bluuebunny/crossref_metadata_2025_split huggingface dataset:
THE HOXD CLUSTER IS A DYNAMIC AND RESILIENT TAD BOUNDARY CONTROLLING THE SEGREGATION OF ANTAGONISTIC REGULATORY LANDSCAPES
Authors: Rodríguez-Carballo Eddie , Lopez-Delisle Lucille , Zhan Ye , Fabre Pierre J. , Beccari Leonardo , El-Idrissi Imane , Nguyen Huynh Thi Hahn , Ozadam Hakan , Dekker Job , Duboule Denis 
Published: September 2017

ABSTRACTThe mammalianHoxDcluster lies between two topologically associating domains (TADs) matching distinct, enhancer-rich regulatory landscapes. During limb development, the telomeric TAD controls the early transcription ofHoxdgene in forearm cells, whereas the centromeric TAD subsequently regulates more posteriorHoxdgenes in digit cells. Therefore, the TAD boundary prevents the terminalHoxd13gene to respond to forearm enhancers, thereby allowing proper limb patterning. To assess the nature and function of this CTCF-rich DNA regionin embryo,we compared chromatin interaction profiles between proximal and distal limb bud cells isolated from mutant stocks where various parts or this boundary region were removed. The resulting progressive release in boundary effect triggered inter-TAD contacts, favored by the activity of the newly accessed enhancers. However, the boundary was highly resilient and only a 400kb large deletion including the whole gene cluster was eventually able to merge the neighboring TADs into a single structure. In this unified TAD, both proximal and distal limb enhancers nevertheless continued to work independently over a targeted transgenic reporter construct. We propose that the wholeHoxDcluster is a dynamic TAD border and that the exact boundary position varies depending on both the transcriptional status and the developmental context.
Abundance and diversity of the fecal resistome in slaughter pigs and broilers in nine European countries
Authors: Munk Patrick , Knudsen Berith Elkær , Lukjacenko Oksana , Duarte Ana Sofia Ribeiro , Luiken Roosmarjin E. C. , Gompel Liese Van , Smit Lidwien A. M. , Schmitt Heike , Garcia Alejandro Dorado , Hansen Rasmus Borup , Petersen Thomas Nordahl , Bossers Alex , Ruppé Etienne , Lund Ole , Tine Hald , Pamp Sünje Johanna , Vigre Håkan , Heederik Dick , Wagenaar Jaap A. , Mevius Dik , Aarestrup Frank M. 
Published: September 2017

EFFORT groupHaitske Graveland, Alieda van Essen, Bruno Gonzalez-Zorn, Gabriel Moyano, Pascal Sanders, Claire Chauvin, Julie David, Antonio Battisti, Andrea Caprioli, Jeroen Dewulf, Thomas Blaha, Katharina Wadepohl, Maximiliane Brandt, Dariusz Wasyl, Magdalena Skarzyñska, Magdalena Zajac, Hristo Daskalov, Helmut W Saatkamp, Katharina D.C. Stärk.AbstractAntimicrobial resistance (AMR) in bacteria and associated human morbidity and mortality is increasing. Use of antimicrobials in livestock selects for AMR that can subsequently be transferred to humans. This flow of AMR between reservoirs demands surveillance in livestock as well as in humans. As part of the EFFORT project (www.effort-against-amr.eu), we have quantified and characterized the acquired resistance gene pools (resistomes) of 181 pig and 178 poultry farms from nine European countries, generating more than 5,000 gigabases of DNA sequence, using shotgun metagenomics. We quantified acquired AMR using the ResFinder database and a database constructed for this study, consisting of AMR genes identified through screening environmental DNA. The pig and poultry resistomes were very different in abundance and composition. There was a significant country effect on the resistomes, more so in pigs than poultry. We found higher AMR loads in pigs, while poultry resistomes were more diverse. We detected several recently described, critical AMR genes, includingmcr-1andoptrA, the abundance of which differed both between host species and countries. We found that the total acquired AMR level, was associated with the overall country-specific antimicrobial usage in livestock and that countries with comparable usage patterns had similar resistomes. Novel, functionally-determined AMR genes were, however, not associated with total drug use.
OpenEHR modeling for genomics in clinical practice
Authors: Mascia Cecilia , Uva Paolo , Leo Simone , Zanetti Gianluigi 
Published: September 2017

AbstractThe increasing usage of high throughput sequencing in personalized medicine brings new challenges to the realm of healthcare informatics. Patient records need to accommodate data of unprecedented size and complexity as well as keep track of their production process. In this work we present a solution for integrating genomic data into electronic health records via openEHR archetypes. We introduce new genomics-specific archetypes based on the popular variant call format and show their applicability to a practical use case. Finally, we discuss their structure in comparison with the HL7®FHIR®standard.
Subtypes of functional brain connectivity as early markers of neurodegeneration in Alzheimer’s disease
Authors: Orban Pierre , Tam Angela , Urchs Sebastian , Savard Melissa , Madjar Cécile , Badhwar AmanPreet , Dansereau Christian , Vogel Jacob , Schmuel Amir , Dagher Alain , Villeneuve Sylvia , Poirier Judes , Rosa-Neto Pedro , Breitner John , Bellec Pierre ,   for the Alzheimer’s Disease Neuroimaging Initiative,   and the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease Program
Published: September 2017

HighlightsReliable functional brain network subtypes accompany cognitive impairment in ADSymptom-related subtypes exist in the default-mode, limbic and salience networksA limbic subtype is associated with a familial risk of AD in healthy older adultsLimbic subtypes also associate with beta amyloid deposition and ApoE4In BriefWe found reliable subtypes of functional brain connectivity networks in older adults, associated with AD-related clinical symptoms in patients as well as several AD risk factors/biomarkers in asymptomatic individuals.SummaryThe heterogeneity of brain degeneration has not been investigated yet for functional brain network connectivity, a promising biomarker of Alzheimer’s disease. We coupled cluster analysis with resting-state functional magnetic resonance imaging to discover connectivity subtypes in healthy older adults and patients with cognitive disorders related to Alzheimer’s disease, noting associations between subtypes and cognitive symptoms in the default-mode, limbic and salience networks. In an independent asymptomatic cohort with a family history of Alzheimer’s dementia, the connectivity subtypes had good test-retest reliability across all tested networks. We found that a limbic subtype was overrepresented in these individuals, which was previously associated with symptoms. Other limbic subtypes showed associations with cerebrospinal fluid Aβ1-42levels and ApoE4 genotype. Our results demonstrate the existence of reliable subtypes of functional brain networks in older adults and support future investigations in limbic connectivity subtypes as early biomarkers of Alzheimer’s degeneration.
MicroRNA miR-128 represses LINE-1 (L1) retrotransposition by downregulating the nuclear import factor TNPO1
Authors: Idica Adam , Sevrioukov Evgueni A , Zisoulis Dimitri G , Hamdorf Matthias , Daugaard Iben , Kadandale Pavan , Pedersen Irene 
Published: September 2017

ABSTRACTRepetitive elements, including LINE-1 (L1), comprise approximately half of the human genome. These elements can potentially destabilize the genome by initiating their own replication and reintegration into new sites (retrotransposition). In somatic cells, transcription of L1 elements are repressed by distinct molecular mechanisms including DNA methylation and histone modifications to repress transcription. Under conditions of hypomethylation (e.g.in tumor cells) a window of opportunity for L1 de-repression arises and additional restriction mechanisms become crucial. We recently demonstrated that the microRNA miR-128 represses L1 activity by directly binding to L1 ORF2 RNA. In this study, we tested whether miR-128 can also control L1 activity by repressing cellular proteins important for L1 retrotransposition. We found that miR-128 targets the 3’UTR of the nuclear import factor transportin 1 (TNPO1) mRNA. Manipulation of miR-128 and TNPO1 levels demonstrated that induction or depletion of TNPO1 affects L1 retrotransposition and nuclear import of an L1-RNP complex (using L1-encoded ORF1p as a proxy for L1-RNP complexes). Moreover, TNPO1 overexpression partially reversed the repressive effect of miR-128 on L1 retrotransposition. Our study represents the first description of a protein factor involved in nuclear import of the L1 element and demonstrates that miR-128 controls L1 activity in somatic cells through two independent mechanisms: direct binding to L1 RNA, and regulating a cellular factor necessary for L1 nuclear import and retrotransposition.
Representational confusion: the plausible consequence of demeaning your data
Authors: Ramírez Fernando M. 
Published: September 2017

AbstractThe use of multivariate pattern analysis (MVPA) methods has enjoyed this past decade a rapid increase in popularity among neuroscientists. More recently, similarity-based multivariate methods aiming not only to extract information regarding the class membership of stimuli from their associated brain patterns, say, decode a face from a potato, but to understand the form of the underlying representational structure associated with stimulus dimensions of interest, say, 2D grating or 3D face orientation, have flourished under the name of Representational Similarity Analysis (RSA). However, data-preprocessing steps implemented prior to RSA can significantly change the covariance (and correlation) structure of the data, hence possibly leading to representational confusion—i.e., a researcher inferring that brain area A encodes information according to representational scheme X, and not Y, when the opposite is true. Here, I demonstrate with simulations that time-series demeaning (including z-scoring) can plausibly lead to representational confusion. Further, I expose potential interactions between the effects of data demeaning and how the brain happens to encode information. Finally, I emphasize the importance in the context of similarity analyses of at least occasionally explicitly considering the direction of pattern vectors in multivariate space, rather than focusing exclusively on the relative location of their endpoints. Overall, I expect this article will promote awareness of the impact of data demeaning on inferences regarding representational structure and neural coding.
Universal Panel Testing of Pancreatic Cancer Cases for Cancer Predisposition
Authors: Young Erin L. , Thompson Bryony A. , Neklason Deborah W. , Snow Angela K. , Firpo Matthew A. , Werner Theresa , Bell Russell , Sutherland Nykole R. , Smith Ken R. , Berger Justin , Fraser Alison , Gammon Amanda , Koptiuch Cathryn , Kohlmann Wendy K , Neumayer Leigh , Goldgar David E. , Mulvihill Sean J. , Cannon-Albright Lisa A. , Tavtigian Sean V. 
Published: September 2017

ABSTRACTBackground and AimsGenes associated with hereditary breast and ovarian cancer (HBOC) and colorectal cancer (CRC) susceptibility have been shown to play a role in pancreatic cancer susceptibility. Germline genetic testing of pancreatic cancer cases could be beneficial for at-risk relatives with pathogenic variants in established HBOC and CRC genes, but it is unclear what proportion of pancreatic cancer cases harbor pathogenic variants in these genes.Methods66 pancreatic cancer cases, unselected for family history and diagnosed at the Huntsman Cancer Hospital (HCH), were sequenced on a custom 34-gene panel including known HBOC and CRC genes. A second set of 156 unselected HCH pancreatic cancer cases were sequenced on an expanded 59-gene panel (n=95) or with a custom 14-gene clinical panel (n=61). Sequencing data from both sets of pancreatic cancer cases, the pancreatic cancer cases of the Cancer Genome Atlas (TCGA), and an unselected pancreatic cancer screen from the Mayo Clinic were combined in a meta-analysis to estimate the proportion of carriers with pathogenic and variants of uncertain significance.ResultsApproximately 8.9% of unselected pancreatic cancer cases at the HCH carried a variant with potential HBOC or CRC screening recommendations. A meta-analysis of unselected pancreatic cancer cases revealed that approximately 10.5% carry a pathogenic variant or HiP-VUS.ConclusionWith the inclusion of both HBOC and CRC susceptibility genes in a panel test, unselected pancreatic cancer cases have a high enough percentage of carriers to rationalize genetic testing for identification of variants that could be further used in cascade testing of healthy relatives to increase HBOC and CRC surveillance measures.
Improved Score Statistics for Meta-analysis in Single-variant and Gene-level Association Studies
Authors: Yang Jingjing , Chen Sai , Abecasis Gonçalo ,   IAMDGC
Published: September 2017

AbstractMeta-analysis is now an essential tool for genetic association studies, allowing these to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate why the standard meta-analysis methods lose power under unbalanced settings, and further propose a novel meta-analysis method that performs as efficiently as joint analysis under general settings. Our proposed method can accurately approximate the score statistics obtainable by joint analysis, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies (MAFs). In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard method. We further showed the power gain of our method in gene-level association studies with 26 unbalanced real studies of Age-related Macular Degeneration (AMD). In addition, we took the meta-analysis of three studies of type 2 diabetes (T2D) as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, we propose improved single-variant score statistics in meta-analysis, requiring “accurate” population-specific MAFs for multi-ethnic studies. These improved score statistics can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses.
Thalamocortical and Intracortical Laminar Connectivity Determines Sleep Spindle Properties
Authors: Krishnan Giri P , Rosen Burke Q , Chen Jen-Yung , Muller Lyle , Sejnowski Terrence J , Cash Sydney S , Halgren Eric , Bazhenov Maxim 
Published: September 2017

AbstractSpindle oscillations are brief oscillatory activity during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the properties of the core vs. matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, projecting to the middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. Our model demonstrates that this property is sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Futhermore, consistent with human recordings, in the model, spindles occurred independently in the core system but matrix system spindles commonly co-occurred with core one. We found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of the intra and inter cortical connectivity can potentially be a mechanism for increasing in spindle density as observed during learning.Author summaryThe density of sleep spindles has been shown to correlate with memory consolidation. Further, sleep spindles occur more often in human MEG than EEG. We developed thalamocortical network model that is capable of spontaneous generation of spindles across cortical layers and that captures the essential statistical features of spindles observed in experiments. We predict that differences in thalamo-cortical connectivity, known from anatomical studies, lead to the differences in the spindle properties between EEG and MEG as observed in human recordings. Further, we predict that the intracortical connectivity between cortical layers, a property influenced by sleep preceding learning, increases spindle density. Results from our study highlight the role of cortical and thalamic projections on the occurrence and properties of spindles.
Ecosystem functional response across precipitation extremes in a sagebrush steppe
Authors: Tredennick Andrew T. , Kleinhesselink Andrew R. , Taylor J. Bret , Adler Peter B. 
Published: September 2017

ABSTRACTBackgroundPrecipitation is predicted to become more variable in the western United States, meaning years of above and below average precipitation will become more common. Periods of extreme precipitation are major drivers of interannual variability in ecosystem functioning in water limited communities, but how ecosystems respond to these extremes over the long-term may shift with precipitation means and variances. Long-term changes in ecosystem functional response could reflect compensatory changes in species composition or species reaching physiological thresholds at extreme precipitation levels.MethodsWe conducted a five year precipitation manipulation experiment in a sagebrush steppe ecosystem in Idaho, United States. We used drought and irrigation treatments (approximately 50% decrease/increase) to investigate whether ecosystem functional response remains consistent under sustained high or low precipitation. We recorded data on aboveground net primary productivity (ANPP), species abundance, and soil moisture. We fit a generalized linear mixed effects model to determine if the relationship between ANPP and soil moisture differed among treatments. We used nonmetric multidimensional scaling to quantify community composition over the five years.ResultsEcosystem functional response, defined as the relationship between soil moisture and ANPP, was similar among irrigation and control treatments, but the drought treatment had a greater slope than the control treatment. However, all estimates for the effect of soil moisture on ANPP overlapped zero, indicating the relationship is weak and uncertain regardless of treatment. There was also large spatial variation in ANPP within-years, which contributes to the uncertainty of the soil moisture effect. Plant community composition was remarkably stable over the course of the experiment and did not differ among treatments.DiscussionDespite some evidence that ecosystem functional response became more sensitive under sustained drought conditions, the response of ANPP to soil moisture was consistently weak and community composition was stable. The similarity of ecosystem functional responses across treatments was not related to compensatory shifts at the plant community level, but instead may reflect the insensitivity of the dominant species to soil moisture. These species may be successful precisely because they have evolved life history strategies which buffer them against precipitation variability.
Cell size-dependent regulation of Wee1 localization by Cdr2 cortical nodes
Authors: Allard Corey A. H. , Opalko Hannah E. , Liu Ko-Wei , Medoh Uche , Moseley James B. 
Published: September 2017

AbstractCell size control requires mechanisms that link cell growth with Cdk1 activity. In fission yeast, the protein kinase Cdr2 forms cortical nodes that include the Cdk1 inhibitor Wee1, along with the Wee1-inhibitory kinase Cdr1. We investigated how nodes inhibit Wee1 during cell growth. Biochemical fractionation revealed that Cdr2 nodes were megadalton structures enriched for activated Cdr2, which increases in level during interphase growth. In live-cell TIRF movies, Cdr2 and Cdr1 remained constant at nodes over time, but Wee1 localized to nodes in short bursts. Recruitment of Wee1 to nodes required Cdr2 kinase activity and the noncatalytic N-terminus of Wee1. Bursts of Wee1 localization to nodes increased 20-fold as cells doubled in size throughout G2. Size-dependent signaling was due in part to the Cdr2 inhibitor Pom1, which suppressed Wee1 node bursts in small cells. Thus, increasing Cdr2 activity during cell growth promotes Wee1 localization to nodes, where inhibitory phosphorylation of Wee1 by Cdr1 and Cdr2 kinases promotes mitotic entry.SummaryCells turn off the mitotic inhibitor Wee1 to enter into mitosis. This study shows how cell growth progressively inhibits fission yeast Wee1 through dynamic bursts of localization to cortical node structures that contain Wee1 inhibitory kinases.
Genomewide significant regions in 43 Utah high-risk families implicate multiple genes involved in risk for completed suicide
Authors: Coon Hilary , Darlington Todd M. , DiBlasi Emily , Callor W. Brandon , Ferris Elliott , Fraser Alison , Yu Zhe , William Nancy , Das Sujan C. , Crowell Sheila E. , Chen Danli , Anderson John S. , Klein Michael , Jerominski Leslie , Cannon Dale , Shabalin Andrey , Docherty Anna , Williams Megan , Smith Ken R. , Keeshin Brooks , Bakian Amanda V. , Christensen Erik , Li Qingqin S. , Camp Nicola J. , Gray Douglas 
Published: September 2017

AbstractSuicide is the 10th leading cause of death in the US. While environment has undeniable impact, evidence suggests genetic factors play a significant role in completed suicide. We linked a resource of >4,500 DNA samples from completed suicides obtained from the Utah Medical Examiner to genealogical records and medical records data available on over 8 million individuals. This linking has resulted in the identification of high-risk extended families (7-9 generations) with significant familial risk of completed suicide. Familial aggregation across distant relatives minimizes effects of shared environment, provides more genetically homogeneous risk groups, and magnifies genetic risks through familial repetition. We analyzed Illumina PsychArray genotypes from suicide cases in 43 high-risk families, identifying 30 distinct shared genomic segments with genome-wide evidence (p=2.02E-07 to 1.30E-18) of segregation with completed suicide. The 207 genes implicated by the shared regions provide a focused set of genes for further study; 18 have been previously associated with suicide risk. While PsychArray variants do not represent exhaustive variation within the 207 genes, we investigated these for specific segregation within the high-risk families, and for association of variants with predicted functional impact in ~1300 additional Utah suicides unrelated to the discovery families. None of the limited PsychArray variants explained the high-risk family segregation; sequencing of these regions will be needed to discover segregating risk variants, which may be rarer or regulatory. However, additional association tests yielded four significant PsychArray variants (SP110, rs181058279;AGBL2, rs76215382;SUCLA2, rs121908538;APH1B, rs745918508), raising the likelihood that these genes confer risk of completed suicide.