The genome sequence and effector complement of the flax rust pathogen Melampsora lini

Rust fungi cause serious yield reductions on crops, including wheat, barley, soybean, coffee, and represent real threats to global food security. Of these fungi, the flax rust pathogen Melampsora lini has been developed most extensively over the past 80 years as a model to understand the molecular mechanisms that underpin pathogenesis. During infection, M. lini secretes virulence effectors to promote disease. The number of these effectors, their function and their degree of conservation across rust fungal species is unknown. To assess this, we sequenced and assembled de novo the genome of M. lini isolate CH5 into 21,130 scaffolds spanning 189 Mbp (scaffold N50 of 31 kbp). Global analysis of the DNA sequence revealed that repetitive elements, primarily retrotransposons, make up at least 45% of the genome. Using ab initio predictions, transcriptome data and homology searches, we identified 16,271 putative protein-coding genes. An analysis pipeline was then implemented to predict the effector complement of M. lini and compare it to that of the poplar rust, wheat stem rust and wheat stripe rust pathogens to identify conserved and species-specific effector candidates. Previous knowledge of four cloned M. lini avirulence effector proteins and two basidiomycete effectors was used to optimize parameters of the effector prediction pipeline. Markov clustering based on sequence similarity was performed to group effector candidates from all four rust pathogens. Clusters containing at least one member from M. lini were further analyzed and prioritized based on features including expression in isolated haustoria and infected leaf tissue and conservation across rust species. Herein, we describe 200 of 940 clusters that ranked highest on our priority list, representing 725 flax rust candidate effectors. Our findings on this important model rust species provide insight into how effectors of rust fungi are conserved across species and how they may act to promote infection on their hosts.This work was funded by a grant from the CSIRO Transformational Biology Capability Platform to Adnane Nemri. Claire Anderson was supported by an ARC Discovery Grant (DP120104044) awarded to David A. Jones and Peter N. Dodds

The ins and outs of rust haustoria

Rust diseases caused by fungi of the order Pucciniales afflict a wide range of plants, including cereals, legumes, ornamentals, and fruit trees, and pose a serious threat to cropping systems and global food security. The obligate parasitic lifestyle of these fungi and their complex life cycles, often involving alternate hosts for the sexual and asexual stages, also make this group of pathogens of great biological interest. One of the most remarkable adaptations of rust fungi is the specialized infection structure that underpins the sustained biotrophic association with hosts; the haustorium.This work has been supported by grants from the TwoBlades corporation and the Australian research council

Comparative genomics of Australian isolates of the wheat stem rust pathogen Puccinia graminis f. sp. tritici reveals extensive polymorphism in candidate effector genes

The wheat stem rust fungus Puccinia graminis f. sp. tritici (Pgt) is one of the most destructive pathogens of wheat. In this study, a draft genome was built for a founder Australian Pgt isolate of pathotype (pt.) 21-0 (collected in 1954) by next generation DNA sequencing. A combination of reference-based assembly using the genome of the previously sequenced American Pgt isolate CDL 75-36-700-3 (p7a) and de novo assembly were performed resulting in a 92 Mbp reference genome for Pgt isolate 21-0. Approximately 13 Mbp of de novo assembled sequence in this genome is not present in the p7a reference assembly. This novel sequence is not specific to 21-0 as it is also present in three other Pgt rust isolates of independent origin. The new reference genome was subsequently used to build a pan-genome based on five Australian Pgt isolates. Transcriptomes from germinated urediniospores and haustoria were separately assembled for pt. 21-0 and comparison of gene expression profiles showed differential expression in ∼10% of the genes each in germinated spores and haustoria. A total of 1,924 secreted proteins were predicted from the 21-0 transcriptome, of which 520 were classified as haustorial secreted proteins (HSPs). Comparison of 21-0 with two presumed clonal field derivatives of this lineage (collected in 1982 and 1984) that had evolved virulence on four additional resistance genes (Sr5, Sr11, Sr27, SrSatu) identified mutations in 25 HSP effector candidates. Some of these mutations could explain their novel virulence phenotypes.Authors wish to thank the Two Blades Foundation for financial support. Part of this work was supported through access to facilities managed by Bioplatforms Australia and funded by the Australian Government National Collaborative Research Infrastructure Strategy and Education Investment Fund Super Science Initiative

Cause-Specific Neonatal Mortality at the Armed Forces Hospital, Southern Region Khamis Mushayt, Kingdom of Saudi Arabia

Abstract Objective: To document the perinatal and neonatal characteristics in a single hospital setting, to identify the main causes of neonatal deaths and to review the trends in neonatal mortality over a 6-year period. Methodology: This is a 6-year retrospective analysis of perinatal and neonatal data at the Armed Force Hospital, Southern Region, Saudi Arabia. Results: During the study period, there were 3 7,3 84 births resulting in 4,352 (11%) admissions to the neonatal intensive care unit (NICU). The average stillbirths rate was 54/1000 of the total births, and perinatal mortality rate was 9.6/1000 live births. Of the total NICU admissions, 2,698 (62%) were preterm, low-birth-weight (LBW) babies and 234 (5.4%) were extreme low birth-weight neonates (ELBW<1000gm). Overall neonatal mortality was 5.3% of the total admissions. Mortality rate was highest among ELBW babies (n=85; 36%). Prematurity-related conditions and multiple congenital anomalies accounted for the majority of deaths in the unit (61% and 44%, respectively), followed by birth asphyxia (10%). In ELBW infants, respiratory failure (45%) and grade IV intraventricular hemorrhage (40%) were the leading causes of early deaths, while sepsis accounted for 50% of late neonatal deaths. The mortality rate was significantly lower for larger neonates (10% for 1000-1500gm birth weight infants and only 3.3% of near-term neonates above 1500gm). The major cause of death was respiratory failure in smaller babies (52%) and multiple congenital anomalies in near-term infants. The presence of multiple congenital anomalies and extreme prematurity were the major contributing factors to neonatal mortality. Conclusions: There is a pressing need to study neonatal mortality to ascertain the cause of neonatal deaths in the Kingdom of Saudi Arabia

Dynamic Resource Management in Integrated NOMA Terrestrial-Satellite Networks using Multi-Agent Reinforcement Learning

This study introduces a resource allocation framework for integrated satellite-terrestrial networks to address these challenges. The framework leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to reduce time delays and improve energy efficiency. Our proposed approach utilizes a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG) to optimize user association, cache design, and transmission power control, resulting in enhanced energy efficiency. The approach comprises two phases: User Association and Power Control, where users are treated as agents, and Cache Optimization, where the satellite (Bs) is considered the agent. Through extensive simulations, we demonstrate that our approach surpasses conventional single-agent deep reinforcement learning algorithms in addressing cache design and resource allocation challenges in integrated terrestrial-satellite networks. Specifically, our proposed approach achieves significantly higher energy efficiency and reduced time delays compared to existing methods.Comment: 16, 1

The genome sequence and effector complement of the flax rust pathogen Melampsora lini

Rust fungi cause serious yield reductions on crops, including wheat, barley, soybean, coffee, and represent real threats to global food security. Of these fungi, the flax rust pathogen Melampsora lini has been developed most extensively over the past 80 years as a model to understand the molecular mechanisms that underpin pathogenesis. During infection, M. lini secretes virulence effectors to promote disease. The number of these effectors, their function and their degree of conservation across rust fungal species is unknown. To assess this, we sequenced and assembled de novo the genome of M. lini isolate CH5 into 21, 130 scaffolds spanning 189 Mbp (scaffold N50 of 31 kbp). Global analysis of the DNA sequence revealed that repetitive elements, primarily retrotransposons, make up at least 45% of the genome. Using ab initio predictions, transcriptome data and homology searches, we identified 16, 271 putative protein-coding genes. An analysis pipeline was then implemented to predict the effector complement of M. lini and compare it to that of the poplar rust, wheat stem rust and wheat stripe rust pathogens to identify conserved and species-specific effector candidates. Previous knowledge of four cloned M. lini avirulence effector proteins and two basidiomycete effectors was used to optimize parameters of the effector prediction pipeline. Markov clustering based on sequence similarity was performed to group effector candidates from all four rust pathogens. Clusters containing at least one member from M. lini were further analyzed and prioritized based on features including expression in isolated haustoria and infected leaf tissue and conservation across rust species. Herein, we describe 200 of 940 clusters that ranked highest on our priority list, representing 725 flax rust candidate effectors. Our findings on this important model rust species provide insight into how effectors of rust fungi are conserved across species and how they may act to promote infection on their hosts

Genome analysis and avirulence gene cloning using a high-density RADseq linkage map of the flax rust fungus, Melampsora lini

Agroinfiltration of avirulence gene constructs. The response of flax cultivars and near-isogenic lines to expression of avirulence gene candidates (AvrM14-A, AvrM14-B and AvrL2-A) using Agrobacterium tumefaciens-mediated transient transformation. (PDF 2637 kb

Influence of Shear-Thinning Rheology on the Mixing Dynamics in Taylor-Couette Flow

Non‐Newtonian rheology can have a significant effect on mixing efficiency, which remains poorly understood. The effect of shear‐thinning rheology in a Taylor‐Couette reactor is studied using a combination of particle image velocimetry and flow visualization. Shear‐thinning is found to alter the critical Reynolds numbers for the formation of Taylor vortices and the higher‐order wavy instability, and is associated with an increase in the axial wavelength. Strong shear‐thinning and weak viscoelasticity can also lead to sudden transitions in wavelength as the Reynolds number is varied. Finally, it is shown that shear‐thinning causes an increase in the mixing time within vortices, due to a reduction in their circulation, but enhances the axial dispersion of fluid in the reactor

Towards the genetic architecture of seed lipid biosynthesis and accumulation in Arabidopsis thaliana

We report the quantitative genetic analysis of seed oil quality and quantity in six Arabidopsis thaliana recombinant inbred populations, in which the parent accessions were from diverse geographical origins, and were selected on the basis of variation for seed oil content and lipid composition. Although most of the biochemical steps involved in lipid biosynthesis are known and the key genes have been identified, the regulation of the processes that results in the final oil composition and total amount is not understood. By using physically anchored markers it was possible to compare results across populations. A total of 219 quantitative trait loci (QTLs) were identified, of which 81 were significant at P<0.001. Some of these colocalise with QTLs identified previously, but many novel QTLs were also identified. The results highlight the importance of studying traits in multiple populations, which will lead to a better understanding of the contribution that natural variation makes to the genetic architecture of a phenotype