bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protein pheromone MUP20/Darcin is a vector and target of indirect genetic effects in mice
Authors: Bachmann Sven O. , Cross Ellen , Kalbassi Shireene , Sarraf Matthew Alexandar ,   Michael Anthony Woodley of Menie, Baudouin Stéphane J. 
Published: February 2018

AbstractSocial behavior in animals is an adaptive process influenced by environmental factors and direct and indirect genetic effects. Indirect genetic effects (IGEs) include mechanisms by which individuals of particular genotypes can influence the behavioral phenotypes and genotypes (via modulated patterns of gene expression) of other individuals with different genotypes. In groups of adult mice, IGEs can be unidirectional, from one genotype to the other, or bidirectional, resulting in a homogenization of the behavioral phenotypes within the group. Critically, it has been theorized that IGEs constitute a large fitness target on which deleterious mutations can have pleiotropic effects, meaning that individuals carrying certain behavior-altering mutations can impose the fitness costs of those mutations on others comprising the broader social genome. Experimental data involving a mouse model support the existence of these IGE-amplified fitness losses; however, the underlying biological mechanisms that facilitate these remain unknown. In a mouse model of IGEs, we demonstrate that the Major Urinary Protein 20 pheromone, also called Darcin, produced by mice lacking the adhesion protein Neuroligin-3 acts as a vector to deleteriously modify the social behavior of wild-type mice. Additionally, we showed that lack of social interest on the part of Neuroligin-3 knockout mice is independent of their environment. These findings reveal a new role for mammalian pheromones in mediating the externalization of social deficits from one individual to others comprising the population through IGEs.Author SummaryIndirect genetic effects (IGEs) are mechanisms by which individuals of particular genotypes can influence the behavioral phenotype of individuals of different genotypes, sometimes disruptively, in instances where one member of the population carriers a deleterious behavior altering variant. Although disruptive IGEs have been demonstrated in mice, its underlying molecular and genetic mechanisms remain unknown. Using an IGEs mouse model, we demonstrated that the pheromone protein Major Urinary Protein 20, also named Darcin, is as a vector and target of social epistasis a specific type of IGEs. This finding reveals a new function for mammalian pheromones in mediating social epistasis to degrade group social behavior.
Epigenome-wide association study of placental DNA methylation and maternal exposure to night shift work in the Rhode Island Child Health Study
Authors: Clarkson-Townsend Danielle A. , Everson Todd M. , Deyssenroth Maya A. , Burt Amber A. , Hermetz Karen E. , Hao Ke , Chen Jia , Marsit Carmen J. 
Published: February 2018

ABSTRACTObjectivesCircadian disruption from environmental and occupational exposures can potentially impact health, including offspring health, through epigenetic alterations. Night shift workers experience circadian disruption, but little is known about how this exposure could influence the epigenome of the placenta, which is situated at the maternal-fetal interface. To investigate whether night shift work is associated with variations in DNA methylation patterns of placental tissue, we conducted an epigenome-wide association study (EWAS) of night shift work.MethodsCpG specific methylation genome-wide of placental tissue (measured with the Illumina 450K array) from participants (n=237) in the Rhode Island Child Health Study (RICHS) who did (n=53) and did not (n=184) report working the night shift was compared using robust linear modeling, adjusting for maternal age, pre-pregnancy smoking, infant sex, maternal adversity, and putative cell mixture.ResultsNight shift work was associated with differential methylation in placental tissue, including CpG sites in the genes NAV1, SMPD1, TAPBP, CLEC16A, DIP2C, FAM172A, and PLEKHG6 (Bonferroni-adjusted p<0.05). CpG sites within NAV1, MXRA8, GABRG1, PRDM16, WNT5A, and FOXG1 exhibited the most hypomethylation, while CpG sites within TDO2, ADAMTSL3, DLX2, and SERPINA1 exhibited the most hypermethylation (BH q<0.10). PER1 was the only core circadian gene demonstrating differential methylation. Functional analysis indicated GO-terms associated with cell-cell adhesion.ConclusionsNight shift work was associated with differential methylation of the placenta, which may have implications for fetal health and development. Additionally, neuron navigator 1 (NAV1) may play a role in the development of the human circadian system.What is already known about this subject?Night shift work and circadian disruption may play a role in the development and progression of many diseases. However, little is known about how circadian disruption impacts human fetal health and development.What are the new findings?Working the night shift is associated with altered placental methylation patterns, and particularly, neuron navigator 1 (NAV1) may play a role in the development of the human circadian system.How might this impact on policy or clinical practice in the foreseeable future?Night shift work prior to or during pregnancy may alter the placental epigenome, which has implications for fetal health. Further studies are needed to evaluate night shift work as a possible risk factor for gestational diabetes and to evaluate the impact of circadian disruption on fetal health and development.
PET by MRI: Glucose Imaging by 13C-MRS without Dynamic Nuclear Polarization by Noise Suppression through Tensor Decomposition Rank Reduction
Authors: Brender Jeffrey R. , Kishimoto Shun , Merkle Hellmut , Reed Galen , Hurd Ralph E. , Chen Albert P. , Ardenkjaer-Larsen Jan Henrik , Munasinghe Jeeva , Saito Keita , Seki Tomohiro , Oshima Nobu , Yamamoto Kazu , Choyke Peter L. , Mitchell James , Krishna Murali C. 
Published: February 2018

AbstractMetabolic reprogramming is one of the defining features of cancer and abnormal metabolism is associated with many other pathologies. Molecular imaging techniques capable of detecting such changes have become essential for cancer diagnosis, treatment planning, and surveillance. In particular, 18F-FDG (fluorodeoxyglucose) PET has emerged as an essential imaging modality for cancer because of its unique ability to detect a disturbed molecular pathway through measurements of glucose uptake. However, FDG-PET has limitations that restrict its usefulness in certain situations and the information gained is limited to glucose uptake only. 13C magnetic resonance spectroscopy theoretically has certain advantages over FDG-PET, but its inherent low sensitivity has restricted its use mostly to single voxel measurements. We show here a new method of imaging glucose metabolism in vivo that relies on a simple, but robust and efficient, post-processing procedure by the higher dimensional analog of singular value decomposition, tensor decomposition. Using this procedure, we achieve an order of magnitude increase in signal to noise in both dDNP and non-hyperpolarized non-localized experiments without sacrificing accuracy. In CSI experiments an approximately 30-fold increase was observed, enough that the glucose to lactate conversion indicative of the Warburg effect can be imaged without hyper-polarization with a time resolution of 12 s and an overall spatial resolution that compares favorably to 18F-FDG PET.
Crowdsourcing Image Analysis for Plant Phenomics to Generate Ground Truth Data for Machine Learning
Authors: Zhou Naihui , Siegel Zachary D , Zarecor Scott , Lee Nigel , Campbell Darwin A , Andorf Carson M , Nettleton Dan , Lawrence-Dill Carolyn J , Ganapathysubramanian Baskar , Kelly Jonathan W , Friedberg Iddo 
Published: February 2018

AbstractThe accuracy of machine learning tasks critically depends on high quality ground truth data. Therefore, in many cases, producing good ground truth data typically involves trained professionals; however, this can be costly in time, effort, and money. Here we explore the use of crowdsourcing to generate a large number of training data of good quality. We explore an image analysis task involving the segmentation of corn tassels from images taken in a field setting. We investigate the accuracy, speed and other quality metrics when this task is performed by students for academic credit, Amazon MTurk workers, and Master Amazon MTurk workers. We conclude that the Amazon MTurk and Master Mturk workers perform significantly better than the for-credit students, but with no significant difference between the two MTurk worker types. Furthermore, the quality of the segmentation produced by Amazon MTurk workers rivals that of an expert worker. We provide best practices to assess the quality of ground truth data, and to compare data quality produced by different sources. We conclude that properly managed crowdsourcing can be used to establish large volumes of viable ground truth data at a low cost and high quality, especially in the context of high throughput plant phenotyping. We also provide several metrics for assessing the quality of the generated datasets.Author SummaryFood security is a growing global concern. Farmers, plant breeders, and geneticists are hastening to address the challenges presented to agriculture by climate change, dwindling arable land, and population growth. Scientists in the field of plant phenomics are using satellite and drone images to understand how crops respond to a changing environment and to combine genetics and environmental measures to maximize crop growth efficiency. However, the terabytes of image data require new computational methods to extract useful information. Machine learning algorithms are effective in recognizing select parts of images, butthey require high quality data curated by people to train them, a process that can be laborious and costly. We examined how well crowdsourcing works in providing training data for plant phenomics, specifically, segmenting a corn tassel – the male flower of the corn plant – from the often-cluttered images of a cornfield. We provided images to students, and to Amazon MTurkers, the latter being an on-demand workforce brokered by Amazon.com and paid on a task-by-task basis. We report on best practices in crowdsourcing image labeling for phenomics, and compare the different groups on measures such as fatigue and accuracy over time. We find that crowdsourcing is a good way of generating quality labeled data, rivaling that of experts.
A Genomic Reference Panel forDrosophila serrata
Authors: Reddiex Adam R. , L. Allen Scott , Chenoweth Stephen F. 
Published: February 2018

AbstractHere we describe a collection of re-sequenced inbred lines ofDrosophila serrata, sampled from a natural population situated deep within the species endemic distribution in Brisbane, Australia.D. serratais a member of the speciosemontiumgroup whose members inhabit much of south east Asia and has been well studied for aspects of climatic adaptation, sexual selection, sexual dimorphism, and mate recognition. We sequenced 110 lines that were inbred via 17-20 generations of full-sib mating at an average coverage of 23.5x with paired-end Illumina reads. 15,228,692 biallelic SNPs passed quality control after being called using the Joint Genotyper for Inbred Lines (JGIL). Inbreeding was highly effective and the average levels of residual heterozygosity (0.86%) were well below theoretical expectations. As expected, linkage disequilibrium decayed rapidly, with r2dropping below 0.1 within 100 base pairs. With the exception of four closely related pairs of lines which may have been due to technical errors, there was no statistical support for population substructure. Consistent with other endemic populations of otherDrosophilaspecies, preliminary population genetic analyses revealed high nucleotide diversity and, on average, negative Tajima’s D values. A preliminary GWAS was performed on a cuticular hydrocarbon trait, 2-MeC28revealing 4 SNPs passing Bonferroni significance residing in or near genes. One geneCht9may be involved in the transport of CHCs from the site of production (oenocytes) to the cuticle. Our panel will facilitate broader population genomic and quantitative genetic studies of this species and serve as an important complement to existingD. melanogasterpanels that can be used to test for the conservation of genetic architectures across theDrosophilagenus.
HISAT-genotype: Next Generation Genomic Analysis Platform on a Personal Computer
Authors: Kim Daehwan , Paggi Joseph , Salzberg Steven L. 
Published: February 2018

AbstractRapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses of human genomes. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT-genotype, for representing and searching an expanded model of the human reference genome, in which a comprehensive catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a very fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate HISAT-genotype’s accuracy for HLA typing, a critical task in human organ transplantation, and for the DNA fingerprinting tests widely used in forensics. In both applications, HISAT-genotype not only improves upon earlier computational methods, but matches or exceeds the accuracy of laboratory-based assays.One Sentence SummaryHISAT-genotype is a software platform that has the ability to genotype all the genes in an individual’s genome within a few hours on a desktop computer.
Feature Specific Prediction Errors and Surprise across Macaque Fronto-Striatal Circuits during Attention and Learning
Authors: Oemisch Mariann , Westendorff Stephanie , Azimi Marzyeh , Hassani Seyed Ali , Ardid Salva , Tiesinga Paul , Womelsdorf Thilo 
Published: February 2018

SummaryPrediction errors signal unexpected outcomes indicating that expectations need to be adjusted. For adjusting expectations efficiently prediction errors need to be associated with the precise features that gave rise to the unexpected outcome. For many visual tasks this credit assignment proceeds in a multidimensional feature space that makes it ambiguous which object defining features are relevant. Here, we report of a potential solution by showing that neurons in all areas of the medial and lateral fronto-striatal networks encode prediction errors that are specific to separate features of attended multidimensional stimuli, with the most ubiquitous prediction error occurring for the reward relevant features. These feature specific prediction error signals (1) are different from a non-specific prediction error signal, (2) arise earliest in the anterior cingulate cortex and later in lateral prefrontal cortex, caudate and ventral striatum, and (3) contribute to feature-based stimulus selection after learning. These findings provide strong evidence for a widely-distributed feature-based eligibility trace that can be used to update synaptic weights for improved feature-based attention.HighlightsNeural reward prediction errors carry information for updating feature-based attention in all areas of the fronto-striatal network.Feature specific neural prediction errors emerge earliest in anterior cingulate cortex and later in lateral prefrontal cortex.Ventral striatum neurons encode feature specific surprise strongest for the goal-relevant feature.Neurons encoding feature-specific prediction errors contribute to attentional selection after learning.
SNAP-tagged nanobodies enable reversible optical control of a G protein-coupled receptor via a remotely tethered photoswitchable ligand
Authors: Farrants Helen , Ruiz Amanda Acosta , Gutzeit Vanessa A. , Trauner Dirk , Johnsson Kai , Levitz Joshua , Broichhagen Johannes 
Published: February 2018

AbstractG protein-coupled receptors (GPCRs) mediate the transduction of extracellular signals into complex intracellular responses. Despite their ubiquitous roles in physiological processes and as drug targets for a wide range of disorders, the precise mechanisms of GPCR function at the molecular, cellular, and systems levels remain partially understood. In order to dissect the function of individual receptors subtypes with high spatiotemporal precision, various optogenetic and photopharmacological approaches have been reported that use the power of light for receptor activation and deactivation. Here, we introduce a novel and, to date, most remote way of applying photoswitchable orthogonally remotely-tethered ligands (PORTLs) by using a SNAP-tag fused nanobody. Our nanobody-photoswitch conjugates (NPCs) can be used to target a GFP-fused metabotropic glutamate receptor by either gene-free application of purified complexes or co-expression of genetically encoded nanobodies to yield robust, reversible control of agonist binding and subsequent downstream activation. By harboring and combining the selectivity and flexibility of both nanobodies and self-labelling enzymes, we set the stage for targeting endogenous receptors in vivo.
Motor cortex is an input-driven dynamical system controlling dexterous movement
Authors: Sauerbrei Britton , Guo Jian-Zhong , Mischiati Matteo , Guo Wendy , Kabra Mayank , Verma Nakul , Branson Kristin , Hantman Adam 
Published: February 2018

AbstractSkillful control of movement is central to our ability to sense and manipulate the world. A large body of work in nonhuman primates has demonstrated that motor cortex provides flexible, time-varying activity patterns that control the arm during reaching and grasping. Previous studies have suggested that these patterns are generated by strong local recurrent dynamics operating autonomously from inputs during movement execution. An alternative possibility is that motor cortex requires coordination with upstream brain regions throughout the entire movement in order to yield these patterns. Here, we developed an experimental preparation in the mouse to directly test these possibilities using optogenetics and electrophysiology during a skilled reach-to-grab-to-eat task. To validate this preparation, we first established that a specific, time-varying pattern of motor cortical activity was required to produce coordinated movement. Next, in order to disentangle the contribution of local recurrent motor cortical dynamics from external input, we optogenetically held the recurrent contribution constant, then observed how motor cortical activity recovered following the end of this perturbation. Both the neural responses and hand trajectory varied from trial to trial, and this variability reflected variability in external inputs. To directly probe the role of these inputs, we used optogenetics to perturb activity in the thalamus. Thalamic perturbation at the start of the trial prevented movement initiation, and perturbation at any stage of the movement prevented progression of the hand to the target; this demonstrates that input is required throughout the movement. By comparing motor cortical activity with and without thalamic perturbation, we were able to estimate the effects of external inputs on motor cortical population activity. Thus, unlike pattern-generating circuits that are local and autonomous, such as those in the spinal cord that generate left-right alternation during locomotion, the pattern generator for reaching and grasping is distributed across multiple, strongly-interacting brain regions.
GeneQC: A quality control tool for gene expression estimation based on RNA-sequencing reads mapping
Authors: McDermaid Adam , Chen Xin , Zhang Yiran , Xie Juan , Wang Cankun , Ma Qin 
Published: February 2018

AbstractMotivationOne of the main benefits of using modern RNA-sequencing (RNA-Seq) technology is the more accurate gene expression estimations compared with previous generations of expression data, such as the microarray. However, numerous issues can result in the possibility that an RNA-Seq read can be mapped to multiple locations on the reference genome with the same alignment scores, which occurs in plant, animal, and metagenome samples. Such a read is so-called a multiple-mapping read (MMR). The impact of these MMRs is reflected in gene expression estimation and all downstream analyses, including differential gene expression, functional enrichment, etc. Current analysis pipelines lack the tools to effectively test the reliability of gene expression estimations, thus are incapable of ensuring the validity of all downstream analyses.ResultsOur investigation into 95 RNA-Seq datasets from seven species (totaling 1,951GB) indicates an average of roughly 22% of all reads are MMRs for plant and animal species. Here we present a tool called GeneQC (Gene expression Quality Control), which can accurately estimate the reliability of each gene’s expression level. The underlying algorithm is designed based on extracted genomic and transcriptomic features, which are then combined using elastic-net regularization and mixture model fitting to provide a clearer picture of mapping uncertainty for each gene. GeneQC allows researchers to determine reliable expression estimations and conduct further analysis on the gene expression that is of sufficient quality. This tool also enables researchers to investigate continued re-alignment methods to determine more accurate gene expression estimates for those with low reliability.AvailabilityGeneQC is freely available at http://bmbl.sdstate.edu/GeneQC/home.html.Contactqin.ma@sdstate.eduSupplementary informationSupplementary data are available at Bioinformatics online.
The Constriction Ring of Amniotic Band Syndrome Reveals Idiosyncrasies of Wound Repair in Infancy
Authors: Bhattacharyya Surjya N. , Ilyashov Isaac M. , Chu Alice 
Published: February 2018

ABSTRACTWe hypothesized that the constriction rings in Amniotic Band Syndrome (ABS) are the sequelae of localized mechanical injury. Typical scarring pattern was examined in skin tissue of ABS origin, containing an amniotic band constriction, for collagen and elastin distribution, and the ratio of collagen I to collagen III (CI:CIII). A skin sample from an extra finger was the control. In the ABS specimens, sub-epidermal structures were intact and present throughout, and collagen I exhibited a normal basket-weave pattern. At the site of constriction in both ABS samples, reticular dermis elastin fibers were fragmented and papillary dermis elastin fibers were absent. In the control tissue, the reticular dermis contained relatively thick, branching fibers of elastin, and papillary dermis elastin was present.The elastin fragmentation at the constriction ring indicates localized elastin remodeling in response to injury. The absence of elastin in the papillary dermis of the constriction likely indicates a localized disruption in elastin formation. The formation and deposition of collagen and the presence of sub-epidermal structures favor a non-scarring phenotype, while the organization of elastin favors that of localized scarring.Summary StatementA rare, fetal model of healing after constrictive injury of skin, in which elastin fragmentation at the constriction injury indicates remodeling explained by the differential expression of elastin during gestation.