bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epigenome-based prediction of gene expression across species
Authors: Ebert Peter , Lengauer Thomas , Bock Christoph 
Published: July 2018

AbstractBackgroundCross-species studies of epigenetic regulation have great potential, yet most epige-nome mapping has focused on human, mouse, and a small number of other model organisms. Here we explore whether existing reference epigenome collections can be leveraged for analyzing other species, by extrapolation and predictive transfer of epigenome information from established model organisms to less well annotated non-model organisms.ResultsWe developed a methodology for cross-species mapping of epigenome data, which we used for predicting tissue-specific gene expression across twelve mammalian and one avian species. Specifically, we trained gradient boosting classifiers to predict gene expression status from reference epigenome data in human and mouse, and we applied these classifiers to epigenome profiles that were computationally transferred between species. The resulting predictions indeed identified tissue-specific differences in gene expression in the target species, thus providing initial validation of the concept of cross-species epigenome extrapolation.ConclusionsOur study establishes a workflow for cross-species epigenome mapping and epigenome-based prediction of gene expression, highlighting the future potential of using epigenome maps from reference species to annotate a potentially large number of target species.
Panoramic stitching of heterogeneous single-cell transcriptomic data
Authors: Hie Brian , Bryson Bryan , Berger Bonnie 
Published: July 2018

AbstractResearchers are generating single-cell RNA sequencing (scRNA-seq) profiles of diverse biological systems1–4 and every cell type in the human body.5 Leveraging this data to gain unprecedented insight into biology and disease will require assembling heterogeneous cell populations across multiple experiments, laboratories, and technologies. Although methods for scRNA-seq data integration exist6,7, they often naively merge data sets together even when the data sets have no cell types in common, leading to results that do not correspond to real biological patterns. Here we present Scanorama, inspired by algorithms for panorama stitching, that overcomes the limitations of existing methods to enable accurate, heterogeneous scRNA-seq data set integration. Our strategy identifies and merges the shared cell types among all pairs of data sets and is orders of magnitude faster than existing techniques. We use Scanorama to combine 105,476 cells from 26 diverse scRNA-seq experiments across 9 different technologies into a single comprehensive reference, demonstrating how Scanorama can be used to obtain a more complete picture of cellular function across a wide range of scRNA-seq experiments.
Programmatic Detection of Diploid-Triploid Mixoploidy via Whole Genome Sequencing
Authors: Holt James M , Birch Camille L , Brown Donna M , Cogan Joy D , Hamid Rizwan , Dorrani Naghmeh , Herzog Matthew R , Lee Hane , Martinez Julian ,   Undiagnosed Diseases Network, Dipple Katrina , Vilain Eric , Phillips John A , Worthey Elizabeth A 
Published: July 2018

AbstractPurposeMixoploidy is a type of mosaicism where an organism is a mixture of cells with different numbers of chromosomes. There are a broad range of phenotypes associated with mixoploidy that vary greatly depending on the fraction of cells that are non-diploid, their chromosome number, their distribution, and presumably the specific variation present in the patient. Clinical detection of mixoploidy is important for diagnosis.MethodsWe developed a method to detect mixoploidy from clinical whole genome sequencing (WGS) data through the identification of excess of variant calls centered on unusual B-allele frequencies. Our method isolates the signal from these variants using trio calls and then solves a basic linear equation to estimate levels of diploid-triploid mixoploidy within the sample.ResultsWe show that our method reflects the results from a cytogenetic test. We provide examples detailing how our method has been used to identify diploid-triploid mixoploid individuals from within the NIH Undiagnosed Diseases Network. We present confirmatory findings obtained by clinical cytogenetic testing and show that our method can be used to identify the diploid-triploid ratio in these cases.ConclusionWGS data from patients with rare diseases can be used to identify mixoploid individuals. Individuals with certain characteristics as discussed should be tested for mixoploidy as part of standard clinical pipeline procedures. Scripts that perform this calculation are publicly available athttps://github.com/HudsonAlpha/mixoviz.
Plasmodium falciparum Niemann-Pick Type C1-Related Protein is a Druggable Target Required for Parasite Membrane Homeostasis
Authors: Istvan Eva S. , Das Sudipta , Bhatnagar Suyash , Beck Josh R. , Owen Edward , Llinás Manuel , Ganesan Suresh M. , Niles Jacquin C. , Winzeler Elizabeth A. , Vaidya Akhil B. , Goldberg Daniel E. 
Published: July 2018

AbstractPlasmodium parasites possess a protein with homology to Niemann-Pick Type C1 proteins (Plasmodium falciparum Niemann-Pick Type C1-Related protein, PfNCR1). We isolated parasites with resistance-conferring mutations in PfNCR1 during selections with three diverse small-molecule antimalarial compounds and show that the mutations are causative for compound resistance. PfNCR1 protein knockdown results in severely attenuated growth and confers hypersensitivity to the compounds. Compound treatment or protein knockdown leads to increased sensitivity of the parasite plasma membrane (PPM) to the amphipathic glycoside saponin and engenders digestive vacuoles (DVs) that are small and malformed. Immuno-electron microscopy and split-GFP experiments localize PfNCR1 to the PPM. Our experiments show that PfNCR1 activity is critically important for the composition of the PPM and is required for DV biogenesis, suggesting PfNCR1 as a novel antimalarial drug target.
Sulforaphane Alters the Acidification of the Vacuole to Trigger Cell Death
Authors: Wilcox Alexander , Murphy Michael , Tucker Douglass , Laprade David , Roussel Breton , Hallisey Victoria , Chin Christopher , Brass Abraham , Austriaco Nicanor 
Published: July 2018

AbstractSulforaphane (SFN) is a compound [1-isothiocyanato-4-(methylsulfinyl)- butane] found in broccoli and other cruciferous vegetables that is currently of interest because of its potential as a chemopreventive and a chemotherapeutic drug. Recent studies in a diverse range of cellular and animal models have shown that SFN is involved in multiple intracellular signaling pathways that regulate cell death, cell cycle progression, and cell invasion. In order to better understand the mechanisms of action behind SFN-induced cell death, we undertook an unbiased genome wide screen with the yeast knockout (YKO) library to identify SFN sensitive (SFNS) mutants. Our mutants were enriched with knockouts in genes linked to vacuolar function suggesting a link between this organelle and SFN’s mechanism of action in yeast. Our subsequent work revealed that SFN increases the vacuolar pH of yeast cells and that varying the vacuolar pH can alter the sensitivity of yeast cells to the drug. In fact, several mutations that lower the vacuolar pH in yeast actually made the cells resistant to SFN (SFNR). Finally, we show that human lung cancer cells with more acidic compartments are also SFNR suggesting that SFN’s mechanism of action identified in yeast may carry over to higher eukaryotic cells.
Metabolic deregulation in prostate cancer
Authors: Srihari Sriganesh , Tattam Paula , Simpson Rebecca , Smith Elliot 
Published: July 2018

AbstractIntroductionThe prostate exhibits a unique metabolism that changes during initial neoplasia to aggressive prostate cancer (PCa) and metastasis. The study of PCa metabolism thus represents a new avenue for diagnostics, particularly early diagnosis of aggressive PCa cases.ResultsHere, using transcriptomics data from The Cancer Genome Atlas (498 PCa patients), we identified six metabolic subgroups (C1-C6) of PCa that showed distinct disease-free survival outcomes (p<0.0001). In particular, we identified at least two PCa subgroups (C5 and C3) that exhibited significant poor prognosis (~70% and 30-40% relapse by the first 72 months; hazards ratios 9.4 and 4.4, respectively, relative to the best prognosis cluster C4 that showed <20% relapse even by 120 months). The subgroups were reproducible in an independent dataset from Taylors et al. 2010 (215 patients; p=0.00088). The subgroups displayed distinct metabolic profiles vis-à-vis normal tissues; measured as ‘deregulation’ of metabolic pathways (using Pathifier, Drier & Domany, 2013). In particular, the poor-prognosis subgroups C5 and C3 showed considerable deregulation for pathways involved in synthesis and catabolism of complex forms of lipids and carbohydrates, amino acids, and TCA cycle, and these were exhibited in parallel or in the face of glycolysis, a common form of energy production in cancer cells. Furthermore, the subgroups were significantly over-enriched for different sets of genetic alterations [particularly, deletions/mutations in BRCA1 and TP53 (C5), RB1 and STK11(C3); and AR amplifications (C1); p≤8.6E-04], suggesting that distinct alterations may be underpinning the subgroups and ‘pushing’ the subgroups towards their unique metabolic profiles. Finally, applying the classifier to blood expression profiles from 42 active surveillance (AS) and 65 advanced castrate resistant PCa (ACRPC) patients determined based on prostate-specific antigen (PSA) levels (Olmos et al., 2012) assigned 70.77% ACPRC, and interestingly reassigned 59.52% AS patients to at least one of the poor prognosis subgroups (C5, C3) with 35.71% to the poor and metabolically deregulated subgroup C3.ConclusionThe identification of PCa subgroups displaying distinct clinical outcomes solely from metabolic expression profiles of PCa tumours reiterates the significant link between deregulated metabolism and PCa outcomes (Eidelman et al., 2017). On the other hand, the time to biochemical relapse (rise in PSA levels) was not indicative of the early relapse seen for the metabolically deregulated subgroups C3 and C5 (these show considerably late BCR compared to C4). Our study thus highlights specific processes (elevated lipid and carbohydrate metabolism pathways) that could be better indicators than PSA for early diagnosis of aggressive PCa.
The most primitive extant ancestor of organisms and discovery of definitive evolutionary equations
Authors: Sorimachi Kenji 
Published: July 2018

AbstractOrganisms are classified into three domains, Prokaryota, Archaea, and Eukaryota, and their evolutionary divergence has been characterized based on morphological and molecular features using rationale based on Darwin’s theory of natural selection. However, universal rules that govern genome evolution have not been identified. Here, a simple, innovative approach has been developed to evaluate biological evolution initiating the origin of life: whole genomes were divided into several fragments, and then differences in normalized nucleotide content between nucleotide pairs were compared. Based on nucleotide content structures, Monosiga brevicollis mitochondria may be the most primitive extant ancestor of the species examined here. The two normalized nucleotide contents are universally expressed by a linear regression line, (X − Y)/(X + Y) = a (X − Y) + b, where X and Y are nucleotide contents and (a) and (b) are constants. The value of (G + C), (G + A), (G + T), (C + A), (C + T) and (A + T) was ~0.5. Plotting (X − Y)/(X + Y) against X/Y showed a logarithmic function (X − Y)/(X + Y) = a ln X/Y + b, where (a) and (b) are constant. Nucleotide content changes are expressed by a definitive equation, (X − Y) ≈ 0.25 ln(X/Y).
Native Mass Spectrometry Reveals the Conformational Diversity of the UVR8 Photoreceptor
Authors: Camacho Inês S. , Theisen Alina , Johannissen Linus O. , Díaz-Ramos L. Aranzazú , Christie John M. , Jenkins Gareth I. , Bellina Bruno , Barran Perdita , Jones Alex R. 
Published: July 2018

AbstractUVR8 is a plant photoreceptor protein that regulates photomorphogenic and protective responses to UV light. The inactive, homodimeric state absorbs UV-B light resulting in dissociation into monomers, which are considered to be the active state and comprise a β-propeller core domain and intrinsically disordered N- and C-terminal tails. The C-terminus is required for functional binding to signalling partner COP1. To date, however, structural studies have only been conducted with the core domain where the terminal tails have been truncated. Here, we report structural investigations of full-length UVR8 using native ion mobility mass spectrometry adapted for photo-activation. We show that, whilst truncated UVR8 photo-converts from a single conformation of dimers to a single monomer conformation, the full-length protein exist in numerous conformational families. The full-length dimer adopts both a compact state and an extended state where the C-terminus is primed for activation. In the monomer the extended C-terminus destabilises the core domain to produce highly extended yet stable conformations, which we propose are the fully active states that bind COP1. Our results reveal the conformational diversity of full-length UVR8. We also demonstrate the potential power of native mass spectrometry to probe functionally important structural dynamics of photoreceptor proteins throughout nature.TOC Graphic
Skull base invasive low-grade meningiomas, a distinct genetic subgroup: A microarray gene expression profile analysis
Authors: Sakuma Jun , Fujii Masazumi , Kishida Yugo , Iwami Kenichiro , Oda Keiko , Iwatate Kensho , Ichikawa Masahiro , Bakhit Mudathir , Sato Taku , Waguri Satoshi , Watanabe Shinya , Saito Kiyoshi 
Published: July 2018

AbstractIntroductionMeningioma is the most common adult primary brain tumor originating from meningeal coverings of the brain and spinal cord. Commonly, World Health Organization (WHO) grade-I meningiomas are slowly growing and surgically curative, some present with clinically aggressive behavior, invading the skull base bone and soft tissues by extending into the extracranial spaces.MethodsTo detect the genetic background of the Skull Base Invasive Low-grade Meningioma (SBILM), we conducted a comprehensive analysis of gene expression was conducted on 32 meningioma samples.ResultsThe cluster analysis of the gene expression profile demonstrated a distinctive clustering pattern of the SBILM. Based on the clinical behavior and the microarray findings, they might be a distinct subgroup of meningiomas.ConclusionFurther studies on characterization of genes specifically expressed by the SBILM could lead to the development of diagnostic tools, differentiating it from other WHO grade-I meningiomas and assist in the appropriate management and follow-up strategy, and open the door for development of pharmacological therapies.
Zebrafishduoxmutations provide a model for human congenital hypothyroidism
Authors: Chopra Kunal , Ishibashi Shoko , Amaya Enrique 
Published: July 2018

ABSTRACTThyroid dyshormonogenesis is a leading cause of congenital hypothyroidism, a highly prevalent but treatable condition. Thyroid hormone synthesis is dependent on the formation of reactive oxygen species (ROS). In humans, the primary sources for ROS production during thyroid hormone synthesis are the NADPH oxidase, DUOX1 and DUOX2. Indeed mutations inDUOX1andDUOX2have been linked with congenital hypothyroidism. Unlike humans, zebrafish has a single orthologue forDUOX1andDUOX2. In this study, we investigated the phenotypes associated with two nonsense mutant alleles of the singleduoxgene in zebrafish,sa9892andsa13017. Both alleles gave rise to readily observable phenotypes reminiscent of congenital hypothyroidism, from the larval stages through to adulthood. By using various methods to examine the external and internal phenotypes, we discovered a strong correlation between TH synthesis andduoxfunction, beginning from the early larval stage, when T4levels are already noticeably absent in the mutants. Loss of T4production resulted in growth retardation, pigmentation defects, ragged fins, thyroid hyperplasia / external goiter, and infertility. Remarkably all of these defects associated with chronic congenital hypothyroidism could be rescued with T4treatment, even when initiated when the fish had already reached adulthood. Our work suggests that these zebrafishduoxmutants may provide a powerful model to understand the aetiology of untreated and treated congenital hypothyroidism even in advance stages of development.
HP1B is a euchromatic Drosophila HP1 homolog with links to metabolism
Authors: Mills Benjamin B. , Thomas Andrew D. , Riddle Nicole C. 
Published: July 2018

ABSTRACTHeterochromatin Protein 1 (HP1) proteins are an important family of chromosomal proteins conserved among all major eukaryotic lineages. While HP1 proteins are best known for their role in heterochromatin, many HP1 proteins function in euchromatin as well. As a group, HP1 proteins carry out diverse functions, playing roles in the regulation of gene expression, genome stability, chromatin structure, and DNA repair. While the heterochromatic HP1 proteins are well studied, our knowledge of HP1 proteins with euchromatic distribution is lagging behind. We have created the first mutations in HP1B, a Drosophila HP1 protein with euchromatic function, and the Drosophila homolog most closely related to mammalian HP1α, HP1β, and HP1γ. We find that HP1B is a non-essential protein in Drosophila, with mutations affecting fertility and animal activity levels. In addition, animals lacking HP1B show altered food intake and higher body fat levels. Gene expression analysis of animals lacking HP1B demonstrates that genes with functions in various metabolic processes are affected primarily by HP1B loss. Our findings suggest that there is a link between the chromatin protein HP1B and the regulation of metabolism.
Information theoretic analysis of hyperspectral imaging systems with applications to fluorescence microscopy
Authors: Ram Sripad 
Published: July 2018

AbstractWe present a general stochastic model for hyperspectral imaging data and derive analytical expressions for the Fisher information matrix for the underlying spectral unmixing problem. We investigate the linear mixing model as a special case and define a linear unmixing performance bound by using the Cramer-Rao inequality. As an application, we consider fluorescence imaging and show how the performance bound provides a spectral resolution limit that predicts how accurately a pair of spectrally similar fluorescent labels can be spectrally unmixed. We also report a novel result that shows how the spectral resolution limit can be overcome by exploiting the phenomenon of anti-Stokes shift fluorescence. In addition, we investigate how photon statistics, channel addition and channel splitting affect the performance bound. Finally by using the performance bound as a benchmark, we compare the performance of the least squares and the maximum likelihood estimators for spectral unmixing. For the imaging conditions tested here, our analysis shows that both estimators are unbiased and that the standard deviation of the maximum likelihood estimator is consistently closer to the performance bound than that of the least squares estimator. The results presented here are based on broad assumptions regarding the underlying data model and are applicable to hyperspectral data acquired with point detectors, sCMOS, CCD and EMCCD imaging detectors.EDICS: ELI-COL, COI-MCI.
Cortical Column and Whole Brain Imaging of Neural Circuits with Molecular Contrast and Nanoscale Resolution
Authors: Gao Ruixuan , Asano Shoh M. , Upadhyayula Srigokul , Igor Pisarev , Milkie Daniel E. , Liu Tsung-Li , Ved Singh , Austin Graves , Huynh Grace H. , Zhao Yongxin , Bogovic John , Colonell Jennifer , Ott Carolyn M. , Zugates Christopher , Tappan Susan , Rodriguez Alfredo , Mosaliganti Kishore R. , Megason Sean G. , Lippincott-Schwartz Jennifer , Hantman Adam , Rubin Gerald M. , Kirchhausen Tom , Saalfeld Stephan , Aso Yoshinori , Boyden Edward S. , Betzig Eric 
Published: July 2018

AbstractOptical and electron microscopy have made tremendous inroads in understanding the complexity of the brain, but the former offers insufficient resolution to reveal subcellular details and the latter lacks the throughput and molecular contrast to visualize specific molecular constituents over mm-scale or larger dimensions. We combined expansion microscopy and lattice light sheet microscopy to image the nanoscale spatial relationships between proteins across the thickness of the mouse cortex or the entireDrosophilabrain, including synaptic proteins at dendritic spines, myelination along axons, and presynaptic densities at dopaminergic neurons in every fly neuropil domain. The technology should enable statistically rich, large scale studies of neural development, sexual dimorphism, degree of stereotypy, and structural correlations to behavior or neural activity, all with molecular contrast.One Sentence SummaryCombined expansion and lattice light sheet microscopy enables high speed, nanoscale molecular imaging of neural circuits over large volumes.
Thresholding of cryo-EM density maps by false discovery rate control
Authors: Beckers Maximilian , Jakobi Arjen J. , Sachse Carsten 
Published: July 2018

AbstractCryo-EM now commonly generates close-to-atomic resolution as well as intermediate resolution maps from macromolecules observed in isolation and in situ. Interpreting these maps remains a challenging task due to poor signal in the highest resolution shells and the necessity to select a threshold for density analysis. In order to facilitate this process, we developed a statistical framework for the generation of confidence maps by multiple hypothesis testing and false discovery rate (FDR) control. In this way, 3D confidence maps contain separated signal from background noise in the form of local detection rates of EM density values. We demonstrate that confidence maps and FDR-based thresholding can be used for the interpretation of near-atomic resolution single-particle structures as well as lower resolution maps determined by subtomogram averaging. Confidence maps represent a conservative way of interpreting molecular structures due to minimized noise. At the same time they provide a detection error with respect to background noise, which is associated with the density and particularly beneficial for the interpretation of weaker cryo-EM densities in cases of conformational flexibility and lower occupancy of bound molecules and ions to the structure.
Comparison of human and murine enteroendocrine cells by transcriptomic and peptidomic profiling
Authors: Roberts Geoffrey P , Larraufie Pierre , Richards Paul , Kay Richard G , Galvin Sam G , Miedzybrodzka Emily L , Leiter Andrew , Joyce Li H. , Glass Leslie L , Ma Marcella KL , Lam Brian , Yeo Giles SH , Scharfmann Raphaël , Chiarugi Davide , Hardwick Richard H , Reimann Frank , Gribble Fiona M 
Published: July 2018

AbstractEnteroendocrine cells (EECs) produce hormones that regulate food absorption, insulin secretion and appetite. Both EECs and their peptide products are foci of drug discovery programmes for diabetes and obesity. We compared the human and mouse EEC transcriptome and peptidome to validate mouse as a model of the human enteroendocrine axis. We present the first RNA sequencing analysis of human EECs, and demonstrate strong correlation with mouse, although with outliers including some low abundance G-protein coupled receptors. Liquid chromatography mass spectrometry (LC-MS) identified peptide hormone gradients along the human and mouse gut that should enhance progress in gut physiology and therapeutics.