Tunicates push the limits of animal evo-devo

The phylum to which humans belong, Chordata, takes its name from one of the major shared derived features of the group, the notochord. All chordates have a notochord, at least during embryogenesis, and there is little doubt about notochord homology at the morphological level. A study in BMC Evolutionary Biology now shows that there is greater variability in the molecular genetics underlying notochord development than previously appreciated

Spatial correlations in attribute communities

Community detection is an important tool for exploring and classifying the properties of large complex networks and should be of great help for spatial networks. Indeed, in addition to their location, nodes in spatial networks can have attributes such as the language for individuals, or any other socio-economical feature that we would like to identify in communities. We discuss in this paper a crucial aspect which was not considered in previous studies which is the possible existence of correlations between space and attributes. Introducing a simple toy model in which both space and node attributes are considered, we discuss the effect of space-attribute correlations on the results of various community detection methods proposed for spatial networks in this paper and in previous studies. When space is irrelevant, our model is equivalent to the stochastic block model which has been shown to display a detectability-non detectability transition. In the regime where space dominates the link formation process, most methods can fail to recover the communities, an effect which is particularly marked when space-attributes correlations are strong. In this latter case, community detection methods which remove the spatial component of the network can miss a large part of the community structure and can lead to incorrect results.Comment: 10 pages and 7 figure

Extreme Ultraviolet Beam Enhancement by Relativistic Surface Plasmons

The emission of high-order harmonics in the extreme ultraviolet range from the interaction of a short, intense laser pulse with a grating target is investigated experimentally. When resonantly exciting a surface plasmon, both the intensity and the highest order observed for the harmonic emission along the grating surface increase with respect to a flat target. Harmonics are obtained when a suitable density gradient is preformed at the target surface, demonstrating the possibility to manipulate the grating profile on a nanometric scale without preventing the surface plasmon excitation. In support of this, the harmonic emission is spatiotemporally correlated to the acceleration of multi-MeV electron bunches along the grating surface. Particle-in-cell simulations reproduce the experimental results and give insight on the mechanism of high harmonic generation in the presence of surface plasmons

Predicting Pneumonia and Influenza Mortality from Morbidity Data

BACKGROUND: Few European countries conduct reactive surveillance of influenza mortality, whereas most monitor morbidity. METHODOLOGY/PRINCIPAL FINDINGS: We developed a simple model based on Poisson seasonal regression to predict excess cases of pneumonia and influenza mortality during influenza epidemics, based on influenza morbidity data and the dominant types/subtypes of circulating viruses. Epidemics were classified in three levels of mortality burden (“high”, “moderate” and “low”). The model was fitted on 14 influenza seasons and was validated on six subsequent influenza seasons. Five out of the six seasons in the validation set were correctly classified. The average absolute difference between observed and predicted mortality was 2.8 per 100,000 (18% of the average excess mortality) and Spearman's rank correlation coefficient was 0.89 (P = 0.05). CONCLUSIONS/SIGNIFICANCE: The method described here can be used to estimate the influenza mortality burden in countries where specific pneumonia and influenza mortality surveillance data are not available

LocoGSE, a sequence-based genome size estimator for plants

Extensive research has focused on exploring the range of genome sizes in eukaryotes, with a particular emphasis on land plants, where significant variability has been observed. Accurate estimation of genome size is essential for various research purposes, but existing sequence-based methods have limitations, particularly for low-coverage datasets. In this study, we introduce LocoGSE, a novel genome size estimator designed specifically for low-coverage datasets generated by genome skimming approaches. LocoGSE relies on mapping the reads on single copy consensus proteins without the need for a reference genome assembly. We calibrated LocoGSE using 430 low-coverage Angiosperm genome skimming datasets and compared its performance against other estimators. Our results demonstrate that LocoGSE accurately predicts monoploid genome size even at very low depth of coverage (<1X) and on highly heterozygous samples. Additionally, LocoGSE provides stable estimates across individuals with varying ploidy levels. LocoGSE fills a gap in sequence-based plant genome size estimation by offering a user-friendly and reliable tool that does not rely on high coverage or reference assemblies. We anticipate that LocoGSE will facilitate plant genome size analysis and contribute to evolutionary and ecological studies in the field. Furthermore, at the cost of an initial calibration, LocoGSE can be used in other lineages

Down syndrome-recent progress and future prospects

Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and is associated with a number of deleterious phenotypes, including learning disability, heart defects, early-onset Alzheimer's disease and childhood leukaemia. Individuals with DS are affected by these phenotypes to a variable extent; understanding the cause of this variation is a key challenge. Here, we review recent research progress in DS, both in patients and relevant animal models. In particular, we highlight exciting advances in therapy to improve cognitive function in people with DS and the significant developments in understanding the gene content of Hsa21. Moreover, we discuss future research directions in light of new technologies. In particular, the use of chromosome engineering to generate new trisomic mouse models and large-scale studies of genotype-phenotype relationships in patients are likely to significantly contribute to the future understanding of DS

MLVA polymorphism of Salmonella enterica subspecies isolated from humans, animals, and food in Cambodia

<p>Abstract</p> <p>Background</p> <p><it>Salmonella </it>(<it>S</it>.) <it>enterica </it>is the main cause of salmonellosis in humans and animals. The epidemiology of this infection involves large geographical distances, and strains related to an episode of salmonellosis therefore need to be reliably discriminated. Due to the limitations of serotyping, molecular genotyping methods have been developed, including multiple loci variable number of tandem repeats (VNTR) analysis (MLVA). In our study, 11 variable number tandem-repeats markers were selected from the <it>S. enterica </it>Typhimurium LT2 genome to evaluate the genetic diversity of 206 <it>S. enterica </it>strains collected in Cambodia between 2001 and 2007.</p> <p>Findings</p> <p>Thirty one serovars were identified from three sources: humans, animals and food. The markers were able to discriminate all strains from 2 to 17 alleles. Using the genotype phylogeny repartition, MLVA distinguished 107 genotypes clustered into two main groups: <it>S. enterica </it>Typhi and other serovars. Four serovars (Derby, Schwarzengrund, Stanley, and Weltevreden) were dispersed in 2 to 5 phylogenic branches. Allelic variations within <it>S. enterica </it>serovars was represented using the minimum spanning tree. For several genotypes, we identified clonal complexes within the serovars. This finding supports the notion of endemo-epidemic diffusion within animals, food, or humans. Furthermore, a clonal transmission from one source to another was reported. Four markers (STTR3, STTR5, STTR8, and Sal20) presented a high diversity index (DI > 0.80).</p> <p>Conclusions</p> <p>In summary, MLVA can be used in the typing and genetic profiling of a large diversity of <it>S. enterica </it>serovars, as well as determining the epidemiological relationships of the strains with the geography of the area.</p

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde