Exploring Genome Structure and Gene Regulation Related to Virulence in Fungal Phytopathogens Using Next Generation Sequencing Techniques

Over the last decade, a technological revolution has provided enormous advances in the knowledge of complex biological processes largely enabled by the development of next-generation sequencing (NGS) techniques. Applications of NGS include studies of entire genomes, characterization of the entire transcriptome (RNA-Seq), and detection of protein-DNA binding sites (ChIP-Seq). The cost of sequencing a fungal genome, for example, has decreased from more than one hundred thousand dollars to currently only three thousand dollars. With the development of the applications and the affordable cost, NGS is changing the way biologists designing and carrying out research. This dissertation describes developed analysis pipelines of NGS data in the field of fungal phytopathogens using four different projects as examples. In a genome comparison project, sequenced short reads are de novo assembled to form a genome draft, then gene models are predicted either ab initial or assisted by RNA-Seq, followed by the comparison between genomes at different resolutions such as the nucleotide level and the genome structural level. Two chapters in this dissertation serve as examples of our genome comparison pipeline put to work to address biological questions. In Chapter 2, the Alternaria arborescens sequences of the unique conditionally dispensable chromosome (CDC) were separated from essential chromosomes (EC) using a novel bioinformatics approach. A pair-wise comparison between the CDC and ECs showed that CDC sequences had significant variation and that it may have been originally acquired through a horizontal gene transfer event. In Chapter 4, seven field isolates of Magnaporthe oryzae were sequenced and their genome content compared. Over 10,000 SNP and Indel locations were identified as well as genes under strong positive selection, which are considered potential virulence related genes. While in a RNA-Seq analysis pipeline, sequence reads are first assembled de novo or mapped to a reference genome, and the expression level for individual genes in each sequencing library is calculated to identify differentially expressed genes. Chapter 3 describes a RNA-Seq analysis project, in which the transcriptome profile in the dollar spot pathosystem has been sequenced using a combination of Illumina and Roche 454 NGS technologies. A large number of genes were found up-regulated during the interaction between Sclerotinia homoeocarpa and Agrostis stolonifera with some having annotations suggesting their roles in virulence related processes. With regard to protein-DNA binding, reads from ChIP-Seq experiment are mapped to the reference genome and the “peak regions” of mapped reads are identified as candidate binding regions, within which binding motifs are predicted. Chapter 5 describes the identifications of the binding sites and motifs of the M. oryzae transcription factor MoCRZ1 using a combination of ChIP-chip and microarray data, and then the prediction accuracy is improved by a novel approach utilizing the spatial distribution pattern of the candidate motifs. Finally, the last chapter summarizes a large scale mutagenesis project to identify two avirulence genes in M. oryzae by generating random mutants, followed by a pathogenicity screen on rice cultivars containing the corresponding resistance genes. Although imperfections and challenges remain, this dissertation shows four successful NGS applications in fungal phytopathogens. With the continued development of sequencing techniques and bioinformatics tools, NGS based projects with more sophisticated experimental designs will undoubtedly produce larger and more accurate data to biologists in the near future.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Plant Pathology

Grantor dc:publisher

The Ohio State University

Year dc:date

2013

Author dc:creator

• Hu, Jinnan

Contributors dc:contributor

• Mitchell, Thomas

• Bioinformatics
• Plant Pathology
• Molecular Biology

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=osu1366213390

OAI identifier oai:identifier

oai:etd.ohiolink.edu:osu1366213390