bluuebunny/crossref_metadata_2025 huggingface dataset:
Coronary Artery Disease Risk of Familial Hypercholesterolemia Genetic Variants Independent of Historical Cholesterol Exposure
Authors: Clarke Shoa L. , Tcheandjieu Catherine , Hilliard Austin , Lee Kyung Min , Lynch Julie , Chang Kyong-Mi , Miller Donald ,   VA Million Veteran Program, Knowles Joshua W. , O’Donnell Christopher , Tsao Phil , Rader Daniel J. , Wilson Peter W. , Sun Yan V. , Gaziano Michael , Assimes Themistocles L.
Published: November 2020

Aims

Familial hypercholesterolemia (FH) genetic variants confer risk for coronary artery disease (CAD) even after adjusting for low-density lipoprotein cholesterol (LDL-C) levels, using a single measurement. This study evaluated whether multiple historical measures of LDL-C observed in the electronic health record (EHR) can account for the risk associated with FH variants.

Methods and Results

We analyzed 418,790 participants in the Million Veteran Program with EHR data spanning up to 15 years prior to and 7 years after enrollment, including ∼6.3 million LDL-C measurements. FH variants in LDLR, APOB, and PCSK9 were identified using a custom genotype array. We implemented a nested case-control design, using incidence density sampling to match etiologic exposure windows and measure CAD risk while adjusting for LDL-C exposure. In a cohort of 23,091 primarily prevalent cases and 230,910 matched controls, FH variants conferred increased risk for CAD (odds ratio: 1.53; 95% confidence interval: 1.24 to 1.89; p: 7.8×10−5). Adjusting for mean LDL-C exposure prior to the index date attenuated this risk more than adjusting for a single measurement, but significant risk remained (odds ratio: 1.33; 95% confidence interval: 1.08 to 1.64; p = 8.4×10−3). The pattern was also apparent in stratified analyses by sex and ancestry, and we found evidence of an interaction between sex and FH carrier status.

Conclusion

The risk associated with FH variants cannot be fully captured by the LDL-C data available in the EHR, even when considering multiple LDL-C measurements spanning more than a decade.
Impact of oseltamivir treatment on influenza A and B dynamics in human volunteers
Authors: Hooker Kyla L. , Ganusov Vitaly V.
Published: November 2020

Influenza viruses infect millions of humans every year causing an estimated 400,000 deaths globally. Due to continuous virus evolution current vaccines provide only limited protection against the flu. Several antiviral drugs are available to treat influenza infection, and one of the most most commonly used drugs is oseltamivir (Tamiflu). While the mechanism of action of oseltamivir as a neuraminidase inhibitor is well understood, the impact of oseltamivir on influenza virus dynamics in humans has been controversial. Many clinical trials with oseltamivir have been done by pharmaceutical companies such as Roche but the results of these trials until recently have been reported as summary reports or papers. Typically, such reports included median virus shedding curves for placebo and drug-treated influenza virus infected volunteers often indicating high efficacy of the early treatment. However, median shedding curves may be not accurately representing drug impact in individual volunteers. Importantly, due to public pressure clinical trials data testing oseltamivir efficacy has been recently released in the form of redacted PDF documents. We digitized and re-analyzed experimental data on influenza virus shedding in human volunteers from three previously published trials: on influenza A (1 trial) or B viruses (2 trials). Given that not all volunteers exposed to influenza viruses actually start virus shedding we found that impact of oseltamivir on the virus shedding dynamics was dependent on i) selection of volunteers that were infected with the virus, and ii) the detection limit in the measurement assay; both of these details were not well articulated in the published studies. By assuming that any viral measurement is above the limit of detection we could match previously published data on median influenza A virus (flu A study) shedding but not on influenza B virus shedding (flu B study B) in human volunteers. Additional analyses confirmed that oseltamivir had an impact on the duration of shedding and overall shedding (defined as area under the curve) but this result was varied by the trial. Interestingly, treatment had no impact on the rates at which shedding increased or declined with time in individual volunteers. Additional analyses showed that oseltamivir impacted the kinetics of the start and end of viral shedding and in about 20-40% of volunteers treatment had no impact on viral shedding duration. Our results suggest an unusual impact of oseltamivir on influenza viruses shedding kinetics and caution about the use of published median data or data from a few individuals for inferences. Furthermore, we call for the need to publish raw data from critical clinical trials that can be then independently analyzed.
Pleiotropy method identifies genetic overlap between orofacial clefts at multiple loci from GWAS of multi-ethnictrios
Authors: Ray Debashree , Venkataraghavan Sowmya , Zhang Wanying , Leslie Elizabeth J. , Hetmanski Jacqueline B. , Marazita Mary L , Ruczinski Ingo , Taub Margaret A. , Beaty Terri H.
Published: November 2020

Based on epidemiologic and embryologic patterns, nonsyndromic orofacial clefts are commonly categorized into cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP). While nearly forty risk genes have been identified for CL/P, few risk genes are known for CP. We used a new statistical method, PLACO, to identify genetic variants influencing risk of both CL/P and CP. In a combined multi-ethnic genome-wide study of 2,771 CL/P and 611 CP case-parent trios, we discovered 6 new loci of genetic overlap between CL/P and CP; 3 new loci between pairwise OFC subtypes; and 4 loci not previously implicated in OFCs. We replicated the shared genetic etiology of subtypes underlying CL/P, and further discovered loci of genetic overlap exhibiting etiologic differences. In summary, we found evidence for new genetic regions and confirmed some recognized OFC genes either exerting shared risk or with opposite effects on risk to OFC subtypes.
Local Ancestry Prediction withPyLAE
Authors: Smetanin Alexander , Moshkov Nikita , Tatarinova Tatiana V.
Published: November 2020

We developed PyLAE - a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimation of many parameters, it can process thousands of genomes within a day. Computational efficiency, straightforward presentation of results, and an ease of installation makesPyLAEa useful tool to study admixed populations.

Availability and implementation

The source code and installation manual are available athttps://github.com/smetam/pylae.
SCNIC: Sparse Correlation Network Investigation for Compositional Data
Authors: Shaffer Michael , Thurimella Kumar , Sterrett John D. , Lozupone Catherine A.
Published: November 2020

Background

Microbiome studies are often limited by a lack of statistical power due to small sample sizes and a large number of features. This problem is exacerbated in correlative studies of multi-omic datasets. Statistical power can be increased by finding and summarizing modules of correlated observations, which is one dimensionality reduction method. Additionally, modules provide biological insight as correlated groups of microbes can have relationships among themselves.

Results

To address these challenges, we developed SCNIC: Sparse Cooccurrence Network Investigation for compositional data. SCNIC is open-source software that can generate correlation networks and detect and summarize modules of highly correlated features. Modules can be formed using either the Louvain Modularity Maximization (LMM) algorithm or a Shared Minimum Distance algorithm (SMD) that we newly describe here and relate to LMM using simulated data. We applied SCNIC to two published datasets and we achieved increased statistical power and identified microbes that not only differed across groups, but also correlated strongly with each other, suggesting shared environmental drivers or cooperative relationships among them.

Conclusions

SCNIC provides an easy way to generate correlation networks, identify modules of correlated features and summarize them for downstream statistical analysis. Although SCNIC was designed considering properties of microbiome data, such as compositionality and sparsity, it can be applied to a variety of data types including metabolomics data and used to integrate multiple data types. SCNIC allows for the identification of functional microbial relationships at scale while increasing statistical power through feature reduction.
Fast Alignment-Free Similarity Estimation By Tensor Sketching
Authors: Joudaki Amir , Rätsch Gunnar , Kahles André
Published: November 2020

The sharp increase in next-generation sequencing technologies’ capacity has created a demand for algorithms capable of quickly searching a large corpus of biological sequences. The complexity of biological variability and the magnitude of existing data sets have impeded finding algorithms with guaranteed accuracy that efficiently run in practice. Our main contribution is the Tensor Sketch method that efficiently and accurately estimates edit distances. In our experiments, Tensor Sketch had 0.956 Spearman’s rank correlation with the exact edit distance, improving its best competitor Ordered MinHash by 23%, while running almost 5 times faster. Finally, all sketches can be updated dynamically if the input is a sequence stream, making it appealing for large-scale applications where data cannot fit into memory.

Conceptually, our approach has three steps: 1) represent sequences as tensors over their sub-sequences, 2) apply tensor sketching that preserves tensor inner products, 3) implicitly compute the sketch. The sub-sequences, which are not necessarily contiguous pieces of the sequence, allow us to outperformk-mer-based methods, such as min-hash sketching over a set ofk-mers. Typically, the number of sub-sequences grows exponentially with the sub-sequence length, introducing both memory and time overheads. We directly address this problem in steps 2 and 3 of our method. While the sketching of rank-1 or super-symmetric tensors is known to admit efficient sketching, the sub-sequence tensor does not satisfy either of these properties. Hence, we propose a new sketching scheme that completely avoids the need for constructing the ambient space.

Our tensor-sketching technique’s main advantages are three-fold: 1) Tensor Sketch has higher accuracy than any of the other assessed sketching methods used in practice. 2) All sketches can be computed in a streaming fashion, leading to significant time and memory savings when there is overlap between input sequences. 3) It is straightforward to extend tensor sketching to different settings leading to efficient methods for related sequence analysis tasks. We view tensor sketching as a framework to tackle a wide range of relevant bioinformatics problems, and we are confident that it can bring significant improvements for applications based on edit distance estimation.
Sharing the burden? Earthworms and woodlice show seasonal complementarity in peak abundances in soil in an oak-beech temperate woodland
Authors: Carpenter Daniel , Sherlock Emma , Inward Kelly , Carroway Kerry , Lidgett Angela , Eggleton Paul
Published: November 2020

Complementarity between functional analogues can confer resistance and resilience on ecosystems in the face of environmental change. High biodiversity can lead to increased ecosystem functionality through complementary effects. Earthworms, woodlice and millipedes can have high densities in leaf litter and soils, but little is known about their seasonal patterns. The two groups play important roles in the breakdown and incorporation of organic matter into soils. Differences in peak abundance could affect the rates of litter break down and incorporation in different seasons. We sampled earthworms, woodlice and millipedes from leaf litter soil every month for ten years in a New Forest woodland. We used non-parametric regression to explore monthly and yearly variation in the abundance of decomposer organisms and soil temperature and moisture. Earthworms have a distinct seasonal peak in density different from woodlice and millipedes. Earthworm peak density is in the winter and spring and is correlated with greatest soil moisture. Woodlice (and millipede) have their peak density is in the summer and is correlated with the highest soil temperatures. This means that earthworms, woodlice and millipedes have complementary peaks in abundance. These two groups have similar functional roles in litter decomposition and these data imply ecological complementarity in this important ecological process. This effect is likely to be widespread in lowland woodland in the UK and Europe, with only extreme temperatures and low pH limiting the distribution. Increased summer drought as a result of climate change may lead to changes in the relative abundance of these three groups and in particular local extinctions of earthworms which will in turn affect litter decomposition.
Facilitated transition in HIV drug trial closure: a conceptual model for HIV post-trial care
Authors: Nalubega Sylivia , Cox Karen , Mugerwa Henry , Evans Catrin
Published: November 2020

Within the HIV clinical trial field, there are gaps in existing ethical regulations in relation to post-trial care. There is need to develop post-trial care guidelines that are flexible and sensitive to local contexts and to the specific needs of different groups of participants, particularly in low income contexts. Evidence regarding HIV trial closure and post-trial care is required to underpin the development of appropriate policies in this area. This article reports research from Uganda that develops a new model of ‘Facilitated Transition’ to conceptualize the transition process of HIV positive trial participants from ‘research’ to ‘usual care’ health facilities after trial conclusion. This was a qualitative grounded theory study that included 21 adult HIV positive post-trial participants and 22 research staff, undertaken between October 2014 and August 2015. The findings showed that trial closure is a complex process for HIV positive participants which includes three phases: the pre-closure, trial-closure, and post-trial phases. The model highlights a range of different needs of research participants and suggests specific and person-centred interventions that can be delivered at different phases with the aim of improving health outcomes and experiences for trial participants in low income settings during trial closure. Further research needs to be done to verify the model in other contexts and for other conditions.
Differentially expressed circular RNAs in peripheral blood mononuclear cells of PD patients
Authors: Ravanidis Stylianos , Bougea Anastasia , Karampatsi Dimitra , Papagiannakis Nikolaos , Maniati Matina , Stefanis Leonidas , Doxakis Epaminondas
Published: November 2020

Background

New noninvasive and affordable molecular approaches that will complement current practices and increase the accuracy of PD diagnosis are urgently needed. CircRNAs are highly stable non-coding RNAs that accumulate with aging in neurons and are increasingly shown to regulate all aspects of neuronal development and function.

Objectives

The aims of the present study were to identify differentially expressed circRNAs in PBMCs of idiopathic PD patients and explore the competing endogenous RNA networks affected.

Methods

Eighty-seven circRNAs were initially selected based on relatively high gene expression in the human brain. Over half of these were readily detectable in PBMCs using RT-qPCR. Comparative expression analysis was then performed in PBMCs from sixty controls and sixty idiopathic subjects with PD.

Results

Six circRNAs derived from MAPK9, HOMER1, SLAIN1, DOP1B, REPS1, and PSEN1 transcripts were significantly downregulated in PD patients. The classifier that best distinguished PD consisted of four circRNAs with an AUC of 0.84. CLIP-Seq data revealed that the RNA binding proteins bound by most of the deregulated circRNAs include the neurodegeneration-associated FUS, TDP43, FMR1 and ATXN2. MicroRNAs predicted to be sequestered by most deregulated circRNAs had the GOslim categories ‘Protein modification’, ‘Transcription factor activity’ and ‘Cytoskeletal protein binding’ mostly enriched.

Conclusions

This is the first study that identifies circRNAs deregulated in the peripheral blood of PD patients. They may serve as diagnostic biomarkers and since they are highly expressed in the brain and are derived from genes with essential brain functions, they may also hint on the PD pathways affected.
Measuring diversity from space: a global view of the free and open source rasterdiv R package under a coding perspective
Authors: Thouverai Elisa , Marcantonio Matteo , Bacaro Giovanni , Da Re Daniele , Iannacito Martina , Ricotta Carlo , Tattoni Clara , Vicario Saverio , Rocchini Duccio
Published: November 2020

The variation of species diversity over space and time has been widely recognised as a key challenge in ecology. However, measuring species diversity over large areas might be difficult for logistic reasons related to both time and cost savings for sampling, as well as accessibility of remote ecosystems. In this paper, we present a newRpackage -rasterdiv- to calculate diversity indices based on remotely sensed data, by discussing the theory beyond the developed algorithms. Obviously, measures of diversity from space should not be viewed as a replacement of in-situ data on biological diversity, but they are rather complementary to existing data and approaches. In practice, they integrate available information of Earth surface properties, including aspects of functional (structural, biophysical and bio-chemical), taxonomic, phylogenetic and genetic diversity. Making use of therasterdivpackage can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.
Active elimination of intestinal cells drives oncogenic growth in organoids
Authors: Garcia Ana Krotenberg , Fumagalli Arianna , Le Huy Quang , Sansom Owen J. , van Rheenen Jacco , Suijkerbuijk Saskia J.E.
Published: November 2020

Competitive cell-interactions play a crucial role in quality control during development and homeostasis. Here we show that cancer cells use such interactions to actively eliminate wild-type intestine cells in enteroid monolayers and organoids. This apoptosis-dependent process boosts proliferation of intestinal cancer cells. The remaining wild-type population activates markers of primitive epithelia and transits to a fetal-like state. Prevention of this cell fate transition avoids elimination of wild-type cells and, importantly, limits the proliferation of cancer cells. JNK signalling is activated in competing cells and is required for cell fate change and elimination of wild-type cells. Thus, cell competition drives growth of cancer cells by active out-competition of wild-type cells through forced cell death and cell fate change in a JNK dependent manner.
The white matter is a pro-differentiative microenvironment for glioblastoma
Authors: Brooks Lucy J. , Clements Melanie P. , Burden Jemima J. , Kocher Daniela , Richards Luca , Devesa Sara Castro , Woodberry Megan , Ellis Michael , Zakka Leila , Jaunmuktane Zane , Brandner Sebastian , Morrison Gillian , Pollard Steven M. , Dirks Peter B. , Marguerat Samuel , Parrinello Simona
Published: November 2020

Glioblastomas are hierarchically organised tumours driven by glioma stem cells that retain partial differentiation potential. Glioma stem cells are maintained in specialised microenvironments, but how they undergo lineage progression outside of these niches remains unclear. Here we identify the white matter as a differentiative niche for glioblastomas with oligodendrocyte lineage competency. Tumour cells in contact with white matter acquire pre-oligodendrocyte-like fate, resulting in decreased proliferation and invasion. Differentiation is a response to white matter injury, which is caused by tumour infiltration itself in a tumoursuppressive feedback loop. Mechanistically, tumour cell differentiation is driven by selective white matter upregulation of SOX10, a master regulator of normal oligodendrogenesis. SOX10 overexpression or treatment with myelination-promoting agents that upregulate endogenous SOX10, mimic this response, leading to white matter-independent pre-oligodendrocyte-like differentiation and tumour suppressionin vivo. Thus, glioblastoma recapitulates an injury response and exploiting this latent programme may offer treatment opportunities for a subset of patients.
Capturing in-field root system dynamics with the RootTracker
Authors: Aguilar Jeffrey J. , Moore Matt , Johnson Logan , Greenhut Rachel F. , Rogers Eric , Walker Drew , O’Neil Fletcher , Edwards Jake L. , Thystrup Jake , Farrow Sam , Windle Jesse B. , Benfey Philip N.
Published: November 2020

Optimizing root system architecture offers a promising approach to developing stress tolerant cultivars in the face of climate change, as root systems are critical for water and nutrient uptake as well as mechanical stability. However, breeding for optimal root system architecture has been hindered by the difficulty in measuring root growth in the field. Here, we describe a technology, the RootTracker (RT), which employs capacitance touch sensors to monitor in-field root growth over time. Configured in a cylindrical shutter-like fashion around a planted seed, 264 electrodes are individually charged multiple times over the course of an experiment. Signature changes in the measured capacitance and resistance readings indicate when a root has touched or grown close to an electrode. Using the RootTracker, we have measured root system dynamics of commercial maize hybrids growing in both typical Midwest field conditions and under different irrigation regimes. We observed rapid responses of root growth to water deficits and found evidence for a “priming response” in which an early water deficit causes more and deeper roots to grow at later time periods. There was genotypic variation among hybrid maize lines in their root growth in response to drought, indicating a potential to breed for root systems adapted for different environments.
Automatic whole cell organelle segmentation in volumetric electron microscopy
Authors: Heinrich Larissa , Bennett Davis , Ackerman David , Park Woohyun , Bogovic John , Eckstein Nils , Petruncio Alyson , Clements Jody , Xu C. Shan , Funke Jan , Korff Wyatt , Hess Harald F. , Lippincott-Schwartz Jennifer , Saalfeld Stephan , Weigel Aubrey V. ,   COSEM Project Team
Published: November 2020

Cells contain hundreds of different organelle and macromolecular assemblies intricately organized relative to each other to meet any cellular demands. Obtaining a complete understanding of their organization is challenging and requires nanometer-level, threedimensional reconstruction of whole cells. Even then, the immense size of datasets and large number of structures to be characterized requires generalizable, automatic methods. To meet this challenge, we developed an analysis pipeline for comprehensively reconstructing and analyzing the cellular organelles in entire cells imaged by focused ion beam scanning electron microscopy (FIB-SEM) at a near-isotropic size of 4 or 8 nm per voxel. The pipeline involved deep learning architectures trained on diverse samples for automatic reconstruction of 35 different cellular organelle classes - ranging from endoplasmic reticulum to microtubules to ribosomes - from multiple cell types.

Automatic reconstructions were used to directly quantify various previously inaccessible metrics about these structures, including their spatial interactions. We show that automatic organelle reconstructions can also be used to automatically register light and electron microscopy images for correlative studies. We created an open data and open source web repository, OpenOrganelle, to share the data, computer code, and trained models, enabling scientists everywhere to query and further reconstruct the datasets.
Identification of an endocannabinoid gut-brain vagal mechanism controlling food reward and energy homeostasis
Authors: Berland Chloé , Castel Julien , Terrasi Romano , Montalban Enrica , Foppen Ewout , Martin Claire , Muccioli Giulio G. , Luquet Serge , Gangarossa Giuseppe
Published: November 2020

The regulation of food intake, asine qua nonrequirement for survival, thoroughly shapes feeding and energy balance by integrating both homeostatic and hedonic values of food. Unfortunately, the widespread access to palatable food has led to the development of feeding habits that are independent from metabolic needs. Among these, binge eating (BE) is characterized by uncontrolled voracious eating. While reward deficit seems to be a major contributor of BE, the physiological and molecular underpinnings of BE establishment remain elusive. Here, we combined a physiologically relevant BE mouse model with multiscalein vivoapproaches to explore the functional connection between the gut-brain axis and the reward and homeostatic brain structures.

Our results show that BE elicits compensatory adaptations requiring the gut-to-brain axis which, through the vagus nerve, relies on the permissive actions of peripheral endocannabinoids (eCBs) signaling. Selective inhibition of peripheral CB1 receptors resulted in a vagus-dependent increased hypothalamic activity, modified metabolic efficiency, and dampened activity of mesolimbic dopamine circuit, altogether leading to the suppression of palatable eating. We provide compelling evidence for a yet unappreciated physiological integrative mechanism by which variations of peripheral eCBs control the activity of the vagus nerve, thereby in turn gating the additive responses of both homeostatic and hedonic brain circuits which govern homeostatic and reward-driven feeding.

In conclusion, we reveal that vagus-mediated eCBs/CB1R functions represent an interesting and innovative target to modulate energy balance and counteract food-reward disorders.
Novel gene-specific translation mechanism of dysregulated, chronic inflammation reveals promising, multifaceted COVID-19 therapeutics
Authors: Wang Li , Muneer Adil , Xie Ling , Zhang Feng , Wu Bing , Mei Liu , Lenarcic Erik M , Feng Emerald Hillary , Song Juan , Xiong Yan , Yu Xufen , Wang Charles , Gheorghe Ciprian , Torralba Karina , Cook Jeanette Gowen , Wan Yisong Y. , Moorman Nathaniel John , Song Hongjun , Jin Jian , Chen Xian
Published: November 2020

Hyperinflammation and lymphopenia provoked by SARS-CoV-2-activated macrophages contribute to the high mortality of Coronavirus Disease 2019 (COVID-19) patients. Thus, defining host pathways aberrantly activated in patient macrophages is critical for developing effective therapeutics. We discovered that G9a, a histone methyltransferase that is overexpressed in COVID-19 patients with high viral load, activates translation of specific genes that induce hyperinflammation and impairment of T cell function or lymphopenia. This noncanonical, pro-translation activity of G9a contrasts with its canonical epigenetic function. In endotoxin-tolerant (ET) macrophages that mimic conditions which render patients with pre-existing chronic inflammatory diseases vulnerable to severe symptoms, our chemoproteomic approach with a biotinylated inhibitor of G9a identified multiple G9a-associated translation regulatory pathways that were upregulated by SARS-CoV-2 infection. Further, quantitative translatome analysis of ET macrophages treated progressively with the G9a inhibitor profiled G9a-translated proteins that unite the networks associated with viral replication and the SARS-CoV-2-induced host response in severe patients. Accordingly, inhibition of G9a-associated pathways produced multifaceted, systematic effects, namely, restoration of T cell function, mitigation of hyperinflammation, and suppression of viral replication. Importantly, as a host-directed mechanism, this G9a-targeted, combined therapeutics is refractory to emerging antiviral-resistant mutants of SARS-CoV-2, or any virus, that hijacks host responses.
DeepMosaic: Control-independent mosaic single nucleotide variant detection using deep convolutional neural networks
Authors: Yang Xiaoxu , Xu Xin , Breuss Martin W. , Antaki Danny , Ball Laurel L. , Chung Changuk , Li Chen , George Renee D. , Wang Yifan , Bae Taejeoing , Abyzov Alexej , Wei Liping , Sebat Jonathan ,   NIMH Brain Somatic Mosaicism Network, Gleeson Joseph G.
Published: November 2020

Introductory paragraph

Mosaic variants (MVs) reflect mutagenic processes during embryonic development1and environmental exposure2, accumulate with aging, and underlie diseases such as cancer and autism3. The detection of MVs has been computationally challenging due to sparse representation in non-clonally expanded tissues. While heuristic filters and tools trained on clonally expanded MVs with high allelic fractions are proposed, they show relatively lower sensitivity and more false discoveries4–9. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs, and a convolutional neural networks-based classification module for control-independent MV detection. DeepMosaic achieved higher accuracy compared with existing methods on biological and simulated sequencing data, with a 96.34% (158/164) experimental validation rate. Of 932 mosaic variants detected by DeepMosaic in 16 whole genome sequenced samples, 21.89-58.58% (204/932-546/932) MVs were overlooked by other methods. Thus, DeepMosaic represents a highly accurate MV classifier that can be implemented as an alternative or complement to existing methods.
Probing the decision-making mechanisms underlying choice between drug and nondrug rewards in rats
Authors: Vandaele Youna , Lenoir Magalie , Vouillac-Mendoza Caroline , Guillem Karine , Ahmed S.H.
Published: November 2020

Investigating the decision-making mechanisms underlying choice between drug and nondrug rewards is essential to understand how their alterations can contribute to substance use disorders. However, despite some recent effort, this investigation remains a challenge in a drug choice setting, notably when it comes to delineate the role of goal-directed versus habitual control mechanisms. The goal of this study was to try probing these different mechanisms by comparing response latencies measured during sampling (i.e., only one option is available) and choice trials. A deliberative goal-directed control mechanism predicts a lengthening of latencies during choice whereas a habitual control mechanism predicts no change in latencies. Alternatively, a race-like response competition mechanism, such as that postulated by the behavioral ecology-inspired Sequential Choice Model (SCM), predicts instead a shortening of response latencies during choice compared to sampling. Here we tested the predictions of these different mechanisms by conducting a systematic retrospective analysis of all cocaine versus saccharin choice experiments conducted in rats in our laboratory over the past 12 years. Overall, we found that rats engage a deliberative goal-directed mechanism after limited training, but shift to a SCM-like response selection mechanism after more extended training. The latter finding suggests that habitual control is engaged in a choice setting via a race-like response competition mechanism, and thus, that the SCM is not a general model of choice, as formulated initially, but a specific model of habitual choice.
Proximity Measures as Graph Convolution Matrices for Link Prediction in Biological Networks
Authors: Coşkun Mustafa , Koyutürk Mehmet
Published: November 2020

Motivation

Link prediction is an important and well-studied problem in computational biology, with a broad range of applications including disease gene prioritization, drug-disease associations, and drug response in cancer. The general principle in link prediction is to use the topological characteristics and the attributes–if available– of the nodes in the network to predict new links that are likely to emerge/disappear. Recently, graph representation learning methods, which aim to learn a low-dimensional representation of topological characteristics and the attributes of the nodes, have drawn increasing attention to solve the link prediction problem via learnt low-dimensional features. Most prominently, Graph Convolution Network (GCN)-based network embedding methods have demonstrated great promise in link prediction due to their ability of capturing non-linear information of the network. To date, GCN-based network embedding algorithms utilize a Laplacian matrix in their convolution layers as the convolution matrix and the effect of the convolution matrix on algorithm performance has not been comprehensively characterized in the context of link prediction in biomedical networks. On the other hand, for a variety of biomedical link prediction tasks, traditional node similarity measures such as Common Neighbor, Ademic-Adar, and other have shown promising results, and hence there is a need to systematically evaluate the node similarity measures as convolution matrices in terms of their usability and potential to further the state-of-the-art.

Results

We select 8 representative node similarity measures as convolution matrices within the single-layered GCN graph embedding method and conduct a systematic comparison on 3 important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug–drug interaction (DDI) prediction, protein–protein interaction (PPI) prediction. Our experimental results demonstrate that the node similarity-based convolution matrices significantly improves GCN-based embedding algorithms and deserve more attention in the future biomedical link prediction

Availability

Our method is implemented as a python library and is available at githublink

Contact

mustafa.coskun@agu.edu.tr

Supplementary information

Supplementary data are available atBioinformaticsonline.
Life histories decide reserve benefits in transient yields and bycatch persistence
Authors: Chen Renfei , Tu Chengyi , Liu Quan-Xing
Published: November 2020

Recent research indicates that marine reserves can both improve fisheries yields of target species and maintain the persistence of bycatch species. However, the prevalent equilibrium analyses prevent our understandings in transient behavior at short-time scales. Here, we develop high dimensional theoretical frameworks by considering age structure to assess the relative advantages between reserve-only and no-reserve fisheries management strategies. Our results show that whether strategies with only reserves can achieve higher fisheries yields (measured by both weight and number) and maintain bycatch persistence depends on the life histories of both target and bycatch species through perspectives of transient oscillations. Our research has important practical applications especially for the West Coast groundfish fishery in the USA, as it suggests that reserves can perform benefits in both fisheries and conservation goals for target species with older ages at maturity and lower adult survivorship.
Discovery of rhodomyrtone as a broad-spectrum antiviral inhibitor with anti-SARS-CoV-2 activity
Authors: Tang Wei , Lu Jing , Song Qiao-Yun , Li Man-Mei , Chen Li-Feng , Hu Li-Jun , Yang Shao-Min , Zhang Dong-Mei , Wang Ying , Li Yao-Lan , Ye Wen-Cai
Published: November 2020

The outbreak of new viruses, such as serve acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as well as the emerging of drug-resistance viruses highlight the urgent need for the development of broad-spectrum antiviral drugs. Herein, we report the discovery of a plant-derived small molecule, 6,8-dihydroxy-9-isobutyl-2,2,4,4-tetramethyl-7-(3-methylbutanoyl)-4,9-dihydro-1H-xanthene-1,3(2H)-dione (rhodomyrtone, RDT), which exhibited potent broad-spectrum antiviral activities against several RNA and DNA viruses, including SARS-CoV-2, respiratory syncytial virus (RSV), herpes simplex virus type 1 (HSV-1), herpes simplex virus type 2 (HSV-2), varicella-zoster virus (VZV), human cytomegalovirus (HCMV), and Kaposi’s sarcoma-associated herpesvirus (KSHV). RDT can significantly suppress viral gene expression and show the low possibility to elicit drug-resistant variants. Mechanistic study implied that RDT inhibited viral infection by disturbing the cellular factors that essential for viral gene expression. Our results suggested that RDT might be a promising lead compound for the development of broad-spectrum antiviral drugs.
Hydrophilic Shell Matrix Proteins ofNautilus pompiliusand The Identification of a Core Set of Conchiferan Domains
Authors: Setiamarga Davin H. E. , Hirota Kazuki , Yoshida Masa-aki , Takeda Yusuke , Kito Keiji , Shimizu Keisuke , Isowa Yukinobu , Ikeo Kazuho , Sasaki Takenori , Endo Kazuyoshi
Published: November 2020

Despite being a member of the shelled mollusks (Conchiferans), most members of extant cephalopods have lost their external biomineralized shells, except for the Nautiloids. Here, we report the result of our study to identify major Shell Matrix Proteins and their domains in the NautiloidNautilus pompilius, in order to gain a general insight into the evolution of Conchiferan Shell Matrix Proteins. In order to do so, we conducted transcriptomics of the mantle, and proteomics of the shell ofN. pompiliussimultaneously. Analyses of obtained data identified 61 distinct shell-specific sequences. Of the successfully annotated 27 sequences, protein domains were predicted in 19. Comparative analysis ofNautilussequences with four Conchiferans for which Shell Matrix Protein data were available (the pacific oyster, the pearl oyster, the limpet, and theEuhadrasnail) revealed that three proteins and six domains of the shell proteins are conserved in all Conchiferans. Interestingly, when the terrestrialEuhadrasnail was excluded, another five proteins and six domains were found to be shared among the four marine Conchiferans. Phylogenetic analyses indicated that most of these proteins and domains were present in the ancestral Conchiferan, but employed in shell formation later and independently in most clades. Although further studies utilizing deeper sequencing techniques to obtain genome and full-length sequences, and functional analyses, must be done in the future, our results here provide important pieces of information for the elucidation of the evolution of Conchiferan shells at the molecular level.
Quaternary climate change explains global patterns of tree beta-diversity
Authors: Xu Wu-Bing , Guo Wen-Yong , Serra-Diaz Josep M. , Schrodt Franziska , Eiserhardt Wolf L. , Enquist Brian J. , Maitner Brian S. , Merow Cory , Violle Cyrille , Anand Madhur , Belluau Michaël , Bruun Hans Henrik , Byun Chaeho , Catford Jane A. , Cerabolini Bruno E. L. , Chacón-Madrigal Eduardo , Ciccarelli Daniela , Cornelissen Johannes H. C. , Dang-Le Anh Tuan , Frutos Angel de , Dias Arildo S. , Giroldo Aelton B. , Gutiérrez Alvaro G. , Hattingh Wesley , He Tianhua , Hietz Peter , Hough-Snee Nate , Jansen Steven , Kattge Jens , Komac Benjamin , Kraft Nathan , Kramer Koen , Lavorel Sandra , Lusk Christopher H. , Martin Adam R. , Ma Ke-Ping , Mencuccini Maurizio , Michaletz Sean T. , Minden Vanessa , Mori Akira S. , Niinemets Ülo , Onoda Yusuke , Onstein Renske E. , Peñuelas Josep , Pillar Valério D. , Pisek Jan , Pound Matthew J. , Robroek Bjorn J.M. , Schamp Brandon , Slot Martijn , Sosinski Ênio , Soudzilovskaia Nadejda A. , Thiffault Nelson , van Bodegom Peter , van der Plas Fons , Zheng Jingming , Svenning Jens-Christian , Ordonez Alejandro
Published: November 2020

Both historical and contemporary environmental conditions determine present biodiversity patterns, but their relative importance is not well understood. One way to disentangle their relative effects is to assess how different dimensions of beta-diversity relate to past climatic changes, i.e., taxonomic, phylogenetic and functional compositional dissimilarity, and their components generated by replacement of species, lineages and traits (turnover) and richness changes (nestedness). Here, we quantify global patterns of each of these aspects of beta-diversity among neighboring sites for angiosperm trees using the most extensive global database of tree species-distributions (43,635 species). We found that temperature change since the Last Glacial Maximum (LGM) was the major influence on both turnover and nestedness components of beta-diversity, with a negative correlation to turnover and a positive correlation to nestedness. Moreover, phylogenetic and functional nestedness was higher than expected from taxonomic beta-diversity in regions that experienced large temperature changes since the LGM. This pattern reflects relatively greater losses of phylogenetic and functional diversity in species-poor assemblages, possibly caused by phylogenetically and functionally selective species extinction and recolonization during glacial-interglacial oscillations. Our results send a strong warning that rapid anthropogenic climate change is likely to result in a long-lasting phylogenetic and functional compositional simplification, potentially impairing forest ecosystem functioning.
Measuring adaptation dynamics to hydrogen peroxide in single human cells using fluorescent reporters
Authors: Simiuc Dana , Dahmani Fatima , Pruvost Alexandra , Guilbert Marie , Brulé Mathilde , Lagadec Chann , Thommen Quentin , Pfeuty Benjamin , Courtade Emmanuel , Anquez François
Published: November 2020

We developed an experimental methodology to monitor response dynamics of single human cells to hydrogen peroxide. Our approach is based on fluidic control of both magnitude and time-evolution of the external perturbation, and on high-throughput imaging of intracellular fluorescent redox reporters. We applied step stimulus to MCF7 cells with hydrogen peroxide concentration in the range of 10 to 500μM. First, our data highlights dynamic adaptation of Reactive Oxygen Species (ROS) scavenging system at several time scales. Nicotinamide Adenine Dinucleotide Phosphate (NADPH) level is rapidly restored within 10 min after a transient decrease, while glutathione (GSH) redox potential is slowly driven back toward pre-stimulus level (within one hour). Extra-cellular glucose is necessary for adaptation of both NADPH level and GSH system. Second, our results also reveal large cell-to-cell variability in the dynamic response to external ROS. Our experimental approach is readily usable to monitor other cellular redox systems such as thioredoxins. As response-heterogeneity can lead to fractional killing, we finally discuss how our methodology can be an opportunity to link dynamics of ROS scavenging and cellular fate such as cell death.
Challenges in Benchmarking Metagenomic Profilers
Authors: Sun Zheng , Huang Shi , Zhang Meng , Zhu Qi-Yun , Haiminen Niina , Carrieri Anna-Paola , Vázquez-Baeza Yoshiki , Parida Laxmi , Kim Ho-Cheol , Knight Rob , Liu Yang-Yu
Published: November 2020

Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classifying metagenomic data and estimating taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Yet, benchmarking metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here, we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community should pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that was analyzed and interpreted, and clearly stating the strategy used for metagenomic profiling.
Inherent population structure determines the importance of filtering parameters for reduced representation sequencing analyses
Authors: Selechnik D. , Richardson M.F. , Hess M.K. , Hess A.S. , Dodds K.G. , Martin M. , Chan T.C. , Cardilini A.P.A. , Sherman C.D.H. , Shine R. , Rollins L.A.
Published: November 2020

As technological advancements enhance our ability to study population genetics, we must understand how the intrinsic properties of our datasets influence the decisions we make when designing experiments. Filtering parameter thresholds, such as call rate and minimum minor allele frequency (MAF), are known to affect inferences of population structure in reduced representation sequencing (RRS) studies. However, it is unclear to what extent the impacts of these parameter choices vary across datasets. Here, we reviewed literature on filtering choices and levels of genetic differentiation across RRS studies on wild populations to highlight the diverse approaches that have been used. Next, we hypothesized that choices in filtering thresholds would have the greatest impact when analyzing datasets with low levels of genetic differentiation between populations. To test this hypothesis, we produced seven simulated RRS datasets with varying levels of population structure, and analyzed them using four different combinations of call rate and MAF. We performed the same analysis on two empirical RRS datasets (low or high population structure). Our simulated and empirical results suggest that the effects of filtering choices indeed vary based on inherent levels of differentiation: specifically, choosing stringent filtering choices was important to detect distinct populations that were slightly differentiated, but not those that were highly differentiated. As a result, experimental design and analysis choices need to consider attributes of each specific dataset. Based on our literature review and analyses, we recommend testing a range of filtering parameter choices, and presenting all results with clear justification for ultimate filtering decisions used in downstream analyses.