Population diversity and genomics of the fungal pathogen of canola Leptosphaeria maculans

Patel, Dhwani Apurva (2016). Population diversity and genomics of the fungal pathogen of canola Leptosphaeria maculans PhD Thesis, School of Agriculture and Food Sciences, The University of Queensland. doi:10.14264/uql.2016.224

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
s4151052_final_thesis.pdf Thesis (open access) application/pdf 6.82MB 0

Author Patel, Dhwani Apurva
Thesis Title Population diversity and genomics of the fungal pathogen of canola Leptosphaeria maculans
Formatted title
Population diversity and genomics of the fungal pathogen of canola Leptosphaeria maculans
School, Centre or Institute School of Agriculture and Food Sciences
Institution The University of Queensland
DOI 10.14264/uql.2016.224
Publication date 2016-05-09
Thesis type PhD Thesis
Supervisor Jacqueline Batley
Total pages 192
Language eng
Subjects 0605 Microbiology
0604 Genetics
Formatted abstract
Canola (Brassica napus) is an important agricultural crop in Australia. Its value as an agricultural commodity has dramatically increased over the past few years to >$2000 million (AUD) in 2015. However, the production of this prosperous crop is threatened by up to 34 different pests, including fungal, bacterial and viral pathogens. Diseases caused by these pathogens lead to substantial crop losses that collectively amount to $130 million (AUD) each year. Leptosphaeria maculans (blackleg) is a ubiquitous ascomycete fungus that is the major causal agent of disease on canola plants. It is called blackleg due to its necrotrophic effects that cause stem canker at the base of the stem during the last stages of infection. When canola was first introduced to Australia as an agricultural crop in the 1970s, blackleg disease led to almost 90% crop losses, threatening to drive the nascent canola industry in Australia to the ground. In recent years, crop losses still amount to $76.6 million (AUD) per annum. Therefore, it is imperative to devise methods to control the devastating effects of this pathogen to protect this economically significant crop. In order to do so, we must decipher the genomic content that drives this pathogen to cause large-scale infections in the field.

Blackleg disease is a major concern not only in Australia, but also in other parts of the world such as Europe and Canada. Over the past few years, scientists have made significant advances in decoding the genome of this pathogen. It has been established that L. maculans interacts in a gene- for-gene manner with its host. It is composed of disease-causing avirulence (Avr) genes that are specifically recognised by the corresponding resistance (R) gene in the host plant. The specific location and characterisation of the Avr genes AvrLm1, AvrLm6, AvrLm4-7, AvrLm11, AvrLmJ1, AvrLm2 and AvrLm3 has been determined. Furthermore, the reference genome for this pathogen was sequenced in 2011. The reference genome based on the strain v23.1.3 is 45.12 Mb and is scaffolded onto 76 supercontigs. It was reported to be bipartite in nature, composed of AT and GC- rich blocks and riddled with truncated copies of transposable elements (TEs) that were affected by Repeat-Induced Point (RIP) mutations. The availability of a reference genome has greatly assisted in designing bioinformatics tools to analyse the genomic content of this pathogen. Here we contribute to the growing pool of knowledge of blackleg genomics.

This thesis begins by shedding light on the population diversity of this pathogen in Australia. We used Single Nucleotide Polymorphisms (SNPs) and sampled a large variety of isolates from different canola-growing regions across Australia. We were able to conclude that the Australian blackleg population is panmictic in nature, where members of the population interact randomly with one another, leading to high diversity via sexual reproduction. Increased genetic diversity amongst the population contributes significantly to increase the evolutionary potential of this pathogen that empowers it to overcome host resistance swiftly. Some clonal subpopulations were also observed, segregated by location of sampling. This indicated that isolates may be affected by different conditions such as temperature and rainfall that may promote asexual reproduction within subpopulations. The panmictic nature of the population was supported by the results of linkage disequilibrium and principle component analyses. The former displayed no association amongst markers and the latter, no groupings based on parameters associated with samples such as state sample was obtained from, stubble cultivar isolated from, stubbled resistance source or year of isolation.

Next we moved to study at the genomic level of the pathogen and conducted a gene loss analysis on nine isolates, which belonged to the differential set for which we possessed phenotypic information. This experiment was based on the hypothesis that Avr genes are deleted or lost in blackleg to avoid host R gene detection and confer virulence. We aimed to discover novel avirulence effectors through this method. Our results supported our previous findings in that conservation or loss of genomic content in the samples was not associated with any particular parameter. Two supercontigs, SC_13 and SC_12 displayed maximum and clustered gene loss in the dataset. Of these, SC_13 gene loss was annotated and found to be a part of a secondary metabolite cluster. Secondary metabolite clusters are disposable in nature, which explained the presence and absence of that set of genes amongst the nine isolates. Genes lost on SC_12 were concluded to be a part of a ‘volatile’ group of genes whose absence does not affect the fitness of the pathogen. There was also functional redundancy for genes that were lost, as results of infection studies on susceptible cultivars could not be correlated to loss of any particular gene. Other aspects such as effects of TEs and RIP mutations also play a role in the loss of genes. This study highlighted regions of the genome under selection pressure and the diversity in genomic content in isolates of blackleg.

Data obtained from other bioinformatics analysis such as SNP prediction and Presence/Absence Variation (PAV) was pooled with gene loss data to form a mega-resource to fill gaps in information about the genome. Firstly, this enabled us to identify three novel avirulence effector candidates A, B and C. Of these, gene C was a candidate for AvrLm5. All these displayed the common traits shared by effectors such as encoding small secreted proteins (SSPs), being upregulated during infection and located in an AT-rich region that contains no other predicted genes. Candidates A and B also displayed a high degree of conservation within a 12 amino acid motif, a feature that is uncommon amongst blackleg effectors. Both candidates also shared partial homology at the same motif with AvrLmJ1. One candidate was not annotated in the reference sequence but high LD in the region of interest on SC_13, gene loss associated with AvrLm8 virulence profile on cultivars and results from SignalP and Open Reading Frame analyses, led us to conclude the high probability of a novel effector being present in that region.

The experiments detailed in this thesis confirmed the presence of high genetic and genomic diversity in isolates of blackleg that enable it to overcome host selection pressure and rapidly cause infection. They also opened up several intriguing avenues of results that warrant further study. In this manner our results contributed to the pool of knowledge about blackleg. Information about the inner workings of this pathogen will greatly assist in the design of more robust, disease-resistant cultivars and preventing future crop losses in Australia.
Keyword Blackleg
Gene Loss
Population diversity
Next generation sequencing
Presence absence variation

Document type: Thesis
Collections: UQ Theses (RHD) - Official
UQ Theses (RHD) - Open Access
Version Filter Type
Citation counts: Google Scholar Search Google Scholar
Created: Wed, 04 May 2016, 11:09:00 EST by Dhwani Patel on behalf of Learning and Research Services (UQ Library)