bluuebunny/crossref_metadata_2025_split huggingface dataset:
Point-of-care testing for COVID-19 using SHERLOCK diagnostics
Authors: Joung Julia , Ladha Alim , Saito Makoto , Segel Michael , Bruneau Robert , Huang Mee-li W. , Kim Nam-Gyun , Yu Xu , Li Jonathan , Walker Bruce D. , Greninger Alexander L. , Jerome Keith R. , Gootenberg Jonathan S. , Abudayyeh Omar O. , Zhang Feng 
Published: May 2020

AbstractThe recent outbreak of the novel coronavirus SARS-CoV-2, which causes COVID-19, can be diagnosed using RT-qPCR, but inadequate access to reagents and equipment has slowed disease detection and impeded efforts to mitigate viral spread. Alternative approaches based on combinations of isothermal amplification and CRISPR-mediated detection, such as the SHERLOCK (SpecificHighSensitivityEnzymaticReporter UnLOCKing) technique, offer reduced dependence on RT-qPCR equipment, but previously reported methods required multiple fluid handling steps, complicating their deployment outside clinical labs. Here we developed a simple test chemistry called STOP (SHERLOCK Testing in One Pot) for detecting SARS-CoV-2 in one hour that is suitable for point-of-care use. This simplified test, STOPCovid, provides sensitivity comparable to RT-qPCR-based SARS-CoV-2 tests and has a limit of detection of 100 copies of viral genome input in saliva or nasopharyngeal swabs per reaction. Using lateral flow readout, the test returns result in 70 minutes, and using fluorescence readout, the test returns result in 40 minutes. Moreover, we validated STOPCovid using nasopharyngeal swabs from COVID-19 patients and were able to correctly diagnose 12 positive and 5 negative patients out of 3 replicates. We envision that implementation of STOPCovid will significantly aid “test-trace-isolate” efforts, especially in low-resource settings, which will be critical for long-term public health safety and effective reopening of the society.
Omics BioAnalytics: Reproducible Research using R Shiny and Alexa
Authors: Singh Amrit , Tebbutt Scott J. , McManus Bruce M. 
Published: May 2020

AbstractSummaryHigh-throughput technologies produce complex high-dimensional datasets which are analyzed using a variety of ever-evolving bioinformatics tools. Well-designed web frameworks enable more intuitive and efficient analysis such that less time is spent on coding and more time is spent on interpretation of results and addressing insightful biological questions aided by interactive visualizations. Here, we present Omics BioAnalytics, a full-service Web framework that enables comprehensive, multi-level characterization, analysis, and integration of omics datasets. Blending web-based (R Shiny) and voice-based (Amazon’s Alexa) analytics, Omics BioAnalytics can be used both by expert computational biologists and non-coding biological domain experts, alike. Our web framework can be utilized to explore complex datasets and identify biosignatures and discriminative biomarkers of health and disease processes, and generate testable hypotheses relating to underlying molecular mechanisms.AvailabilityOmics BioAnalytics is freely available athttps://github.com/singha53/omicsBioAnalyticsand the web app is deployed athttps://amritsingh.shinyapps.io/omicsBioAnalytics/. The source code for the companion Alexa Skill can be found athttps://github.com/singha53/omics-bioanalytics-alexa-skill.
Multidimensional plasticity in the Glanville fritillary butterfly: larval performance curves are temperature, host and family specific
Authors: Verspagen Nadja , Ikonen Suvi , Saastamoinen Marjo , Bergen Erik van 
Published: May 2020

AbstractVariation in environmental conditions during development can lead to changes in life-history traits with long-lasting effects. Here, we study environmentally induced variation, i.e. the consequences of potential maternal oviposition choices, in a suite of life-history traits in pre-diapause larvae of the Glanville fritillary butterfly. We focus on offspring survival, early growth rates and relative fat reserves, and pay specific attention to intraspecific variation in the responses (GxExE). Globally, we found that thermal performance and survival curves varied between diets of two host plants, suggesting that host modifies the temperature impact, orvice versa. Additionally, we show that the relative fat content has a host-dependent, discontinuous response to developmental temperature. This implies that a potential switch in resource allocation, from more investment in growth at lower temperatures to storage at higher temperatures, is dependent on other environmental variables. Interestingly, we find that a large proportion of the variance in larval performance is explained by differences among families, or interactions with this variable. Finally, we demonstrate that these family-specific responses to the host plant remain largely consistent across thermal environments. Altogether, the results of our study underscore the importance of paying attention to intraspecific trait variation in the field of evolutionary ecology.
Single cell resolution landscape of equine peripheral blood mononuclear cells reveals diverse immune cell subtypes including T-bet+B cells
Authors: Patel Roosheel S. , Tomlinson Joy E. , Divers Thomas J. , Van de Walle Gerlinde R. , Rosenberg Brad R. 
Published: May 2020

ABSTRACTTraditional laboratory model organisms represent a small fraction of the diversity of multicellular life, and findings in any given experimental model often do not translate to other species. Immunology research in non-traditional model organisms can be advantageous or even necessary (e.g. for host-pathogen interaction studies), but presents multiple challenges, many stemming from an incomplete understanding of potentially species-specific immune cell types, frequencies and phenotypes. Identifying and characterizing immune cells in such organisms is frequently limited by the availability of species-reactive immunophenotyping reagents for flow cytometry, and insufficient prior knowledge of cell type-defining markers. Here, we demonstrate the utility of single cell RNA sequencing (scRNA-Seq) to characterize immune cells for which traditional experimental tools are limited. Specifically, we used scRNA-Seq to comprehensively define the cellular diversity of equine peripheral blood mononuclear cells (PBMCs) from healthy horses across different breeds, ages, and sexes. We identified 30 cell type clusters partitioned into five major populations: Monocytes/Dendritic Cells, B cells, CD3+PRF1+lymphocytes, CD3+PRF1-lymphocytes, and Basophils. Comparative analyses revealed many cell populations analogous to human PBMC, including transcriptionally heterogeneous monocytes and distinct dendritic cell subsets (cDC1, cDC2, plasmacytoid DC). Unexpectedly, we found that a majority of the equine peripheral B cell compartment is comprised of T-bet+B cells; an immune cell subpopulation typically associated with chronic infection and inflammation in human and mouse. Taken together, our results demonstrate the potential of scRNA-Seq for cellular analyses in non-traditional model organisms, and form the basis for an immune cell atlas of horse peripheral blood.
Repeated genomic signatures of adaptation to urbanisation in a songbird across Europe
Authors: Salmón Pablo , Jacobs Arne , Ahrén Dag , Biard Clotilde , Dingemanse Niels J. , Dominoni Davide M. , Helm Barbara , Lundberg Max , Senar Juan Carlos , Sprau Philipp , Visser Marcel E. , Isaksson Caroline 
Published: May 2020

AbstractUrbanisation is currently increasing worldwide, and there is now ample evidence of phenotypic changes in wild organisms in response to this novel environment, but the extent to which this adaptation is due to genetic changes is poorly understood. Current evidence for evolution is based on localised studies, and thus lacking replicability. Here, we genotyped great tits (Parus major) from nine cities across Europe, each paired with a rural site, and provide evidence of repeated polygenic responses to urban habitats. In addition, we show that selective sweeps occurred in response to urbanisation within the same genes across multiple cities. These genetic responses were mostly associated with genes related to neural function and development, demonstrating that genetic adaptation to urbanisation occurred around the same pathways in wildlife populations across a large geographical scale.
RNA and DNA G-quadruplexes bind to human Dicer and inhibit its activity
Authors: Koralewska Natalia , Szczepanska Agnieszka , Ciechanowska Kinga , Wojnicka Marta , Pokornowska Maria , Milewski Marek C. , Gudanis Dorota , Baranowski Daniel , Nithin Chandran , Bujnicki Janusz M. , Gdaniec Zofia , Figlerowicz Marek , Kurzynska-Kokorniak Anna 
Published: May 2020

AbstractGuanine (G)-rich single-stranded nucleic acids can adopt G-quadruplex structures. Accumulating evidence indicates that G-quadruplexes serve important regulatory roles in fundamental biological processes such as DNA replication, transcription, and translation, while aberrant G-quadruplex formation is linked to genome instability and cancer. Understanding the biological functions played by G-quadruplexes requires detailed knowledge of their protein interactome. Here, we report that both RNA and DNA G-quadruplexes are bound by human Dicerin vitro. Usingin vitrobinding assays, mutation studies, and computational modeling we demonstrate that G-quadruplexes can interact with the Platform-PAZ-Connector helix cassette of Dicer, the region responsible for anchoring microRNA precursors (pre-miRNAs). Consequently, we show that G-quadruplexes efficiently and stably inhibit the cleavage of pre-miRNA by Dicer. Our data highlight the potential of human Dicer for binding of G-quadruplexes and allow us to propose a G-quadruplex-driven sequestration mechanism of Dicer regulation.
Predicting dynamic cellular protein-RNA interactions using deep learning andin vivoRNA structure
Authors: Sun Lei , Xu Kui , Huang Wenze , Yang Yucheng T. , Tang Lei , Xiong Tuanlin , Zhang Qiangfeng Cliff 
Published: May 2020

AbstractInteractions with RNA-binding proteins (RBPs) are crucial for RNA regulation and function. While both RNA sequence and structure are critical determinants, RNA structure is dependent on cellular environment and especially important in regulating dynamic RBP bindings across various conditions. However, how distinct it contributes to RBP bindingin vivoremains poorly understood. To address this issue, we obtained transcriptome-wide RNA secondary structure profiles in multiple cell-types, and established a deep neural network, PrismNet, that uses invivoRNA structures to accurately predict cellular protein-RNA interactions. With a deep learning “attention” strategy, PrismNet discovers the exact binding nucleotides and their mutational effect. The predicted binding sites are highly conserved and enriched for rare, deleterious genetic variants. Remarkably, dynamic RBP binding sites are enriched for structure-changing variants (riboSNitches), which are often associated with disease, reflecting dysregulated RBP bindings. Our resource enables the analysis of cell-type-specific RNA regulation, with applications in human disease.Highlights1, A big data resource of transcriptome-wide RNA secondary structure profiles in multiple cell types2, PrismNet, a deep neural network, accurately models the sequence and structural combined patterns of protein-RNA interactionsin vivo3, RNA structural informationin vivois critical for the accurate prediction of dynamic RBP binding in various cellular conditions4, PrismNet can dissect and predict how mutations affect RBP binding via RNA sequence or structure changes5, RNA structure-changing RiboSNitches are enriched in dynamic RBP binding sites and often associated with disease, likely disrupting RBP-based regulation
Genetic structure and molecular diversity of Brazilian grapevine germplasm: management and use in breeding programs
Authors: de Oliveira Geovani Luciano , de Souza Anete Pereira , de Oliveira Fernanda Ancelmo , Zucchi Maria Imaculada , de Souza Lívia Moura , Moura Mara Fernandes 
Published: May 2020

AbstractThe management of germplasm banks is complex, especially when many accessions are involved. Microsatellite markers are an efficient tool for assessing the genetic diversity of germplasm collections, optimizing their use in breeding programs. This study genetically characterizes a large collection of 410 grapevine accessions maintained at the Agronomic Institute of Campinas (IAC) (Brazil). The accessions were genotyped with 17 highly polymorphic microsatellite markers. Genetic data were analyzed to determine the genetic structure of the germplasm, quantify its allelic diversity, suggest the composition of a core collection, and discover cases of synonymy, duplication, and misnaming. A total of 304 alleles were obtained, and 334 unique genotypes were identified. The molecular profiles of 145 accessions were confirmed according to the literature and databases, and the molecular profiles of more than 100 genotypes were reported for the first time. The analysis of the genetic structure revealed different levels of stratification. The primary division was between accessions related toVitis viniferaandV. labrusca, followed by their separation from wild grapevine. A core collection of 120 genotypes captured 100% of all detected alleles. The accessions selected for the core collection may be used in future phenotyping efforts, in genome association studies, and for conservation purposes. Genetic divergence among accessions has practical applications in grape breeding programs, as the choice of relatively divergent parents will maximize the frequency of progeny with superior characteristics. Together, our results can enhance the management of grapevine germplasm and guide the efficient exploitation of genetic diversity to facilitate the development of new grape cultivars for fresh fruits, wine, and rootstock.
Validity of the Lumen®hand-held metabolic device to measure fuel utilization in healthy young adults
Authors: Lorenz Kent A. , Yeshurun Shlomo , Aziz Richard , Ortiz-Delatorre Julissa , Bagley James R. , Mor Merav , Kern Marialice 
Published: May 2020

AbstractBackgroundMetabolic carts measure the carbon dioxide produced and oxygen consumed from the breath in order to assess metabolic fuel usage (carbohydrates vs. fats). However, these systems are expensive, time-consuming, and only available in the clinic. A small hand-held device capable of measuring metabolic fuel via CO2from exhaled air has been developedObjectiveTo evaluate the validity of a novel hand-held device (Lumen®) for measuring metabolic fuel utilization in healthy young adultsMethodsMetabolic fuel usage was assessed in healthy participants (n = 33; age: 23.1 ± 3.9 y) via respiratory exchange ratio (RER) values from the “gold-standard” metabolic cart as well as %CO2from the Lumen device. Measurements were performed at rest in two conditions, fasting, and after consuming 150 grams of glucose in order to determine changes in metabolic fuel. Reduced major axis regression was performed as well as Bland-Altman plots and linear regressions to test for agreement between RER and Lumen %CO2.ResultsBoth RER and Lumen %CO2significantly increased after glucose intake compared with fasting conditions (P< .0001). Regression analyses and Bland-Altman plots revealed an agreement between the two measurements with a systematic bias resulting from the nature of the different units.ConclusionsThis study shows the validity of Lumen®to estimate metabolic fuel utilization in a comparable manner with the “gold-standard” metabolic cart, providing the ability for real-time metabolic information for users under any circumstances.
Where in the leaf is intercellular CO2(Ci)? Considerations and recommendations for assessing gaseous diffusion in leaves
Authors: Stinziano Joseph R. , Tominaga Jun , Hanson David T. 
Published: May 2020

AbstractThe assumptions that water vapor exchange occurs exclusively through stomata, that the intercellular airspace is fully saturated with water vapor, and that CO2gradients are negligible between stomata and the intercellular airspace have enabled significant advancements in photosynthetic gas exchange research for nearly 60 years via calculation of intercellular CO2(Ci). However, available evidence suggests that these assumptions may be overused. Here we review the literature surrounding evidence for and against the assumptions made by Moss & Rawlins (1963). We reinterpret data from the literature by propagating different rates of cuticular water loss, CO2gradients, and unsaturation through the data. We find that in general, when cuticle conductance is less than 1% of stomatal conductance, the assumption that water vapor exchange occurs exclusively through stomata has a marginal effect on gas exchange calculations, but this is not true when cuticle conductance exceeds 5% of stomatal conductance. Our analyses further suggest that CO2and water vapor gradients have stronger impacts at higher stomatal conductance, while cuticle conductance has a greater impact at lower stomatal conductance. Therefore, we recommend directly measuring Ciwhenever possible, measuring apoplastic water potentials to estimate humidity inside the leaf, and exercising caution when interpreting data under conditions of high temperature and/or low stomatal conductance, and when a species is known to have high cuticular conductance.HighlightLeaf water vapor and CO2exchange have been successfully used to model photosynthetic biochemistry. We review critical assumptions in these models and make recommendations about which need to be re-assessed.
Phenotype Heritability in holobionts: An Evolutionary Model
Authors: Huitzil Saúl , Sandoval-Motta Santiago , Frank Alejandro , Aldana Maximino 
Published: May 2020

AbstractMany complex diseases are expressed with high incidence only in certain populations. Genealogy studies determine that these diseases are inherited with a high probability. However, genetic studies have been unable to identify the genomic signatures responsible for such heritability, as identifying the genetic variants that make a population prone to a given disease is not enough to explain its high occurrence within the population. This gap is known as the missing heritability problem. We know that the microbiota plays a very important role in determining many important phenotypic characteristics of its host, in particular, the complex diseases for which the missing heritability occurs. Therefore, when computing the heritability of a phenotype it is important to consider not only the genetic variation in the host but also in its microbiota. Here we test this hypothesis by studying an evolutionary model based on gene regulatory networks. Our results show that the holobiont (the host plus its microbiota) is capable of generating a much larger variability than the host alone, greatly reducing the missing heritability of the phenotype. This result strongly suggests that a considerably large part of the missing heritability can be attributed to the microbiome.
Chromatin profiling reveals reorganization of lysine specific demethylase 1 by an oncogenic fusion protein
Authors: Theisen Emily R. , Selich-Anderson Julia , Miller Kyle R. , Tanner Jason M. , Taslim Cenny , Pishas Kathleen I. , Sharma Sunil , Lessnick Stephen L. 
Published: May 2020

ABSTRACTPediatric cancers commonly harbor quiet mutational landscapes and are instead characterized by single driver events such as the mutation of critical chromatin regulators, expression of oncohistones, or expression of oncogenic fusion proteins. These events ultimately promote malignancy through disruption of normal gene regulation and development. The driver protein in Ewing sarcoma, EWS/FLI, is an oncogenic fusion and transcription factor that reshapes the enhancer landscape, resulting in widespread transcriptional dysregulation. Lysine-specific demethylase 1 (LSD1) is a critical functional partner for EWS/FLI as inhibition of LSD1 reverses the transcriptional activity of EWS/FLI. However, how LSD1 participates in fusion-directed epigenomic regulation and aberrant gene activation is unknown. We now show EWS/FLI causes dynamic rearrangement of LSD1 and we uncover a role for LSD1 in gene activation through colocalization at EWS/FLI binding sites throughout the genome. LSD1 is integral to the establishment of Ewing sarcoma super-enhancers at GGAA-microsatellites, which ubiquitously overlap non-microsatellite loci bound by EWS/FLI. Together, we show that EWS/FLI induces widespread changes to LSD1 distribution in a process that impacts the enhancer landscape throughout the genome.
Rare variant enriched identity-by-descent enables the detection of distant relatedness and older divergence between populations
Authors: Shetty Amol C. ,   NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium,   TOPMed Population Genetics Working Group, O’Connell Jeffrey , Mitchell Braxton D. , O’Connor Timothy D. 
Published: May 2020

AbstractMotivationThe global human population has experienced an explosive growth from a few million to roughly 7 billion people in the last 10,000 years. Accompanying this growth has been the accumulation of rare variants that can inform our understanding of human evolutionary history. Common variants have primarily been used to infer the structure of the human population and relatedness between two individuals. However, with the increasing abundance of rare variants observed in large-scale projects, such as Trans-Omics for Precision Medicine (TOPMed), the use of rare variants to decipher cryptic relatedness and fine-scale population structure can be beneficial to the study of population demographics and association studies. Identity-by-descent (IBD) is an important framework used for identifying these relationships. IBD segments are broken down by recombination over time, such that longer shared haplotypes give strong evidence of recent relatedness while shorter shared haplotypes are indicative of more distant relationships. Current methods to identify IBD accurately detect only long segments (> 2cM) found in related individuals.AlgorithmWe describe a metric that leverages rare-variants shared between individuals to improve the detection of short IBD segments. We computed IBD segments using existing methods implemented inRefined IBDwhere we enrich the signal using our metric that facilitates the detection of short IBD segments (<2cM) by explicitly incorporating rare variants.ResultsTo test our new metric, we simulated datasets involving populations with varying divergent time-scales. We show that rare-variant IBD identifies shorter segments with greater confidence and enables the detection of older divergence between populations. As an example, we applied our metric to the Old-Order Amish cohort with known genealogies dating 14 generations back to validate its ability to detect genetic relatedness between distant relatives. This analysis shows that our method increases the accuracy of identifying shorter segments that in turn capture distant relationships.ConclusionsWe describe a method to enrich the detection of short IBD segments using rare-variant sharing within IBD segments. Leveraging rare-variant sharing improves the information content of short IBD segments better than common variants alone. We validated the method in both simulated and empirical datasets. This method can benefit association analyses, IBD mapping analyses, and demographic inferences.