Genome-wide fine-scale recombination rate variation in Drosophila melanogaster

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity

Spatial memory in the grey mouse lemur (Microcebus murinus)

Wild animals face the challenge of locating feeding sites distributed across broad spatial and temporal scales. Spatial memory allows animals to find a goal, such as a productive feeding patch, even when there are no goal-specific sensory cues available. Because there is little experimental information on learning and memory capabilities in free-ranging primates, the aim of this study was to test whether grey mouse lemurs (Microcebus murinus), as short-term dietary specialists, rely on spatial memory in relocating productive feeding sites. In addition, we asked what kind of spatial representation might underlie their orientation in their natural environment. Using an experimental approach, we set eight radio-collared grey mouse lemurs a memory task by confronting them with two different spatial patterns of baited and non-baited artificial feeding stations under exclusion of sensory cues. Positional data were recorded by focal animal observations within a grid system of small foot trails. A change in the baiting pattern revealed that grey mouse lemurs primarily used spatial cues to relocate baited feeding stations and that they were able to rapidly learn a new spatial arrangement. Spatially concentrated, non-random movements revealed preliminary evidence for a route-based restriction in mouse lemur space; during a subsequent release experiment, however, we found high travel efficiency in directed movements. We therefore propose that mouse lemur spatial memory is based on some kind of mental representation that is more detailed than a route-based network map

Challenge of conducting a placebo-controlled randomized efficacy study for influenza vaccine in a season with low attack rate and a mismatched vaccine B strain: a concrete example

<p>Abstract</p> <p>Background</p> <p>Our aim was to determine the efficacy of a trivalent inactivated split virus influenza vaccine (TIV) against culture-confirmed influenza A and/or B in adults 18 to 64 years of age during the 2005/2006 season in the Czech Republic.</p> <p>Methods</p> <p>6203 subjects were randomized to receive TIV (N = 4137) or placebo (N = 2066). The sample size was based on an assumed attack rate of 4% which provided 90% power to reject the hypothesis that vaccine efficacy (VE) was ≥ 45%. Cases of influenza like illness (defined as fever (oral temperature ≥37.8°C) plus cough and/or sore throat) were identified both by active (biweekly phone contact) and passive (self reporting) surveillance and nasal and throat swabs were collected from subjects for viral culture.</p> <p>Results</p> <p>TIV was well tolerated and induced a good immune response. The 2005/2006 influenza season was exceptionally mild in the study area, as it was throughout Europe, and only 46 culture-confirmed cases were found in the study cohort (10 influenza A and 36 influenza B). Furthermore among the B isolates, 35 were identified as B/Hong Kong 330/2001-like (B/Victoria/2/87 lineage) which is antigenically unrelated to the vaccine B strain (B/Yamagata/16/88 lineage). The attack rate in the vaccine group (0.7%) was not statistically significantly different from the attack rate in the placebo group (0.9%).</p> <p>Conclusion</p> <p>Due to the atypical nature of the influenza season during this study we were unable to assess TIV efficacy. This experience illustrates the challenge of conducting a prospective influenza vaccine efficacy trial during a single season when influenza attack rates and drift in circulating strains or B virus lineage match can be difficult to estimate in advance.</p> <p>Trial Registration</p> <p>Clinical trial registery: NCT00197223.</p

Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Cancer is a severe condition of uncontrolled cell division that results in a tumor formation that spreads to other tissues of the body. Therefore, the development of new medication and treatment methods for this is in demand. Classification of microarray data plays a vital role in handling such situations. The relevant gene selection is an important step for the classification of microarray data. This work presents gene encoder, an unsupervised two-stage feature selection technique for the cancer samples’ classification. The first stage aggregates three filter methods, namely principal component analysis, correlation, and spectral-based feature selection techniques. Next, the genetic algorithm is used, which evaluates the chromosome utilizing the autoencoder-based clustering. The resultant feature subset is used for the classification task. Three classifiers, namely support vector machine, k-nearest neighbors, and random forest, are used in this work to avoid the dependency on any one classifier. Six benchmark gene expression datasets are used for the performance evaluation, and a comparison is made with four state-of-the-art related algorithms. Three sets of experiments are carried out to evaluate the proposed method. These experiments are for the evaluation of the selected features based on sample-based clustering, adjusting optimal parameters, and for selecting better performing classifier. The comparison is based on accuracy, recall, false positive rate, precision, F-measure, and entropy. The obtained results suggest better performance of the current proposal

Genome-wide methylation and gene expression changes in newborn rats following maternal protein restriction and reversal by folic acid

A large body of evidence from human and animal studies demonstrates that the maternal diet during pregnancy can programme physiological and metabolic functions in the developing fetus, effectively determining susceptibility to later disease. The mechanistic basis of such programming is unclear but may involve resetting of epigenetic marks and fetal gene expression. The aim of this study was to evaluate genome-wide DNA methylation and gene expression in the livers of newborn rats exposed to maternal protein restriction. On day one postnatally, there were 618 differentially expressed genes and 1183 differentially methylated regions (FDR 5%). The functional analysis of differentially expressed genes indicated a significant effect on DNA repair/cycle/maintenance functions and of lipid, amino acid metabolism and circadian functions. Enrichment for known biological functions was found to be associated with differentially methylated regions. Moreover, these epigenetically altered regions overlapped genetic loci associated with metabolic and cardiovascular diseases. Both expression changes and DNA methylation changes were largely reversed by supplementing the protein restricted diet with folic acid. Although the epigenetic and gene expression signatures appeared to underpin largely different biological processes, the gene expression profile of DNA methyl transferases was altered, providing a potential link between the two molecular signatures. The data showed that maternal protein restriction is associated with widespread differential gene expression and DNA methylation across the genome, and that folic acid is able to reset both molecular signatures

Implementing a stepped-care approach in primary care: results of a qualitative study

Contains fulltext : 108260.pdf (publisher's version ) (Open Access)BACKGROUND: Since 2004, 'stepped-care models' have been adopted in several international evidence-based clinical guidelines to guide clinicians in the organisation of depression care. To enhance the adoption of this new treatment approach, a Quality Improvement Collaborative (QIC) was initiated in the Netherlands. METHODS: Alongside the QIC, an intervention study using a controlled before-and-after design was performed. Part of the study was a process evaluation, utilizing semi-structured group interviews, to provide insight into the perceptions of the participating clinicians on the implementation of stepped care for depression into their daily routines. Participants were primary care clinicians, specialist clinicians, and other healthcare staff from eight regions in the Netherlands. Analysis was supported by the Normalisation Process Theory (NPT). RESULTS: The introduction of a stepped-care model for depression to primary care teams within the context of a depression QIC was generally well received by participating clinicians. All three elements of the proposed stepped-care model (patient differentiation, stepped-care treatment, and outcome monitoring), were translated and introduced locally. Clinicians reported changes in terms of learning how to differentiate between patient groups and different levels of care, changing antidepressant prescribing routines as a consequence of having a broader treatment package to offer to their patients, and better working relationships with patients and colleagues. A complex range of factors influenced the implementation process. Facilitating factors were the stepped-care model itself, the structured team meetings (part of the QIC method), and the positive reaction from patients to stepped care. The differing views of depression and depression care within multidisciplinary health teams, lack of resources, and poor information systems hindered the rapid introduction of the stepped-care model. The NPT constructs 'coherence' and 'cognitive participation' appeared to be crucial drivers in the initial stage of the process. CONCLUSIONS: Stepped care for depression is received positively in primary care. While it is difficult for the implementation of a full stepped-care approach to occur within a short time frame, clinicians can make progress towards achieving a stepped-care approach, particularly within the context of a QIC. Creating a shared understanding within multidisciplinary teams of what constitutes depression, reaching a consensus about the content of depression care, and the division of tasks are important when addressing the implementation process