bluuebunny/crossref_metadata_2025 huggingface dataset:
The projected economic and health burden of uncontrolled asthma in the United States
Authors: Yaghoubi Mohsen , Adibi Amin , Safari Abdollah , FitzGerald J Mark , Sadatsafavi Mohsen ,   for the Canadian Respiratory Research Network
Published: January 2019

Rationale

Despite effective treatments, a large proportion of asthma patients do not achieve sustained asthma control. The ‘preventable’ burden associated with lack of proper control is likely taking a high toll at the population level.

Objective

We predicted the future health and economic burden of uncontrolled asthma among American adults for the next 20 years.

Methods

We built a probabilistic model that linked state-specific estimates of population growth, asthma prevalence rates, and distribution of asthma control levels. We conducted several meta-analyses to estimate the adjusted differences in healthcare resource use, quality-adjusted life years (QALYs), and productivity loss across control levels. We projected, nationally and at the state-level, total direct and indirect costs (in 2018 USD) and QALYs lost due to uncontrolled asthma from 2019 to 2038 in the United States.

Measurements and Main Results

Over the next 20 years, the total undiscounted direct costs associated with suboptimal asthma control will be $300.6 billion (95% confidence interval [CI] $190.1 – $411.1). When indirect costs are added, total economic burden will be $963.5 billion (95%CI $664.1 – $1,262.9). American adolescents and adults will lose 15.46 million (95%CI 12.77 million – 18.14 million) QALYs over this period due to suboptimal control of asthma. In state-level analysis, the average 20-year per-capita costs due to uncontrolled asthma ranged from $2,209 (Arkansas) to $6,132 (Connecticut).

Conclusion

The burden of uncontrolled asthma will continue to grow for the next twenty years. Strategies towards better management of asthma may be associated with substantial return on investment.
Iron-sequestering nanocompartments as multiplexed Electron Microscopy gene reporters
Authors: Sigmund Felix , Pettinger Susanne , Kube Massimo , Schneider Fabian , Schifferer Martina , Aichler Michaela , Schneider Steffen , Walch Axel , Misgeld Thomas , Dietz Hendrik , Westmeyer Gil G.
Published: January 2019

Multi-colored gene reporters such as fluorescent proteins are indispensable for biomedical research, but equivalent tools for electron microscopy (EM), a gold standard for deciphering mechanistic details of cellular processes1,2and uncovering the network architecture of cell-circuits3,4, are still sparse and not easily multiplexable. Semi-genetic EM reporters are based on the precipitation of exogenous chemicals5–9which may limit spatial precision and tissue penetration and can affect ultrastructure due to fixation and permeabilization. The latter technical constraints also affect EM immunolabeling techniques10–13which may furthermore be complicated by limited epitope accessibility. The fully genetic iron storage protein ferritin generates contrast via its electron-dense iron core14–16, but its small size complicates differentiation of individual ferritin particles from cellular structures. To enable multiplexed gene reporter imaging via conventional transmission electron microscopy (TEM), we here introduce the encapsulin system ofQuasibacillus thermotolerans(Qt) as a fully genetic iron-biomineralizing nanocompartment. We reveal by cryo-electron reconstructions that the Qt monomers (QtEnc) self-assemble to nanospheres with T=4 icosahedral symmetry and an ~44 nm diameter harboring two putative pore regions at the fivefold and threefold axes. We furthermore show that the native cargo (QtlMEF) auto-targets to the inner surface of QtEnc and exhibits ferroxidase activity leading to efficient iron sequestration inside mammalian cells. We then demonstrate that QtEnc can be robustly differentiated from the non-intermixing encapsulin ofMyxococcus xanthus17(Mx, ~32 nm) via a deep-learning model, thus enabling automated multiplexed EM gene reporter imaging in mammalian cells.
How to test for phasic modulation of neural and behavioural responses
Authors: Zoefel Benedikt , Davis Matthew H , Valente Giancarlo , Riecke Lars
Published: January 2019

Research on whether perception or other processes depend on the phase of neural oscillations is rapidly gaining popularity. However, it is unknown which methods are optimally suited to evaluate the hypothesized phase effect. Using a simulation approach, we here test the ability of different methods to detect such an effect on dichotomous (e.g., “hit” vs “miss”) and continuous (e.g., scalp potentials) response variables. We manipulated parameters that characterise the phase effect or define the experimental approach to test for this effect. For each parameter combination and response variable, we identified an optimal method. We found that methods regressing single-trial responses on circular (sine and cosine) predictors perform best for all of the simulated parameters, regardless of the nature of the response variable (dichotomous or continuous). In sum, our study lays a foundation for optimized experimental designs and analyses in future studies investigating the role of phase for neural and behavioural responses. We provide MATLAB code for the statistical methods tested.
Tumor mutational landscape is a record of the pre-malignant state
Authors: Kübler Kirsten , Karlić Rosa , Haradhvala Nicholas J. , Ha Kyungsik , Kim Jaegil , Kuzman Maja , Jiao Wei , Gakkhar Sitanshu , Mouw Kent W. , Braunstein Lior Z. , Elemento Olivier , Biankin Andrew V. , Rooman Ilse , Miller Mendy , Karthaus Wouter R. , Nogiec Christopher D. , Juvenson Edouard , Curry Edward , Kenudson Mari Mino- , Ellisen Leif W. , Brown Robert , Gusev Alexander , Tomasetti Cristian , Lolkema Martijn P. , Steeghs Neeltje , van Herpen Carla , Kim Hong-Gee , Lee Hwajin , Vlahoviček Kristian , Bernstein Bradley E. , Sawyers Charles L. , Hoadley Katherine A. , Cuppen Edwin , Koren Amnon , Arndt Peter F. , Louis David N. , Stein Lincoln D. , Foulkes William D. , Polak Paz , Getz Gad ,   on behalf of the PCAWG Pathology and Clinical Correlates Working Group, and the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Network
Published: January 2019

Chromatin structure has a major influence on the cell-specific density of somatic mutations along the cancer genome. Here, we present a pan-cancer study in which we searched for the putative cancer cell-of-origin of 2,550 whole genomes, representing 32 cancer types by matching their mutational landscape to the regional patterns of chromatin modifications ascertained in 104 normal tissue types. We found that, in almost all cancer types, the cell-of-origin can be predicted solely from their DNA sequences. Our analysis validated the hypothesis that high-grade serous ovarian cancer originates in the fallopian tube and identified distinct origins of breast cancer subtypes. We also demonstrated that the technique is equally capable of identifying the cell-of-origin for a series of 2,044 metastatic samples from 22 of the tumor types available as primaries. Moreover, cancer drivers, whether inherited or acquired, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings highlight that many somatic mutations accumulate while the chromatin structure of the cell-of-origin is maintained and that this historical record, captured in the DNA, can be used to identify the often elusive cancer cell-of-origin.
Acoustic and Visual Stimulus Parameters Underlying Sound Symbolic Crossmodal Correspondences
Authors: List Sara M. , McCormick Kelly , Lacey Simon , Sathian K. , Nygaard Lynne C.
Published: January 2019

It is often assumed that a fundamental property of language is the arbitrariness of the relationship between sound and meaning. Sound symbolism, which refers to non-arbitrary mapping between the sound of a word and its meaning, contradicts this assumption. Sensitivity to sound symbolism has been studied through crossmodal correspondences (CCs) between auditory pseudowords (e.g. ‘loh-moh’) and visual shapes (e.g. a blob). We used representational similarity analysis to examine the relationships between physical stimulus parameters and perceptual ratings that varied on dimensions of roundedness and pointedness, for a range of auditory pseudowords and visual shapes. We found that perceptual ratings of these stimuli relate to certain physical features of both the visual and auditory domains. Representational dissimilarity matrices (RDMs) of parameters that capture the spatial profile of the visual shapes, such as the simple matching coefficient and Jaccard distance, were significantly correlated with those of the visual ratings. RDMs of certain acoustic parameters of the pseudowords, such as the temporal fast Fourier transform (FFT) and spectral tilt, that reflect spectral composition, as well as shimmer and speech envelope that reflect aspects of amplitude variation over time, were significantly correlated with those of the auditory perceptual ratings. RDMs of the temporal FFT (acoustic) and the simple matching coefficient (visual) were significantly correlated. These findings suggest that sound-symbolic CCs are related to basic properties of auditory and visual stimuli, and thus provide insights into the fundamental nature of sound symbolism and how this might evoke specific impressions of physical meaning in natural language.
A mutation in the endonuclease domain of mouse MLH3 reveals novel roles for MutLγ during crossover formation in meiotic prophase I
Authors: Toledo Melissa , Sun Xianfei , Brieño-Enríquez Miguel A. , Raghavan Vandana , Gray Stephen , Pea Jeffrey , Venkatesh Anita , Patel Lekha , Borst Peter L. , Alani Eric , Cohen Paula E.
Published: January 2019

During meiotic prophase I, double-strand breaks (DSBs) initiate homologous recombination leading to non-crossovers (NCOs) and crossovers (COs). In mouse, 10% of DSBs are designated to become COs, primarily through a pathway dependent on the MLH1-MLH3 heterodimer (MutLγ). Mlh3 contains an endonuclease domain that is critical for resolving COs in yeast. We generated a mouse (Mlh3DN/DN) harboring a mutation within this conserved domain that is predicted to generate a protein that is catalytically inert.Mlh3DN/DNmales, like fully nullMlh3-/-males, have no spermatozoa and are infertile, yet spermatocytes have normal DSBs and undergo normal synapsis events in early prophase I. UnlikeMlh3-/-males, mutation of the endonuclease domain within MLH3 permits normal loading and frequency of MutLγ in pachynema. However, key DSB repair factors (RAD51) and mediators of CO pathway choice (BLM helicase) persist into pachynema inMlh3DN/DNmales, indicating a temporal delay in repair events and revealing a mechanism by which alternative DSB repair pathways may be selected. WhileMlh3DN/DNspermatocytes retain only 22% of wildtype chiasmata counts, this frequency is greater than observed inMlh3-/-males (10%), suggesting that the allele may permit partial endonuclease activity, or that other pathways can generate COs from these MutLγ-defined repair intermediates inMlh3DN/DNmales. Double mutant mice homozygous for theMlh3DN/DNandMus81-/-mutations show losses in chiasmata that approach levels observed inMlh3-/-males, indicating that the MUS81-EME1-regulated crossover pathway accounts for some of the increased residual chiasmata observed inMlh3DN/DNspermatocytes. Our data demonstrate that mouse spermatocytes bearing the MLH1-MLH3DN/DNcomplex display the proper loading of factors essential for CO resolution (MutSγ, CDK2, HEI10, MutLγ). Despite these functions, mice bearing theMlh3DN/DNallele show defects in the repair of meiotic recombination intermediates and a loss of most chiasmata.

The MLH1-MLH3 complex is essential for crossing over in mammalian meiosis. We generated a mutation in mouse MLH3 that alters its conserved endonuclease domain and show that it disrupts crossing over in a manner distinct from the full nullMlh3mouse, but also results in male infertility.
Insulin enhances presynaptic glutamate release via opioid receptor-mediated disinhibition
Authors: Fetterly Tracy L. , Oginsky Max F. , Nieto Allison M. , Alonso-Caraballo Yanaira , Santana-Rodriguez Zuleirys , Ferrario Carrie R.
Published: January 2019

Insulin influences activity in brain centers that mediate reward and motivation in humans. However, nothing is known about how insulin influences excitatory transmission in regions like the nucleus accumbens (NAc), which governs motivational processes in the adult brain. Further, insulin dysregulation that accompanies obesity is linked to cognitive decline, depression, anxiety, and aberrant motivation that also rely on NAc excitatory transmission. Using a combination of whole-cell patch clamp and biochemical approaches we determined how insulin affects NAc glutamatergic transmission. We show that insulin receptor activation increases presynaptic glutamate release via a previously unidentified form of opioid receptor-mediated disinhibition. In contrast, activation of IGF receptors by insulin decreases presynaptic glutamate release in adult male rats. Furthermore, obesity results in a loss of insulin receptor-mediated increases and a reduction in NAc insulin receptor surface expression, while preserving reductions in transmission mediated by IGRFs. These results provide the first insights into how insulin influences excitatory transmission in the adult brain, they provide foundational information about opioid-mediated regulation of NAc glutamatergic transmission, and have broad implications for the regulation of motivation and reward related processes by peripheral hormones.
Efficient estimation and applications of cross-validated genetic predictions
Authors: Mefford Joel , Park Danny , Zheng Zhili , Ko Arthur , Ala-Korpela Mika , Laakso Markku , Pajukanta Päivi , Yang Jian , Witte John , Zaitlen Noah
Published: January 2019

Large-scale cohorts with combined genetic and phenotypic data, coupled with methodological advances, have produced increasingly accurate genetic predictors of complex human phenotypes called polygenic risk scores (PRS). In addition to the potential translational impacts of identifying at-risk individuals, PRS are being utilized for a growing list of scientific applications including causal inference, identifying pleiotropy and genetic correlation, and powerful gene-based and mixed model association tests. Existing PRS approaches rely on external large-scale genetic cohorts that have also measured the phenotype of interest. They further require matching on ancestry and genotyping platform or imputation quality. In this work we present a novel reference-free method to produce PRS that does not rely on an external cohort. We show that naive implementations of reference-free PRS either result in substantial over-fitting or prohibitive increases in computational time. We show that our algorithm avoids both of these issues, and can produce informative in-sample PRS over any existing cohort without over-fitting. We then demonstrate several novel applications of reference-free PRS including detection of pleiotropy across 246 metabolic traits and efficient mixed-model association testing.
Cancer Classification from Healthy DNA
Authors: Jain Siddharth , Mazaheri Bijan , Raviv Netanel , Bruck Jehoshua
Published: January 2019

The genome is traditionally viewed as atime-independentsource of information; a paradigm that drives researchers to seek correlations between the presence of certain genes and a patient’s risk of disease. This analysis neglectsgenomic temporal changes, which we believe to be a crucial signal for predicting an individual’s susceptibility to cancer. We hypothesize that each individual’s genome passes through anevolution channel(The termchannelis motivated by the notion of communication channel introduced by Shannon1 in 1948 and started the area ofInformation Theory), that is controlled by hereditary, environmental and stochastic factors. This channel differs among individuals, giving rise to varying predispositions to developing cancer. We introduce the concept ofmutation profilesthat are computed without any comparative analysis, but by analyzing the short tandem repeat regions in asingle healthy genomeand capturing information about the individual’s evolution channel. Using machine learning on data from more than 5,000 TCGA cancer patients, we demonstrate that thesemutation profilescan accurately distinguish between patients with various types of cancer. For example, the pairwise validation accuracy of the classifier between PAAD (pancreas) patients and GBM (brain) patients is 93%. Our results show that healthy unaffected cells still contain a cancer-specific signal, which opens the possibility of cancer prediction from a healthy genome.
Comparative genomics identified a genetic locus in plant-associated Pseudomonas spp. that is necessary for induced systemic susceptibility
Authors: Beskrovnaya Polina , Melnyk Ryan A. , Liu Zhexian , Liu Yang , Higgins Melanie A. , Song Yi , Ryan Katherine , Haney Cara H.
Published: January 2019

Plant root-associated microbes promote plant growth and induce systemic resistance (ISR) to foliar pathogens. In an attempt to find novel growth-promoting and ISR-inducing strains, we previously identified strains of root-associated Pseudomonas spp. that promote plant growth but unexpectedly induced systemic susceptibility (ISS) rather than ISR to foliar pathogens. Here we demonstrate that the ISS-inducing phenotype is common among root-associated Pseudomonas spp. Using comparative genomics, we identified a single P. fluorescens locus that is unique to ISS strains. We generated a clean deletion of the 11-gene ISS locus and found that it is necessary for the ISS phenotype. Although the functions of the predicted genes in the locus are not apparent based on similarity to genes of known function, the ISS locus is present in diverse bacteria and a subset of the genes have previously been implicated in pathogenesis in animals. Collectively these data show that a single bacterial locus contributes to modulation of systemic plant immunity.

Importance

Microbiome-associated bacteria can have diverse effects on health of their hosts, yet the genetic and molecular basis of these effects have largely remained elusive. This work demonstrates that a novel bacterial locus can modulate systemic plant immunity. Additionally, this work demonstrates that growth promoting strains may have unanticipated consequences on plant immunity and this is critical to consider when engineering the plant microbiome for agronomic improvement.
Artificial Dendritic Neurons Enable Self-Supervised Temporal Feature Extraction
Authors: Asabuki Toshitake , Fukai Tomoki
Published: January 2019

The brain identifies potentially salient features within continuous information streams to appropriately process external and internal temporal events. This requires the compression or abstraction of information streams, for which no effective information principles are known. Here, we propose conditional entropy minimization learning as the fundamental principle of such temporal processing. We show that this learning rule resembles Hebbian learning with backpropagating action potentials in dendritic neuron models. Moreover, networks of the dendritic neurons can perform a surprisingly wide variety of complex unsupervised learning tasks. Our model not only accounts for the mechanisms of chunking of temporal inputs in the human brain but also accomplishes blind source separation of correlated mixed signals, which cannot be solved by conventional machine learning methods, such as independent-component analysis.

One Sentence Summary

Neurons use soma-dendrite interactions to self-supervise the learning of characteristic features of various temporal inputs.
Recent origin of an XX/XY sex-determination system in the ancient plant lineageGinkgo biloba
Authors: Zhang He , Zhang Rui , Yang Xianwei , Gu Kai-Jie , Chen Wenbin , Chang Yue , Xu Qiwu , Liu Qun , Qin Yating , Hong Xiaoning , Yin  , Seim Inge , Lin Han-Yang , Li Wen-Hao , Tian Jinfu , Li Shanshan , Liu  , Liu Junnian , Liu Shanshan , Su Xiaoshan , Wang Congyan , Zhang Fu-Ming , Ge Song , Fu Cheng-Xin , Lee Simon Ming-Yuen , Xia Yiji , Wang Jian , Yang Huanming , Fan Guangyi , Xu Xun , Zhao Yun-Peng , Xin
Published: January 2019

Sexual dimorphism like dioecy (separate male and female individuals) have evolved in diverse multicellular eukaryotes while the molecular mechanisms underlying the development of such a key biological trait remains elusive (1). The living fossilGinkgo bilobarepresents an early diverged lineage of land plants with dioecy. However, its sex-determination system and molecular basis have long been controversial or unknown. In the present research, we assembled the first and largest to date chromosome-level genome of a non-model tree species using Hi-C data. With this reference genome, we addressed both questions using genome resequencing data gathered from 97 male and 265 female trees of ginkgo, as well as transcriptome data from three developmental stages for both sexes. Our results support vertebrate-like XY chromosomes for ginkgo and five potential sex-determination genes, which may originate ~14 million years ago. This is the earliest diverged sex determination region in all reported plants as yet. The present research resolved a long-term controversy, lay a foundation for future studies on the origin and evolution of plant sexes, and provide genetic markers for sex identification of ginkgo which will be valuable for both nurseries and field ecology of ginkgo.
Integrating past, present and future wheat research with Pretzel
Authors: Keeble-Gagnère Gabriel , Isdale Don , Suchecki Rados-ław , Kruger Alex , Lomas Kieran , Carroll David , Li Sean , Whan Alex , Hayden Matthew , Tibbits Josquin
Published: January 2019

Motivation

Major advances have been made in the assembly of complex genomes such as wheat. Remaining challenges include linking these new resources to legacy research, as well as lowering the bar to entry for members of the research community who may lack specific bioinformatics skills.

Results

Pretzel aims to solve these problems by providing an interactive, online environment for data visualisation and analysis which, when loaded with appropriately curated data, can enable researchers with no bioinformatics training to exploit the latest genomic resources. We demonstrate that Pretzel can be used to answer common questions asked by researchers as well as for advanced curation of pseudomolecule structure.

Availability

Pretzel is implemented in JavaScript and is freely available under a GPLv3 license online at: https://github.com/plantinformatics/pretzel.

Contact

gabriel.keeble-gagnere@ecodev.vic.gov.au
Data-driven detection of subtype-specific and differentially expressed genes
Authors: Chen Lulu , Lu Yingzhou , Yu Guoqiang , Clarke Robert , Van Eyk Jennifer E. , Herrington David M. , Wang Yue
Published: January 2019

Tissue or cell subtype-specific and differentially-expressed genes (SDEGs) are defined as being differentially expressed in a particular tissue or cell subtype among multiple subtypes. Detecting SDEGs plays a critical rolse in molecularly characterizing and identifying tissue or cell subtypes, and facilitating supervised deconvolution of complex tissues. Unfortunately, classic differential analysis assumes a convenient null hypothesis and associated test statistic that is subtype-non-specific and thus, resulting in a high false positive rate and/or lower detection power with respect to particular subtypes. Here we introduce One-Versus-Everyone Fold Change (OVE-FC) test for detecting SDEGs. To assess the statistical significance of such test, we also propose the scaled test statistic OVE-sFC together with a mixture null distribution model and a tailored permutation scheme. Validated with realistic synthetic data sets on both type 1 error and detection power, OVE-FC/sFC test applied to two benchmark gene expression data sets detects many known and de novo SDEGs. Subsequent supervised deconvolution results, obtained using the SDEGs detected by OVE-FC/sFC test, showed superior performance in deconvolution accuracy when compared with popular peer methods.
A Note on Computing Interval Overlap Statistics
Authors: Sarmashghi Shahab , Bafna Vineet
Published: January 2019

We consider the following problem: Let I and If each describe a collection of n and m non-overlapping intervals on a line segment of finite length. Suppose that k of the m intervals of If are intersected by some interval(s) in I. Under the null hypothesis that intervals in I are randomly arranged w.r.t If, what is the significance of this overlap? This is a natural abstraction of statistical questions that are ubiquitous in the post-genomic era. The interval collections represent annotations that reveal structural or functional regions of the genome, and overlap statistics can provide insight into the correlation between different structural and functional regions. However, the statistics of interval overlaps have not been systematically explored. In this manuscript, we formulate a statistical significance problem which considers the length and structure of intervals. We describe a combinatorial algorithm for a constrained interval overlap problem that can accurately compute very small p-values. We also propose a fast approximate method to facilitate problems consisted of very large number of intervals. These methods are all implemented in a tool, iStat. We applied iStat to simulated interval data to obtain precise estimates of low p-values, and characterize the performance of our methods. We also test iStat on real datasets from previous studies, and compare iStat results with the reported p-values using basic permutation or parametric tests. The iStat software is made publicly available on https://github.com/shahab-sarmashghi/ISTAT.git
Phylogenomics resolves major relationships and reveals significant diversification rate shifts in the evolution of silk moths and relatives
Authors: Hamilton CA , St Laurent RA , Dexter K , Kitching IJ , Breinholt JW , Zwick A , Timmermans MJTN , Barber JR , Kawahara AY
Published: January 2019

Background

The silkmoths and their relatives constitute the ecologically and taxonomically diverse superfamily Bombycoidea, which includes some of the most charismatic species of Lepidoptera. Despite displaying some of the most spectacular forms and ecological traits among insects, relatively little attention has been given to understanding their evolution and the drivers of their diversity.

Results

To begin to address this problem, we created a new Bombycoidea-specific Anchored Hybrid Enrichment (AHE) probe set and sampled up to 571 loci for 117 taxa across all major lineages of the Bombycoidea, producing a well-supported phylogeny. The tree was overall consistent with prior morphological and molecular studies, although some taxa (e.g.,ArotrosSchaus) were misplaced in the Bombycidae and here formally transferred to Apatelodidae. We identified important evolutionary patterns (e.g., morphology, biogeography, and differences in speciation and extinction), and our analysis of diversification rates highlights the stark increases that exist within the Sphingidae (hawkmoths) and Saturniidae (wild silkmoths).

Conclusions

We postulate that these rate shifts are due to the well-documented bat-moth “arms race” and differences in selective pressures from insectivorous bats. The study establishes a backbone for future evolutionary, comparative, and taxonomic studies, and presents a modified DNA extraction protocol that allows Lepidoptera specimens to be readily sequenced from pinned natural history collections, succeeding in samples up to 30 years old. Our research highlights the flexibility of AHE to generate genomic data from a wide range of museum specimens, both age and preservation method, and will allow researchers to tap into the wealth of biological data residing in natural history collections around the globe.
Complex-Traits Genetics Virtual Lab: A community-driven web platform for post-GWAS analyses
Authors: Cuellar-Partida Gabriel , Lundberg Mischa , Kho Pik Fang , D’Urso Shannon , Gutierrez-Mondragon Luis F. , Hwang Liang-Dar
Published: January 2019

Background

Genome-wide association studies (GWAS) are an important method for mapping genetic variation underlying complex traits and diseases. Tools to visualize, annotate and analyse results from these studies can be used to generate hypotheses about the molecular mechanisms underlying the associations.

Findings

The Complex-Traits Genetics Virtual Lab (CTG-VL) integrates over a thousand publicly-available GWAS summary statistics, a suite of analysis tools, visualization functions and diverse data sets for genomic annotations. CTG-VL also makes available results from gene, pathway and tissue-based analyses from over 1,500 complex-traits allowing to assess pleiotropy not only at the genetic variant level but also at the gene, pathway and tissue levels. In this manuscript, we showcase the platform by analysing GWAS summary statistics of mood swings derived from UK Biobank. Using analysis tools in CTG-VL we highlight hippocampus as a potential tissue involved in mood swings, and that pathways including neuron apoptotic process may underlie the genetic associations. Further, we report a negative genetic correlation with educational attainment rG = −0.41 ± 0.018 and a potential causal effect of BMI on mood swings OR = 1.01 (95% CI = 1.00–1.02). Using CTG-VL’s database, we show that pathways and tissues associated with mood swings are also associated with neurological traits including reaction time and neuroticism, as well as traits such age at menopause and age at first live birth.

Conclusions

CTG-VL is a platform with the most complete set of tools to carry out post-GWAS analyses. The CTG-VL is freely available at https://genoma.io as an online web application.
Srs2 helicase prevents the formation of toxic DNA damage during late prophase I of yeast meiosis
Authors: Sasanuma Hiroyuki , Sakurai Hana Subhan M. , Furihata Yuko , Challa Kiran , Palmer Lira , Gasser Susan M. , Shinohara Miki , Shinohara Akira
Published: January 2019

Proper repair of double-strand breaks (DSBs) is key to ensure proper chromosome segregation. In this study, we found that the deletion of the SRS2 gene, which encodes a DNA helicase necessary for the control of homologous recombination, induces aberrant chromosome segregation during budding yeast meiosis. This abnormal chromosome segregation in srs2 cells accompanies the formation of a novel DNA damage induced during late meiotic prophase-I. The damage may contain long stretches of single-stranded DNAs (ssDNAs), which lead to aggregate formation of a ssDNA binding protein, RPA, and a RecA homolog, Rad51, as well as other recombination proteins inside of the nuclei. The Rad51 aggregate formation in the srs2 mutant depends on the initiation of meiotic recombination and occurs in the absence of chromosome segregation. Importantly, as an early recombination intermediate, we detected a thin bridge of Rad51 between two Rad51 foci or among the foci in the srs2 mutant, which is rarely seen in wild type. These might be cytological manifestation of the connection of two DSB ends and multi-invasion. The DNA damage with Rad51 aggregates in the srs2 mutant is passed through anaphase-I and -II, suggesting the absence of DNA damage-induced cell-cycle arrest after the pachytene stage. We propose that Srs2 helicase resolves early protein-DNA recombination intermediates to suppress the formation of aberrant lethal DNA damage during late prophase-I.
In vitro synergy between Sodium Deoxycholate and Furazolidone against Enterobacteria via Inhibition of Multidrug Efflux Pumps
Authors: Le Vuong Van Hung , Olivera Catrina , Spagnuolo Julian , Davies Ieuan , Rakonjac Jasna
Published: January 2019

Antimicrobial combinations have been proven to be a promising approach in the confrontation with multi-drug resistant bacterial pathogens, owing to enhancement of antibacterial efficacy, deceleration of resistance development rate and mitigation of side effects by lowering the doses of two drugs. In the present study, we report that combination of furazolidone (FZ) and other nitrofurans with a secondary bile salt, Sodium Deoxycholate (DOC), generates a profound synergistic effect on growth inhibition and lethality in enterobacteria, including Escherichia coli, Salmonella, Citrobacter gillenii and Klebsiella pneumoniae. Taking E. coli as the model organism to study the mechanism of DOC-FZ synergy, we found that the synergistic effect involves FZ-mediated inhibition of efflux pumps that normally remove DOC from bacterial cells. We further show that the FZ–mediated nitric oxide production contributes to the synergistic effect. This is to our knowledge the first report of nitrofuran-DOC synergy against Gram-negative bacteria.
Eurotium cristatum, a new fungi probiotic from Fuzhuan brick tea, alleviated obesity in mice by modulating gut microbiota
Authors: Kang Dingding , Su Meng , Duan Yanwen , Huang Yong
Published: January 2019

Obesity is one of the major public health problems worldwide, mainly resulting from unhealthy lifestyles and diet. Gut microbiota dysbiosis may also lead to obese humans and animals. Modulating gut bacteria through fecal transplantation, the use of probiotics or certain dietary supplements, could normalize gut microbiota and subsequently alleviate obesity. Daily consumption of Fuzhuan brick tea (FBT) or its extracts have been observed to alleviate obesity in humans and experimental animals. In this study, high-fat diet-induced dysbiosis of gut microbiota in C57BL/6J mice was partially reversed by consumption of Eumtium cristatum, the dominant fungi during the manufacturing and storage of FBT. E. cristatum was able to modulate both gut fungi and bacteria composition, based on the analysis of microbiota composition of mice fecal samples. E. cristatum increased acetate and butyrate-producing bacteria in mice gut, and produced five times more butyrate than both obese and normal mice. Our results suggested that E. cristatum may be used as a fungi probiotic to beneficially modulate gut microbiota and to alleviate obesity in humans.
Prediction of pyrazinamide resistance inMycobacterium tuberculosisusing structure-based machine learning approaches
Authors: Carter Joshua J , Walker Timothy M , Walker A Sarah , Whitfield Michael G. , Morlock Glenn P. , Lynch Charlotte I. , Adlard Dylan , Peto Timothy EA , Posey James E. , Crook Derrick W , Fowler Philip W
Published: January 2019

Synopsis

Background

Pyrazinamide is one of four first-line antibiotics used to treat tuberculosis, however antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation inpncA,an enzyme that converts pyrazinamide into its active form.

Methods

We curated a dataset of 664 non-redundant, missense amino acid mutations inpncAwith associated high-confidence phenotypes from published studies and then trained three different machine learning models to predict pyrazinamide resistance. All models had access to a range of protein structural-, chemical- and sequence-based features.

Results

The best model, a gradient-boosted decision tree, achieved a sensitivity of 80.2% and a specificity of 76.9% on the hold-out Test dataset. The clinical performance of the models was then estimated by predicting the binary pyrazinamide resistance phenotype of 4,027 samples harboring 367 unique missense mutations inpncAderived from 24,231 clinical isolates.

Conclusions

This work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs.
SGI-4 in monophasic Salmonella Typhimurium ST34 is a novel ICE that enhances resistance to copper
Authors: Branchu Priscilla , Charity Oliver J. , Bawn Matt , Thilliez Gaetan , Dallman Timothy J , Petrovska Liljana , Kingsley Robert A.
Published: January 2019

A multi drug resistant (MDR) Salmonella enterica 4,[5],12:i-of sequence type 34 (monophasic S. Typhimurium ST34) is a current pandemic clone associated with livestock and numerous outbreaks in the human population. A large genomic island, termed SGI-4, is present in the monophasic Typhimurium ST34 clade and absent from other S. Typhimurium strains. SGI-4 consists of 78 open reading frames including sil and pco genes previously implicated in resistance to copper and silver, and multiple genes predicted to be involved in mobilisation and transfer by conjugation. SGI-4 was excised from the chromosome, circularised and transferred to recipient strains of S. Typhimurium at a frequency influenced by stress and induced by mitomycin C and oxygen tension. The presence of SGI-4 was associated with increased resistance to copper, particularly but not exclusively under anaerobic conditions. The presence of silCBA genes, predicted to encode an RND family efflux pump that transports copper from the periplasm to the external milieu, was sufficient to impart the observed enhanced resistance to copper. The presence of silCBA genes resulted in the absence of copper-dependent induction of a multicopper oxidase system encoded by pco genes, also present on SGI-4, suggesting that the system effectively limits the copper availability in the periplasm. The presence of silCBA genes did not affect SodCI-dependent macrophage survival.
Loss of a glutaredoxin gene underlies parallel evolution of trichome pattern inAntirrhinum
Authors: Tan Ying , Barnbrook Matthew , Wilson Yvette , Molnár Attila , Hudson Andrew
Published: January 2019

Most angiosperms produce trichomes--epidermal hairs that have protective or more specialised roles. In almost all species trichomes are multicellular and, in the majority, secretory. Despite the importance of multicellular trichomes for plant protection and as a source of high-value products, little is known about the mechanisms that control their development. Here we use natural variation betweenAntirrhinum(snapdragon) species to examine how trichome distribution is regulated and has evolved. We show that a single gene,Hairy(H), which is needed to repress trichome fate, underlies variation in trichome distribution patterns between allAntirrhinumspecies except one.Hencodes an epidermis-specific glutaredoxin and trichome distribution within individual plants reflects the location ofHexpression. Gene phylogenies and functional tests suggest thatHgained its trichome-repressing role late in eudicot evolution and thatAntirrhinumspecies with widespread trichomes evolved multiple times from a largely bald ancestor though independent losses of H activity. We also find evidence for an evolutionary reversal involving a suppressor mutation, and for a pleiotropic effect ofHthat might constrain the evolution of trichome patterns.
Cleaning genotype data from Diversity Outbred mice
Authors: Broman Karl W. , Gatti Daniel M. , Svenson Karen L. , Sen Śaunak , Churchill Gary A.
Published: January 2019

Data cleaning is an important first step in most statistical analyses, including efforts to map the genetic loci that contribute to variation in quantitative traits. Here we illustrate approaches to quality control and cleaning of array-based genotyping data for multiparent populations (experimental crosses derived from more than two founder strains), using MegaMUGA array data from a set of 291 from Diversity Outbred (DO) mice. Our approach employs data visualizations that can reveal problems at the level of individual mice or with individual SNP markers. We find that the proportion of missing genotypes for each mouse is an effective indicator of sample quality. We use microarray probe intensities for SNPs on the X and Y chromosomes to confirm the sex of each mouse, and we use the proportion of matching SNP genotypes between pairs of mice to detect sample duplicates. We use a hidden Markov model (HMM) reconstruction of the founder haplotype mosaic across each mouse genome to estimate the number of crossovers and to identify potential genotyping errors. To evaluate marker quality, we find that missing data and genotyping error rates are the most effective diagnostics. We also examine the SNP genotype frequencies with markers grouped according to their minor allele frequency in the founder strains. For markers with high apparent error rates, a scatterplot of the allele-specific probe intensities can reveal the underlying cause of incorrect genotype calls. The decision to include or exclude low-quality samples can have a significant impact on the mapping results for a given study. We find that the impact of low-quality markers on a given study is often minimal, but reporting problematic markers can improve the utility of the genotyping array across many studies.
The Ptr1 locus of Solanum lycopersicoides confers resistance to race 1 strains of Pseudomonas syringae pv. tomato and to Ralstonia pseudosolanacearum by recognizing the type III effectors AvrRpt2/RipBN
Authors: Mazo-Molina Carolina , Mainiero Samantha , Hind Sara R. , Kraus Christine M. , Vachev Mishi , Maviane-Macia Felicia , Lindeberg Magdalen , Saha Surya , Strickler Susan R. , Feder Ari , Giovannoni James J. , Smart Christine D. , Peeters Nemo , Martin Gregory B.
Published: January 2019

Race 1 strains of Pseudomonas syringae pv. tomato, which causes bacterial speck disease of tomato, are becoming increasingly common and no simply-inherited genetic resistance to such strains is known. We discovered that a locus in Solanum lycopersicoides, termed Pseudomonas tomato race 1 (Ptr1), confers resistance to race 1 Pst strains by recognizing the type III effector AvrRpt2. In Arabidopsis, AvrRpt2 degrades the RIN4 protein thereby activating RPS2-mediated immunity. Ptr1 also recognized homologs of AvrRpt2 from diverse bacteria including one in Ralstonia pseudosolanacearum and this correlated with the ability of AvrRpt2 to degrade RIN4. Using site-directed mutagenesis of AvrRpt2 we found that Ptr1 and RPS2 recognize identical features of AvrRpt2. However, the genome sequence of S. lycopersicoides revealed no RPS2 homolog in the Ptr1 region. Ptr1 could play an important role in controlling bacterial speck disease and its future cloning may shed light on an example of convergent evolution for recognition of a widespread type III effector.
Computational Drug Recommendation Approaches toward Safe Polypharmacy
Authors: Chiang Wen-Hao , Ning Xia
Published: January 2019

Adverse drug reactions (ADRs) induced from high-order drug-drug interactions (DDIs) due to polypharmacy - simultaneous use of multiple drugs - represent a significant public health problem. Unfortunately, computational efforts to facilitate decision making for safe polypharmacy, particularly to assist safe multi-drug prescribing, are lacking. We formally formulate the to-avoid and safe drug recommendation problems for multi-drug prescriptions. We investigate preliminary computational approaches to tackling these problems, utilizing a minimum set of available prescription data from a large population, and demonstrate their potentials in assisting safe-polypharmacy decision making once richer data (e.g., electronic medical records, omics data and pathology data) are available. We develop a joint model with a recommendation component and an ADR label prediction component to conduct to-avoid and safe drug recommendation. We also develop real drug-drug interaction datasets and corresponding evaluation protocols to facilitate future computational research on safe polypharmacy.
Species dynamics and interactions via metabolically informed consumer-resource models
Authors: Muscarella Mario E. , O’Dwyer James P.
Published: January 2019

Quantifying the strength, sign, and origin of species interactions, along with their dependence on environmental context, is at the heart of prediction and understanding in ecological communities. Pairwise interaction models like Lotka-Volterra provide an important and flexible foundation, but notably absent is an explicit mechanism mediating interactions. Consumer-resource models incorporate mechanism, but describing competitive and mutualistic interactions is more ambiguous. Here, we bridge this gap by modeling a coarse-grained version of a species’ true, cellular metabolism to describe resource consumption via uptake and conversion into biomass, energy, and byproducts. This approach does not require detailed chemical reaction information, but it provides a more explicit description of underlying mechanisms than pairwise interaction or consumer-resource models. Using a model system, we find that when metabolic reactions require two distinct resources we recover Liebig’s Law and multiplicative co-limitation in particular limits of the intracellular reaction rates. In between these limits, we derive a more general phenomenological form for consumer growth rate, and we find corresponding rates of secondary metabolite production, allowing us to model competitive and non-competitive interactions (e.g., facilitation). Using the more general form, we show how secondary metabolite production can support coexistence even when two species compete for a shared resource, and we show how differences in metabolic rates change species’ abundances in equilibrium. Building on these findings, we make the case for incorporating coarse-grained metabolism to update the phenomenology we use to model species interactions.
iPSC-derived Cancer Organoids Recapitulate Genomic and Phenotypic Alterations of c-met-mutated Hereditary Kidney Cancer
Authors: Hwang Jin Wook , Desterke Christophe , Féraud Olivier , Richard Stephane , Ferlicot Sophie , Verkarre Virginie , Patard Jean Jacques , Loisel-Duwattez Julien , Foudi Adlen , Griscelli Frank , Bennaceur-Griscelli Annelise , Turhan Ali G
Published: January 2019

Hereditary cancers with cancer-predisposing mutations represent unique models of human oncogenesis as a driving oncogenic event is present in germline, exposing the healthy member of a family to the occurrence of cancer. The study of the secondary events in a tissue-specific manner is now possible by the induced pluripotent stem cell (iPSC) technology offering the possibility to generate an unlimited source of cells that can be induced to differentiate towards a tissue at risk of malignant transformation. We report here for the first time, the generation of a c-met-mutated iPSC lines from the somatic cells of a patient with type 1 papillary renal cell carcinoma (PRCC). We demonstrate the feasibility of kidney differentiation with iPSC-derived organoids expressing markers of kidney progenitors with presence of tight junctions and brush borders in tubular structures at transmission electron microscopy. Importantly, c-met-mutated kidney organoids expressed PRCC markers both in vitro and in vivo in NSG mice. Gene expression profiling of c-met-mutated iPSC-derived organoid structures showed striking molecular similarities with signatures found in a large cohort of PRCC patient samples and identified 11 common genes. Among these, BHLHE40 and KDM4C, well-known factors involved in PRCC pathogenesis, were expressed in c-met-mutated kidney organoids. This analysis applied to primary cancers with and without c-met mutation showed overexpression of the BHLHE40 and KDM4C only in the c-met-mutated PRCC tumors, as predicted by c-met-mutated organoid transcriptome. These data represent therefore the first proof of concept of the generation of “renal carcinoma in a dish” model using c-met-mutated iPSC-derived organoids, opening new perspectives for discovery of novel potentially predictive disease markers and novel drugs for future precision medicine strategies.