bluuebunny/crossref_metadata_2025_split huggingface dataset:
The conflict between adaptation and dispersal for maintaining biodiversity in changing environments
Authors: Thompson Patrick L. , Fronhofer Emanuel A. 
Published: December 2018

AbstractDispersal and adaptation both allow species to persist in changing environments. Yet, we have limited understanding of how these processes interact to affect species persistence, especially in diverse communities where biotic interactions greatly complicate responses to environmental change. Here we use a stochastic metacommunity model to demonstrate how dispersal and adaptation to environmental change independently and interactively contribute to biodiversity maintenance. Dispersal provides spatial insurance, whereby species persist on the landscape by shifting their distributions to track favourable conditions. In contrast, adaptation allows species to persist by allowing for evolutionary rescue. But, when species both adapt and disperse, dispersal and adaptation do not combine positively to affect biodiversity maintenance, even if they do increase the persistence of individual species. This occurs because faster adapting species evolve to hold onto their initial ranges (i.e. monopolization effects), thus impeding slower adapting species from shifting their ranges and thereby causing extinctions. Importantly, these differences in adaptation speed emerge as the result of competition, which alters population sizes and colonization success. By demonstrating how dispersal and adaptation each independently and interactively contribute to the maintenance of biodiversity, we provide a framework that links the theories of spatial insurance, evolutionary rescue, and monopolization. This highlights the expectation that the maintenance of biodiversity in changing environments depends jointly on rates of dispersal and adaptation, and, critically, the interaction between these processes.Significance StatementSpecies can persist when the environment changes by shifting their ranges through dispersal or by adapting to the new conditions that they experience. Thus, we might expect that dispersal and adaptation in combination would increase persistence. Using a simulation model, we show that this may not be the case. Instead, species competition causes dispersal and adaptation to have conflicting contributions to biodiversity maintenance. Dispersal and adaptation each independently increase biodiversity maintenance. But when species both disperse and evolve, faster adapting species persist in their current ranges, preventing others from shifting their ranges to track environmental change. These findings highlight the need to consider ecological and evolutionary processes together, or we risk underestimating how global change will impact biodiversity.
Inferring Processes of Coevolutionary Diversification in a Community of Panamanian Strangler Figs and Associated Pollinating Wasps
Authors: Satler Jordan D. , Herre Edward Allen , Jandér K. Charlotte , Eaton Deren A. R. , Machado Carlos A. , Heath Tracy A. , Nason John D. 
Published: December 2018

1AbstractThe fig and pollinator wasp obligate mutualism is diverse (~750 described species), ecologically important, and ancient (~80-90 Ma), providing model systems for generating and testing many questions in evolution and ecology. Once thought to be a prime example of strict one-to-one cospeciation, current thinking suggests that genera of pollinator wasps co-evolve with corresponding subsections of figs, but the degree to which cospeciation or other processes contributes to the association at finer scales is unclear. Here we use genome-wide sequence data from a community of Panamanian strangler figs (Ficus subgenus Urostigma, section Americana) and associated fig wasp pollinators (Pegoscapus spp.) to infer the process of coevolutionary diversification in this obligate mutualism. Using a model-based approach adapted from the study of gene family evolution, our results indicate pervasive and ongoing host switching of pollinator wasps at this fine phylogenetic and regional scale. Although the model estimates a modest amount of cospeciation, simulations reveal this signal to be consistent with levels of co-association expected under a model of free host switching. Our findings provide an outline for testing how ecological and evolutionary processes can be modeled to evaluate the history of association of interacting lineages in a phylogenetic framework.
Predictive validity of effective shunt fraction in critically ill patients
Authors: Chang Emma M , Bretherick Andrew , Drummond Gordon B , Baillie J Kenneth 
Published: December 2018

AbstractAccurate measurement of pulmonary oxygenation is important for classification of disease severity and quantification of outcomes in clinical studies. We compared predictive validity of established tension-based methods with two new measures of shunt fraction: (1) a non-invasive effective shunt (ES); and (2) inferred values from an integrated mathematical model of gas exchange (DB). Median absolute error (MAE) values for the four measures considered were: alveolar-arterial difference, 7.30kPa; PaO2/FIO2 ratio, 2.41kPa; DB, 2.13kPa; ES: 1.88kPa. ES performed significantly better than other measures (p<10−10 in all comparisons). While the simplicity of P/F is suitable for routine use, the superior predictive validity of ES should make this measure the preferred choice where physiological accuracy is important, such as for use as surrogate outcome in clinical research.
GeTallele: a method for integrative analysis and visualization of DNA and RNA allele frequencies
Authors: Słowiński Piotr , Li Muzi , Restrepo Paula , Alomran Nawaf , Spurr Liam F. , Miller Christian , Tsaneva-Atanasova Krasimira , Horvath Anelia 
Published: December 2018

AbstractBackgroundAsymmetric allele expression typically indicates functional and/or structural features associated with the underlying genetic variants. When integrated, RNA and DNA allele frequencies can reveal patterns characteristic of a wide-range of biological traits, including ploidy changes, genome admixture, allele-specific expression and gene-dosage transcriptional response.ResultsTo assess RNA and DNA allele frequencies from matched sequencing datasets, we introduce a method for generating model distributions of variant allele frequencies (VAF) with a given variant read probability. In contrast to other methods, based on whole sequences or single SNV, proposed methodology uses continuous multi-SNV genomic regions. The methodology is implemented in a GeTallele toolbox that provides a suite of functions for integrative analysis, statistical assessment and visualization ofGenome andTranscriptomeallelefrequencies. Using model VAF probabilities, GeTallele allows estimation and comparison of variant read probabilities (VAF distributions) in a sequencing dataset. We demonstrate this functionality across cancer DNA and RNA sequencing datasets.ConclusionBased on our evaluation, variant read probabilities can serve as a dependable indicator to assess gene and chromosomal allele asymmetries and to aid calls of genomic events in matched sequencing RNA and DNA datasets.ContactP.M.Slowinski@exeter.ac.uk
Uncovering the role of admixture in disease and drug response: Association of hepatocyte gene expression and DNA methylation with African Ancestry in African Americans
Authors: Park CS , De T , Xu Y , Zhong Y , Gamazon ER , Smithberger E , Alarcon C , Perera MA 
Published: December 2018

ABSTRACTBackgroundAfrican Americans (AAs) are an admixed population with portions of their genome derived from West Africans and Europeans. In AAs, the proportion of West African ancestry (WAA) can vary widely and may explain the genetic drivers of disease, specifically those that disproportionately affect this understudied population. To examine the relationship between the proportion of WAA and gene expression, we used high dimensional data obtained from AA primary hepatocytes, a tissue important in disease and drug response.MethodsRNA sequencing (Illumina HiSeq Platform) was conducted on 60 AA-derived primary hepatocytes, with methylation profiling (Illumina MethylationEPIC BeadChip) of 44 overlapping samples. WAA for each sample was calculated using fastSTRUCTURE and correlated to both gene expression and DNA methylation. The GTEx consortium (n = 15) was used for replication and a second cohort (n = 206) was using used for validation using differential gene expression between AAs and European-Americans.ResultsWe identified 131 genes associated with WAA (FDR< 0.1), of which 28 gene expression traits were replicated (FDR<0.1) and enriched in angiogenesis and inflammatory pathways (FDR<0.1). These 28 replicated gene expression traits represented 257 GWAS catalog phenotypes. Among the PharmGKB pharmacogenes, VDR, PTGIS, ALDH1A1, CYP2C19 and P2RY1 were associated with WAA (p < 0.05) with replication of CYP2C19 and VDR in GTEx. Association of DNA methylation with WAA identified 1037 differentially methylated regions (FDR<0.05), with hypomethylated genes enriched in drug response pathways. Overlapping of differentially methylated regions with the 131 significantly correlated gene expression traits identified 5 genes with concordant directions of effect: COL26A1, HIC1, MKNK2, RNF135, SNAI1 and TRIM39.ConclusionsWe conclude that WAA contributes to variability in hepatic gene expression and DNA methylation with identified genes indicative of diseases disproportionately affecting AAs. Specifically, WAA-associated genes were linked to previously identified loci in cardiovascular disease (PTGIS, PLAT), renal disease (APOL1) and drug response (CYP2C19).
Predicting Methylation from Sequence and Gene Expression Using Deep Learning with Attention
Authors: Levy-Jurgenson Alona , Tekpli Xavier , Kristensen Vessela N. , Yakhini Zohar 
Published: December 2018

AbstractDNA methylation has been extensively linked to alterations in gene expression, playing a key role in the manifestation of multiple diseases, most notably cancer. For this reason, researchers have long been measuring DNA methylation in living organisms. The relationship between methylation and expression, and between methylation in different genomic regions is of great theoretical interest from a molecular biology perspective. Therefore, several models have been suggested to support the prediction of methylation status in samples. These models, however, have two main limitations: (a) they heavily rely on partially measured methylation levels as input, somewhat defeating the object as one is required to collect measurements from the sample of interest before applying the model; and (b) they are largely based on human mediated feature engineering, thus preventing the model from unveiling its own representations. To address these limitations we used deep learning, with an attention mechanism, to produce a general model that predicts DNA methylation for a given sample in any CpG position based solely on the sample's gene expression profile and the sequence surrounding the CpG.We show that our model is capable of generalizing to a completely separate test set of CpG positions and subjects. Depending on gene-CpG proximity conditions, our model can attain a Spearman correlation of up to 0.8 and MAE of 0.14 for thousands of CpG sites in the test data. We also identify and analyze several motifs and genes that our model suggests may be linked to methylation activity, such as Nodal and Hand1. Moreover, our approach, and most notably the use of attention mechanisms, offers a novel framework with which to extract valuable insights from gene expression data when combined with sequence information.The code and trained models are available at:https://github.com/YakhiniGroup/Methylation
Proteomic and Genomic Signatures of Repeat-instability in Cancer and Adjacent Normal Tissues
Authors: Persi Erez , Prandi Davide , Wolf Yuri I. , Pozniak Yair , Barbieri Christopher , Gasperini Paola , Beltran Himisha , Faltas Bishoy M. , Rubin Mark A. , Geiger Tamar , Koonin Eugene V. , Demichelis Francesca , Horn David 
Published: December 2018

SummaryRepetitive sequences are hotspots of evolution at multiple levels. However, due to technical difficulties involved in their assembly and analysis, the role of repeats in tumor evolution is poorly understood. We developed a rigorous motif-based methodology to quantify variations in the repeat content of proteomes and genomes, directly from proteomic and genomic raw sequence data, and applied it to analyze a wide range of tumors and normal tissues. We identify high similarity between the repeat-instability in tumors and their patient-matched normal tissues, but also tumor-specific signatures, both in protein expression and in the genome, that strongly correlate with cancer progression and robustly predict the tumorigenic state. In a patient, the hierarchy of genomic repeat instability signatures accurately reconstructs tumor evolution, with primary tumors differentiated from metastases. We find an inverse relationship between repeat-instability and point mutation load, within and across patients, and independently of other somatic aberrations. Thus, repeat-instability is a distinct, transient and compensatory adaptive mechanism in tumor evolution.
Novel algorithms for efficient subsequence searching and mapping in nanopore raw signals towards targeted sequencing
Authors: Han Renmin , Wang Sheng , Gao Xin 
Published: December 2018

ABSTRACTGenome diagnostics have gradually become a prevailing routine for human healthcare. With the advances in understanding the causal genes for many human diseases, targeted sequencing provides a rapid, cost-efficient and focused option for clinical applications, such as SNP detection and haplotype classification, in a specific genomic region. Although nanopore sequencing offers a perfect tool for targeted sequencing because of its mobility, PCR-freeness, and long read properties, it poses a challenging computational problem of how to efficiently and accurately search and map genomic subsequences of interest in a pool of nanopore reads (or raw signals). Due to its relatively low sequencing accuracy, there is no reliable solution to this problem, especially at low sequencing coverage.Here, we propose a brand new signal-based subsequence inquiry pipeline as well as two novel algorithms to tackle this problem. The proposed algorithms follow the principle of subsequence dynamic time warping and directly operate on the electrical current signals, without loss of information in base-calling. Therefore, the proposed algorithms can serve as a tool for sequence inquiry in targeted sequencing. Two novel criteria are offered for the consequent signal quality analysis and data classification. Comprehensive experiments on real-world nanopore datasets show the efficiency and effectiveness of the proposed algorithms. We further demonstrate the potential applications of the proposed algorithms in two typical tasks in nanopore-based targeted sequencing: SNP detection under low sequencing coverage, and haplotype classification under low sequencing accuracy.
L-Norvaline, a New Therapeutic Agent against Alzheimer’s disease
Authors: Polis Baruh , Srikanth Kolluru D , Gurevich Vyacheslav , Gil-Henn Hava , Samson Abraham O. 
Published: December 2018

AbstractAlzheimer’s disease (AD) is a slowly progressive neurodegenerative disorder with an insidious onset. The disease is characterized by cognitive impairment and a distinct pathology with neuritic plaques and neurofibrillary tangles.Growing evidence highlights the role of arginase activity in the manifestation of AD. Upregulation of arginase was shown to contribute to endothelial dysfunction, atherosclerosis, diabetes, and neurodegeneration. Regulation of arginase activity appears to be a promising approach for interfering with the pathogenesis of AD and other metabolic disorders. Therefore, the enzyme represents a novel therapeutic target.Here, we administer an arginase inhibitor L-norvaline to a mouse model of AD. Then, we evaluate the neuroprotective effect of L-norvaline using immunohistochemistry, proteomics, and quantitative polymerase chain reaction assays. Finally, we identify the biological pathways activated by the treatment.Remarkably, we find that L-norvaline treatment reverses the cognitive decline in AD mice. We show the treatment is neuroprotective as indicated by reduced beta-amyloidosis, alleviated microgliosis, and TNFα transcription levels. Moreover, elevated levels of neuroplasticity related protein PSD-95 were detected in the hippocampi of mice treated with L-norvaline. Furthermore, we disclose several biological pathways, which are involved in cell survival and neuroplasticity and are activated by the treatment.Through these modes of action, L-norvaline has the potential to improve the symptoms of AD and even interfere with its pathogenesis. As such, L-norvaline is a promising neuroprotective molecule that might be tailored for the treatment of a range of neurodegenerative disorders.
A practical method for efficient and optimal production of selenomethionine-labeled recombinant protein complexes in the insect cells
Authors: Wenzel Sabine , Imasaki Tsuyoshi , Takagi Yuichiro 
Published: December 2018

AbstractThe use of Selenomethionine (SeMet) incorporated protein crystals for single or multiwavelength anomalous diffraction (SAD or MAD) to facilitate phasing has become almost synonymous with modern X-ray crystallography. The anomalous signals from SeMets can be used for phasing as well as sequence markers for subsequent model building. The production of large quantities of SeMet incorporated recombinant proteins is relatively straightforward when expressed inE. coli. In contrast, production of SeMet substituted recombinant proteins expressed in the insect cells is not as robust due to the toxicity of SeMet in eukaryotic systems. Previous protocols for SeMet-incorporation in the insect cells are laborious, and more suited for secreted proteins. In addition, these protocols have generally not addressed the SeMet toxicity issue, and typically result in low recovery of the labeled proteins. Here we report that SeMet toxicity can be circumvented by fully infecting insect cells with baculovirus. Quantitatively controlling infection levels using our Titer Estimation of Quality Control (TEQC) method allows for incorporation of substantial amounts of SeMet, resulting in an efficient and optimal production of labeled recombinant protein complexes. With the method described here, we were able to consistently reach incorporation levels of about 75% and protein yield of 60-90% compared to native protein expression.
Highly specific enrichment of rare nucleic acids usingThermus thermophilusArgonaute
Authors: Song Jinzhao , Hegge Jorrit W. , Mauk Michael G. , Bhagwat Neha , Till Jacob E. , Azink Lotte T. , Peng Jing , Sen Moen , Chen Junman , Mays Jazmine , Carpenter Erica , van der Oost John , Bau Haim H. 
Published: December 2018

ABSTRACTCharacterization of disease-associated, cell-free nucleic acids (liquid biopsy) provides a powerful, minimally-invasive means for early detection, genotyping, and personalized therapy; but is challenged by alleles of interest differing by single nucleotide from and residing among large abundance of wild-type alleles. We describe a new multiplexed enrichment assay, dubbed NAVIGATER, that utilizes short nucleic acid-guided endonucleases Argonaute (Ago), derived from the bacteriumThermus thermophilus(TtAgo), to specifically cleave complementary DNA and RNA while sparing alleles having single nucleotide mismatches with the guides. NAVIGATER greatly increases the fractions of rare alleles of interest in samples and enhances sensitivity of downstream procedures such ddPCR, sequencing, and clamped enzymatic amplification. We demonstrate60-foldenrichment ofKRASG12D in blood samples from pancreatic cancer patients and detection ofKRAS,EGFR, andBRAFmutants with XNA-PCR at 0.01% fraction.
Mechanical Stretch Kills Transformed Cancer Cells
Authors: Tijore Ajay , Yao Mingxi , Wang Yu-Hsiu , Nematbakhsh Yasaman , Hariharan Anushya , Teck Lim Chwee , Sheetz Michael 
Published: December 2018

AbstractTransformed cancer cells differ from normal cells in several important features like anchorage independence, Warburg effect and mechanosensing. Consequently, transformed cancer cells develop an anaplastic morphology and respond aberrantly to external mechanical forces. Consistent with altered mechano-responsiveness, here we show that transformed cancer cells from many different tissues have reduced growth and become apoptotic upon cyclic stretch as do normal cells after the transformation. When matrix rigidity sensing is restored in transformed cancer cells, they survive and grow faster on soft surface upon cyclic stretch like normal cells but undergo anoikis without stretch by activation of death associated protein kinase1 (DAPK1). In contrast, stretch-dependent apoptosis (mechanoptosis) of transformed cells is driven by stretch-mediated calcium influx and calcium-dependent calpain 2 protease activation on both collagen and fibronectin matrices. Further, mechanosensitive calcium channel, Piezo1 is needed for mechanoptosis. Thus, cyclic stretching of transformed cells from different tissues activates apoptosis, whereas similar stretching of normal cells stimulates growth.
Cross-talk between Hippo and Wnt signalling pathways in intestinal crypts: insights from an agent-based model
Authors: Ward Daniel , Fletcher Alexander G. , Homer Martin , Marucci Lucia 
Published: December 2018

AbstractIntestinal crypts are responsible for the total cell renewal of the lining of the intestines; this turnover is governed by the interplay between signalling pathways and the cell cycle. The role of Wnt signalling in governing cell proliferation and differentiation in the intestinal crypt has been extensively studied, with increased signalling found towards the lower regions of the crypt. Recent studies have shown that the Wnt signalling gradient found within the crypt may arise as a result of division-based spreading from a Wnt ‘reservoir’ at the crypt base. The discovery of the Hippo pathway’s involvement in maintaining crypt homeostasis is more recent; a mechanistic understanding of Hippo pathway dynamics, and its possible cross-talk with the Wnt pathway, remains lacking. To explore how the interplay between these pathways may control crypt homeostasis, we extended an ordinary differential equation model of the Wnt signalling to include a phenomenological description of Hippo signalling in single cells, and then coupled it to a cell-based description of cell movement, proliferation and contact inhibition in agent-based simulations. Furthermore, we compared an imposed Wnt gradient with a division-based Wnt gradient model. Our results suggest that Hippo signalling affects the Wnt pathway by reducing the presence of free cytoplasmic β-catenin, causing cell cycle arrest. We also show that a division-based spreading of Wnt can form a Wnt gradient, resulting in proliferative dynamics comparable to imposed-gradient models. Finally, a simulated APC double mutant, with misregulated Wnt and Hippo signalling activity, is predicted to cause monoclonal conversion of the crypt.