bluuebunny/crossref_metadata_2025_split huggingface dataset:
CLN3 regulates endosomal function by modulating Rab7A activity
Authors: Yasa Seda , Modica Graziana , Sauvageau Etienne , Kaleem Abuzar , Hermey Guido , Lefrancois Stephane 
Published: May 2019

AbstractMutations in CLN3 are a cause of juvenile NCL (JNCL), also known as Batten Disease. Clinical manifestations includes cognitive regression, progressive loss of vision and motor function, epileptic seizures, and a significantly reduced lifespan. CLN3 localizes to endosomes and lysosomes, and has been implicated in intracellular trafficking and autophagy. However, the precise molecular function of CLN3 remains to be elucidated. We show that CLN3 interacts with Rab7A, a small GTPase that regulates several functions at late endosomes. We found that CLN3 is required for the efficient endosome-to-TGN trafficking of the lysosomal sorting receptors by regulating the Rab7A/retromer interaction. In cells lacking CLN3 or expressing CLN3 harbouring a disease-causing mutation, the lysosomal sorting receptors were degraded. We also demonstrated that CLN3 is required for the Rab7A/PLEKHM1 interaction, which is required for autophagosome/lysosome fusion. Overall, our data provides a molecular explanation behind phenotypes observed in JNCL.
Context-dependent requirement of H3K9 methyltransferase activity during cellular reprogramming to iPSCs
Authors: Vidal Simon , Polyzos Alexander , Valencia Jorge Morales , Wang Hongsu , Swanzey Emily , Ee Ly-sha , Amlani Bhishma , Tu Shengjiang , Gong Yixiao , Snetkova Valentina , Skok Jane A. , Tsirigos Aristotelis , Kim Sangyong , Apostolou Effie , Stadtfeld Matthias 
Published: May 2019

SUMMARYMethylation of histone 3 at lysine 9 (H3K9) is widely regarded as a major roadblock for cellular reprogramming and interference with associated methyltransferases such as EHMT1 and EHMT2 (also known as GLP and G9A, respectively) increases the efficiencies at which induced pluripotent stem cells (iPSCs) can be derived. Activation of histone and DNA demethylases by ascorbic acid (AA) has become a common approach to facilitate the extensive epigenetic remodeling required for iPSC formation, but possible functional interactions between the H3K9 methylation machinery and AA-stimulated enzymes remain insufficiently explored. Here we show that reduction of EHMT1/2 activity counteracts iPSC formation in an optimized reprogramming system in the presence of AA. Mechanistically, EHMT1/2 activity under these conditions is required for efficient downregulation of somatic genes and transition into an epithelial state. Of note, transient inhibition of EHMT1/2 during reprogramming yields iPSCs that fail to efficiently give rise to viable mice, suggesting persistent molecular defects in these cells. Genetic interference with the H3K9 demethylase KDM3B ameliorated the adverse effect of EHMT1/2 inhibition on iPSC formation. Together, our observations document novel functions of H3K9 methyltransferases during iPSC formation and suggest that the balancing of AA-stimulated enzymes by EHMT1/2 supports efficient and error-free iPSC reprogramming to pluripotency.
Mesoscale liquid model of chromatin recapitulates nuclear order of eukaryotes
Authors: Laghmach Rabia , Di Pierro Michele , Potoyan Davit A 
Published: May 2019

ABSTRACTThe nuclear envelope segregates the genome of Eukaryota from the cytoplasm. Within the nucleus, chromatin is further compartmentalized into architectures that change throughout the lifetime of the cell. Epigenetic patterns along the chromatin polymer strongly correlate with chromatin compartmentalization and, accordingly, also change during the cell life cycle and at differentiation. Recently, it has been suggested that sub-nuclear chromatin compartmentalization might result from a process of liquid-liquid phase separation orchestrated by the epigenetic marking and operated by proteins that bind to chromatin. Here, we translate these observations into a diffuse interface model of chromatin, which we named MEsoscale Liquid mOdel of Nucleus (MELON). Using this streamlined continuum model of the genome, we study the large-scale rearrangements of chromatin that happen at different stages of the growth and senescence of the cell, and during nuclear inversion events. Particularly, we investigate the role of droplet diffusion, fluctuations, and heterochromatin-lamina interactions during nuclear remodeling. Our results indicate that the physical process of liquid-liquid phase separation, together with surface effects is sufficient to recapitulate much of the large-scale morphology and dynamics of chromatin along the life cycle of cells.SIGNIFICANCE STATEMENTEukaryotic chromatin occupies a few micrometers of nuclear space while remaining dynamic and accessible for gene regulation. The physical state of nuclear chromatin is shaped by the juxtaposition of complex, out of equilibrium processes on one hand and intrinsic polymeric aspect of the genome on the other. Recent experiments have revealed a remarkable ability of disordered nuclear proteins to drive liquid-liquid phase separation of chromatin domains. We have built a mesoscale liquid model of nuclear chromatin which allows dissecting the contribution of liquid behavior of chromatin to nuclear order of eukaryotes. Our results show that liquid-liquid phase separation, together with surface effects is sufficient for recapitulating large-scale morphology and dynamics of chromatin at many stages of the nuclear cycle.
Paragraph: A graph-based structural variant genotyper for short-read sequence data
Authors: Chen Sai , Krusche Peter , Dolzhenko Egor , Sherman Rachel M. , Petrovski Roman , Schlesinger Felix , Kirsche Melanie , Bentley David R. , Schatz Michael C. , Sedlazeck Fritz J. , Eberle Michael A. 
Published: May 2019

AbstractAccurate detection and genotyping of structural variations (SVs) from short-read data is a long-standing area of development in genomics research and clinical sequencing pipelines. We introduce Paragraph, an accurate genotyper that models SVs using sequence graphs and SV annotations. We demonstrate the accuracy of Paragraph on whole-genome sequence data from three samples using long read SV calls as the truth set, and then apply Paragraph at scale to a cohort of 100 short-read sequenced samples of diverse ancestry. Our analysis shows that Paragraph has better accuracy than other existing genotypers and can be applied to population-scale studies.
Improved assembly and variant detection of a haploid human genome using single-molecule, high-fidelity long reads
Authors: Vollger Mitchell R. , Logsdon Glennis A. , Audano Peter A. , Sulovari Arvis , Porubsky David , Peluso Paul , Wenger Aaron M. , Concepcion Gregory T. , Kronenberg Zev N. , Munson Katherine M. , Baker Carl , Sanders Ashley D. , Spierings Diana C.J. , Lansdorp Peter M. , Surti Urvashi , Hunkapiller Michael W. , Eichler Evan E. 
Published: May 2019

AbstractThe sequence and assembly of human genomes using long-read sequencing technologies has revolutionized our understanding of structural variation and genome organization. We compared the accuracy, continuity, and gene annotation of genome assemblies generated from either high-fidelity (HiFi) or continuous long-read (CLR) datasets from the same complete hydatidiform mole human genome. We find that the HiFi sequence data assemble an additional 10% of duplicated regions and more accurately represent the structure of tandem repeats, as validated with orthogonal analyses. As a result, an additional 5 Mbp of pericentromeric sequences are recovered in the HiFi assembly, resulting in a 2.5-fold increase in the NG50 within 1 Mbp of the centromere (HiFi 480.6 kbp, CLR 191.5 kbp). Additionally, the HiFi genome assembly was generated in significantly less time with fewer computational resources than the CLR assembly. Although the HiFi assembly has significantly improved continuity and accuracy in many complex regions of the genome, it still falls short of the assembly of centromeric DNA and the largest regions of segmental duplication using existing assemblers. Despite these shortcomings, our results suggest that HiFi may be the most effective stand-alone technology for de novo assembly of human genomes.
Pan cancer patterns of allelic imbalance from chromosomal aberrations in 33 tumor types
Authors: Sivakumar Smruthy , San Lucas F Anthony , Jakubek Yasminka A , Fowler Jerry , Scheet Paul 
Published: May 2019

ABSTRACTSomatic copy number alterations (SCNAs), including deletions and duplications, serve as hallmarks of tumorigenesis. SCNAs may span entire chromosomes and typically result in deviations from an expected one-to-one ratio of alleles at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation (CBS) algorithm, providing segment mean copy number estimates from Affymetrix single-nucleotide polymorphism DNA microarray total (log R ratio) intensities, but not allele-specific (“B allele”) intensities that inform of AI. Here we seek to provide a TCGA-wide description of AI in tumor genomes, including AI induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH), using a powerful haplotype-based method applied to allele-specific intensities. We present AI summaries for all 33 tumor sites and propose an automated adjustment procedure to improve calibration of existing SCNA calls in TCGA for tumors with high levels of aneuploidy where baseline intensities were difficult to establish without annotation of AI. Overall, 94% of tumor samples exhibited AI. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p as well as mixed event types on 8p and 13q. The AI-based approach identified frequent cnLOH on 17p across multiple tumor sites, with additional site-specific cnLOH patterns. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.
Cell numbers, distribution, shape, and regional variation throughout the murine hippocampal formation from the adult brain Allen Reference Atlas
Authors: Attili Sarojini M. , Silva Marcos F.M. , Nguyen Thuy-vi , Ascoli Giorgio A. 
Published: May 2019

ABSTRACTQuantifying the distribution of cells in every brain region is fundamental to attaining a comprehensive census of distinct neuronal and glial types. Until recently, estimating neuron numbers involved time-consuming procedures that were practically limited to stereological sampling. Progress in open-source image recognition software, growth in computing power, and unprecedented neuroinformatics developments now offer the potentially paradigm-shifting alternative of comprehensive cell-by-cell analysis in an entire brain region. The Allen Brain Atlas provides free digital access to complete series of raw Nissl-stained histological section images along with regional delineations. Automated cell segmentation of these data enables reliable and reproducible high-throughput quantification of regional variations in cell count, density, size, and shape at whole-system scale. While this strategy is directly applicable to any regions of the mouse brain, we first deploy it here on the closed-loop circuit of the hippocampal formation: the medial and lateral entorhinal cortices; dentate gyrus (DG); areas Cornu Ammonis 3 (CA3), CA2, and CA1; and dorsal and ventral subiculum. Using two independent image processing pipelines and the adult mouse reference atlas, we report the first cellular-level soma segmentation in every sub-region and layer of the left hippocampal formation through the full rostral-caudal extent, except for the (already well characterized) principal layers of CA and DG. The overall numbers (∼600k cells in entorhinal cortex, ∼200k in DG, ∼430k in CA1-3, and ∼290k in subiculum) are corroborated by traditional stereological sampling on a data subset and well match sparse published reports.
Fast and accurate bacterial species identification in biological samples using LC-MS/MS mass spectrometry and machine learning
Authors: Roux-Dalvai Florence , Gotti Clarisse , Leclercq Mickaël , Hélie Marie-Claude , Boissinot Maurice , Arrey Tabiwang N. , Dauly Claire , Fournier Frédéric , Kelly Isabelle , Marcoux Judith , Bestman-Smith Julie , Bergeron Michel G. , Droit Arnaud 
Published: May 2019

ABSTRACTThe identification of microbial species in biological samples is essential to many applications in health, food safety and environment. MALDI-TOF MS technology has become a tool of choice for microbial identification but it has several drawbacks including: it requires a long step of bacterial culture prior to analysis (24h), it has a low specificity and is not quantitative. We have developed a new strategy for identifying bacterial species in biological samples using specific LC-MS/MS peptidic signatures. In the first training step, deep proteome coverage of bacteria of interest is obtained in Data Independent Acquisition (DIA) mode, followed by the use of machine learning to define the peptides the most susceptible to distinguish each bacterial species from the others. Then, in the second step, this peptidic signature is monitored in biological samples using targeted proteomics. This method, which allows the bacterial identification from clinical specimens in less than 4h, has been applied to fifteen species representing 84% of all Urinary Tract Infections (UTI). More than 31000 peptides in 200 samples have been quantified by DIA and analyzed by machine learning to determine an 82 peptides signature and build prediction models able to classify the fifteen bacterial species. This peptidic signature was validated for its use in routine conditions using Parallel Reaction Monitoring on a capillary flow chromatography coupled to a Thermo Scientific™ Q Exactive HF-X instrument. Linearity and reproducibility of the method were demonstrated as well as its accuracy on donor specimens. Within 4h and without bacterial culture, our method was able to predict the predominant bacteria infecting a sample in 97% of cases and 100% above the 1×105 CFU/mL threshold commonly used by clinical laboratories. This work demonstrates the efficiency of our method for the rapid and specific identification of the bacterial species causing UTI and could be extended in the future to other biological specimens and to bacteria having specific virulence or resistance factors.
Mouse IgG2a antibodies specific for the commensalStreptococcus mitisshow stronger cross-reactivity withStreptococcus pneumoniaethan IgG1 antibodies
Authors: Shekhar Sudhanshu , Khan Rabia , Khan Ata Ul Razzaq , Petersen Fernanda Cristina 
Published: May 2019

AbstractHere we show that mouse IgG2a and IgG1 antibodies specific for the commensalStreptococcus mitiscross-react with the pathogenStreptococcus pneumoniae, although the cross-reactivity conferred by IgG2a is stronger than IgG1 antibodies. These findings may have implications for designingS. mitis-based vaccines against pneumococcal infections.
Development of an innovative in vitro method for mass production of Verticillium dahliae microsclerotia
Authors: Sayago P. , Juncosa F , Albarracín Orio A. , Paccioretti M. , Gonzalez V. , Otero M.L. , Ducasse D.A 
Published: May 2019

AbstractThe soil-borne fungal plant pathogen Verticillium dahliae can infect more than 300 plant species including important economic crops, causing great economic loses. V. dahliae can persist and survive more than 14 years in the soil by resistance structures, known as microsclerotia, which constitute the primary inoculum in the field. In vitro mass production of microsclerotia is essential for performing many pathological assays. Nevertheless to harvest the microsclerotia is not an easy task and several protocols have been described although none of them is completely satisfying for different reasons. here we present a new protocol that is reproducible, robust, simple and fast allows to overcome the difficulties for obtaining massive amounts of microsclerotia. In summary, we developed a new culture medium that we called Pluronic Potato Medium (PPM) because it is essentially potato dextrose media with the hydrogel, Pluronic F127 as a solidifying agent. The microsclerotia collected in form PPM were infectious in tomato plants were they were able to reproduce the disease and we recovered and quantitated V. dahliae in infected plants.
Recurrent interactions can explain the variance in single trial responses
Authors: Kotekal Subhodh , MacLean Jason N. 
Published: May 2019

1.AbstractTo develop a complete description of sensory encoding, it is necessary to account for trial-to-trial variability in cortical neurons. Using a generalized linear model with terms corresponding to the visual stimulus, mouse running speed, and experimentally measured neuronal correlations, we modeled short term dynamics of L2/3 murine visual cortical neurons to evaluate the relative importance of each factor to neuronal variability within single trials. We find single trial predictions improve most when conditioning on the experimentally measured local correlations in comparison to predictions based on the stimulus or running speed. Specifically, accurate predictions are driven by positively co-varying and synchronously active functional groups of neurons. Including functional groups in the model enhances decoding accuracy of sensory information compared to a model that assumes neuronal independence. Functional groups, in encoding and decoding frameworks, provide an operational definition of Hebbian assemblies in which local correlations largely explain neuronal responses on individual trials.
Pan-Cancer Study Detects Novel Genetic Risk Variants and Shared Genetic Basis in Two Large Cohorts
Authors: Rashkin Sara R. , Graff Rebecca E. , Kachuri Linda , Thai Khanh K. , Alexeeff Stacey E. , Blatchins Maruta A. , Cavazos Taylor B. , Corley Douglas A. , Emami Nima C. , Hoffman Joshua D. , Jorgenson Eric , Kushi Lawrence H. , Meyers Travis J. , Van Den Eeden Stephen K. , Ziv Elad , Habel Laurel A. , Hoffmann Thomas J. , Sakoda Lori C. , Witte John S. 
Published: May 2019

AbstractDeciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. However, no studies have investigated pan-cancer pleiotropy within single, well-defined populations unselected for phenotype. We undertook novel genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (413,870 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detected 21 novel genome-wide significant risk variants. In addition, numerous cancer sites exhibited clear heritability. Investigations of pleiotropy identified 12 cancer pairs exhibiting either positive or negative genetic correlations and 43 pleiotropic loci. We identified 158 pleiotropic variants, many of which were enriched for regulatory elements and influenced cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.
Molecular basis for dyneinopathies reveals insight into dynein regulation and dysfunction
Authors: Marzo Matthew G. , Griswold Jacqueline M. , Ruff Kristina M. , Buchmeier Rachel E. , Fees Colby P. , Markus Steven M. 
Published: May 2019

SUMMARYCytoplasmic dynein plays critical roles within the developing and mature nervous systems, including effecting nuclear migration, and retrograde transport of various cargos. Unsurprisingly, mutations in dynein are causative of various developmental neuropathies and motor neuron diseases. These “dyneinopathies” define a broad spectrum of diseases with no known correlation between mutation identity and disease state. To overcome complications associated with studying dynein function in human cells, we employed budding yeast as a screening platform to characterize the motility properties of seventeen disease-correlated dynein mutants. Using this system, we have determined the molecular basis for several broad classes of etiologically related diseases. Moreover, by engineering compensatory mutations, we have alleviated the mutant phenotypes in two of these cases, one of which we confirmed with recombinant human dynein complexes. In addition to revealing molecular insight into dynein regulation, our data reveal an unexpected correlation between the degree of dynein dysfunction and disease type.
Population selection and sequencing ofC. eleganswild isolates identifies a region on chromosome III affecting starvation resistance
Authors: Webster Amy K. , Hung Anthony , Moore Brad T. , Guzman Ryan , Jordan James M. , Kaplan Rebecca E. W. , Hibshman Jonathan D. , Tanny Robyn E. , Cook Daniel E. , Andersen Erik , Ryan Baugh L. 
Published: May 2019

ABSTRACTTo understand the genetic basis of complex traits, it is important to be able to efficiently phenotype many genetically distinct individuals. In the nematodeCaenorhabditis elegans, individuals have been isolated from diverse populations around the globe and whole-genome sequenced. As a result, hundreds of wild strains with known genome sequences can be used for genome-wide association studies (GWAS). However, phenotypic analysis of these strains can be laborious, particularly for quantitative traits requiring multiple measurements per strain. Starvation resistance is likely a fitness-proximal trait for nematodes, and it is related to metabolic disease risk in humans. However, natural variation inC. elegansstarvation resistance has not been characterized, and precise measurement of the trait is time-intensive. Here, we developed a population selection and sequencing-based approach to phenotype starvation resistance in a pool of 96 wild strains. We used restriction site-associated DNA sequencing (RAD-seq) to infer the frequency of each strain among survivors in a mixed culture over time during starvation. We used manual starvation survival assays to validate the trait data, confirming that strains that increased in frequency over time are starvation-resistant relative to strains that decreased in frequency. These results document natural variation in starvation resistance. Further, we found that variation in starvation resistance is significantly associated with variation at a region on chromosome III. Using a near-isogenic line (NIL), we showed the importance of this genomic interval for starvation resistance. This study demonstrates the feasibility of using population selection and sequencing in an animal model for phenotypic analyses of quantitative traits, reveals natural variation of starvation resistance inC. elegans, and identifies a genomic region that contributes to such variation.