Christine Sambles

The genome sequence and genetic diversity of European ash (Fraxinus excelsior) trees reveals the species’ varying susceptibility to ash dieback. Woodlands and forests around the world are increasingly susceptible to the spread of pests and pathogens resulting from climate change and global trade. In particular, ash trees across Europe and North America are currently threatened by the fungal disease ash dieback and infestation by the emerald ash borer beetle, respectively. Against this background, Richard Buggs and colleagues report the first genome sequence of an ash tree, the European ash Fraxinus excelsior, and the re-sequencing of 37 F. excelsior trees from across Europe. They find a number of genetic variants associated with reduced susceptibility to disease, and use these for an assessment of the susceptibility of host populations in an area newly under threat from the pathogen. On the basis of transcriptomic markers, they predict that ash trees in the UK will prove to be less susceptible to ash dieback than ash trees in Denmark. Ash trees (genus Fraxinus, family Oleaceae) are widespread throughout the Northern Hemisphere, but are being devastated in Europe by the fungus Hymenoscyphus fraxineus, causing ash dieback, and in North America by the herbivorous beetle Agrilus planipennis1,2. Here we sequence the genome of a low-heterozygosity Fraxinus excelsior tree from Gloucestershire, UK, annotating 38,852 protein-coding genes of which 25% appear ash specific when compared with the genomes of ten other plant species. Analyses of paralogous genes suggest a whole-genome duplication shared with olive (Olea europaea, Oleaceae). We also re-sequence 37 F. excelsior trees from Europe, finding evidence for apparent long-term decline in effective population size. Using our reference sequence, we re-analyse association transcriptomic data3, yielding improved markers for reduced susceptibility to ash dieback. Surveys of these markers in British populations suggest that reduced susceptibility to ash dieback may be more widespread in Great Britain than in Denmark. We also present evidence that susceptibility of trees to H. fraxineus is associated with their iridoid glycoside levels. This rapid, integrated, multidisciplinary research response to an emerging health threat in a non-model organism opens the way for mitigation of the epidemic.

BACKGROUND: Downy mildews are the most speciose group of oomycetes and affect crops of great economic importance. So far, there is only a single deeply-sequenced downy mildew genome available, from Hyaloperonospora arabidopsidis. Further genomic resources for downy mildews are required to study their evolution, including pathogenicity effector proteins, such as RxLR effectors. Plasmopara halstedii is a devastating pathogen of sunflower and a potential pathosystem model to study downy mildews, as several Avr-genes and R-genes have been predicted and unlike Arabidopsis downy mildew, large quantities of almost contamination-free material can be obtained easily. RESULTS: Here a high-quality draft genome of Plasmopara halstedii is reported and analysed with respect to various aspects, including genome organisation, secondary metabolism, effector proteins and comparative genomics with other sequenced oomycetes. Interestingly, the present analyses revealed further variation of the RxLR motif, suggesting an important role of the conservation of the dEER-motif. Orthology analyses revealed the conservation of 28 RxLR-like core effectors among Phytophthora species. Only six putative RxLR-like effectors were shared by the two sequenced downy mildews, highlighting the fast and largely independent evolution of two of the three major downy mildew lineages. This is seemingly supported by phylogenomic results, in which downy mildews did not appear to be monophyletic. CONCLUSIONS: The genome resource will be useful for developing markers for monitoring the pathogen population and might provide the basis for new approaches to fight Phytophthora and downy mildew pathogens by targeting core pathogenicity effectors.

In Arabidopsis thaliana, changes in metabolism and gene expression drive increased drought tolerance and initiate diverse drought avoidance and escape responses. To address regulatory processes that link these responses, we set out to identify genes that govern early responses to drought. To do this, a high-resolution time series transcriptomics data set was produced, coupled with detailed physiological and metabolic analyses of plants subjected to a slow transition from well-watered to drought conditions. A total of 1815 drought-responsive differentially expressed genes were identified. The early changes in gene expression coincided with a drop in carbon assimilation, and only in the late stages with an increase in foliar abscisic acid content. To identify gene regulatory networks (GRNs) mediating the transition between the early and late stages of drought, we used Bayesian network modeling of differentially expressed transcription factor (TF) genes. This approach identified AGAMOUS-LIKE22 (AGL22), as key hub gene in a TF GRN. It has previously been shown that AGL22 is involved in the transition from vegetative state to flowering but here we show that AGL22 expression influences steady state photosynthetic rates and lifetime water use. This suggests that AGL22 uniquely regulates a transcriptional network during drought stress, linking changes in primary metabolism and the initiation of stress responses.

We report production of chlorophyll f and chlorophyll d in the cyanobacterium Chlorogloeopsis fritschii cultured under near-infrared and natural light conditions. C. fritschii produced chlorophyll f and chlorophyll d when cultured under natural light to a high culture density in a 20 L bubble column photobioreactor. In the laboratory, the ratio of chlorophyll f to chlorophyll a changed from 1:15 under near-infrared, to an undetectable level of chlorophyll f under artificial white light. The results provide support that chlorophylls f and d are both red-light inducible chlorophylls in C. fritschii.