Miracle-dz/UniFAR-FTUs huggingface dataset:
Adomaviruses: an emerging virus family provides insights into DNA virus evolution

Diverse eukaryotic dsDNA viruses, including adenoviruses, are thought to have evolved from bacteriophages of the family Tectiviridae. The evolutionary relationship of the small circular dsDNA tumor viruses of the families Papillomaviridae and Polyomaviridae to other DNA virus families remains uncertain. Metagenomic surveys of fish reveal 5 previously unknown circular dsDNA viruses that could become founding members of a distinct viral family. These viruses encode predicted superfamily 3 helicases that are related to the replicative helicases of polyomaviruses and papillomaviruses. Additionally, the new viruses encode a gene cluster coding for homologs of adenovirus-like maturation proteases and putative homologs of adenovirus major and minor capsid proteins. We show that these predicted capsid protein are indeed incorporated into the adomavirus virions. Such combination of genes from unrelated virus families is unprecedented among known DNA viruses. We propose the name “Adomaviridae” for this emerging virus family. Significance Statement Although investigation of the origins of viruses is hampered by the poor conservation of the sequences of many viral genes, substantial progress has been made by applying powerful computational methods to compare key viral proteins. Another challenge for understanding viral evolution is the rampant gene exchange between different groups of viruses, and between viruses and their hosts. We describe a group of fish viruses that possess an unexpected combination of genes. The proteins implicated in virus genome replication have homologs in polyomaviruses and papillomaviruses, whereas the structural gene module is related to the corresponding genes of adenoviruses. The unusual genomic layout of these fish viruses suggests unanticipated evolutionary connections between multiple families of tumor-causing viruses.
Comparing EEG/MEG neuroimaging methods based on localization error, false positive activity, and false positive connectivity

EEG/MEG neuroimaging consists of estimating the cortical distribution of time varying signals of electric neuronal activity, for the study of functional localization and connectivity. Currently, many different imaging methods are being used, with very different capabilities of correct localization of activity and of correct localization of connectivity. The aim here is to provide a guideline for choosing the best (i.e. least bad) imaging method. This first study is limited to the comparison of the following methods for EEG signals: sLORETA and eLORETA (standardized and exact low resolution electromagnetic tomography), MNE (minimum norm estimate), dSPM (dynamic statistical parametric mapping), and LCMVBs (linearly constrained minimum variance beamformers). These methods are linear, except for the LCMVBs that make use of the quadratic EEG covariances. To achieve a fair comparison, it is assumed here that the generators are independent and widely distributed (i.e. not few in number), giving a well-defined theoretical population EEG covariance matrix for use with the LCMVBs. Measures of localization error, false positive activity, and false positive connectivity are defined and computed under ideal no-noise conditions. It is empirically shown with extensive simulations that: (1) MNE, dSPM, and all LCMVBs are in general incapable of correct localization, while sLORETA and eLORETA have exact (zero-error) localization; (2) the brain volume with false positive activity is significantly larger for MN, dSPM, and all LCMVBs, as compared to sLORETA and eLORETA; and (3) the number of false positive connections is significantly larger for MN, dSPM, all LCMVBs, and sLORETA, as compared to eLORETA. Non-vague and fully detailed equations are given. PASCAL program codes and data files are available. It is noted that the results reported here do not apply to the LCMVBs based on EEG covariance matrices generated from extremely few generators, such as only one or two independent point sources.
LiMMBo: a simple, scalable approach for linear mixed models in high-dimensional genetic association studies

Genome-wide association studies have helped to shed light on the genetic architecture of complex traits and diseases. Deep phenotyping of population cohorts is increasingly applied, where multi-to high-dimensional phenotypes are recorded in the individuals. Whilst these rich datasets provide important opportunities to analyse complex trait structures and pleiotropic effects at a genome-wide scale, existing statistical methods for joint genetic analyses are hampered by computational limitations posed by high-dimensional phenotypes. Consequently, such multivariate analyses are currently limited to a moderate number of traits. Here, we introduce a method that combines linear mixed models with bootstrapping (LiMMBo) to enable computationally efficient joint genetic analysis of high-dimensional phenotypes. Our method builds on linear mixed models, thereby providing robust control for population structure and other confounding factors, and the model scales to larger datasets with up to hundreds of phenotypes. We first validate LiMMBo using simulations, demonstrating consistent covariance estimates at greatly reduced computational cost compared to existing methods. We also find LiMMBo yields consistent power advantages compared to univariate modelling strategies, where the advantages of multivariate mapping increases substantially with the phenotype dimensionality. Finally, we applied LiMMBo to 41 yeast growth traits to map their genetic determinants, finding previously known and novel pleiotropic relationships in this high-dimensional phenotype space. LiMMBo is accessible as open source software (https://github.com/HannahVMeyer/limmbo). Author summary In multi-trait genetic association studies one is interested in detecting genetic variants that are associated with one or multiple traits. Genetic variants that influence two or more traits are referred to as pleiotropic. Multivariate linear mixed models have been successfully applied to detect pleiotropic effects, by jointly modelling association signals across traits. However, these models are currently limited to a moderate number of phenotypes as the number of model parameters grows steeply with the number of phenotypes, raising a computational burden. We developed LiMMBo, a new approach for the joint analysis of high-dimensional phenotypes. Our method reduces the number of effective model parameters by introducing an intermediate subsampling step. We validate this strategy using simulations, where we apply LiMMBo for the genetic analysis of hundreds of phenotypes, detecting pleiotropic effects for a wide range of simulated genetic architectures. Finally, to illustrate LiMMBo in practice, we apply the model to a study of growth traits in yeast, where we identify pleiotropic effects for traits with formerly known genetic effects as well as revealing previously unconnected traits.
Comparing yield estimates derived from LiDAR and aerial photogrammetric point-cloud data with cut-to-length harvester data in a Pinus radiata plantation in Tasmania

ABSTRACT Accurate mapping of timber resources in commercial forestry is essential to support planning and management operations of forest growers. Over the last two decades, Light Detection and Ranging (LiDAR) systems have been successfully deployed for the collection of point-cloud data for accurate modelling of forest attributes that are traditionally obtained from plot-based inventory. In recent years, studies conducted in North America and Scandinavia have shown that three-dimensional point clouds derived from digital aerial photogrammetric (AP) data can be used to model forest attributes with a level of accuracy similar to traditional LiDAR-based approaches. A comparative analysis of the performance of the two point-cloud technologies has never been attempted in Australian plantations. In this study, we compared the performance of LiDAR-based and AP-based point clouds for estimating total recoverable volume in a Pinus radiata plantation at Springfield in north-eastern Tasmania, using volume data collected by harvesting machines as a reference. Our results showed that AP point clouds can be used for mapping total recoverable volume in P. radiata plantations with levels of accuracy that are comparable to LiDAR-based estimates. Plot-level relative root mean squared error (RMSE%) values were 23.85% for LiDAR and ranged from 22.07% to 27.10% for the three AP dense point-cloud settings evaluated. At the stand level, RMSE% decreased to 9.86% and 8.91% for LiDAR and AP, respectively. Both LiDAR-based and AP-based modelled volumes showed a close agreement with volumes measured using harvester head data, demonstrating the potential of AP technology for the management and planning of forestry operations in softwood plantations.
The effect of susceptible and resistant potato cultivars on bacterial communities in the tuberosphere of potato in soil suppressive or conducive to common scab disease

Connections between the structure of bacterial communities in suppressive soils and potato resistance to common scab (CS) are not well understood. In this study, one resistant and one susceptible cultivar were grown in a conducive and suppressive field to assess cultivar resistance × soil suppressiveness interactions. The resistant cultivar had a higher Mg content in periderm compare to susceptible cultivar, while suppressive soil had lower pH (5.3 vs 5.9), N, C, P, Ca contents but higher Fe and S compared with the conducive soil. Bacteria and actinobacteria numbers were higher in the conducive soil. Copy numbers of txtB gene (coding for a pathogenicity determinant) were similar in both soils but were higher in the conducive soil (for periderm samples) and in the susceptible cultivar (for conducive soil samples). Taxonomic microarray analysis and Illumina sequencing of 16S rRNA genes amplicon showed that bacterial community differed between resistant vs susceptible cultivar and to a lesser extend between suppressive vs conducive soil. Bacteria participating in soil suppression belonged to Pseudomonadaceae, Bradyrhizobiaceae, Acetobacteraceae and Paenibacillaceae, while resistant cultivars selected a bacterial community resembling that of the suppressive soil, which was enriched in Nitrospirae and Acidobacteria. Thus, the analysis of soil suppressiveness×cultivar resistance interactions enabled to gain new insight to CS control in the field. IMPORTANCE It was demonstrated that potato cultivars susceptible and resistant to common scab select differing bacterial community and above that this trait is further modified in suppressive and conducive soil. Common scab severity was diminished by either resistant cultivar or suppressive soil but without additive effect between them. Out of the two factors, potato cultivar had a more significant influence on tuberosphere bacterial community composition than soil. Results highlighted the usefulness of both cultivar resistance and soil suppressiveness traits in understanding and managing disease control of crops.
Development and Characterization of Microsatellite Markers for Three Pollination Morphs of Cimicifuga simplex (Ranunculaceae)

Cimicifuga simplex Wormsk. (Ranunculaceae) is a perennial herb distributed in eastern and northeastern Asia for which at least three different pollination morphs have been reported. It is classified as endangered or near threatened in some Japanese regions, and its rhizome is commercially used as a crude drug. To examine genetic differentiation and gene flow among the three morphs, we developed eight microsatellite markers by using next-generation sequencing and estimated the genetic structure of C. simplex. We tested eight primer pairs on 93 individuals from six populations of C. simplex in Nagano, central Japan, and found that heterozygosity in morphs I and III was low compared to expected heterozygosity. Bayesian clustering performed with the STRUCTURE program clearly distinguished the three morphs of C. simplex, and only a little gene flow was detected among the morphs. These eight microsatellite markers are expected to be useful in conservation genetic studies of this species and for future conservation planning.
Prepupal diapause synchronizes adult emergence in the pine processionary moth Thaumetopoea pityocampa (Lepidoptera: Notodontidae)

Insects with short‐lived adults must synchronize their emergence to maximize fitness. However, pre‐imaginal development time often varies among individuals as a result of exposure to varied abiotic and biotic factors; therefore, mechanisms adjusting pre‐imaginal development time are expected. Larvae of the pine processionary moth feed throughout the winter and conclude their development with characteristic processions in spring, leaving the trees to pupate in soil. The procession period can be as long as 2 months in some regions because of prior desynchronization of larval colonies, whereas the emergence period of the adults in summer remains short (less than 1 month). Through weekly sampling of larvae leaving trees to pupate in soil and subsequent rearing under field and laboratory conditions, it was observed that early prepupae waited longer than late prepupae before moulting into pupa. The differential duration of the prepupal stage was independent of temperature conditions and allowed resynchronization of colonies and overlapping emergences. The prepupal phase therefore appears to be critical for understanding the regulation of adult emergence of this important pest insect.
Target variant detection in leukemia using unaligned RNA-Seq reads

Mutations identified in each Acute Myeloid Leukemia (AML) patients are useful for prognosis and to select targeted therapies. Detection of such mutations by the analysis of Next-Generation Sequencing (NGS) data requires a computationally intensive read mapping step and application of several variant calling methods. Targeted mutation identification drastically shifts the usual tradeoff between accuracy and performance by concentrating all computations over a small portion of sequence space. Here, we present km, an efficient approach leveraging k-mer decomposition of reads to identify targeted mutations. Our approach is versatile, as it can detect single-base mutations, several types of insertions and deletions, as well as fusions. We used two independent AML cohorts (The Cancer Genome Atlas and Leucegene), to show that mutation detection by km is fast, accurate and mainly limited by sequencing depth. Therefore, km allows to establish fast diagnostics from NGS data, and could be suitable for clinical applications.
A Date Palm Disease (Bunch Blight) Caused by Acremonium strictum (Cephalosporium) in Saudi Arabia

Acrimonium strictum is reported as a new causal agent of a disease it names (bunch blight) in date palm (phoenix dactylefera) in Saudi Arabia. Symptoms and necrosis caused by A. strictum in susceptible cultivars showed small brown necrosis streak at midrib of fruit stalk in an early stage. There was an increase in number and size as the disease progresses; then extended to the bases of fruit strands due to death of bases and strands wilt, the infection of fruit strand caused drying the fruits and their fall. A. strictum attacks the bunches and move quickly inside and out the tissues causing brown necrosis and death of the tissues. A. strictum was isolated and pathogenicity tests were repeated more than once during two seasons and the identifications was caried several ways to confirm The confirmation of results by Biolog technique and DNA sequence were done. The proper temperature for infection was between 20-30 °C and the optimum 25 °C. When testing the susceptibility of varieties of infection, more varieties like Medjool, Saqae and Kholas were susceptible to infection and the most resistant to infection were Barhy and Khidri. The best results in the control of the fungus in vitro were due to use of Karpendazem followed Topsen M70, at the same time, the worst results were seen with the use of Abredion followed Karant (Cupper hydroxide).
Use of video monitoring to quantify spatial and temporal patterns in fishing activity across sectors at moored fish aggregating devices off Puerto Rico

A key challenge in small-scale fisheries that use moored fish aggregating devices (mFADs) is the ability to accurately quantify multi-sector fishing activity through fishery-independent methods. Here, we present a novel fishery-independent assessment of multi-sector fishing activity associated with a newly developed open access mFAD programme off San Juan, Puerto Rico. We identified three fishing sectors (recreational, charter and commercial) and 158 individual fishing vessels that routinely operated in the vicinity of the mFADs. The results indicate that daytime fishing activity varied by time of day, day of week, location and sector. During fishing tournaments, the data revealed that fishing activity increased threefold; across monitoring periods, for-hire charter vessels were the most consistent day-to-day user segment, and recreational activity peaked on weekends. Our study represents a new technique for rapidly identifying and detecting multi-sector fishing activity near mFADs and highlights the potential to gather comparable data wherever mFADs are deployed. The results are used to discuss how this technique can be used to assess the performance of mFADs to identify sector overlap and guide management in determining deployment patterns and facilitate the design of cost-effective surveys to estimate mFAD vessel activity, and potentially catch, of mFAD-associated species.
Mécanismes d'action de l'homéoprotéine Engrailed dans les neurones dopaminergiques adultes du mésencéphale

Les homeoproteines sont des facteurs de transcription qui en plus de leur role important durant le developpement des metazoaires, beneficient de fonctions autonome et non autonome-cellulaire dans le cerveau adulte. Parmi ces homeoproteines, Engrailed1/2 (collectivement Engrailed) est exprimee dans les neurones dopaminergiques mesencephaliques adulte, ceux-la meme qui degenerent dans la maladie de Parkinson. Chez les souris deletees d’une copie du gene (En1+/-), une degenerescence progressive des neurones dopaminergiques s’accompagne de symptomes moteurs et non moteurs rappelant la maladie de Parkinson, ce qui pourrait faire de ces souris un modele nouveau et interessant de cette maladie neurodegenerative. Des experiences de transduction de la proteine En1 dans les cellules du mesencephale de souris demontrent son effet neuroprotecteur dans des modeles toxicologiques de la maladie de Parkinson et chez les souris En1+/-, menant a l’hypothese qu’Engrailed est important dans la physiopathologie de cette maladie. L’essentiel de ce travail de these s’inscrit dans la comprehension des mecanismes d’action de l’homeoproteine Engrailed dans les neurones dopaminergiques mesencephaliques. L’activite physiologique importante de ces neurones et le stress metabolique oxydant qui est genere touche plusieurs compartiments cellulaires, dont le noyau. La stabilite du genome semble etre un aspect majeur de l’action d’Engrailed dans ces neurones. D’abord contre les effets deleteres du stress oxydatif sur l’integrite de l’ADN et la structure de la chromatine, ensuite, contre l’activite genotoxique des elements transposables LINE-1.
The complete mitochondrial genome of the stalk-forming diatom Didymosphenia Geminata

Abstract The complete mitogenome of the stalk-forming diatom Didymosphenia geminata collected from Mineral County, WV, USA was sequenced on the Ion Torrent PGM and Proton sequencers. The D. geminata mitogenome is 37,765 bp and encodes 35 protein coding genes, 25 tRNAs, and both large and small subunit ribosomal RNA genes. The nad11 gene is split into two domains as observed in Phaeodactylum tricornutum, and D. geminata also lacks the large repeat region found in the P. tricornutum mitogenome. Gene order and content within the D. geminata mitogenome is similar to the diatom Berkeleya fennica.
Lempel-Ziv complexity of the EEG predicts long-term functional recovery after stroke in rats

Non-linear complexity of the EEG signal can be used to detect abnormal brain function relating to behavioral deficits. Here, we compare the effects of experimental stroke on EEG complexity using Lempel-Ziv complexity analysis (LZC) and multiscale entropy analysis (SampEn). EEG was recorded in bilateral motor cortex at baseline and during a 30-day recovery period after distal middle cerebral artery occlusion in rats. Motor function was assessed using a single pellet reaching task. Stroke caused an acute drop in both LZC and SampEn in the ipsilesional hemisphere in wakefulness, NREM and REM sleep, as well as reduced pellet reaching success. SampEn reductions persisted for at least 10 days post-stroke, whereas LZC had returned to baseline levels by day 4. EEG complexity in the contralesional hemisphere and in sham-operated animals were unaffected. If EEG complexity reflects post-stroke brain function, post-stroke asymmetry could be used to predict behavioral recovery. In rats, acute LZC asymmetry was significantly correlated with the amount of motor function recovery by post-stroke day 31, but SampEn asymmetry was not. EEG LZC may thus be a useful tool for predicting functional recovery after stroke. MSE could be effective in identifying cortical dysfunction, but does not reflect behavioral outcomes.
Immunomodulatory effects of the methanolic extract from Pouteria campechiana leaves in macrophage functions

ABSTRACT The present study aimed to examine the immunomodulatory properties of the methanolic (MeOH) extract from Pouteria. campechiana leaves in peritoneal macrophages of Balb/c mice. Peritoneal macrophages isolated from mice and Vero cells were treated with the MeOH extract from leaves. Cell viability of the macrophages and Vero cells were evaluated by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide method. The phagocytic activity, as nitric oxide (NO), hydrogen peroxide (H2O2), interleukin 6 (IL-6) and tumour necrosis factor α (TNF-α) production were evaluated on peritoneal macrophages. Results showed that the MeOH extract from leaves was able to stimulate the phagocytic activity and increase NO, H2O2 and cytokines production. The viability assays do not show cytotoxic effect on cell viability and cause a significative proliferative effect in the macrophages of a concentration-dependent manner. These results conclude that the MeOH extract from P. campechiana leaves possessed a stronger immunostimulatory effect in a concentration-dependent manner without affect the cell viability.