Genome analysis of the necrotrophic fungal pathogens Sclerotinia sclerotiorum and Botrytis cinerea

Sclerotinia sclerotiorum and Botrytis cinerea are closely related necrotrophic plant pathogenic fungi notable for their wide host ranges and environmental persistence. These attributes have made these species models for understanding the complexity of necrotrophic, broad host-range pathogenicity. Despite their similarities, the two species differ in mating behaviour and the ability to produce asexual spores. We have sequenced the genomes of one strain of S. sclerotiorum and two strains of B. cinerea. The comparative analysis of these genomes relative to one another and to other sequenced fungal genomes is provided here. Their 38–39 Mb genomes include 11,860–14,270 predicted genes, which share 83% amino acid identity on average between the two species. We have mapped the S. sclerotiorum assembly to 16 chromosomes and found large-scale co-linearity with the B. cinerea genomes. Seven percent of the S. sclerotiorum genome comprises transposable elements compared t

Dynamic Effective Connectivity of Inter-Areal Brain Circuits

Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities

5th generation district heating and cooling systems: A review of existing cases in Europe

Abstract This article investigates 40 thermal networks in operation in Europe that are able to cover both the heating and cooling demands of buildings by means of distributed heat pumps installed at the customer substations. The technology of thermal networks that work at a temperature close to the ground, can strongly contribute to the decarbonisation of the heating and cooling sector and furthermore exploit a multitude of low temperature heat sources. Nevertheless, the nomenclature used in literature shows that misinterpretations could easily result when comparing the different concepts of thermal networks that operate at a temperature level lower than traditional district heating. The scope of this work is to revise the definitions encountered and to introduce an unambiguous definition of Fifth-Generation District Heating and Cooling networks. A drawback-benefit analysis is presented to identify the pros and cons of such technology. The survey on the current networks shows that on average three Fifth-Generation District Heating and Cooling systems per year have entered the heating and cooling market in the last decade. Pioneer countries in such technology are Germany and Switzerland. For some networks, the assessed Linear Heating Power Demand Density results are lower than the feasibility threshold adopted in traditional district heating. High performances and low non-renewable primary energy factors are achieved in systems that exploit a very high share of renewable or urban excess heat sources. With respect to traditional district heating, the surveyed pumping energy consumptions result one order of magnitude higher, whereas the implemented control strategies can be completely different, leading the network temperature to float freely

Fully Automated Myocardial Strain Estimation from Cardiovascular MRI–tagged Images Using a Deep Learning Framework in the UK Biobank

Purpose: To demonstrate the feasibility and performance of a fully automated deep learning framework to estimate myocardial strain from short-axis cardiac magnetic resonance tagged images. Methods and Materials: In this retrospective cross-sectional study, 4508 cases from the UK Biobank were split randomly into 3244 training and 812 validation cases, and 452 test cases. Ground truth myocardial landmarks were defined and tracked by manual initialization and correction of deformable image registration using previously validated software with five readers. The fully automatic framework consisted of 1) a convolutional neural network (CNN) for localization, and 2) a combination of a recurrent neural network (RNN) and a CNN to detect and track the myocardial landmarks through the image sequence for each slice. Radial and circumferential strain were then calculated from the motion of the landmarks and averaged on a slice basis. Results: Within the test set, myocardial end-systolic circumferential Green strain errors were -0.001 +/- 0.025, -0.001 +/- 0.021, and 0.004 +/- 0.035 in basal, mid, and apical slices respectively (mean +/- std. dev. of differences between predicted and manual strain). The framework reproduced significant reductions in circumferential strain in diabetics, hypertensives, and participants with previous heart attack. Typical processing time was ~260 frames (~13 slices) per second on an NVIDIA Tesla K40 with 12GB RAM, compared with 6-8 minutes per slice for the manual analysis. Conclusions: The fully automated RNNCNN framework for analysis of myocardial strain enabled unbiased strain evaluation in a high-throughput workflow, with similar ability to distinguish impairment due to diabetes, hypertension, and previous heart attack.Comment: accepted in Radiology Cardiothoracic Imagin

Earth resources. A continuing bibliography with indexes, issue 23

This bibliography lists 226 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1, 1979 and September 30, 1979. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Small-scale gene duplications played a major role in the recent evolution of wheat chromosome 3B

Background: Bread wheat is not only an important crop, but its large (17 Gb), highly repetitive, and hexaploid genome makes it a good model to study the organization and evolution of complex genomes. Recently, we produced a high quality reference sequence of wheat chromosome 3B (774 Mb), which provides an excellent opportunity to study the evolutionary dynamics of a large and polyploid genome, specifically the impact of single gene duplications.Results: We find that 27 % of the 3B predicted genes are non-syntenic with the orthologous chromosomes of Brachypodium distachyon, Oryza sativa, and Sorghum bicolor, whereas, by applying the same criteria, non-syntenic genes represent on average only 10 % of the predicted genes in these three model grasses. These non-syntenic genes on 3B have high sequence similarity to at least one other gene in the wheat genome, indicating that hexaploid wheat has undergone massive small-scale interchromosomal gene duplications compared to other grasses. Insertions of non-syntenic genes occurred at a similar rate along the chromosome, but these genes tend to be retained at a higher frequency in the distal, recombinogenic regions. The ratio of non-synonymous to synonymous substitution rates showed a more relaxed selection pressure for non-syntenic genes compared to syntenic genes, and gene ontology analysis indicated that non-syntenic genes may be enriched in functions involved in disease resistance.Conclusion: Our results highlight the major impact of single gene duplications on the wheat gene complement and confirm the accelerated evolution of the Triticeae lineage among grasses

Empirical Measurement and Model Validation of Infrared Spectra of Contaminated Surfaces

The goal of this thesis was to validate predicted infrared spectra of liquid contaminated surfaces from a micro-scale bi-directional reflectance distribution function (BRDF) model through the use of empirical measurement. Liquid contaminated surfaces generally require more sophisticated radiometric modeling to numerically describe surface properties. The Digital Image and Remote Sensing Image Generation (DIRSIG) model utilizes radiative transfer modeling to generate synthetic imagery for a variety of applications. Aside from DIRSIG, a micro-scale model known as microDIRSIG has been developed as a rigorous ray tracing physics-based model that could predict the BRDF of geometric surfaces that are defined as micron to millimeter resolution facets. The model offers an extension from the conventional BRDF models by allowing contaminants to be added as geometric objects to a micro-facet surface. This model was validated through the use of Fourier transform infrared spectrometer measurements. A total of 18 different substrate and contaminant combinations were measured and compared against modeled outputs. The substrates used in this experiment were wood and aluminum that contained three different paint finishes. The paint finishes included no paint, Krylon ultra-flat black, and Krylon glossy black. A silicon based oil (SF96) was measured out and applied to each surface to create three different contamination cases for each surface. Radiance in the longwave infrared region of the electromagnetic spectrum was measured by a Design and Prototypes (D\&P) Fourier transform infrared spectrometer and a Physical Sciences Inc. Adaptive Infrared Imaging Spectroradiometer (AIRIS). The model outputs were compared against the measurements quantitatively in both the emissivity and radiance domains. A temperature emissivity separation (TES) algorithm had to be applied to the measured radiance spectra for comparison with the microDIRSIG predicted emissivity spectra. The model predicted emissivity spectra was also forward modeled through a DIRSIG simulation for comparisons to the radiance measurements. The results showed a promising agreement for homogeneous surfaces with liquid contamination that could be well characterized geometrically. Limitations arose in substrates that were modeled as homogeneous surfaces, but had spatially varying artifacts due to uncertainties with contaminant and surface interactions. There is high desire for accurate physics based modeling of liquid contaminated surfaces and this validation framework may be extended to include a wider array of samples for more realistic natural surfaces that are often found in real world scenarios

The genome and gene editing system of sea barleygrass provide a novel platform for cereal domestication and stress tolerance studies

The tribe Triticeae provides important staple cereal crops and contains elite wild species with wide genetic diversity and high tolerance to abiotic stresses. Sea barleygrass (Hordeum marinum Huds.), a wild Triticeae species, thrives in saline marshlands and is well known for its high tolerance to salinity and waterlogging. Here, a 3.82-Gb high-quality reference genome of sea barleygrass is assembled de novo, with 3.69 Gb (96.8%) of its sequences anchored onto seven chromosomes. In total, 41 045 high-confidence (HC) genes are annotated by homology, de novo prediction, and transcriptome analysis. Phylogenetics, non-synonymous/synonymous mutation ratios (Ka/Ks), and transcriptomic and functional analyses provide genetic evidence for the divergence in morphology and salt tolerance among sea barleygrass, barley, and wheat. The large variation in post-domestication genes (e.g. IPA1 and MOC1) may cause interspecies differences in plant morphology. The extremely high salt tolerance of sea barleygrass is mainly attributed to low Na+ uptake and root-to-shoot translocation, which are mainly controlled by SOS1, HKT, and NHX transporters. Agrobacterium-mediated transformation and CRISPR/Cas9-mediated gene editing systems were developed for sea barleygrass to promote its utilization for exploration and functional studies of hub genes and for the genetic improvement of cereal crops

Control of divergent noncoding transcription in Saccharomyces cerevisiae

The regulation of gene expression underlies all cellular processes and fundamentally enables complexity of eukaryotic organisms. Aberrant expression of noncoding RNAs can compromise normal gene expression. Gene promoters are inherently bidirectional and generate divergent noncoding RNAs along with protein-coding messenger RNAs. Chromatin and RNA turnover pathways limit expression of noncoding RNAs, but how sequence-specific transcription factors regulate divergent noncoding transcription and promoter directionality is not well understood. Here, I investigate how divergent transcription is repressed at highly expressed genes in Saccharomyces cerevisiae. I find that the sequence-specific transcription factor Rap1 limits divergent noncoding transcription at a large fraction of its target genes. Rap1 safeguards normal gene expression by limiting aberrant transcription that overlaps with neighbouring loci. Divergent RNAs initiate at or extremely close to Rap1 binding sites, indicating that Rap1 limits initiation of transcription from divergent core promoters. Stable binding of Rap1 near cryptic promoters is required and sufficient to suppress divergent transcription. Silencing cofactors or transcriptional coactivators associated with Rap1 are not required for repression of noncoding RNAs at promoters. In contrast, a small region within the Rap1 carboxy-terminal domain is required for repression of divergent transcription and affects interaction between Rap1 and the RSC chromatin remodeller. RSC and Rap1 regulate divergent transcription at Rap1-regulated gene promoters in distinct ways. Promoter output shifts from unidirectional to bidirectional transcription in the absence of Rap1, which is partially suppressed after co-depletion of Rap1 and RSC. RSC activity is not strictly required for divergent transcription suggesting that additional regulators also play important roles. I propose that certain sequence-specific transcription factors limit the access of transcription machinery and coactivators to divergent core promoters by steric hindrance, thereby providing directionality towards productive transcription of coding genes