of plant pathogens in a given sample. Additionally, EDNA relies on a continuous design and curation of unique signatures termed e-probes. EDNA has been successfully validated in viral, bacterial and eukaryotic plant pathogens. However, most of these validations have been performed solely at the species level and only using DNA sequencing. My thesis involved the refinement of EDNA to increase its detection scope to include plant pathogens at the strain/isolate level. Additional refinements included its increasing EDNA’s capacity to use transcriptomic analysis to detect actively infecting plant pathogens and metabolic pathways. Actively infecting/growing plant pathogen detection was performed by using Slerotinia minor as an eukaryotic model system. We sequenced and annotated the genome of S. minor to be able to use its genome for e-probe generation. In vitro detection of actively growing S. minor was successfully achieved using EDNA for RNA sequencing analysis. However, actively infecting S. minor in peanut was non-detectable. EDNA’s capacity to detect the aflatoxin metabolic pathway was also assesed. Actively producing aflatoxin A. flavus strains (AF70) were successfully used to differentially detect the production of aflatoxin when A. flavus grows in an environment conducive for the production of aflatoxin (maize). Finally, EDNA’s detection scope was assesed with eukaryotic strains having very low genetic diversity within its species (Pythium aphanidermatum). We were able to successfully discriminate P. aphanidermatum P16 strain from P. aphanidermatum BR444, concomitantly, these two strains were differentiated from other related species (Globisporangium irregulare and Pythium deliense) in the same detection run trial. iv TABLE OF CONTENTS CHAPTER I ...................................................................................................................... 1 I INTRODUCTION AND OBJECTIVES ................................................................ 1 Objectives .................................................................................................................... 6 Literature cited............................................................................................................ 6 CHAPTER II ................................................................................................................... 10 II LITERATURE REVIEW...................................................................................... 10 The plant microbiome: microbial diversity and interactions ................................... 10 DNA sequencing: past, present and insights into the future ..................................... 12 First generation sequencing .................................................................................. 12 Second generation sequencing .............................................................................. 14 Third generation sequencing ................................................................................. 18 DNA/RNA–omics in plants ........................................................................................ 20 Metagenomics and community composition ........................................................ 20 Metatranscriptomics and community function ..................................................... 21 EDNA in Plant Pathology ..................................................................................... 22 Model organisms in this study .................................................................................. 23 Pythium aphanidermatum ..................................................................................... 23 Sclerotinia minor .................................................................................................. 28 Aspergillus flavus .................................................................................................. 30 Literature cited.......................................................................................................... 33 v CHAPTER III ................................................................................................................. 47 III GENOME SEQUENCING AND COMPARATIVE GENOMICS OF SCLEROTINIA MINOR, THE CAUSAL AGENT OF SCLEROTINIA BLIGHT PROVIDES INSIGHTS INTO ITS EVOLUTION AND INFECTION STRATEGY .. 47 Abstract ..................................................................................................................... 47 Introduction............................................................................................................... 48 Experimental Procedures.......................................................................................... 51 Fungal culture preparation and inoculation .......................................................... 51 Genome sequence and assembly ........................................................................... 52 Genome annotation ............................................................................................... 52 Phylogenetic analysis ............................................................................................ 53 Phylogenomic analysis.......................................................................................... 53 Carbohydrate active enzymes annotation ............................................................. 54 Pectate lyase protein modeling ............................................................................. 54 Results/Discussion .................................................................................................... 55 Genome annotation ............................................................................................... 55 Orthologs............................................................................................................... 56 CAZymes analysis ................................................................................................ 57 Oxalic acid ............................................................................................................ 59 Phylogenomics of the Leotiomycetes ................................................................... 60 Phylogenetic analysis ............................................................................................ 61 Acknowledgements .................................................................................................... 62 Literature cited.........................................................................................................