bluuebunny/crossref_metadata_2025_split huggingface dataset:
Saturating Single-Cell atlas Datasets
Authors: Bhaduri Aparna , Nowakowski Tomasz J. , Pollen Alex A. , Kriegstein Arnold R. 
Published: November 2017

AbstractHigh throughput methods for profiling the transcriptomes of single cells have recently emerged as transformative approaches for large-scale population surveys of cellular diversity in heterogeneous primary tissues. Efficient generation of such an atlas will depend on sufficient sampling of the diverse cell types while remaining cost-effective to enable a comprehensive examination of organs, developmental stages, and individuals. To examine the relationship between cell number and transcriptional heterogeneity in the context of unbiased cell type classification, we explicitly explored the population structure of a publically available 1.3 million cell dataset from the E18.5 mouse brain. We propose a computational framework for inferring the saturation point of cluster discovery in a single cell mRNA-seq experiment, centered around cluster preservation in downsampled datasets. In addition, we introduce a “complexity index”, which characterizes the heterogeneity of cells in a given dataset. Using Cajal-Retzius cells as an example of a limited complexity dataset, we explored whether biological distinctions relate to technical clustering. Surprisingly, we found that clustering distinctions carrying biologically interpretable meaning are achieved with far fewer cells (20,000). Together, these findings suggest that most of the biologically interpretable insights from the 1.3 million cells can be recapitulated by analyzing 50,000 randomly selected cells, indicating that instead of profiling few individuals at high “cellular coverage”, the much anticipated cell atlasing studies may instead benefit from profiling more individuals, or many time points at lower cellular coverage.Recent efforts seek to create a comprehensive cell atlas of the human body1,2 Current technology, however, makes it precipitously expensive to perform analysis of every cell. Therefore, designing effective sampling strategies be critical to generate a working atlas in an efficient, cost-effective, and streamlined manner. The advent of single cell and single nucleus mRNA sequencing (RNAseq) in droplet format3,4 now enables large scale sampling of cells from any tissue, and a recently released publicly available dataset of 1.3 million single cells from the E18.5 mouse brain generated with the 10X Chromium5 provides an opportunity to explore the relationship between population structure and the number of sampled cells necessary to reveal the underlying diversity of cell types. Here, we present a framework for how researchers can evaluate whether a dataset has reached saturation, and we estimate how many cells would be required to generate an atlas of the sample analyzed here. This framework can be applied to any organ or cell type specific atlas for any organism.
Energetic Evolution of Cellular Transportomes
Authors: Darbani Behrooz , Kell Douglas B. , Borodina Irina 
Published: November 2017

ABSTRACTTransporter proteins mediate the translocation of substances across the membranes of living cells. We performed a genome-wide analysis of the compositional reshaping of cellular transporters (the transportome) across the kingdoms of bacteria, archaea, and eukarya. We show that the transportomes of eukaryotes evolved strongly towards a higher energetic efficiency, as ATP-dependent transporters diminished and secondary transporters and ion channels proliferated. This change has likely been important in the development of tissues performing energetically costly cellular functions. The transportome analysis also indicated seven bacterial species, includingNeorickettsia risticiiandNeorickettsia sennetsu, as likely origins of the mitochondrion in eukaryotes, due to the restricted presence therein of clear homologues of modern mitochondrial solute carriers.
Heritability Informed Power Optimization (HIPO) Leads to Enhanced Detection of Genetic Associations Across Multiple Traits
Authors: Qi Guanghao , Chatterjee Nilanjan 
Published: November 2017

AbstractGenome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account estimates of heritability, sample size variations and overlaps across the traits. Simulation studies show that the proposed method has correct type I error, robust to population stratification and leads to desired genome-wide enrichment of association signals. Application of the proposed method to publicly available data for three groups of genetically related traits, lipids (N=188,577), psychiatric diseases (Ncase=33,332, Ncontrol=27,888) and social science traits (N ranging between 161,460 to 298,420 across individual traits) increased the number of genome-wide significant loci by 12%, 200% and 50%, respectively, compared to those found by analysis of individual traits. Evidence of replication is present for many of these loci in subsequent larger studies for individual traits. HIPO can potentially be extended to high-dimensional phenotypes as a way of dimension reduction to maximize power for subsequent genetic association testing.
Fine scale diversification of endolithic microbial communities in the hyper-arid Atacama Desert
Authors: Meslier Victoria , Casero Maria Cristina , Dailey Micah , Wierzchos Jacek , Ascaso Carmen , Artieda Octavio , DiRuggiero Jocelyne 
Published: November 2017

ABSTRACTThe expansion of desertification across our planet is accelerating as the result of human activity and global climate change. In hyper-arid deserts, endolithic microbial communities colonize the rocks’ interior as a survival strategy. Yet, the composition of these communities and the drivers promoting their assembly are still poorly understood. Using a sampling strategy that minimized climate regime and biogeography effects, we analyzed the diversity and community composition of endoliths from four different lithic substrates – calcite, gypsum, ignimbrite and granite – collected in the hyper-arid zone of the Atacama Desert, Chile. By combining microscopy, mineralogy, and high throughput sequencing, we found these communities to be highly specific to their lithic substrate, although they were all dominated by the same four main phyla, Cyanobacteria, Actinobacteria, Chloroflexi and Proteobacteria. This finding indicates a fine scale diversification of the microbial reservoir driven by substrate properties. Our data suggest that the overall rock chemistry is not an essential driver of community structure and we propose that the architecture of the rock, i.e. the space available for colonization and its physical structure, linked to water retention capabilities, is ultimately the driver of community diversity and composition at the dry limit of life.Originality-Significance StatementIn this study, we demonstrated that endolithic microbial communities are highly specific to their substrates, suggesting a fine scale diversification of the available microbial reservoir. By using an array of rock substrates from the same climatic region, we established, for the first time, that the architecture of the rock is linked to water retention and is ultimately the driver of community diversity and composition at the dry limit for life.
Transcriptional landscape and regulatory roles of small non-coding RNAs in the oxidative stress response of the haloarchaeon Haloferax volcanii
Authors: Gelsinger Diego R. , DiRuggiero Jocelyne 
Published: November 2017

ABSTRACTHaloarchaea in their natural environment are exposed to hyper-salinity, intense solar radiation, and desiccation, all of which generate high levels of oxidative stress. Previous work has shown that Haloarchaea are an order of magnitude more resistant to oxidative stress than most mesophilic organisms. Despite this resistance, the pathways Haloarchaea use to respond to oxidative stress damage are similar to that of non-resistant organisms suggesting that regulatory processes might be key to their robustness. Recently, small non-coding RNAs (sRNAs) were discovered in Archaea under a variety of environmental conditions. We report here the transcriptional landscape and functional roles of sRNAs in the regulation of the oxidative stress response of the model haloarchaeon Haloferax volcanii. Thousands of sRNAs, both intergenic and antisense, were discovered using strand-specific sRNA-seq, comprising around 30% of the transcriptome during non-challenged and oxidative stress conditions. We identified hundreds of differentially expressed sRNAs in response to hydrogen peroxide induced oxidative stress in H. volcanii. Targets of antisense sRNAs decreased in expression when sRNAs were up-regulated indicating that sRNAs are likely playing a negative regulatory role on mRNA targets at the transcript level. Target enrichment of these antisense sRNAs included mRNAs involved in transposons mobility, chemotaxis signaling, peptidase activity, and transcription factors.IMPORTANCEWhile a substantial body of experimental work has been done to uncover functions of sRNAs in gene regulation in Bacteria and Eukarya, the functional roles of sRNAs in Archaea are still poorly understood. This study is the first to establish the regulatory effects of sRNAs on mRNAs during the oxidative stress response in the haloarchaeon Haloferax volcanii. Our work demonstrates that common principles for the response to a major cellular stress exist across the 3 domains of life while uncovering pathways that might be specific to the Archaea. This work also underscores the relevance of sRNAs in adaptation to extreme environmental conditions.
Clinker: visualising fusion genes detected in RNA-seq data
Authors: Schmidt Breon M , Davidson Nadia M , Hawkins Anthony DK , Bartolo Ray , Majewski Ian J , Ekert Paul G , Oshlack Alicia 
Published: November 2017

ABSTRACTGenomic profiling efforts have revealed a rich diversity of oncogenic fusion genes, and many are emerging as important therapeutic targets. While there are many ways to identify fusion genes from RNA-seq data, visualising these transcripts and their supporting reads remains challenging. Clinker is a bioinformatics tool written in Python, R and Bpipe, that leverages the superTranscript method to visualise fusion genes. We demonstrate the use of Clinker to obtain interpretable visualisations of the RNA-seq data that lead to fusion calls. In addition, we use Clinker to explore multiple fusion transcripts with novel breakpoints within the P2RY8-CRLF2 fusion gene in B-cell Acute Lymphoblastic Leukaemia (B-ALL).Availability and ImplementationClinker is freely available from Github https://github.com/Oshlack/Clinker under a MIT License.Contactalicia.oshlack@mcri.edu.au
Age-dependent neurodegeneration and organelle transport deficiencies in mutant TDP43 patient-derived neurons are independent of TDP43 aggregation
Authors: Kreiter N , Pal A , Lojewski X , Corcia P , Naujock M , Reinhardt P , Sterneckert J , Petri S , Wegner F , Storch A , Hermann A 
Published: November 2017

AbstractTAR DNA-binding protein 43 (TDP43) is a cause of familiar and sporadic amyotrophic lateral sclerosis (ALS). The diverse postulated mechanisms by which TDP43 mutations cause the disease are not fully understood. Human wildtype and TDP43 S393L and G294V mutant spinal motor neuron cultures were differentiated from patient-derived iPSCs. Mutant hTDP43 and wildtype motor neuron cultures did not differ in neuron differentiation capacity during early maturation stage. During aging we detected a dramatic neurodegeneration including neuron loss and pathological neurofilament abnormalities in TDP43 mutant cultures only. Additionally mitochondria and lysosomes of aging spinal motor neurons revealed robust TDP43 mutation dependent abnormal phenotypes in size, shape, speed and motility which all appeared without TDP43 mislocalization or aggregation formation. Furthermore, D-sorbitol – known to induce stress granules and cytoplasmic mislocalization of TDP43 – rescued axonal trafficking phenotypes without any signs of TDP43 mislocalization or aggregation formation. Our data indicate TDP43 mutation-dependent but cytosolic aggregation-independent mechanisms of motor neuron degeneration in TDP43 ALS.
Online detection of auditory attention with mobile EEG: closing the loop with neurofeedback
Authors: Zink Rob , Proesmans Stijn , Bertrand Alexander , Van Huffel Sabine , De Vos Maarten 
Published: November 2017

AbstractAuditory attention detection (AAD) is promising for use in auditory-assistive devices to detect to which sound the user is attending. Being able to train subjects in achieving high AAD performance would greatly increase its application potential. In order to do so an acceptable temporal resolution and online implementation are essential prerequisites. Consequently, users of an online AAD can be presented with feedback about their performance. Here we describe two studies that investigate the effects of online AAD with feedback. In the first study, we implemented a fully automated closed-loop system that allows for user-friendly recording environments. Subjects were presented online with visual feedback on their ongoing AAD performance. Following these results we implemented a longitudinal case study in which two subjects were presented with AAD sessions during four weeks. The results prove the feasibility of a fully working online (neuro)feedback system for AAD decoding. The detected changes in AAD for the feedback subject during and after training suggest that changes in AAD may be achieved via training. This is early evidence of such training effects and needs to be confirmed in future studies to evaluate training of AAD in more detail. Finally, the large number of sessions allowed to examine the correlation between the stimuli (i.e. acoustic stories) and AAD performance which was found to be significant. Future studies are suggested to evaluate their acoustic stimuli with care to prevent spurious associations.
How Changes in Common Practice Can Improve the Quality of Biomedical Science
Authors: Steinfath Matthias , Vogl Silvia , Violet Norman , Schwarz Franziska , Mielke Hans , Selhorst Thomas , Greiner Matthias , Schöenfelder Gilbert 
Published: November 2017

AbstractAssessing the impact of recommendations rectifying the reproducibility crisis (publishing both positive and “negative” results and increasing statistical power) on competing objectives, such as discovering causal relationships, avoiding publishing false positive results, and reducing resource consumption, we developed a new probabilistic model. Our model quantifies the impact of each single suggestion for an individual study and their relation and consequences for the entire research process. We can prove that higher-powered experiments can save resources in the overall research process without generating excess false positives. The better the quality of the pre-study information and its exploitation, the more likely this beneficial effect is to occur. Additionally, we quantify the adverse effects of neglecting good practices in the design and conduct of hypotheses-based research, and the responsibility to publish “negative” findings. Our contribution is a plea for adherence to or reinforcement of the good scientific practice and publication of “negative” findings.
Phenome-wide association studies (PheWAS) across large “real-world data” population cohorts support drug target validation
Authors: Diogo Dorothée , Tian Chao , Franklin Christopher S. , Alanne-Kinnunen Mervi , March Michael , Spencer Chris C. A. , Vangjeli Ciara , Weale Michael E. , Mattsson Hannele , Kilpeläinen Elina , Sleiman Patrick M.A. , Reilly Dermot F. , McElwee Joshua , Maranville Joseph C. , Chatterjee Arnaub K , Bhandari Aman ,   the 23andMe Research Team, Reeve Mary-Pat , Hutz Janna , Bing Nan , John Sally , MacArthur Daniel , Salomaa Veikko , Ripatti Samuli , Hakonarson Hakon , Daly Mark J. , Palotie Aarno , Hinds David , Donnelly Peter , Fox Caroline S. , Day-Williams Aaron , Plenge Robert M. , Runz Heiko 
Published: November 2017

AbstractPhenome-wide association studies (PheWAS), which assess whether a genetic variant is associated with multiple phenotypes across a phenotypic spectrum, have been proposed as a possible aid to drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we evaluate whether PheWAS can inform target validation during drug development. We selected 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease therapeutic indications. We independently interrogated these SNPs through PheWAS in four large “real-world data” cohorts (23andMe, UK Biobank, FINRISK, CHOP) for association with a total of 1,892 binary endpoints. We then conducted meta-analyses for 145 harmonized disease endpoints in up to 697,815 individuals and joined results with summary statistics from 57 published GWAS. Our analyses replicate 70% of known GWAS associations and identify 10 novel associations with study-wide significance after multiple test correction (P<1.8x10-6; out of 72 novel associations with FDR<0.1). By leveraging directionality and point estimate of the effect sizes, we describe new associations that may predict ADEs, e.g., acne, high cholesterol, gout and gallstones for rs738409 (p.I148M) in PNPLA3; or asthma for rs1990760 (p.T946A) in IFIH1. We further propose how quantitative estimates of genetic safety/efficacy profiles can be used to help prioritize candidate targets for a specific indication. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.One Sentence SummaryMatching genetics with phenotypes in 800,000 individuals predicts efficacy and on-target safety of future drugs.
ADAM17 is the Principal Ectodomain Sheddase of the EGF-Receptor Ligand Amphiregulin
Authors: Hosur Vishnu , Farley Michelle L. , Burzenski Lisa M. , Shultz Leonard D. , Wiles Michael V. 
Published: November 2017

AbstractThe epidermal growth factor (EGF)-receptor ligand amphiregulin (AREG) is a potent growth factor implicated in proliferative skin diseases and in primary and metastatic epithelial cancers. AREGin vitro, synthesized as a pro-peptide, requires conversion to an active peptide by metalloproteases by a process known as ectodomain shedding. Although, (Adam17) a disintegrin and metalloprotease 17 is implicated in ectodomain shedding of AREG, it remains to be establishedin vivowhether ADAM17 contributes to AREG shedding. In the present study, using a curly bare (Rhbdf2cub) mouse model that shows loss-of-hair, enlarged sebaceous glands, and rapid cutaneous wound-healing phenotypes mediated by enhancedAregmRNA and protein levels, we sought to identify the principal ectodomain sheddase of AREG. To this end, we generatedRhbdf2cubmice lacking ADAM17 specifically in the skin and examined the above phenotypes ofRhbdf2cubmice. We find that ADAM17 deficiency in the skin ofRhbdf2cubmice restores a full hair coat, prevents sebaceous-gland enlargement, and impairs the rapid wound-healing phenotype observed inRhbdf2cubmice. Furthermore,in vitro, stimulated shedding of AREG is abolished inRhbdf2cubmouse embryonic keratinocytes lacking ADAM17. Thus, our data demonstrate that ADAM17 is the major ectodomain sheddase of AREG.
New routes for PTP1B allosteric inhibition by multitemperature crystallography, fragment screening and covalent tethering
Authors: Keedy Daniel A. , Hill Zachary B. , Biel Justin T. , Kang Emily , Rettenmaier T. Justin , Brandao-Neto Jose , Pearce Nicholas M. , von Delft Frank , Wells James A. , Fraser James S. 
Published: November 2017

AbstractAllostery is an inherent feature of proteins and provides alternative routes to regulating function. Small-molecule allosteric inhibitors are often desirable; however, it remains challenging to identify surface sites in proteins which can bind small molecules and modulate function. We identified new allosteric sites in protein tyrosine phosphatase 1B (PTP1B) by combining multiple-temperature X-ray crystallography experiments and structure determination from hundreds of individual small-molecule fragment soaks. New modeling approaches reveal “hidden” low-occupancy conformational states for protein and ligands. Our results converge on a new allosteric site that is conformationally coupled to the active-site WPD loop, a hotspot for fragment binding, not conserved in the closest homolog, and distinct from other recently reported allosteric sites in PTP1B. Targeting this site with covalently tethered molecules allosterically inhibits enzyme activity. Overall, this work demonstrates how the ensemble nature of macromolecular structure revealed by multitemperature crystallography can be exploited for developing allosteric modulators.
Towards a unified resource for transcriptional regulation inEscherichia coliK-12: Incorporating high throughput-generated binding data within the classic framework of regulation of initiation of transcription in RegulonDB
Authors: Santos-Zavaleta Alberto , Sánchez-Pérez Mishael , Salgado Heladia , Velázquez-Ramírez David A. , Gama-Castro Socorro , Tierrafría Víctor H. , Busby Stephen J.W. , Fang Xin , Palsson Bernhard , Galagan James , Collado-Vides Julio 
Published: November 2017

ABSTRACTOur understanding of the regulation of gene expression has been strongly benefited by the availability of high throughput technologies that enable questioning the whole genome for the binding of specific transcription factors and expression profiles. In the case of genome models, such asEscherichia coliK-12, this knowledge needs to be integrated with the legacy of accumulated genetics and molecular biology pre-genomic knowledge in order to attain deeper levels in the understanding of their biology. In spite of the several repositories and curated databases, there is no effort, nor electronic site yet, to comprehensively integrate the available knowledge from all these different sources around the regulation of gene expression ofE. coliK-12. In this paper, we describe a first effort to expand RegulonDB, the database containing the rich legacy of decades of classic molecular biology experiments supporting what we know about gene regulation and operon organization inE. coliK-12, to include the genome-wide data set collections from 25 ChIP and 18 gSELEX publications, respectively, in addition to around 60 expression profiles used in their curation. Three essential features for the integration of this information coming from different methodological approaches are; first, a controlled vocabulary within an ontology for precisely defining growth conditions, second, the criteria to separate elements with enough evidence to consider them involved in gene regulation from isolated sites, and third, an expanded computational model supporting this knowledge. Altogether, this constitutes the basis for adequately gathering and enabling the comparisons and integration strongly needed to manage and access such wealth of knowledge. This version of RegulonBD is a first step toward what should become the unifying access point for current and future knowledge on gene regulation inE. coliK-12. Furthermore, this model platform and associated methodologies and criteria, can well be emulated for gathering knowledge on other microbial organisms.