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As we celebrate the fiftieth anniversary of NASA's Apollo missions, images of Earth simulated with the ECMWF Integrated Forecasting System (IFS) are visually compared with pictures collected during space missions of the past five decades, in particular from the Apollo missions (1968-72). The numerical weather reforecasts use the latest version of the IFS and are initialized from (re)analysis data, which provide our current best representation of the atmospheric state for any given date back to the 1950s. Visible images of our planet are produced from the IFS with a simple simulator whose main inputs are the solar fluxes at the top of the atmosphere. First, a comparison to recent imagery from deep space illustrates the high level of performance of the IFS on recent dates. Then, the validation of the IFS against photographs taken by Apollo 11 and 17 both in-flight and from the lunar surface exhibits a significant level of agreement, despite the absence or very limited number of satellite observations available. This short study confirms that the combination of high-quality initial conditions with a modern numerical weather prediction model can yield reasonably accurate reforecasts of global meteorological conditions, especially cloud systems, for dates as far back as the late 1960s. [ABSTRACT FROM AUTHOR]

A new parameterization able to diagnose lightning flash densities is proposed for the ECMWF Integrated Forecasting System, including its tangent-linear and adjoint versions. Total lightning densities are expressed as a function of hydrometeors contents, convective available potential energy, and cloud-base height output by the convective parameterization. Potential future applications range from the computation of NO x emissions by lightning in atmospheric chemistry models, severe convection forecasting, and data assimilation. In this study, a decade-long experiment is used to calibrate the simulated global annual mean flash density against the LIS/Optical Transient Detector (OTD) climatological value. On the seasonal and continental scales, the new parameterization is shown to agree well with the LIS/OTD observations. In forecast mode, output lightning densities are found to be almost independent of the horizontal resolution used in the model. Decade-long experiments also show that the new parameterization gives better results overall than the main existing lightning parameterizations designed for global models. Sensitivity experiments using its adjoint version are also performed to assess its potential for the future assimilation of lightning observations in the ECMWF 4D-Var system. [ABSTRACT FROM AUTHOR]

The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families–genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts. [ABSTRACT FROM AUTHOR]

Background: Microbial genetic diversity is often investigated via the comparison of relatively similar 16S molecules through multiple alignments between reference sequences and novel environmental samples using phylogenetic trees, direct BLAST matches, or phylotypes counts. However, are we missing novel lineages in the microbial dark universe by relying on standard phylogenetic and BLAST methods? If so, how can we probe that universe using alternative approaches? We performed a novel type of multi-marker analysis of genetic diversity exploiting the topology of inclusive sequence similarity networks. Results: Our protocol identified 86 ancient gene families, well distributed and rarely transferred across the 3 domains of life, and retrieved their environmental homologs among 10 million predicted ORFs from human gut samples and other metagenomic projects. Numerous highly divergent environmental homologs were observed in gut samples, although the most divergent genes were over-represented in non-gut environments. In our networks, most divergent environmental genes grouped exclusively with uncultured relatives, in maximal cliques. Sequences within these groups were under strong purifying selection and presented a range of genetic variation comparable to that of a prokaryotic domain. Conclusions: Many genes families included environmental homologs that were highly divergent from cultured homologs: in 79 gene families (including 18 ribosomal proteins), Bacteria and Archaea were less divergent than some groups of environmental sequences were to any cultured or viral homologs. Moreover, some groups of environmental homologs branched very deeply in phylogenetic trees of life, when they were not too divergent to be aligned. These results underline how limited our understanding of the most diverse elements of the microbial world remains, and encourage a deeper exploration of natural communities and their genetic resources, hinting at the possibility that still unknown yet major divisions of life have yet to be discovered. Reviewers: This article was reviewed by Eugene Koonin, William Martin and James McInerney. [ABSTRACT FROM AUTHOR]

The experimental device previously used to study the hydromechanical behaviour of individual fractures on a laboratory scale, was adapted to make it possible to measure flow through porous rock mass samples in addition to fracture flows. A first series of tests was performed to characterize the hydromechanical behaviour of the fracture individually as well as the porous matrix (sandstone) comprising the fracture walls. A third test in this series was used to validate the experimental approach. These tests showed non-linear evolution of the contact area on the fracture walls with respect to effective normal stress. Consequently, a non-linear relationship was noted between the hydraulic aperture on the one hand, and the effective normal stress and mechanical opening on the other hand. The results of the three tests were then analysed by numerical modelling. The VIPLEF/HYDREF numerical codes used take into account the dual-porosity of the sample (fracture + rock matrix) and can be used to reproduce hydromechanical loading accurately. The analyses show that the relationship between the hydraulic aperture of the fracture and the mechanical closure has a significant effect on fracture flow rate predictions. By taking simultaneous measurements of flow in both fracture and rock matrix, we were able to carry out a global evaluation of the conceptual approach used. [ABSTRACT FROM AUTHOR]

Four-dimensional variational data assimilation (4D-Var) experiments with 6-hourly rain gauge accumulations observed at synoptic stations (SYNOP) around the globe have been run over several months, both at high resolution in an ECMWF operations-like framework and at lower resolution with the reference observational coverage reduced to surface pressure data only, as would be expected in early twentieth-century periods. The key aspects of the technical implementation of rain gauge data assimilation in 4D-Var are described, which include the specification of observation errors, bias correction procedures, screening, and quality control. Results from experiments indicate that the positive impact of rain gauges on forecast scores remains limited in the operations-like context because of their competition with all other observations already available. In contrast, when only synoptic station surface pressure observations are assimilated in the data-poor control experiment, the additional assimilation of rain gauge measurements substantially improves not only surface precipitation scores, but also analysis and forecast scores of temperature, geopotential, wind, and humidity at most atmospheric levels and for forecast ranges up to 10 days. The verification against Meteosat infrared imagery also shows a slight improvement in the spatial distribution of clouds. This suggests that assimilating rain gauge data available during data-sparse periods of the past might help to improve the quality of future reanalyses and subsequent forecasts. [ABSTRACT FROM AUTHOR]

All evolutionary biologists are familiar with evolutionary units that evolve by vertical descent in a tree-like fashion in single lineages. However, many other kinds of processes contribute to evolutionary diversity. In vertical descent, the genetic material of a particular evolutionary unit is propagated by replication inside its own lineage. In what we call introgressive descent, the genetic material of a particular evolutionary unit propagates into different host structures and is replicated within these host structures. Thus, introgressive descent generates a variety of evolutionary units and leaves recognizable patterns in resemblance networks. We characterize six kinds of evolutionary units, of which five involve mosaic lineages generated by introgressive descent. To facilitate detection of these units in resemblance networks, we introduce terminology based on two notions, P3s (subgraphs of three nodes: A, B, and C) and mosaic P3s, and suggest an apparatus for systematic detection of introgressive descent. Mosaic P3s correspond to a distinct type of evolutionary bond that is orthogonal to the bonds of kinship and genealogy usually examined by evolutionary biologists. We argue that recognition of these evolutionary bonds stimulates radical rethinking of key questions in evolutionary biology (e.g., the relations among evolutionary players in very early phases of evolutionary history, the origin and emergence of novelties, and the production of new lineages). This line of research will expand the study of biological complexity beyond the usual genealogical bonds, revealing additional sources of biodiversity. It provides an important step to a more realistic pluralist treatment of evolutionary complexity. [ABSTRACT FROM AUTHOR]

Direct four-dimensional variational data assimilation (4D-Var) of NCEP stage IV radar and gauge precipitation observations over the eastern United States has been developed and tested in ECMWF''s global Integrated Forecasting System. This is the natural extension of earlier work using a two-step 1D++4D-Var approach. Major aspects of the implementation are described and discussed in this paper. In particular, it is found that assimilating 6-h precipitation accumulations instead of the original hourly data substantially improves the behavior of 4D-Var, especially as regards the validity of the tangent-linear assumption. The comparison of background and analysis precipitation departures demonstrates that most of the information contained in the new precipitation observations is properly assimilated. Experiments run over the periods April--May and September--October 2009 also show that local precipitation forecasts become significantly better for ranges up to 12 h, which indicates that a genuine precipitation analysis can now be obtained over the eastern United States. Geopotential, temperature, moisture, and wind forecast scores are generally neutral or slightly positive for all regions of the globe and at all ranges, which is consistent with previous 1D++4D-Var results. The most crucial issue that remains unsolved is the treatment of nonprecipitating model background occurrences because of the corresponding absence of sensitivity in the linearized moist physics. For the moment, only points where both model background and observations are rainy are assimilated. Operational implementation using U.S. data is planned in 2011 and one can hope that new networks of radars (and maybe rain gauges) can be added in the 4D-Var assimilation process in the future. [ABSTRACT FROM AUTHOR]

Prokaryotic evolution takes place within and between genomes, when significant amounts of genes are transferred and recombined between interacting genetic partners. These non-tree-like evolutionary processes, intertwined with events of vertical descent, lead to a massive production of unrooted trees in which branches, nodes and groupings have different biological meanings than for the rooted trees usually studied by phylogenetics. Such unrooted gene trees can not only inform us about organismal phylogeny, but also about the variety of evolutionary, genetic, functional and ecological relationships affecting a plurality of evolutionary units, at multiple levels – from genes, groups of genes, organisms and consortia, to communities. Here we introduce new notions designed to analyze unrooted trees with more depth and accuracy. We demonstrate how a clanistic perspective can significantly improve our knowledge of evolutionary processes and relationships for most evolving systems, whether they are mobile genetic elements or cellular genomes. [ABSTRACT FROM AUTHOR]

Abstract: Phylogeny, be it morphological or molecular, has long tried to explain the extant biodiversity by the Tree of Species, which is a logical consequence of strict Darwinian evolutionary principles. Through constant improvement of both methods and data sets, some parts of this diversity have actually been demonstrated to be the result of a tree-like process. For some other parts, and especially for prokaryotes, different molecular markers have, however, produced different evolutionary trees, preventing the reconstruction of such a Tree. While technical artifacts could be blamed for these discrepancies, Lateral Gene Transfers are now largely held for responsible, and their existence requires an extension of the Darwinian framework, since genetic material is not always vertically inherited from parents to offspring. Through a variety of biological processes, sometimes large parts of DNA are exchanged between phylogenetically distant contemporary organisms, especially between those sharing the same environment. While mainly concerning prokaryotes, Lateral Gene Transfers have been also demonstrated to affect eukaryotes, and even multicellular ones, like plants or animals. Most of the time, these transfers allow important adaptations and the colonisation of new niches. The quantitative and qualitative importance of genetic transfers has thus severely challenged the very existence of a universal Tree of Species, since genetic connections, at least for microbes, seem more reticulated than tree-like. Even traditional biological concepts, like the concept of species, need to be re-evaluated in the light of recent discoveries. In short, instead of focusing on a elusive universal tree, biologists are now considering the whole forest corresponding to the multiple processes of inheritance, both vertical and horizontal. This constitutes the major challenge of evolutionary biology for the years to come. To cite this article: P. Lopez, E. Bapteste, C. R. Biologies 332 (2009). [Copyright &y& Elsevier]

The propagation of electromagnetic waves emitted from ground-based meteorological radars is determined by the stratification of the atmosphere. In extreme superrefractive situations characterized by strong temperature inversions or strong vertical gradients of moisture, the radar beam can be deflected toward the ground (ducting or trapping). This phenomenon often results in spurious returned echoes and misinterpretation of radar images such as erroneous precipitation detection. In this work, a 5-yr global climatology of the frequency of superrefractive and ducting conditions and of trapping-layer base height has been produced using refractivity computations from ECMWF temperature, moisture, and pressure analyses at a 40-km horizontal resolution. The aim of this climatology is to better document how frequent such events are, which is a prerequisite for fully benefiting from radar data information for the multiple purposes of model validation, precipitation analysis, and data assimilation. First, the main climatological features are summarized for the whole globe: high- and midlatitude oceans seldom experience superrefraction or ducting whereas tropical oceans are strongly affected, especially in regions where the trade wind inversion is intense and lying near the surface. Over land, seasonal averages of superrefraction (ducting) frequencies reach 80% (40%) over tropical moist areas year-round but remain below 40% (15%) in most other regions. A particular focus is then laid on Europe and the United States, where extensive precipitation radar networks already exist. Seasonal statistics exhibit a pronounced diurnal cycle of ducting occurrences, with averaged frequencies peaking at 60% in summer late afternoon over the eastern half of the United States, the Balkans, and the Po Valley but no ducts by midday. Similarly high ducting frequencies are found over the southwestern coast of the United States at night. A potentially strong reduction of ducting occurrences with increased radar height (especially in midlatitude summer late afternoon) is evidenced by initiating refractivity vertical gradient computations from either the lowest or the second lowest model level. However, installing radar on tall towers also brings other problems, such as a possible amplification of sidelobe clutter echoes. [ABSTRACT FROM AUTHOR]

This study is a part of a wide multi-scale research based on in situ experiments and laboratory tests. The latest, radial water injections in the centre of the lower joint wall are done at constant normal stress ranging from 0 to 110 MPa and at pressures from 0 to 4 MPa. Four hydromechanical tests have been performed in the L3S laboratory on fractured limestone samples (two diaclase and two bedding plane). The measurement analysis shows a relation between the contact surface variations and the flow values inside the fracture. The hydromechanical modelling performed using 3DEC code can be improved compared with the previous analysis due to the modification of the relation between the joint hydraulic opening and the joint mechanical closure. The gap between simulations and measurements can be related to fracture asperity degradation and turbulent flow that have not been taken into account in the modelling. [ABSTRACT FROM AUTHOR]

Abstract: An assay for glucosamine-6-phosphate synthase using a yeast glucosamine-6-phosphate N-acetyltransferase 1 (GNA1) as coupling enzyme was developed. GNA1 transfers the acetyl moiety from acetyl-coenzyme A (CoA) to glucosamine-6-phosphate, releasing coenzyme A. The assay measures the production of glucosamine-6-phosphate by either following the consumption of acetyl-CoA spectrophotometrically at 230nm or quantifying the free thiol with 5,5′-dithio-bis(2-nitrobenzoic acid) (Ellman’s reagent) in a discontinuous manner. This method is simple to perform and can be adapted to a 96-well microtiter plate format, which will facilitate high-throughput inhibitor screening and mechanistic studies using purified GlmS. [Copyright &y& Elsevier]

This paper first reviews the current status, issues, and limitations of the parameterizations of atmospheric large-scale and convective moist processes that are used in numerical weather prediction and climate general circulation models. Both large-scale (resolved) and convective (subgrid scale) moist processes are dealt with. Then, the general question of the inclusion of diabatic processes in variational data assimilation systems is addressed. The focus is put on linearity and resolution issues, the specification of model and observation error statistics, the formulation of the control vector, and the problems specific to the assimilation of observations directly affected by clouds and precipitation. [ABSTRACT FROM AUTHOR]

The one- plus four-dimensional variational data assimilation (“1D+4DVAR”) method currently run in operations at ECMWF with rain-affected radiances from the Special Sensor Microwave Imager is used to study the potential impact of assimilating NCEP stage-IV analyses of hourly accumulated surface precipitation over the U.S. mainland. These data are a combination of rain gauge measurements and observations from the high-resolution Doppler Next-Generation Weather Radars. Several 1D+4DVAR experiments have been run over a month in spring 2005. First, the quality of the precipitation forecasts in the control experiment is assessed. Then, it is shown that the impact of the assimilation of the additional rain observations on global scores of dynamical fields and temperature is rather neutral, while precipitation scores are improved for forecast ranges up to 12 h. Additional 1D+4DVAR experiments in which all moisture-affected observations are removed over the United States demonstrate that the NCEP stage-IV precipitation data on their own can clearly be beneficial to the analyses and subsequent forecasts of the moisture field. This result suggests that the potential impact of precipitation observations is overshadowed by the influence of other high-quality humidity observations, in particular, radiosondes. It also confirms that the assimilation of precipitation observations has the ability to improve the quality of moisture analyses and forecasts in data-sparse regions. Finally, the limitations inherent in the current assimilation of precipitation data, their implications for the future, and possible ways of improvement are discussed. [ABSTRACT FROM AUTHOR]

Multicellular organization arose several times by convergence during the evolution of eukaryotes (e.g., in terrestrial plants, several lineages of “algae,” fungi, and metazoans). To reconstruct the evolutionary transitions between unicellularity and multicellularity, we need a proper understanding of the origin and diversification of regulatory molecules governing the construction of a multicellular organism in these various lineages. Homeodomain (HD) proteins offer a paradigm for studying such issues, because in multicellular eukaryotes, like animals, fungi and plants, these transcription factors are extensively used in fundamental developmental processes and are highly diversified. A number of large eukaryote lineages are exclusively unicellular, however, and it remains unclear to what extent this condition reflects their primitive lack of “good building blocks” such as the HD proteins. Taking advantage from the recent burst of sequence data from a wide variety of eukaryote taxa, we show here that HD-containing transcription factors were already existing and diversified (in at least two main classes) in the last common eukaryote ancestor. Although the family was retained and independently expanded in the multicellular taxa, it was lost in several lineages of unicellular parasites or intracellular symbionts. Our findings are consistent with the idea that the common ancestor of eukaryotes was complex in molecular terms, and already possessed many of the regulatory molecules, which later favored the multiple convergent acquisition of multicellularity. [ABSTRACT FROM AUTHOR]

The potential of the inclusion of two prognostic variables for cloud condensate and precipitation content in adjoint calculations has been investigated in the framework of Météo-France's operational spectral global model, ARPEGE. The tangent linear and adjoint versions of the recently developed explicit large-scale cloud and precipitation scheme have been coded and tested. In particular, the validity of the linear hypothesis has been checked when finite-size perturbations are applied to the initial model state vector. Then, the new explicit cloud and precipitation scheme and its adjoint version have been integrated in a set of sensitivity experiments. These allowed the assessment of the relative impacts of initial perturbations imposed on each model variable on the variations of various meteorological aspects of the forecast that relate either to the dynamics or to the cloud and precipitating activity of some extratropical cloud systems. [ABSTRACT FROM AUTHOR]

Provides information in a study which identified a single origin of bidirectional replication in Pyrococcus abyssi by means of in silico analyses of cumulative oligomer skew. Replication mechanisms in cumulative skew; Features of the archaeal replication origin identified in the study.

Understanding how major organismal lineages originated is fundamental for understanding processes by which life evolved. Major evolutionary transitions, like eukaryogenesis, merging genetic material from distantly related organisms, are rare events, hence difficult ones to explain causally. If most archaeal lineages emerged after massive acquisitions of bacterial genes, a rule however arises: metabolic bacterial genes contributed to all major evolutionary transitions. [ABSTRACT FROM AUTHOR]

Presents a comments on the mechanisms of DNA replication. Characteristics of the archaeal genomes; Identification of the chromosome regions; Occurrence of the skewed oligomers in the Archaea.

Suggests that the evolution of proteins should be considered a complex phenomenon than assumed by standard models. Factors that affect the function of a protein; Comment on a study that compared proteins between certain eukaryotic and prokaryotic organisms; Paradox of molecular evolution.

Recently, we uncovered the genetic components from six carbon fixation autotrophic pathways in cleaned ultrasmall size fractions from marine samples (<0.22 µm) gathered worldwide by the Tara Oceans Expedition. This first finding suggested that prokaryotic nanoorganisms, phylogenetically distantly related to the known CPR and DPANN groups, could collectively impact carbon cycling and carbon fixation across the world's ocean. To extend our mining of the functional and taxonomic microbial dark matter from the ultrasmall size fraction from the Tara Oceans Expedition, we investigated the distribution of 28 metabolic pathways associated with the cycling of carbon, methane, nitrogen, and sulfur. For all of these pathways, we report the existence not only of novel metabolic homologs in the ultrasmall size fraction of the oceanic microbiome, associated with nanoorganisms belonging to the CPR and DPANN lineages, but also of metabolic homologs exclusively found in marine host taxa belonging to other (still unassigned) microbial lineages. Therefore, we conclude that marine nanoorganisms contribute to a greater diversity of key biogeochemical cycles than currently appreciated. In particular, we suggest that oceanic nanoorganisms may be involved in a metabolic loop around Acetyl-CoA, have an underappreciated genetic potential to degrade methane, contribute to sustaining redox-reactions by producing Coenzyme F420, and affect sulfur cycling, notably as they harbor a complete suite of homologs of enzymes of the SOX system. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the origin and evolution of eukaryotes using gene similarity network tools. It says that a network displaying the similarities in proteins encoded in the genomes of 52 eubacteria, 52 archaebacteria, and 14 eukaryotic lineages is constructed. According to the statistical analysis of the network, eukaryotic genes are highly connected to either eubacterial or archaebacterial genes.

Autotrophic carbon fixation is a crucial process for sustaining life on Earth. To date, six pathways, the Calvin–Benson–Bassham cycle, the reductive tricarboxylic acid cycle, the 3-hydroxypropionate bi-cycle, the Wood–Ljungdahl pathway, the dicarboxylate/4-hydroxybutyrate cycle, and the 4-hydroxybutyrate cycle, have been described. Nano-organisms such as members of the Candidate Phyla Radiation (CPR) bacterial superphylum and the Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohalorchaeota (DPANN) archaeal superphylum could deeply impact carbon cycling and carbon fixation in ways that are still to be determined. CPR and DPANN are ubiquitous in the environment but understudied; their gene contents are not exhaustively described; and their metabolisms are not yet fully understood. Here, the completeness of each of the above pathways was quantified and tested for the presence of all key enzymes in nano-organisms from across the World Ocean. The novel marine ultrasmall prokaryotes were demonstrated to collectively harbor the genes required for carbon fixation, in particular the "energetically efficient" dicarboxylate/4-hydroxybutyrate pathway and the 4-hydroxybutyrate pathway. This contrasted with the known carbon metabolic pathways associated with CPR members in aquifers, where they are described as degraders (Castelle CJ, et al. 2015. Genomic expansion of domain archaea highlights roles for organisms from new phyla in anaerobic carbon cycling. Curr Biol. 25(6):690–701; Castelle CJ, et al. 2018. Biosynthetic capacity, metabolic variety and unusual biology in the CPR and DPANN radiations. Nat Rev Microbiol. 16(10):629–645; Anantharaman K, et al. 2016. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun. 7:13219.). Our findings suggest that nano-organisms have a broader contribution to carbon fixation and cycling than currently assumed. Furthermore, CPR and DPANN superphyla are possibly not the only nanosized prokaryotes; therefore, the discovery of new autotrophic marine nano-organisms by future single cell genomics is anticipated. [ABSTRACT FROM AUTHOR]

Background: For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. Results: We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Conclusions: Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to complement their studies, trying to identify cross-disciplinary and discipline-specific evolutionary processes. The fact that we found many process-based analogies favoring transfer from biology to linguistics further shows that certain biological methods and models have a broader scope than previously recognized. This opens fruitful paths for collaboration between the two disciplines. [ABSTRACT FROM AUTHOR]

During the pre-monsoon season (March–April–May), the eastern and northeastern parts of India, Himalayan foothills, and southern parts of India experience extensive lightning activity. Mean moisture, surface and upper-level winds, the sheared atmosphere in the lower level, and high positive values of vertically integrated moisture flux convergence (VIMFC) create favorable conditions for deep convective systems to occur, generating lightning. From mid-2018, the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) operationally introduced lightning flash density on a global scale. This study evaluates the ECMWF lightning forecasts over India during the pre-monsoon season of 2020 using the Indian Institute of Tropical Meteorology (IITM) Lightning Location Network (LLN) observation data. Qualitative and quantitative analysis of the ECMWF lightning forecast has shown that the lightning forecast with a 72-h lead time can capture the spatial and temporal variation of lightning with a 90% skill score. [ABSTRACT FROM AUTHOR]

Complex nongradual evolutionary processes such as gene remodeling are difficult to model, to visualize, and to investigate systematically. Despite these challenges, the creation of composite (or mosaic) genes by combination of genetic segments from unrelated gene families was established as an important adaptive phenomena in eukaryotic genomes. In contrast, almost no general studies have been conducted to quantify composite genes in viruses. Although viral genome mosaicism has been well-described, the extent of gene mosaicism and its rules of emergence remain largely unexplored. Applying methods from graph theory to inclusive similarity networks, and using data from more than 3,000 complete viral genomes, we provide the first demonstration that composite genes in viruses are 1) functionally biased, 2) involved in key aspects of the arm race between cells and viruses, and 3) can be classified into two distinct types of composite genes in all viral classes. Beyond the quantification of the widespread recombination of genes among different viruses of the same class, we also report a striking sharing of genetic information between viruses of different classes and with different nucleic acid types. This latter discovery provides novel evidence for the existence of a large and complex mobilome network, which appears partly bound by the sharing of genetic information and by the formation of composite genes between mobile entities with different genetic material. Considering that there are around 10E31 viruses on the planet, gene remodeling appears as a hugely significant way of generating and moving novel sequences between different kinds of organisms on Earth. [ABSTRACT FROM AUTHOR]

A new diagnostic convective closure, which is dependent on convective available potential energy (CAPE), is derived under the quasi-equilibrium assumption for the free troposphere subject to boundary layer forcing. The closure involves a convective adjustment time scale for the free troposphere and a coupling coefficient between the free troposphere and the boundary layer based on different time scales over land and ocean. Earlier studies with the ECMWF Integrated Forecasting System (IFS) have already demonstrated the model's ability to realistically represent tropical convectively coupled waves and synoptic variability with use of the 'standard' CAPE closure, given realistic entrainment rates. A comparison of low-resolution seasonal integrations and high-resolution short-range forecasts against complementary satellite and radar data shows that with the extended CAPE closure it is also possible, independent of model resolution and time step, to realistically represent nonequilibrium convection such as the diurnal cycle of convection and the convection tied to advective boundary layers, although representing the late night convection over land remains a challenge. A more in-depth regional analysis of the diurnal cycle and the closure is provided for the continental United States and particularly Africa, including comparison with data from satellites and a cloud-resolving model (CRM). Consequences for global numerical weather prediction (NWP) are not only a better phase representation of convection, but also better forecasts of its spatial distribution and local intensity. [ABSTRACT FROM AUTHOR]

Background: Increasingly, similarity networks are being used for evolutionary analyses of molecular datasets. These networks are very useful, in particular for the analysis of gene sharing, lateral gene transfer and for the detection of distant homologs. Currently, such analyses require some computer programming skills due to the limited availability of user-friendly freely distributed software. Consequently, although appealing, the construction and analyses of these networks remain less familiar to biologists than do phylogenetic approaches. Results: In order to ease the use of similarity networks in the community of evolutionary biologists, we introduce a software program, EGN, that runs under Linux or MacOSX. EGN automates the reconstruction of gene and genome networks from nucleic and proteic sequences. EGN also implements statistics describing genetic diversity in these samples, for various user-defined thresholds of similarities. In the interest of studying the complexity of evolutionary processes affecting microbial evolution, we applied EGN to a dataset of 571,044 proteic sequences from the three domains of life and from mobile elements. We observed that, in Borrelia, plasmids play a different role than in most other eubacteria. Rather than being genetic couriers involved in lateral gene transfer, Borrelia's plasmids and their genes act as private genetic goods, that contribute to the creation of genetic diversity within their parasitic hosts. Conclusion: EGN can be used for constructing, analyzing, and mining molecular datasets in evolutionary studies. The program can help increase our knowledge of the processes through which genes from distinct sources and/or from multiple genomes co-evolve in lineages of cellular organisms. [ABSTRACT FROM AUTHOR]

Escherichia coli glucosamine-6-phosphate synthase (GlmS) is a dimeric enzyme from the glutamine-dependent amidotransferases family, which catalyses the conversion of D-fructose-6-phosphate (Fru6P) and glutamine (Gln) into D-glucosamine-6-phosphate (GlcN6P) and glutamate, respectively. Extensive X-ray crystallography investigations have been reported, highlighting the importance of the dimeric association to form the sugar active site as well as significant conformational changes of the protein upon substrate and product binding. In the present work, an approach based on time-resolved noncovalent mass spectrometry has been developed to study the dynamics of GlmS subunit exchange. Using N versus N labeled proteins, the kinetics of GlmS subunit exchange was monitored with the wild-type enzyme in the presence of different substrates and products as well as with the protein bearing a key amino acid mutation specially designed to weaken the dimer interface. Determination of rate constants of subunit exchange revealed important modifications of the protein dynamics: while glutamine, glutamate, and K603A mutation accelerates subunit exchange, Fru6P and GlcN6P totally prevent it. These results are described in light of the available structural information, providing additional useful data for both the characterization of GlmS catalytic process and the design of new GlmS inhibitors. Finally, time-resolved noncovalent MS can be proposed as an additional biophysical technique for real-time monitoring of protein dynamics. [ABSTRACT FROM AUTHOR]

Congruence is a broadly applied notion in evolutionary biology used to justify multigene phylogeny or phylogenomics, as well as in studies of coevolution, lateral gene transfer, and as evidence for common descent. Existing methods for identifying incongruence or heterogeneity using character data were designed for data sets that are both small and expected to be rarely incongruent. At the same time, methods that assess incongruence using comparison of trees test a null hypothesis of uncorrelated tree structures, which may be inappropriate for phylogenomic studies. As such, they are ill-suited for the growing number of available genome sequences, most of which are from prokaryotes and viruses, either for phylogenomic analysis or for studies of the evolutionary forces and events that have shaped these genomes. Specifically, many existing methods scale poorly with large numbers of genes, cannot accommodate high levels of incongruence, and do not adequately model patterns of missing taxa for different markers. We propose the development of novel incongruence assessment methods suitable for the analysis of the molecular evolution of the vast majority of life and support the investigation of homogeneity of evolutionary process in cases where markers do not share identical tree structures. [ABSTRACT FROM AUTHOR]

Summary: The origin of many of the defining features of animal body plans, such as symmetry, nervous system, and the mesoderm, remains shrouded in mystery because of major uncertainty regarding the emergence order of the early branching taxa: the sponge groups, ctenophores, placozoans, cnidarians, and bilaterians. The “phylogenomic” approach has recently provided a robust picture for intrabilaterian relationships but not yet for more early branching metazoan clades. We have assembled a comprehensive 128 gene data set including newly generated sequence data from ctenophores, cnidarians, and all four main sponge groups. The resulting phylogeny yields two significant conclusions reviving old views that have been challenged in the molecular era: (1) that the sponges (Porifera) are monophyletic and not paraphyletic as repeatedly proposed , thus undermining the idea that ancestral metazoans had a sponge-like body plan; (2) that the most likely position for the ctenophores is together with the cnidarians in a “coelenterate” clade. The Porifera and the Placozoa branch basally with respect to a moderately supported “eumetazoan” clade containing the three taxa with nervous system and muscle cells (Cnidaria, Ctenophora, and Bilateria). This new phylogeny provides a stimulating framework for exploring the important changes that shaped the body plans of the early diverging phyla. [Copyright &y& Elsevier]

Abstract: The structures of crustacean hyperglycemic hormones (CHH) were investigated in two crabs, the coastal euryhaline crab Pachygrapsus marmoratus 1 [1] The sequences of PamCHHA XO, PamCHHB XO and PamCHHB PO have been included in the GenBank sequence database with accession numbers AY180333, AY180334 and AY180335 respectively. and the fresh water crab Potamon ibericum. 2 [2] The sequences of PoiCHH XO and PoiCHH PO have been included in the GenBank sequence database with accession numbers DQ176431 and DQ176432 respectively. The neuropeptide mRNAs were extracted from pericardial and X-organs (PO and XO), and the sequences of the cDNA encoding the hormones’ precursors were determined. The X-organ preprohormones are composed of 29 and 28 amino acid signal peptides in P. marmoratus and P. ibericum respectively, followed by 43 and 41 amino acid crustacean hyperglycemic hormone precursor related peptide (CPRP) flanking the 72 amino acid crustacean hyperglycemic hormones. A similar organization is reported for pericardial preprohormones with identical sequences for the signal peptide, the CPRP and the N-terminal sequences of CHH (1–40), but remaining sequences (41–72 and 41–71) differing considerably. In P. marmoratus two CHH cDNAs were characterized from XO and evidences were obtained for the existence of at least two forms in the PO. From our results and by comparison with other known sequences, a consensus pattern for crab pericardial CHH could be pointed out. Analysis of the data presented in this article using phylogenetic methods reveals that the two crab species studied are much closer than previously predicted. [Copyright &y& Elsevier]

We assess the ability of neural network emulators of physical parametrization schemes in numerical weather prediction models to aid in the construction of linearized models required by four‐dimensional variational (4D‐Var) data assimilation. Neural networks can be differentiated trivially, and so if a physical parametrization scheme can be accurately emulated by a neural network then its tangent‐linear and adjoint versions can be obtained with minimal effort, compared with the standard paradigms of manual or automatic differentiation of the model code. Here we apply this idea by emulating the non‐orographic gravity wave drag parametrization scheme in an atmospheric model with a neural network, and deriving its tangent‐linear and adjoint models. We demonstrate that these neural network‐derived tangent‐linear and adjoint models not only pass the standard consistency tests but also can be used successfully to do 4D‐Var data assimilation. This technique holds the promise of significantly easing maintenance of tangent‐linear and adjoint codes in weather forecasting centers, if accurate neural network emulators can be constructed. Plain Language Summary: The neural network is an algorithm developed in the field of artificial intelligence that can in principle learn the relationship between any two variables, provided you give it enough real‐world data. There are countless applications for such an algorithm in the field of weather and climate simulation. The application that we focus on here is to use the neural network as a replacement for one component of a weather simulation. Essentially, you train the neural network so that it can accurately emulate the component that it replaces. For expensive components, using the neural network emulator instead of the original can provide a significant computational saving. Other studies have already demonstrated that this technique can be applied in weather simulations. What we show here, however, is that neural networks can also be used to easily and automatically calculate the slope of the line relating the two variables in question, through a slight modification of the network. This is an essential procedure for constructing the initial conditions for weather forecasts through a process known as data assimilation. Key Points: Neural network emulators of physical parametrization schemes can be used to easily construct tangent‐linear and adjoint modelsThese neural network‐based linear models are potentially much easier to maintain compared with the traditional approachWe test these tangent‐linear and adjoint models in data assimilation experiments in a state‐of‐the‐art weather forecasting model [ABSTRACT FROM AUTHOR]

Lightning-caused wildfires are a significant contributor to burned areas, with lightning ignitions remaining one of the most unpredictable aspects of the fire environment. There is a clear connection between fuel moisture and the probability of ignition; however, the mechanisms are poorly understood and predictive methods are underdeveloped. Establishing a lightning-ignition relationship would be useful in developing a model that would complement early warning systems designed for fire control and prevention. A machine learning (ML) approach was used to define a predictive model for wildfire ignition based on lightning forecasts and environmental conditions. Three different binary classifiers were adopted: a decision tree, an AdaBoost and a Random Forest, showing promising results, with both ensemble methods (Random Forest and AdaBoost) exhibiting an out-ofsample accuracy of 78%. Data provided by a Western Australia wildfire database allowed a comprehensive verification on over 145 lightning-ignited wildfires in regions of Australia during 2016. This highlighted that in a minimum of 71% of the cases the ML models correctly predicted the occurrence of an ignition when a fire was actually initiated. The super-learner developed is planned to be used in an operational context to the enhance information connected to fire management. [ABSTRACT FROM AUTHOR]

In an attempt to advance the understanding of the Earth's weather and climate by representing deep convection explicitly, we present a global, four‐month simulation (November 2018 to February 2019) with ECMWF's hydrostatic Integrated Forecasting System (IFS) at an average grid spacing of 1.4 km. The impact of explicitly simulating deep convection on the atmospheric circulation and its variability is assessed by comparing the 1.4 km simulation to the equivalent well‐tested and calibrated global simulations at 9 km grid spacing with and without parametrized deep convection. The explicit simulation of deep convection at 1.4 km results in a realistic large‐scale circulation, better representation of convective storm activity, and stronger convective gravity wave activity when compared to the 9 km simulation with parametrized deep convection. Comparison of the 1.4 km simulation to the 9 km simulation without parametrized deep convection shows that switching off deep convection parametrization at a too coarse resolution (i.e., 9 km) generates too strong convective gravity waves. Based on the limited statistics available, improvements to the Madden‐Julian Oscillation or tropical precipitation are not observed at 1.4 km, suggesting that other Earth system model components and/or their interaction are important for an accurate representation of these processes and may well need adjusting at deep convection resolving resolutions. Overall, the good agreement of the 1.4 km simulation with the 9 km simulation with parametrized deep convection is remarkable, despite one of the most fundamental parametrizations being turned off at 1.4 km resolution and despite no adjustments being made to the remaining parametrizations. Plain Language Summary: We present the world's first global simulation of an entire season of the Earth's atmosphere with 1.4 km average grid spacing and the top of the modeled atmosphere as high as 80 km. Albeit only a single realization due to its considerable computational cost, the resulting model output provides a reference and guidance for future simulations. For illustration we compare to simulations at 9 km grid spacing that represent the state of the art in numerical weather prediction and are still considerably finer when compared to models that are used for climate projections today. Thanks to its unprecedented detail, the simulation output will support future model development and satellite mission planning and may be seen as a prototype contribution to a future digital twin of our Earth. Key Points: A unique simulation with 1.4 km average grid spacing is presented for model development and process evaluationThe 1.4 km simulation shows remarkable fidelity with respect to the well‐calibrated simulation at 9 km with parametrized deep convectionSwitching off deep convection at a too coarse resolution (9 km) generates too strong convective gravity waves [ABSTRACT FROM AUTHOR]

Explaining the evolution of animals requires ecological, developmental, paleontological, and phylogenetic considerations because organismal traits are affected by complex evolutionary processes. Modeling a plurality of processes, operating at distinct time-scales on potentially interdependent traits, can benefit from approaches that are complementary treatments to phylogenetics. Here, we developed an inclusive network approach, implemented in the command line software ComponentGrapher, and analyzed trait co-occurrence of rhinocerotoid mammals. We identified stable, unstable, and pivotal traits, as well as traits contributing to complexes, that may follow to a common developmental regulation, that point to an early implementation of the postcranial Bauplan among rhinocerotoids. Strikingly, most identified traits are highly dissociable, used repeatedly in distinct combinations and in different taxa, which usually do not form clades. Therefore, the genes encoding these traits are likely recruited into novel gene regulation networks during the course of evolution. Our evo-systemic framework, generalizable to other evolved organizations, supports a pluralistic modeling of organismal evolution, including trees and networks. [ABSTRACT FROM AUTHOR]

Assessing support for molecular phylogenies is difficult because the data is heterogeneous in quality and overwhelming in quantity. Traditionally, node support values (bootstrap frequency, Bayesian posterior probability) are used to assess confidence in tree topologies. Other analyses to assess the quality of phylogenetic data (e.g. Lento plots, saturation plots, trait consistency) and the resulting phylogenetic trees (e.g. internode certainty, parameter permutation tests, topological tests) exist but are rarely applied. Here we argue that a single qualitative analysis is insufficient to assess support of a phylogenetic hypothesis and relate data quality to tree quality. We use six molecular markers to infer the phylogeny of Blattodea and apply various tests to assess relationship support, locus quality, and the relationship between the two. We use internode-certainty calculations in conjunction with bootstrap scores, alignment permutations, and an approximately unbiased (AU) test to assess if the molecular data unambiguously support the phylogenetic relationships found. Our results show higher support for the position of Lamproblattidae, high support for the termite phylogeny, and low support for the position of Anaplectidae, Corydioidea and phylogeny of Blaberoidea. We use Lento plots in conjunction with mutation-saturation plots, calculations of locus homoplasy to assess locus quality, identify long branch attraction, and decide if the tree’s relationships are the result of data biases. We conclude that multiple tests and metrics need to be taken into account to assess tree support and data robustness. [ABSTRACT FROM AUTHOR]

The inclusion of introgressive processes in evolutionary studies induces a less constrained view of evolution. Network-based methods (like large-scale similarity networks) allow to include in comparative genomics all extrachromosomic carriers (like viruses, the most abundant biological entities on the planet) with their cellular hosts. The integration of several levels of biological organization (genes, genomes, communities, environments) enables more comprehensive analyses of gene sharing and improved sequence-based classifications. However, the algorithmic tools for the analysis of such networks are usually restricted to people with high programming skills. We present an integrated suite of software tools named MultiTwin, aimed at the construction, structuring, and analysis of multipartite graphs for evolutionary biology. Typically, this kind of graph is useful for the comparative analysis of the gene content of genomes in microbial communities from the environment and for exploring patterns of gene sharing, for example between distantly related cellular genomes, pangenomes, or between cellular genomes and their mobile genetic elements. We illustrate the use of this tool with an application of the bipartite approach (using gene family–genome graphs) for the analysis of pathogenicity traits in prokaryotes. [ABSTRACT FROM AUTHOR]

Microbes are the oldest and most widespread, phylogenetically and metabolically diverse life forms on Earth. However, they have been discovered only 334 years ago, and their diversity started to become seriously investigated even later. For these reasons, microbial studies that unveil novel microbial lineages and processes affecting or involving microbes deeply (and repeatedly) transformknowledge in biology. Considering the quantitative prevalence of taxonomically and functionally unassigned sequences in environmental genomics data sets, and that of unculturedmicrobes on the planet, we propose that unraveling themicrobial dark matter should be identified as a central priority for biologists. Based on former empirical findings of microbial studies, we sketch a logic of discovery with the potential to further highlight the microbial unknowns. [ABSTRACT FROM AUTHOR]

How, when, and why organisms age are fascinating issues that can only be fully addressed by adopting an evolutionary perspective. Consistently, the main evolutionary theories of ageing, namely the Mutation Accumulation theory, the Antagonistic Pleiotropy theory, and the Disposable Soma theory, have formulated stimulating hypotheses that structure current debates on both the proximal and ultimate causes of organismal ageing. However, all these theories leave a common area of biology relatively under-explored. The Mutation Accumulation theory and the Antagonistic Pleiotropy theory were developed under the traditional framework of population genetics, and therefore are logically centred on the ageing of individuals within a population. The Disposable Soma theory, based on principles of optimising physiology, mainly explains ageing within a species. Consequently, current leading evolutionary theories of ageing do not explicitly model the countless interspecific and ecological interactions, such as symbioses and host-microbiomes associations, increasingly recognized to shape organismal evolution across the Web of Life. Moreover, the development of network modelling supporting a deeper understanding on the molecular interactions associated with ageing within and between organisms is also bringing forward new questions regarding how and why molecular pathways associated with ageing evolved. Here, we take an evolutionary perspective to examine the effects of organismal interactions on ageing across different levels of biological organisation, and consider the impact of surrounding and nested systems on organismal ageing. We also apply this perspective to suggest open issues with potential to expand the standard evolutionary theories of ageing. • Ageing organisms belong to networks of molecular, ecological and social interactions. • How surrounding or nested systems impact organismal ageing is yet to be characterized. • Focusing on hybridization, (endo)symbioses and social interactions raises open issues. • Using concepts of individuality, unit of selection and fitness measures raises issues. • Network analyses may help understand the evolution of ageing across the Web of Life. [ABSTRACT FROM AUTHOR]

Based on their small size and genomic properties, ultrasmall prokaryotic groups like the Candidate Phyla Radiation have been proposed as possible symbionts dependent on other bacteria or archaea. In this study, we use a bipartite graph analysis to examine patterns of sequence similarity between draft and complete genomes from ultrasmall bacteria and other complete prokaryotic genomes, assessing whether the former group might engage in significant gene transfer (or even endosymbioses) with other community members. Our results provide preliminary evidence for many lateral gene transfers with other prokaryotes, including members of the archaea, and report the presence of divergent, membrane-associated proteins among these ultrasmall taxa. In particular, these divergent genes were found in TM6 relatives of the intracellular parasite Babela massiliensis. [ABSTRACT FROM AUTHOR]

The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the "recycling" of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance. [ABSTRACT FROM AUTHOR]

Background: High-throughput sequencing technologies are lifting major limitations to molecular-based ecological studies of eukaryotic microbial diversity, but analyses of the resulting millions of short sequences remain a major bottleneck for these approaches. Here, we introduce the analytical and statistical framework of sequence similarity networks, increasingly used in evolutionary studies and graph theory, into the field of ecology to analyze novel pyrosequenced V4 small subunit rDNA (SSU-rDNA) sequence data sets in the context of previous studies, including SSU-rDNA Sanger sequence data from cultured ciliates and from previous environmental diversity inventories. Results: Our broadly applicable protocol quantified the progress in the description of genetic diversity of ciliates by environmental SSU-rDNA surveys, detected a fundamental historical bias in the tendency to recover already known groups in these surveys, and revealed substantial amounts of hidden microbial diversity. Moreover, network measures demonstrated that ciliates are not globally dispersed, but are structured by habitat and geographical location at intermediate geographical scale, as observed for bacteria, plants, and animals. Conclusions: Currently available 'universal' primers used for local in-depth sequencing surveys provide little hope to exhaust the significantly higher ciliate (and most likely microbial) diversity than previously thought. Network analyses such as presented in this study offer a promising way to guide the design of novel primers and to further explore this vast and structured microbial diversity. [ABSTRACT FROM AUTHOR]

A comprehensive examination of 5 years of European Centre for Medium-Range Weather Forecasts (ECMWF) data from T511 L60 version of the ECMWF model to determine ducting conditions over West Africa and the computation of statistical distributions of the vertical gradient of refractivity determined from 2 years of radiosonde data over Dakar (14.41°N, 17.26°W), Douala (4°N, 9.7°E) and Niamey (13.35°N, 2.03°E) were carried out. It is found that diurnal and seasonal variations of the refractivity of the atmosphere are influenced by air temperature and water vapor pressure fluctuation. Refractivity gradients lower than −157 km −1 often results in spurious returned echoes and misinterpretation of radar images such as erroneous precipitation detection. The results obtained show that the local climate has an appreciable influence on the vertical profile of refractivity, especially the seasonal north–south movement of the Inter Tropical Discontinuity which is associated with the alternance of wet and dry seasons over the region. It is found that most of ducts occur in the night, morning (0000, 0600 UTC) and late afternoon (1800 UTC). The occurrence probability of abnormal propagation events, such as ducts, can provide some valuable information about the propagation of electromagnetic waves over West Africa. [ABSTRACT FROM AUTHOR]

Medium-range weather prediction has become more skillful over recent decades, but forecast centers still suffer from occasional very poor forecasts, which are often referred to as "dropouts" or "busts." This study focuses on European Centre for Medium-Range Weather Forecasts (ECMWF) day-6 forecasts for Europe. Although busts are defined by gross scores, bust composites reveal a coherent "Rex type" blocking situation, with a high over northern Europe and a low over the Mediterranean. Initial conditions for these busts also reveal a coherent flow, but this is located over North America and involves a trough over the Rockies, with high convective available potential energy (CAPE) to its east. This flow type occurs in spring and is often associated with a Rossby wave train that has crossed the Pacific. A composite on this initial flow type displays enhanced day-6 random forecast errors and somewhat enhanced ensemble forecast spread, indicating reduced inherent predictability. Mesoscale convective systems, associated with the high levels of CAPE, act to slow the motion of the trough. Hence, convection errors play an active role in the busts. The subgrid-scale nature of convection highlights the importance of the representation of model uncertainty in probabilistic forecasts. The cloud and extreme conditions associated with mesoscale convective systems also reduce the availability and utility of observations provided to the data assimilation. A question of relevance to the wider community is, do we have observations with sufficient accuracy to better constrain the important error structures in the initial conditions? Meanwhile, improvements to ensemble prediction systems should help us better predict the increase in forecast uncertainty. [ABSTRACT FROM AUTHOR]

Motivation: Gene fusion is an important evolutionary process. It can yield valuable information to infer the interactions and functions of proteins. Fused genes have been identified as non-transitive patterns of similarity in triplets of genes. To be computationally tractable, this approach usually imposes an a priori distinction between a dataset in which fused genes are searched for, and a dataset that may have provided genetic material for fusion. This reduces the ‘genetic space’ in which fusion can be discovered, as only a subset of triplets of genes is investigated. Moreover, this approach may have a high–false-positive rate, and it does not identify gene families descending from a common fusion event.Results: We represent similarities between sequences as a network. This leads to an efficient formulation of previous methods of fused gene identification, which we implemented in the Python program FusedTriplets. Furthermore, we propose a new characterization of families of fused genes, as clique minimal separators of the sequence similarity network. This well-studied graph topology provides a robust and fast method of detection, well suited for automatic analyses of big datasets. We implemented this method in the C++ program MosaicFinder, which additionally uses local alignments to discard false-positive candidates and indicates potential fusion points. The grouping into families will help distinguish sequencing or prediction errors from real biological fusions, and it will yield additional insight into the function and history of fused genes.Availability: FusedTriplets and MosaicFinder are published under the GPL license and are freely available with their source code at this address: http://sourceforge.net/projects/mosaicfinder.Contact: pogorelc@isima.frSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM PUBLISHER]

DNA flows between chromosomes and mobile elements, following rules that are poorly understood. This limited knowledge is partly explained by the limits of current approaches to study the structure and evolution of genetic diversity. Network analyses of 119,381 homologous DNA families, sampled from 111 cellular genomes and from 165,529 phage, plasmid, and environmental virome sequences, offer challenging insights. Our results support a disconnected yet highly structured network of genetic diversity, revealing the existence of multiple "genetic worlds." These divides define multiple isolated groups of DNA vehicles drawing on distinct gene pools. Mathematical studies of the centralities of these worlds' subnetworks demonstrate that plasmids, not viruses, were key vectors of genetic exchange between bacterial chromosomes, both recently and in the past Furthermore, network methodology introduces new ways of quantifying current sampling of genetic diversity. [ABSTRACT FROM AUTHOR]

Background: Improving knowledge of biodiversity will benefit conservation biology, enhance bioremediation studies, and could lead to new medical treatments. However there is no standard approach to estimate and to compare the diversity of different environments, or to study its past, and possibly, future evolution. Presentation of the hypothesis: We argue that there are two conditions for significant progress in the identification and quantification of biodiversity. First, integrative metagenomic studies - aiming at the simultaneous examination (or even better at the integration) of observations about the elements, functions and evolutionary processes captured by the massive sequencing of multiple markers - should be preferred over DNA barcoding projects and over metagenomic projects based on a single marker. Second, such metagenomic data should be studied with novel inclusive network-based approaches, designed to draw inferences both on the many units and on the many processes present in the environments. Testing the hypothesis: We reached these conclusions through a comparison of the theoretical foundations of two molecular approaches seeking to assess biodiversity: metagenomics (mostly used on prokaryotes and protists) and DNA barcoding (mostly used on multicellular eukaryotes), and by pragmatic considerations of the issues caused by the 'species problem' in biodiversity studies. Implications of the hypothesis: Evolutionary gene networks reduce the risk of producing biodiversity estimates with limited explanatory power, biased either by unequal rates of LGT, or difficult to interpret due to (practical) problems caused by type I and type II grey zones. Moreover, these networks would easily accommodate additional (meta)transcriptomic and (meta)proteomic data. [ABSTRACT FROM AUTHOR]