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347 results found. For more information, click each entry to expand.
4 tweets bioinformatics
Background: Although gene set enrichment analysis has become an integral part of high-throughput gene expression data analysis, the assessment of enrichment methods remains rudimentary and ad hoc. In the absence of suitable gold standards, evaluations are commonly restricted to selected data sets and biological reasoning on the relevance of resulting enriched gene sets. However, this is typically incomplete and biased towards the goals of individual investigations. Results: We present a general framework for standardized and structured benchmarking of enrichment methods based on defined criteria for applicability, gene set prioritization, and detection of relevant processes. This framework incorporates a curated compendium of 75 expression data sets investigating 42 different human diseases. The compendium features microarray and RNA-seq measurements, and each dataset is associated with a precompiled GO/KEGG relevance ranking for the corresponding disease under investigation. We perform a comprehensive assessment of 10 major enrichment methods on the benchmark compendium, identifying significant differences in (i) runtime and applicability to RNA-seq data, (ii) fraction of enriched gene sets depending on the type of null hypothesis tested, and (iii) recovery of the a priori defined relevance rankings. Based on these findings, we make practical recommendations on (i) how methods originally developed for microarray data can efficiently be applied to RNA-seq data, (ii) how to interpret results depending on the type of gene set test conducted, and (iii) which methods are best suited to effectively prioritize gene sets with high relevance for the phenotype investigated. Conclusion: We carried out a systematic assessment of existing enrichment methods, and identified best performing methods, but also general shortcomings in how gene set analysis is currently conducted. We provide a directly executable benchmark system for straightforward assessment of additional enrichment methods. Availability: http://bioconductor.org/packages/GSEABenchmarkeR
4 tweets biophysics
Signalling is of particular importance in immune cells, and upstream in the signalling pathway many membrane receptors are functional only as complexes, co-locating with particular lipid species. Work over the last 15 years has shown that plasma membrane lipid composition is close to a critical point of phase separation, with evidence that cells adapt their composition in ways that alter the proximity to this thermodynamical point. Macrophage cells are a key component of the innate immune system, responsive to infections, regulating the local state of inflammation. We investigate changes in the plasma membrane's proximity to the critical point, as a response to stimulation by various pro- and anti-inflammatory agents. Pro-inflammatory (IFN-, Kdo-LipidA, LPS) perturbations induce an increase in the transition temperature of the GMPVs; anti-inflammatory IL4 has the opposite effect. These changes recapitulate complex plasma membrane composition changes, and are consistent with lipid criticality playing a master regulatory role: being closer to critical conditions increases membrane protein activity.
4 tweets evolutionary biology
Bacterial symbionts that manipulate the reproduction of their hosts to increase their successful transmission are important factors in invertebrate ecology and evolution. In light of their use as a biological control agent, studying the genomic and phenotypic diversity of reproductive manipulators can improve efforts to control infectious diseases and contribute to our understanding of host-symbiont evolution. Despite the vast genomic and phenotypic diversity of reproductive manipulators, only a handful of Wolbachia strains are used as biological control agents because little is known about the broad scale infection frequencies of these bacteria in nature. Here we develop a data mining approach to quantify the number of arthropod and nematode host species available on the Sequence Read Archive (SRA) that are infected with Wolbachia and other reproductive manipulators such as Rickettsia and Spiroplasma. Across the entire database, we found reproductive manipulators infected 1733 arthropod and 103 nematode samples, representing 121 and 10 species, respectively. We estimated that Wolbachia infects approximately 24% of all arthropod species and 20% of all nematode species. In contrast, we estimated other reproductive manipulators infect 0-8% of arthropod and nematode species. We show that relative Wolbachia density within hosts, titer, is significantly lower than the titer of the other reproductive manipulators. Considering the fitness costs of high titers, low titer may contribute to enabling Wolbachia's high prevalence across hosts species and mitigate impacts on host biology compared with other reproductive manipulator taxa. Our study demonstrates that data mining is a powerful tool for understanding host-symbiont co-evolution and opens an array of previously inaccessible questions for further analysis.
4 tweets genetics
Spinal Muscular Atrophy (SMA) is the most common genetic disease in childhood. SMA is generally caused by mutations in SMN1. The Survival of Motor Neurons (SMN) complex consists of SMN1, Gemins (2-8) and Strap/Unrip. We previously demonstrated smn1 and gemin5 inhibited tissue regeneration in zebrafish. Here we investigated each individual SMN complex member and identified gemin3 as another regeneration-essential gene. These three genes are likely pan-regenerative since they affect the regeneration of hair cells, liver and caudal fin. RNA-Seq and miRNA-Seq analyses reveal that smn1, gemin3, and gemin5 are linked to a common set of genetic pathways, including the tp53 and ErbB pathways. Additional studies indicated all three genes facilitate regeneration by inhibiting the ErbB pathway, thereby allowing cell proliferation in the injured neuromasts. This study provides a new understanding of the SMN complex and a potential etiology for SMA and potentially other rare unidentified genetic diseases with similar symptoms.
4 tweets neuroscience
Background: Depression affects one in nine people, but treatment response rates remain low. There is significant potential in the use of computational modelling techniques to predict individual patient responses and thus provide more personalized treatment. Deep learning is a promising computational technique that can be used for differential treatment selection based on predicted remission probability. Methods: Using STAR*D and CO-MED trial data, we employed deep neural networks to predict remission after feature selection. Differential treatment benefit was estimated in terms of improvement of population remission rates after application of the model for treatment selection using both naive and conservative approaches. The naive approach assessed population remission rate in five sets of 200 patients held apart from the training set; the conservative approach used bootstrapping for sample generation and focused on population remission rate for patients who actually received the drug predicted by the model compared to the general population. Results: Our deep learning model predicted remission in a pooled CO-MED/STAR*D dataset (including four treatments) with an AUC of 0.69 using 17 input features. Our naive analysis showed an improvement of remission of over 30% (from a 34.33% population remission rate to 46.12%). Our conservative analysis showed a 7.2% improvement in population remission rate (p= 0.01, C.I. 2.48% +/- .5%). Conclusion: Our model serves as proof-of-concept that deep learning has utility in differential prediction of antidepressant response when selecting from a number of treatment options. These models may have significant real-world clinical implications.
4 tweets neuroscience
A cognitive map, representing an environment around oneself, is necessary for spatial navigation. However, compared with its constituent elements such as individual landmarks, neural substrates of the coherent spatial information remain largely unknown. The present study investigated how the brain codes map-like representations in a virtual environment specified by relative positions of three objects. Representational similarity analysis revealed the object-based spatial environment in the hippocampus (HPC) when participants located their self-positions within it, while the medial prefrontal cortex (mPFC) represented it when they recollected a target object location relative to their self-body. During the recollection, task-dependent functional connectivity increased between the two areas implying exchange of self- and target-location signals between HPC and mPFC. Together, the coherent cognitive map may be recruited in HPC and mPFC for complementary functions when we relate ourselves with a target object including person for navigation, and presumably for social interactions.
4 tweets microbiology
Type I CRISPR-Cas systems are the most abundant and widespread adaptive immune systems of bacteria and can greatly enhance bacterial survival in the face of temperate phage infection. However, it is less clear how these systems protect against virulent phages. Here we experimentally show that type I CRISPR immunity of Pectobacterium atrosepticum leads to rapid suppression of two unrelated virulent phages, ΦTE and ΦM1. However, unlike the case where bacteria are infected with temperate phages, this is the result of an abortive infection-like phenotype, where infected cells do not survive the infection but instead become metabolically inactive and lose their membrane integrity. Our findings challenge the view of CRISPR-Cas as a system that protects the individual cell and supports growing evidence of an Abi-like function for some types of CRISPR-Cas systems.
4 tweets bioinformatics
De novo genome assembly is a fundamental problem in the field of bioinformatics, that aims to assemble the DNA sequence of an unknown genome from numerous short DNA fragments (aka reads) obtained from it. With the advent of high-throughput sequencing technologies, billions of reads can be generated in a matter of hours, necessitating efficient parallelization of the assembly process. While multiple parallel solutions have been proposed in the past, conducting a large-scale assembly at scale remains a challenging problem because of the inherent complexities associated with data movement, and irregular access footprints of memory and I/O operations. In this paper, we present a novel algorithm, called PaKman, to address the problem of performing large-scale genome assemblies on a distributed memory parallel computer. Our approach focuses on improving performance through a combination of novel data structures and algorithmic strategies for reducing the communication and I/O footprint during the assembly process. PaKman presents a solution for the two most time-consuming phases in the full genome assembly pipeline, namely, k-mer counting and contig generation.A key aspect of our algorithm is its graph data structure, which comprises fat nodes (or what we call "macro-nodes") that reduce the communication burden during contig generation. We present an extensive performance and qualitative evaluation of our algorithm, including comparisons to other state-of-the-art parallel assemblers. Our results demonstrate the ability to achieve near-linear speedups on up to 8K cores (tested); outperform state-of-the-art distributed memory and shared memory tools in performance while delivering comparable (if not better) quality; and reduce time to solution significantly. For instance, PaKman is able to generate a high-quality set of assembled contigs for complex genomes such as the human and wheat genomes in a matter of minutes on 8K cores.
4 tweets microbiology
S. pastorianus strains are hybrids of S. cerevisiae and S. eubayanus that have been domesticated for several centuries in lager-beer brewing environments. As sequences and structures of S. pastorianus genomes are being resolved, molecular mechanisms and evolutionary origin of several industrially relevant phenotypes remain unknown. This study investigates how maltotriose metabolism, a key feature in brewing, may have arisen in early S. eubayanus x S. cerevisiae hybrids. To address this question, we generated a near-complete genome assembly of Himalayan S. eubayanus strains of the Holarctic subclade. This group of strains have been proposed to be the origin of the S. eubayanus subgenome of current S. pastorianus strains. The Himalayan S. eubayanus genomes harbored several copies of a SeAGT1 alpha-oligoglucoside transporter gene with high sequence identity to genes encountered in S. pastorianus. Although Himalayan S. eubayanus strains are unable to grown on maltose and maltotriose, their maltose-hydrolase and SeMALT1 and SeAGT1 maltose-transporter genes complemented the corresponding null mutants of S. cerevisiae. Expression, in a Himalayan S. eubayanus strain, of a functional S. cerevisiae maltose-metabolism regulator gene (MALx3) enabled growth on oligoglucosides. The hypothesis that the maltotriose-positive phenotype in S. pastorianus is a result of heterosis was experimentally tested by constructing a S. cerevisiae x S. eubayanus laboratory hybrid with a complement of maltose-metabolism genes that resembles that of current S. pastorianus strains. The ability of this hybrid to consume maltotriose in brewer s wort demonstrated regulatory cross talk between sub-genomes and thereby validated this hypothesis. These results provide experimental evidence of the evolutionary origin of an essential phenotype of lager-brewing strains and valuable knowledge for industrial exploitation of laboratory-made S. pastorianus-like hybrids.
4 tweets neuroscience
A neuronal population encodes information most efficiently when its activity is uncorrelated and high-dimensional, and most robustly when its activity is correlated and lower-dimensional. Here, we analyzed the correlation structure of natural image coding, in large visual cortical populations recorded from awake mice. Evoked population activity was high dimensional, with correlations obeying an unexpected power-law: the n-th principal component variance scaled as 1/n. This was not inherited from the 1/f spectrum of natural images, because it persisted after stimulus whitening. We proved mathematically that the variance spectrum must decay at least this fast if a population code is smooth, i.e. if small changes in input cannot dominate population activity. The theory also predicts larger power-law exponents for lower-dimensional stimulus ensembles, which we validated experimentally. These results suggest that coding smoothness represents a fundamental constraint governing correlations in neural population codes.
4 tweets neuroscience
Sarah E. Morgan, Jakob Seidlitz, Kirstie Whitaker, Rafael Romero-Garcia, Nicholas E Clifton, Cristina Scarpazza, Therese van Amelsvoort, Machteld Marcelis, Jim van Os, Gary Donohoe, David Mothersill, Aiden Corvin, Andrew Pocklington, Armin Raznahan, Philip McGuire, The PSYSCAN Consortium, Petra E. Vértes, Edward T. Bullmore
Schizophrenia has been conceived as a disorder of brain connectivity but it is unclear how this network phenotype is related to the emerging genetics. We used morphometric similarity analysis of magnetic resonance imaging (MRI) data as a marker of inter-areal cortical connectivity in three prior case-control studies of psychosis: in total, N=185 cases and N=227 controls. Psychosis was associated with globally reduced morphometric similarity (MS) in all 3 studies. There was also a replicable pattern of case-control differences in regional MS which was significantly reduced in patients in frontal and temporal cortical areas, but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in MS was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms and pathways. In addition, genes that were normally over-expressed in cortical areas with reduced MS were significantly up-regulated in a prior post mortem study of schizophrenia. We propose that this combination of neuroimaging and transcriptional data provides new insight into how previously implicated genes and proteins, as well as a number of unreported proteins in their vicinity on the protein interaction network, may interact to drive structural brain network changes in schizophrenia.
4 tweets bioinformatics
Graphics processing units (GPU) allow image processing at unprecedented speed. We present CLIJ, a Fiji plugin enabling end-users with entry level experience in programming to benefit from GPU-accelerated image processing. Freely programmable workflows can sped up image processing in Fiji by factor 10 and more using high-end GPU hardware and on affordable mobile computers with built-in GPUs.
4 tweets ecology
Biodiversity underlies many of the ecosystem services demanded by humans. For cities, the design of ‘green infrastructures’ or ‘nature-based solutions’ has been proposed to maintain the provisioning of these services and the preservation of biodiversity. It is unclear, however, how such green infrastructure can be implemented given existing planning practices that generally ignore biodiversity. Urban open spaces are normally designed by landscape architects with a primary focus on plants, aesthetic design and functionality for human users. As a consequence, conservation of species only plays a minor role, in fact, protected animals are often considered detrimental to the design, e.g. when the need to conserve a protected species demand modifications of a building project. Conversely, conservationists are often in favor of protected areas, also in cities, with little access of humans and no human design. We propose ‘Animal-Aided Design’ (AAD) as a methodology for the design of urban open spaces, to integrate conservation into open space planning. The basic idea of AAD is to include the presence of animals in the planning process, such that they are an integral part of the design. For AAD, the desired species are chosen at the beginning of a project. The requirements of the target species then not only set boundary conditions for the design, but also serve as an inspiration for the design itself. The aim of AAD is to establish a stable population at the project site, or contribute to population growth of species with larger habitats. AAD thus allows a combination of good urban design with species conservation. We illustrate our approach with designs for urban spaces in Munich.
4 tweets ecology
1. Food web stability, a fundamental characteristic of ecosystems, is influenced by the nature and strength of species interactions. Theory posits that food webs are stabilized by omnivory and disrupted by novel consumers. 2. To test the effects of secondary consumer origin and trophic level on basal resource stability, we constructed crayfish-snail-algae modules using four congeneric species of crayfish (Faxonius spp.), two from native populations (F. propinquus and F. virilis) and two from non-native populations (F. limosus and F. rusticus). We performed surgical manipulations of crayfish feeding structures to create omnivore food web and predator food chain modules. We compared the temporal stability of these modules using measures of the coefficient of variation of the basal resource (benthic algae). 3. Consistent with theoretical and empirical predictions, food web modules with omnivory had the lowest coefficient of variation. However, contrary to prediction, we did not find consistently higher coefficients of variation in modules with non-native species. Rather, across species, we found the lowest coefficient of variation in modules with one of the non-native species (F. rusticus) and one native species (F. virilis), owing to stronger interactions between these crayfish species and their snail and algal food resources. 4. The results suggest that omnivory is indeed stabilizing and that very weak interactions or very low attack rates of the consumer on the basal resource can be unstable. Thus, we demonstrate that omnivores may have different impacts than predators when introduced into a novel ecosystem, differences that can supersede the effect of species identity.
4 tweets plant biology
Stalk lodging in maize results in substantial yield losses worldwide. These losses could be prevented through genetic improvement. However, breeding efforts and genetics studies are hindered by lack of a robust and economical phenotyping method for assessing stalk lodging resistance. A field-based phenotyping platform that induces failure patterns consistent with natural stalk lodging events and measures stalk bending strength in field-grown plants was recently developed. Here we examine the association between data gathered from this new phenotyping platform with counts of stalk lodging incidence on a select group of maize hybrids. For comparative purposes, we examine four additional predictive phenotypes commonly assumed to be related to stalk lodging resistance; namely, rind puncture resistance, cellulose, hemicellulose, and lignin. Historical counts of lodging incidence were gathered on 47 hybrids, grown in 98 distinct environments, spanning four years and 41 unique geographical locations in North America. Using Bayesian generalized linear mixed effects models, we show that stalk lodging incidence is associated with each of the five predictive phenotypes. Further, based on a joint analysis we demonstrate that, among the phenotypes considered, stalk bending strength measured by the new phenotyping platform is the most important predictive phenotype of naturally occurring stalk lodging incidence in maize, followed by rind puncture resistance and cellulose content. This study demonstrates that field-based measurements of stalk bending strength provide a reliable estimate of stalk lodging incidence. The stalk bending strength data acquired from the new phenotyping platform will be valuable for phenotypic selection in breeding programs and for generating mechanistic insights into the genetic regulation of stalk lodging resistance.
4 tweets evolutionary biology
Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. This issue creates a tradeoff between noise and power in empirical applications. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. Moreover, these methods display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Further, we applied these statistics on a bonobo population-genomic dataset. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and NKAIN3, associated with sexuality. Finally, we integrated the set of statistics into open-source software named BalLeRMix, for future applications by the scientific community.
4 tweets neuroscience
One remarkable feature of neuronal activity in the mammalian cortex is the high level of variability in response to repeated stimuli. First, we used an open dataset, the Allen Brain Observatory, to quantify the distribution of responses to repeated presentations of natural movies. We find that even for their preferred moment in the movie clip, neurons have high variability which cannot be well captured by Gaussian or Poisson distributions. A large fraction of responses are better fit by log-normal or Gaussian mixture models with two components. These distributions are similar to activity distributions during training of deep neural networks using dropout. This poses the interesting hypothesis: is the role of cortical noise to help in generalization during learning? Second, to ensure the robustness of our results we analyzed electrophysiological recordings in the same areas of mouse visual cortex, again using repeated natural movie presentations and found similar response distributions. To make sure that the trial-by-trial variations we observe are not due exclusively to the result of changes in state, we constructed a population coupling model, where each neuron's activity is coupled to a low-dimension version of the activity of all other simultaneously recorded neurons. The population coupling model can capture global, brain-wide activity fluctuations that are state-dependent. The residuals from this model also show non-Gaussian noise distributions. Third, we ask a more specific question: is the noise in the cortex more likely to move the representation of the stimulus in-class versus out-of-class? To address this question, we analyzed the responses of neurons across trials from multiple sections of different movie clips. We observe that the noise in the cortex better aligns to in-class variations. We argue that a useful noise for learning generalizations is to move from representations of different exemplars in-class, similar to cortical noise.
4 tweets microbiology
Type VI secretion systems (T6SSs) are nanomachines widely used by bacteria to compete with rivals. T6SSs deliver multiple toxic effector proteins directly into neighbouring cells and play key roles in shaping diverse polymicrobial communities. A number of families of T6SS-dependent anti-bacterial effectors have been characterised, however the mode of action of others remains unknown. Here we report that Ssp6, an anti-bacterial effector delivered by the Serratia marcescens T6SS, is an ion-selective pore-forming toxin. In vivo, Ssp6 inhibits growth by causing depolarisation of the inner membrane of intoxicated cells and also leads to increased outer membrane permeability, whilst reconstruction of Ssp6 activity in vitro demonstrated that it forms cation-selective pores. A survey of bacterial genomes revealed that Ssp6-like effectors are widespread in Enterobacteriaceae and often linked with T6SS genes. We conclude that Ssp6 represents a new family of T6SS-delivered anti-bacterial effectors, further diversifying the portfolio of weapons available for deployment during inter-bacterial conflict.
4 tweets epidemiology
Ayse Demirkan, Rene Pool, Joris Deelen, Marian Beekman, Jun Liu, Amy C Harms, Anika Varhoorst, Fiona A. Hagenbeek, Gonneke Willemsen, Aswin Verhoeven, Najaf Amin, Ko Willems van Dijk, Thomas Hankemeier, Dorret I Boomsma, Eline Slagboom, Cornelia M. van Duijn
There is continuous interest in the genetic determinants of plasma triglycerides (TGs) and phospholipids and their role in the etiology of cardiovascular disease (CVD). Here, we report the results of a Dutch genome wide association study (GWAS) of an in-house developed lipidomics platform, focusing on 90 plasma lipids. Lipids were assessed by liquid chromatography mass spectrometry in participants from the Leiden Longevity Study, the Netherlands Twin Register and the Erasmus Rucphen Family (ERF) study and meta-analysed, resulting in a sample size of 5537 participants. In addition, we performed genetic correlation analyses between the 90 plasma lipids and markers of metabolic health, as well as vascular pathology and CVD combining our GWAS results with publicly available GWAS outputs. We replicated previously known associations between 34 lipids and 10 lipid quantitative trait loci (lipQTL) (GCKR, APOA1, FADS1, SGPP1,TMEM229B, LIPC, PDXDC1, CETP, CERS4 and SPTLC3) with metabolome-wide (P < 1.61 x 10-9 ) significance. Moreover, we report 6 novel phospholipid-related and 5 triglyceride (TG)-related loci: SGGP1 (SM21:0), SPTLC3 (SM21:0 and SM25:1), FADS1 (LPCO16:1, PC38:2, PEO36:5, PEO38:5, TG56:5, TG56:6, and TG56:7), TMEM229 (LPCO16:1), GCKR (TG50:2), and APOA1 (TG54:4). In addition, we report suggestively significant (P < 5 x 10-8) associations mapping to eleven novel lipid quantitative trait loci (lipQTLs), three of which are supported by mining previous GWAS data: MAU (PC34:4), LDLR (SM16:0), and MLXIPL (TG48:1 and TG50:1)). Genetic correlation analysis indicates that one specific sphingomyelin, SM22:0, shares common genetic background with CVD. Levels of SM22:0 also positively associate with carotid artery intima-media thickness in the ERF study, and this observation is independent of LDL-C level. Our findings yield higher resolution of plasma lipid species and new insights in the biology of circulating phosholipids and their relation to CVD risk.
4 tweets neuroscience
Degenerative retinal diseases such as retinitis pigmentosa and macular degeneration cause irreversible vision loss in more than 10 million people worldwide. Retinal prostheses, now implanted in more than 250 patients worldwide, electrically stimulate surviving cells in order to evoke neuronal responses that are interpreted by the brain as visual percepts ('phosphenes'). However, instead of seeing focal spots of light, users of current epiretinal devices perceive highly distorted phosphenes, which vary in shape not just across subjects but also across electrodes, resulting in distorted percepts. We characterized these distortions by asking users of the Argus retinal prosthesis system (Second Sight Medical Products, Inc.) to draw percepts elicited by single-electrode stimulation on a touchscreen. Based on ophthalmic fundus photographs, we then developed a computational model of the topographic organization of optic nerve fiber bundles in each subject's retina, and used this model to successfully simulate predicted patient percepts. Our model shows that activation of passing axon fibers contributes to the rich repertoire of phosphene shapes reported by patients in our psychophysical measurements, successfully replicating visual percepts ranging from 'blobs' to oriented 'streaks' and 'wedges' depending on the retinal location of the stimulating electrode. This model provides a first step towards future devices that incorporate stimulation strategies tailored to each individual patient's retinal neurophysiology.
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