bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive, integrated, and phased whole-genome analysis of the primary ENCODE cell line K562
Authors: Zhou Bo , Ho Steve S. , Greer Stephanie U. , Zhu Xiaowei , Bell John M. , Arthur Joseph G. , Spies Noah , Zhang Xianglong , Byeon Seunggyu , Pattni Reenal , Ben-Efraim Noa , Haney Michael S. , Haraksingh Rajini R. , Ji Hanlee P. , Song Giltae , Perrin Dimitri , Wong Wing H. , Abyzov Alexej , Urban Alexander E. 
Published: December 2017

ABSTRACTK562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and Indels (both corrected for CN in aneuploid regions), loss of heterozygosity, mega-base-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs) including small and large-scale complex SVs and non-reference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor geneFHIT. Taking aneuploidy into account, we re-analyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.
Genetic architecture drives seasonal onset of hibernation in the 13-lined ground squirrel
Authors: Grabek Katharine R. , Cooke Thomas F. , Epperson L. Elaine , Spees Kaitlyn K. , Cabral Gleyce F. , Sutton Shirley C. , Merriman Dana K. , Martin Sandy L. , Bustamante Carlos D. 
Published: December 2017

AbstractHibernation is a highly dynamic phenotype whose timing, for many mammals, is controlled by a circannual clock and accompanied by rhythms in body mass and food intake. When housed in an animal facility, 13-lined ground squirrels exhibit individual variation in the seasonal onset of hibernation, which is not explained by environmental or biological factors, such as body mass and sex. We hypothesized that underlying genetic architecture instead drives variation in this timing. After first increasing the contiguity of the genome assembly, we therefore employed a genotype-by-sequencing approach to characterize genetic variation in 153 13-lined ground squirrels. Combining this with datalogger records, we estimated high heritability (61-100%) for the seasonal onset of hibernation. After applying a genome-wide scan with 46,996 variants, we also identified 21 loci significantly associated with hibernation immergence, which alone accounted for 54% of the variance in the phenotype. The most significant marker (SNP 15, p=3.81×10−6) was located near prolactin-releasing hormone receptor (PRLHR), a gene that regulates food intake and energy homeostasis. Other significant loci were located near genes functionally related to hibernation physiology, including muscarinic acetylcholine receptor M2 (CHRM2), involved in the control of heart rate, exocyst complex component 4 (EXOC4) and prohormone convertase 2 (PCSK2), both of which are involved in insulin signaling and processing. Finally, we applied an expression quantitative loci (eQTL) analysis using existing transcriptome datasets, and we identified significant (q<0.1) associations for 9/21 variants. Our results highlight the power of applying a genetic mapping strategy to hibernation and present new insight into the genetics driving its seasonal onset.
DNCON2: Improved protein contact prediction using two-level deep convolutional neural networks
Authors: Adhikari Badri , Hou Jie , Cheng Jianlin 
Published: December 2017

AbstractMotivationSignificant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key contributors to the recent progress in ab initio protein structure prediction, as demonstrated in the recent CASP experiments. Continuing the development of new methods to reliably predict contact maps is essential to further improve ab initio structure prediction.ResultsIn this paper we discuss DNCON2, an improved protein contact map predictor based on two-level deep convolutional neural networks. It consists of six convolutional neural networks – the first five predict contacts at 6, 7.5, 8, 8.5, and 10 Å distance thresholds, and the last one uses these five predictions as additional features to predict final contact maps. On the free-modeling datasets in CASP10, 11, and 12 experiments, DNCON2 achieves mean precisions of 35%, 50%, and 53.4%, respectively, higher than 30.6% by MetaPSICOV on CASP10 dataset, 34% by MetaPSICOV on CASP11 dataset, and 46.3% by Raptor-X on CASP12 dataset, when top L/5 long-range contacts are evaluated. We attribute the improved performance of DNCON2 to the inclusion of short- and medium-range contacts into training, two-level approach to prediction, use of the state-of-the-art optimization and activation functions, and a novel deep learning architecture that allows each filter in a convolutional layer to access all the input features of a protein of arbitrary length.AvailabilityThe web server of DNCON2 is at http://sysbio.rnet.missouri.edu/dncon2/ where training and testing datasets as well as the predictions for CASP10, 11, and 12 free-modeling datasets can also be downloaded. Its source code is available at https://github.com/multicom-toolbox/DNCON2/.Contactchengji@missouri.eduSupplementary informationSupplementary data are available online.
A new analysis of resting state connectivity and graph theory reveals distinctive short-term modulations due to whisker stimulation in rats
Authors: Kreitz Silke , de Celis Alonso Benito , Uder Michael , Hess Andreas 
Published: December 2017

AbstractResting state (RS) connectivity has been increasingly studied in healthy and diseased brains in humans and animals. This paper presents a new method to analyze RS data from fMRI that combines multiple seed correlation analysis with graph-theory (MSRA). We characterize and evaluate this new method in relation to two other graph-theoretical methods and ICA. The graph-theoretical methods calculate cross-correlations of regional average time-courses, one using seed regions of the same size (SRCC) and the other using whole brain structure regions (RCCA). We evaluated the reproducibility, power, and capacity of these methods to characterize short term RS modulation to unilateral physiological whisker stimulation in rats. Graph-theoretical networks found with the MSRA approach were highly reproducible, and their communities showed large overlaps with ICA components. Additionally, MSRA was the only one of all tested methods that had the power to detect significant RS modulations induced by whisker stimulation that are controlled by family-wise error rate (FWE). Compared to the reduced resting state network connectivity during task performance, these modulations implied decreased connectivity strength in the bilateral sensorimotor and entorhinal cortex. Additionally, the contralateral ventromedial thalamus (part of the barrel field related lemniscal pathway) and the hypothalamus showed reduced connectivity. Enhanced connectivity was observed in the amygdala, especially the contralateral basolateral amygdala (involved in emotional learning processes). In conclusion, MSRA is a powerful analytical approach that can reliably detect tiny modulations of RS connectivity. It shows a great promise as a method for studying RS dynamics in healthy and pathological conditions.
CytoGAN: Generative Modeling of Cell Images
Authors: Goldsborough Peter , Pawlowski Nick , Caicedo Juan C , Singh Shantanu , Carpenter Anne E 
Published: December 2017

AbstractWe explore the application of Generative Adversarial Networks to the domain of morphological profiling of human cultured cells imaged by fluorescence microscopy. When evaluated for their ability to group cell images responding to treatment by chemicals of known classes, we find that adversarially learned representations are superior to autoencoder-based approaches. While currently inferior to classical computer vision and transfer learning, the adversarial framework enables useful visualization of the variation of cellular images due to their generative capabilities.
Analysis of archaic human haplotypes suggest 5-hmC to act as epigenetic guide for meiotic point recombination
Authors: Lee Bernett , Cyrill Samantha , Lee Wendy , Melchiotti Rosella , Andiappan Anand , Poidinger Michael , Rötzschke Olaf 
Published: December 2017

AbstractMeiotic “point recombination” refers to homologue recombination events affecting only individual SNPs. Driven mostly by gene conversion, it is common process that allows for a gradual adaptation and maturation of haplotypes during genetic evolution. In contrast to crossover recombination it is not tied to predetermined recombination sites and therefore assumed to occur largely randomly. Our analysis of archaic human haplotypes however revealed striking differences in the local point recombination rate. A linkage-study of 1.9 million SNPs defined by the sequence of denisovan hominids revealed low rates in introns and quiescent intergenic regions but high rates in splice sites, exons, 5’- and 3’-UTRs, and CpG islands. Correlations with ChIP-Seq tracks from ENCODE and other public sources identified a number of epigenetic modifications, that associated directly with these recombination events. A particularly tight association was observed for 5-hydroxymethylcytosine marks (5hmC). The mark was enriched in virtually all of the functional regions associated with elevated point recombination rates, including CpG islands and ‘poised’ bivalent regions. As intermediate of oxidative demethylation, 5hmC is also a marker of recently opened gene loci. The data, thus, supports a model of ‘guided’ evolution, in which point recombination is directed by 5hmC marks towards the functionally relevant regions.
Natively Oxidized Amino Acid Residues in the Spinach Cytochromeb6fComplex
Authors: Taylor Ryan M. , Sallans Larry , Frankel Laurie K. , Bricker Terry M. 
Published: December 2017

AbstractThe cytochromeb6fcomplex of oxygenic photosynthesis produces substantial levels of reactive oxygen species (ROS). It has been observed that the ROS production rate byb6fis 10-20 fold higher than that observed for the analogous respiratory cytochromebc1complex. The types of ROS produced (O2•−,1O2, and, possibly, H2O2) and the site(s) of ROS production within theb6fcomplex has been the subject of some debate. Proposed sources of ROS have include the hemebp, PQp•−(possible sources for O2•−), the Rieske iron-sulfur cluster (possible source of O2•−and/or H2O2), Chla(possible source of1O2) and hemeCn(possible source of O2•−and/or H2O2). Our working hypothesis is that amino acid residues proximal to the ROS production sites will be more susceptible to oxidative modification than distant residues. In the current study, we have identified natively oxidized amino acid residues in the subunits of the spinach cytochromeb6fcomplex. The oxidized residues were identified by tandem mass spectrometry using the MassMatrix Program. Our results indicate that numerous residues, principally localized nearp-side cofactors and Chla, were oxidatively modified. We hypothesize that these sites are sources for ROS generation in the spinach cytochromeb6fcomplex.
Decoding the regulatory logic of theDrosophilamale stem cell system
Authors: Papagiannouli Fani , Tamirisa Srividya , Rempel Eugen , Ermakova Olga , Trost Nils , Zhou Jun , Mundorf Juliane , Brunel Samantha , Ruhland Naima , Boutros Michael , Lohmann Jan U. , Lohmann Ingrid 
Published: December 2017

ABSTRACTIn the past decade, the importance of the niche to provide regulatory inputs to balance stem cell self-renewal and differentiation has become clear. However, the regulatory interplay between stem cells and their niche at the whole genome level is still poorly understood. To elucidate the mechanisms controlling stem cells and their progenies as they progress through their developmental program at the transcriptional level, we recorded the regulatory program of two independent cell lineages in theDrosophilatestis stem cell model. To this end, we identified genes active in the soma or germline as well as genome-wide binding profiles of two essential transcription factors, Zfh-1 and Abd-A, expressed in somatic support cells and crucial for fate acquisition of both cell lineages. Our data identified key roles for TOR signalling, signal processing V-ATPase proton pumps and the nuclear transport engaged nucleoporins and we demonstrate their importance in controlling germline maintenance, proliferation and differentiation from the support side. To make our dataset publicly available and support quick and intuitive data mining, we generated an interactive online analysis tool. Applying our tool for comparative analysis, we uncovered conserved core gene sets of adult stem cells across species boundaries. We have tested the functional relevance of these genes in theDrosophilatestis and intestine and find a striking overrepresentation of stem cell defects when the corresponding genes were depleted. In summary, our dataset and interactive platform represents a versatile tool for identifying novel gene networks active in diverse stem cell types and provides a valuable resource for elucidating the multifaceted regulatory inputs required to guide proper stem cell behaviour.
Cellular responses to reactive oxygen species can be predicted on multiple biological scales from molecular mechanisms
Authors: Yang Laurence , Mih Nathan , Anand Amitesh , Park Joon Ho , Tan Justin , Yurkovich James T. , Monk Jonathan M. , Lloyd Colton J. , Sandberg Troy E. , Seo Sang Woo , Kim Donghyuk , Sastry Anand V. , Phaneuf Patrick , Gao Ye , Broddrick Jared T. , Chen Ke , Heckmann David , Szubin Richard , Hefner Ying , Feist Adam M. , Palsson Bernhard O. 
Published: December 2017

SummaryCatalysis using iron-sulfur clusters and transition metals can be traced back to the last universal common ancestor. The damage to metalloproteins caused by reactive oxygen species (ROS) can completely inhibit cell growth when unmanaged and thus elicits an essential stress response that is universal and fundamental in biology. We develop a computable multi-scale description of the ROS stress response in Escherichia coli. We show that this quantitative framework allows for the understanding and prediction of ROS stress responses at three levels: 1) pathways: amino acid auxotrophies, 2) networks: the systemic response to ROS stress, and 3) genetic basis: adaptation to ROS stress during laboratory evolution. These results show that we can now develop fundamental and quantitative genotype-phenotype relationships for stress responses on a genome-wide basis.
C-type lectin-like receptor 2 (CLEC-2)-dependent DC migration is controlled by tetraspanin CD37
Authors: de Winde Charlotte M , Matthews Alexandra L , van Deventer Sjoerd , van der Schaaf Alie , Tomlinson Neil D , Jansen Erik , Eble Johannes A , Nieswandt Bernhard , McGettrick Helen M , Figdor Carl G , Acton Sophie E , Tomlinson Michael G , van Spriel Annemiek B 
Published: December 2017

AbstractCell migration is central to evoke a potent immune response. Dendritic cell (DC) migration to lymph nodes is dependent on the interaction of C-type lectin-like receptor 2 (CLEC-2) expressed by DCs, with podoplanin expressed by lymph node stromal cells (LNSCs). However, the underlying molecular mechanisms by which CLEC-2 influences DC migration remain elusive. Here, we show that CLEC-2-dependent DC migration is tightly controlled by tetraspanin CD37, a membrane-organizing protein. Our findings demonstrate a specific molecular interaction between CLEC-2 and CD37. Myeloid cells lacking CD37 (Cd37-/-) expressed less CLEC-2 on their surface compared to wild-type cells, indicating that CD37 is required to stabilize membrane expression of CLEC-2. In addition, CLEC-2-expressing DCs lacking CD37 showed impaired adhesion, migration velocity and displacement on LNSCs. Moreover, Cd37-/- DCs failed to form actin protrusions in a 3D collagen matrix upon podoplanin-induced CLEC-2 stimulation, phenocopying CLEC-2-deficient DCs (CD11cΔCLEC-2). Microcontact printing experiments revealed that CD37 is required for CLEC-2 recruitment in the membrane to its ligand podoplanin. This study demonstrates that tetraspanin CD37 controls CLEC-2 membrane organization and provides new molecular insights underlying CLEC-2-dependent DC migration.
HOME: A histogram based machine learning approach for effective identification of differentially methylated regions
Authors: Srivastava Akanksha , Karpievitch Yuliya V , Eichten Steven R , Borevitz Justin O , Lister Ryan 
Published: December 2017

AbstractBackgroundThe development of whole genome bisulfite sequencing has made it possible to identify methylation differences at single base resolution throughout an entire genome. However, a persistent challenge in DNA methylome analysis is the accurate identification of differentially methylated regions (DMRs) between samples. Sensitive and specific identification of DMRs among different conditions requires accurate and efficient algorithms, and while various tools have been developed to tackle this problem, they frequently suffer from inaccurate DMR boundary identification and high false positive rate.ResultsWe present a novel Histogram Of MEthylation (HOME) based method that takes into account the inherent difference in the distribution of methylation levels between DMRs and non-DMRs to discriminate between the two using a Support Vector Machine. We show that generated features used by HOME are dataset-independent such that a classifier trained on, for example, a mouse methylome training set of regions of differentially accessible chromatin, can be applied to any other organism’s dataset and identify accurate DMRs. We demonstrate that DMRs identified by HOME exhibit higher association with biologically relevant genes, processes, and regulatory events compared to the existing methods. Moreover, HOME provides additional functionalities lacking in most of the current DMR finders such as DMR identification in non-CG context and time series analysis. HOME is freely available at https://github.com/ListerLab/HOME.ConclusionHOME produces more accurate DMRs than the current state-of-the-art methods on both simulated and biological datasets. The broad applicability of HOME to identify accurate DMRs in genomic data from any organism will have a significant impact upon expanding our knowledge of how DNA methylation dynamics affect cell development and differentiation.
PET studies of the glial cell marker TSPO in psychosis patients - a meta-analysis using individual participant data
Authors: Plavén-Sigray Pontus , Matheson Granville J. , Collste Karin , Ashok Abhishekh H. , Coughlin Jennifer M. , Howes Oliver D. , Mizrahi Romina , Pomper Martin G. , Rusjan Pablo , Veronese Mattia , Wang Yuchuan , Cervenka Simon 
Published: December 2017

Background:Accumulating evidence suggests that the immune system may be an important target for new treatment approaches in schizophrenia. Positron emission tomography (PET) and radioligands binding to the translocator protein (TSPO), which is expressed in glial cells in brain including immune cells, represents a potential method for patient stratification and treatment monitoring. This study examined if patients with first episode psychosis and schizophrenia had altered TSPO levels as compared to healthy control subjects.Methods:PubMed was searched for studies comparing patients with psychosis to healthy controls using second-generation TSPO radioligands. The outcome measure was distribution volume (VT), an index of TSPO levels, in frontal cortex (FC), temporal cortex (TC) and hippocampus (HIP). Bayes factors (BF) were applied to examine the relative support for higher, lower or no-change of TSPO levels in patients as compared to healthy controls.Results:Five studies, with 75 patients with first-episode psychosis or schizophrenia and 77 healthy control subjects were included. BF showed strong support for lower patient VT relative to no-change (all BF>32) or relative to an increase (all BF>422) in all brain regions. From the posterior distributions, mean patient-control differences in standardized VT values were −0.48 for FC (95% credible interval (CredInt)=-0.88 to −0.09), −0.47 for TC (CredInt=−0.87 to −0.07) and −0.63 for HIP (CredInt=−1.00 to −0.25).Discussion:The observed reduction of TPSO in compared to control subjects in patients may correspond to altered function or lower density of brain immune cells. Future studies should focus on investigating the underlying biological mechanisms and their relevance for treatment.
Tuberculosis outbreak investigation using phylodynamic analysis
Authors: Küehnert Denise , Coscolla Mireia , Stucki David , Metcalfe John , Fenner Lukas , Gagneux Sebastien , Stadler Tanja 
Published: December 2017

AbstractThe fast evolution of pathogenic viruses has allowed for the development of phylodynamic approaches that extract information about the epidemiological characteristics of viral genomes. Thanks to advances in whole genome sequencing, they can be applied to slowly evolving bacterial pathogens like Mycobacterium tuberculosis.In this study, we investigate the epidemiological dynamics underlying two M. tuberculosis outbreaks using phylodynamic methods. The first outbreak occurred in the Swiss city of Bern (1993-2012) and was caused by a drug-susceptible strain belonging to the phylogenetic M. tuberculosis Lineage 4. The second outbreak was caused by a multidrug-resistant (MDR) strain of Lineage 2, imported from the Wat Tham Krabok (WTK) refugee camp in Thailand into California.There is little temporal signal in the Bern data set and moderate temporal signal in the WTK data set. We estimate an evolutionary rate of 0.0039 per single nucleotide polymorphism (SNP) per year for Bern and 0.0024 per SNP per year for WTK. Nevertheless, due to its high sampling proportion (90%) the Bern outbreak allows robust estimation of epidemiological parameters despite the poor temporal signal. Conversely, there’s much uncertainty in the epidemiological estimates concerning the WTK outbreak, which has a small sampling proportion (9%). Our results suggest that both outbreaks peaked around 1990, although the Bernese outbreak was only detected in 1993, and the WTK outbreak around 2004. Furthermore, individuals were infected for a significantly longer period (around 9 years) in the WTK outbreak than in the Bern outbreak (4-5 years).Our work highlights both the limitations and opportunities of phylodynamic analysis of outbreaks involving slowly evolving pathogens: (i) estimation of the evolutionary rate is difficult on outbreak time scales and (ii) a high sampling proportion allows quantification of the age of the outbreak based on the sampling times, and thus allows for robust estimation of epidemiological parameters.