Comparative Gene Expression Analysis Reveals Mechanism of Pinus contorta Response to the Fungal Pathogen Dothistroma septosporum

Comparative transcriptomics reveals divergence in pathogen response gene families amongst 20 forest tree species

Forest trees provide critical ecosystem services for humanity that are under threat due to ongoing global change. Measuring and characterizing genetic diversity are key to understanding adaptive potential and developing strategies to mitigate negative consequences arising from climate change. In the area of forest genetic diversity, genetic divergence caused by large-scale changes at the chromosomal level has been largely understudied. In this study, we used the RNA-seq data of 20 co-occurring forest trees species from genera including Acer, Alnus, Amelanchier, Betula, Cornus, Corylus, Dirca, Fraxinus, Ostrya, Populus, Prunus, Quercus, Ribes, Tilia, and Ulmus sampled from Upper Peninsula of Michigan. These data were used to infer the origin and maintenance of gene family variation, species divergence time, as well as gene family expansion and contraction. We identified a signal of common whole genome duplication events shared by core eudicots. We also found rapid evolution, namely fast expansion or fast contraction of gene families, in plant-pathogen interaction genes amongst the studied diploid species. Finally, the results lay the foundation for further research on the genetic diversity and adaptive capacity of forest trees, which will inform forest management and conservation policies.

Beyond the genomes of Fulvia fulva (syn. Cladosporium fulvum) and Dothistroma septosporum: New insights into how these fungal pathogens interact with their host plants

Fulvia fulva and Dothistroma septosporum are closely related apoplastic pathogens with similar lifestyles but different hosts: F. fulva is a pathogen of tomato, whilst D. septosporum is a pathogen of pine trees. In 2012, the first genome sequences of these pathogens were published, with F. fulva and D. septosporum having highly fragmented and near-complete assemblies, respectively. Since then, significant advances have been made in unravelling their genome architectures. For instance, the genome of F. fulva has now been assembled into 14 chromosomes, 13 of which have synteny with the 14 chromosomes of D. septosporum, suggesting these pathogens are even more closely related than originally thought. Considerable advances have also been made in the identification and functional characterization of virulence factors (e.g., effector proteins and secondary metabolites) from these pathogens, thereby providing new insights into how they promote host colonization or activate plant defence responses. For example, it has now been established that effector proteins from both F. fulva and D. septosporum interact with cell-surface immune receptors and co-receptors to activate the plant immune system. Progress has also been made in understanding how F. fulva and D. septosporum have evolved with their host plants, whilst intensive research into pandemics of Dothistroma needle blight in the Northern Hemisphere has shed light on the origins, migration, and genetic diversity of the global D. septosporum population. In this review, we specifically summarize advances made in our understanding of the F. fulva-tomato and D. septosporum-pine pathosystems over the last 10 years.

Chromosome-level assembly of the Phytophthora agathidicida genome reveals adaptation in effector gene families

Phytophthora species are notorious plant pathogens, with some causing devastating tree diseases that threaten the survival of their host species. One such example is Phytophthora agathidicida, the causal agent of kauri dieback - a root and trunk rot disease that kills the ancient, iconic and culturally significant tree species, Agathis australis (New Zealand kauri). A deeper understanding of how Phytophthora pathogens infect their hosts and cause disease is critical for the development of effective treatments. Such an understanding can be gained by interrogating pathogen genomes for effector genes, which are involved in virulence or pathogenicity. Although genome sequencing has become more affordable, the complete assembly of Phytophthora genomes has been problematic, particularly for those with a high abundance of repetitive sequences. Therefore, effector genes located in repetitive regions could be truncated or missed in a fragmented genome assembly. Using a combination of long-read PacBio sequences, chromatin conformation capture (Hi-C) and Illumina short reads, we assembled the P. agathidicida genome into ten complete chromosomes, with a genome size of 57 Mb including 34% repeats. This is the first Phytophthora genome assembled to chromosome level and it reveals a high level of syntenic conservation with the complete genome of Peronospora effusa, the only other completely assembled genome sequence of an oomycete. All P. agathidicida chromosomes have clearly defined centromeres and contain candidate effector genes such as RXLRs and CRNs, but in different proportions, reflecting the presence of gene family clusters. Candidate effector genes are predominantly found in gene-poor, repeat-rich regions of the genome, and in some cases showed a high degree of duplication. Analysis of candidate RXLR effector genes that occur in multicopy gene families indicated half of them were not expressed in planta. Candidate CRN effector gene families showed evidence of transposon-mediated recombination leading to new combinations of protein domains, both within and between chromosomes. Further analysis of this complete genome assembly will help inform new methods of disease control against P. agathidicida and other Phytophthora species, ultimately helping decipher how Phytophthora pathogens have evolved to shape their effector repertoires and how they might adapt in the future.

Evaluating the accuracy of variant calling methods using the frequency of parent-offspring genotype mismatch

The use of next‐generation sequencing (NGS) data sets has increased dramatically over the last decade, but there have been few systematic analyses quantifying the accuracy of the commonly used variant caller programs. Here we used a familial design consisting of diploid tissue from a single lodgepole pine (Pinus contorta) parent and the maternally derived haploid tissue from 106 full‐sibling offspring, where mismatches could only arise due to mutation or bioinformatic error. Given the rarity of mutation, we used the rate of mismatches between parent and offspring genotype calls to infer the single nucleotide polymorphism (SNP) genotyping error rates of FreeBayes, HaplotypeCaller, SAMtools, UnifiedGenotyper, and VarScan. With baseline filtering HaplotypeCaller and UnifiedGenotyper yielded more SNPs and higher error rates by one to two orders of magnitude, whereas FreeBayes, SAMtools and VarScan yielded lower numbers of SNPs and more modest error rates. To facilitate comparison between variant callers we standardized each SNP set to the same number of SNPs using additional filtering, where UnifiedGenotyper consistently produced the smallest proportion of genotype errors, followed by HaplotypeCaller, VarScan, SAMtools, and FreeBayes. Additionally, we found that error rates were minimized for SNPs called by more than one variant caller. Finally, we evaluated the performance of various commonly used filtering metrics on SNP calling. Our analysis provides a quantitative assessment of the accuracy of five widely used variant calling programs and offers valuable insights into both the choice of variant caller program and the choice of filtering metrics, especially for researchers using non‐model study systems.

Apoplastic effector candidates of a foliar forest pathogen trigger cell death in host and non-host plants

Forests are under threat from pests, pathogens, and changing climate. A major forest pathogen worldwide is the hemibiotroph Dothistroma septosporum, which causes dothistroma needle blight (DNB) of pines. While D. septosporum uses effector proteins to facilitate host infection, it is currently unclear whether any of these effectors are recognised by immune receptors to activate the host immune system. Such information is needed to identify and select disease resistance against D. septosporum in pines. We predicted and investigated apoplastic D. septosporum candidate effectors (DsCEs) using bioinformatics and plant-based experiments. We discovered DsCEs that trigger cell death in the angiosperm Nicotiana spp., indicative of a hypersensitive defence response and suggesting their recognition by immune receptors in non-host plants. In a first for foliar forest pathogens, we developed a novel protein infiltration method to show that tissue-cultured pine shoots can respond with a cell death response to a DsCE, as well as to a reference cell death-inducing protein. The conservation of responses across plant taxa suggests that knowledge of pathogen-angiosperm interactions may also be relevant to pathogen-gymnosperm interactions. These results contribute to our understanding of forest pathogens and may ultimately provide clues to disease immunity in both commercial and natural forests.