Gradual polyploid genome evolution revealed by pan-genomic analysis of Brachypodium hybridum and its diploid progenitors.

Our understanding of polyploid genome evolution is constrained because we cannot know the exact founders of a particular polyploid. To differentiate between founder effects and post polyploidization evolution, we use a pan-genomic approach to study the allotetraploid Brachypodium hybridum and its diploid progenitors. Comparative analysis suggests that most B. hybridum whole gene presence/absence variation is part of the standing variation in its diploid progenitors. Analysis of nuclear single nucleotide variants, plastomes and k-mers associated with retrotransposons reveals two independent origins for B. hybridum, ~1.4 and ~0.14 million years ago. Examination of gene expression in the younger B. hybridum lineage reveals no bias in overall subgenome expression. Our results are consistent with a gradual accumulation of genomic changes after polyploidization and a lack of subgenome expression dominance. Significantly, if we did not use a pan-genomic approach, we would grossly overestimate the number of genomic changes attributable to post polyploidization evolution.

Two Is Better Than One: Studying Ustilago bromivora-Brachypodium Compatibility by Using a Hybrid Pathogen.

Pathogenic fungi can have devastating effects on agriculture and health. One potential challenge in dealing with pathogens is the possibility of a host jump (i.e., when a pathogen infects a new host species). This can lead to the emergence of new diseases or complicate the management of existing threats. We studied host specificity by using a hybrid fungus formed by mating two closely related fungi: Ustilago bromivora, which normally infects Brachypodium spp., and U. hordei, which normally infects barley. Although U. hordei was unable to infect Brachypodium spp., the hybrid could. These hybrids also displayed the same mating-type bias that had been observed in U. bromivora and provide evidence of a dominant spore-killer-like system on the sex chromosome of U. bromivora. By analyzing the genomic composition of 109 hybrid strains, backcrossed with U. hordei over four generations, we identified three regions associated with infection on Brachypodium spp. and 75 potential virulence candidates. The most strongly associated region was located on chromosome 8, where seven genes encoding predicted secreted proteins were identified. The fact that we identified several regions relevant for pathogenicity on Brachypodium spp. but that none were essential suggests that host specificity, in the case of U. bromivora, is a multifactorial trait which can be achieved through different subsets of virulence factors.

The 'PhenoBox', a flexible, automated, open-source plant phenotyping solution.

There is a need for flexible and affordable plant phenotyping solutions for basic research and plant breeding. We demonstrate our open source plant imaging and processing solution ('PhenoBox'/'PhenoPipe') and provide construction plans, source code and documentation to rebuild the system. Use of the PhenoBox is exemplified by studying infection of the model grass Brachypodium distachyon by the head smut fungus Ustilago bromivora, comparing phenotypic responses of maize to infection with a solopathogenic Ustilago maydis (corn smut) strain and effector deletion strains, and studying salt stress response in Nicotiana benthamiana. In U. bromivora-infected grass, phenotypic differences between infected and uninfected plants were detectable weeks before qualitative head smut symptoms. Based on this, we could predict the infection outcome for individual plants with high accuracy. Using a PhenoPipe module for calculation of multi-dimensional distances from phenotyping data, we observe a time after infection-dependent impact of U. maydis effector deletion strains on phenotypic response in maize. The PhenoBox/PhenoPipe system is able to detect established salt stress responses in N. benthamiana. We have developed an affordable, automated, open source imaging and data processing solution that can be adapted to various phenotyping applications in plant biology and beyond.

Overrepresentation Analyses of Differentially Expressed Genes in the Smut Fungus Ustilago bromivora during Saprophytic and in planta Growth.

We have established the Ustilago bromivora-Brachypodium spp. interaction as a new model pathosystem for biotrophic fungal plant infections of the head smut type (Rabe et al., 2016). In this protocol, the methodology used for comparing gene expression between saprophytic and in planta growth of the fungus is described. The experimental and analytical pipeline, how next generation RNA sequencing (Illumina RNA-Seq) analysis can be used to obtain lists of genes significantly up or down regulated in planta in comparison to axenic culture is given. Furthermore, different methods to identify functional categories that are over- or under-represented among specific classes of genes are presented.

A complete toolset for the study of Ustilago bromivora and Brachypodium sp. as a fungal-temperate grass pathosystem.

Due to their economic relevance, the study of plant pathogen interactions is of importance. However, elucidating these interactions and their underlying molecular mechanisms remains challenging since both host and pathogen need to be fully genetically accessible organisms. Here we present milestones in the establishment of a new biotrophic model pathosystem: Ustilago bromivora and Brachypodium sp. We provide a complete toolset, including an annotated fungal genome and methods for genetic manipulation of the fungus and its host plant. This toolset will enable researchers to easily study biotrophic interactions at the molecular level on both the pathogen and the host side. Moreover, our research on the fungal life cycle revealed a mating type bias phenomenon. U. bromivora harbors a haplo-lethal allele that is linked to one mating type region. As a result, the identified mating type bias strongly promotes inbreeding, which we consider to be a potential speciation driver.

The Interplay between Carbon Availability and Growth in Different Zones of the Growing Maize Leaf.

Plants assimilate carbon in their photosynthetic tissues in the light. However, carbon is required during the night and in nonphotosynthetic organs. It is therefore essential that plants manage their carbon resources spatially and temporally and coordinate growth with carbon availability. In growing maize (Zea mays) leaf blades, a defined developmental gradient facilitates analyses in the cell division, elongation, and mature zones. We investigated the responses of the metabolome and transcriptome and polysome loading, as a qualitative proxy for protein synthesis, at dusk, dawn, and 6, 14, and 24 h into an extended night, and tracked whole-leaf elongation over this time course. Starch and sugars are depleted by dawn in the mature zone, but only after an extension of the night in the elongation and division zones. Sucrose (Suc) recovers partially between 14 and 24 h into the extended night in the growth zones, but not the mature zone. The global metabolome and transcriptome track these zone-specific changes in Suc. Leaf elongation and polysome loading in the growth zones also remain high at dawn, decrease between 6 and 14 h into the extended night, and then partially recover, indicating that growth processes are determined by local carbon status. The level of Suc-signaling metabolite trehalose-6-phosphate, and the trehalose-6-phosphate:Suc ratio are much higher in growth than mature zones at dusk and dawn but fall in the extended night. Candidate genes were identified by searching for transcripts that show characteristic temporal response patterns or contrasting responses to carbon starvation in growth and mature zones.

Phytohormone sensing in the biotrophic fungus Ustilago maydis - the dual role of the transcription factor Rss1.

The phenolic compound salicylic acid (SA) is a key signalling molecule regulating local and systemic plant defense responses, mainly against biotrophs. Many microbial organisms, including pathogens, share the ability to degrade SA. However, the mechanism by which they perceive SA is unknown. Here we show that Ustilago maydis, the causal agent of corn smut disease, employs a so far uncharacterized SA sensing mechanism. We identified and characterized the novel SA sensing regulator, Rss1, a binuclear zinc cluster protein with dual functions as putative SA receptor and transcriptional activator regulating genes important for SA and tryptophan degradation. Rss1 represents a major component in the identified SA sensing pathway during the fungus' saprophytic stage. However, Rss1 does not have a detectable impact on virulence. The data presented in this work indicate that alternative or redundant sensing cascades exist that regulate the expression of SA-responsive genes in U. maydis during its pathogenic development.

Comparative analyses of C4 and C3 photosynthesis in developing leaves of maize and rice.

C4 and C3 photosynthesis differ in the efficiency with which they consume water and nitrogen. Engineering traits of the more efficient C4 photosynthesis into C3 crops could substantially increase crop yields in hot, arid conditions. To identify differences between C4 and C3 photosynthetic mechanisms, we profiled metabolites and gene expression in the developing leaves of Zea mays (maize), a C4 plant, and Oryza sativa (rice), a C3 plant, using a statistical method named the unified developmental model (UDM). Candidate cis-regulatory elements and transcription factors that might regulate photosynthesis were identified, together with differences between C4 and C3 nitrogen and carbon metabolism. The UDM algorithms could be applied to analyze and compare development in other species. These data sets together with community viewers to access and mine them provide a resource for photosynthetic research that will inform efforts to engineer improvements in carbon fixation in economically valuable grass crops.

Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize.

The diversity of metabolites found in plants is by far greater than in most other organisms. Metabolic profiling techniques, which measure many of these compounds simultaneously, enabled investigating the regulation of metabolic networks and proved to be useful for predicting important agronomic traits. However, little is known about the genetic basis of metabolites in crops such as maize. Here, a set of 289 diverse maize inbred lines was genotyped with 56,110 SNPs and assayed for 118 biochemical compounds in the leaves of young plants, as well as for agronomic traits of mature plants in field trials. Metabolite concentrations had on average a repeatability of 0.73 and showed a correlation pattern that largely reflected their functional grouping. Genome-wide association mapping with correction for population structure and cryptic relatedness identified for 26 distinct metabolites strong associations with SNPs, explaining up to 32.0% of the observed genetic variance. On nine chromosomes, we detected 15 distinct SNP-metabolite associations, each of which explained more then 15% of the genetic variance. For lignin precursors, including p-coumaric acid and caffeic acid, we found strong associations (P values to ) with a region on chromosome 9 harboring cinnamoyl-CoA reductase, a key enzyme in monolignol synthesis and a target for improving the quality of lignocellulosic biomass by genetic engineering approaches. Moreover, lignin precursors correlated significantly with lignin content, plant height, and dry matter yield, suggesting that metabolites represent promising connecting links for narrowing the genotype-phenotype gap of complex agronomic traits.

Genomic and metabolic prediction of complex heterotic traits in hybrid maize.

Maize is both an exciting model organism in plant genetics and also the most important crop worldwide for food, animal feed and bioenergy production. Recent genome-wide association and metabolic profiling studies aimed to resolve quantitative traits to their causal genetic loci and key metabolic regulators. Here we present a complementary approach that exploits large-scale genomic and metabolic information to predict complex, highly polygenic traits in hybrid testcrosses. We crossed 285 diverse Dent inbred lines from worldwide sources with two testers and predicted their combining abilities for seven biomass- and bioenergy-related traits using 56,110 SNPs and 130 metabolites. Whole-genome and metabolic prediction models were built by fitting effects for all SNPs or metabolites. Prediction accuracies ranged from 0.72 to 0.81 for SNPs and from 0.60 to 0.80 for metabolites, allowing a reliable screening of large collections of diverse inbred lines for their potential to create superior hybrids.

A guide to using MapMan to visualize and compare Omics data in plants: a case study in the crop species, Maize.

MapMan is a software tool that supports the visualization of profiling data sets in the context of existing knowledge. Scavenger modules generate hierarchical and essentially non-redundant gene ontologies ('mapping files'). An ImageAnnotator module visualizes the data on a gene-by-gene basis on schematic diagrams ('maps') of biological processes. The PageMan module uses the same ontologies to statistically evaluate responses at the pathway or processes level. The generic structure of MapMan also allows it to be used for transcripts, proteins, enzymes and metabolites. MapMan was developed for use with Arabidopsis, but has already been extended for use with several other species. These tools are available as downloadable and web-based versions. After providing an introduction to the scope and use of MapMan, we present a case study where MapMan is used to analyse the transcriptional response of the crop plant maize to diurnal changes and an extension of the night. We then explain how MapMan can be customized to visually and systematically compare responses in maize and Arabidopsis. These analyses illustrate how MapMan can be used to analyse and compare global transcriptional responses between phylogenetically distant species, and show that analyses at the level of functional categories are especially useful in cross-species comparisons.