Search results for " Genomica"

showing 10 items of 31 documents

Covariation and phenotypic integration in chemical communication displays: biosynthetic constraints and eco-evolutionary implications

2018

Chemical communication is ubiquitous. The identification of conserved structural elements in visual and acoustic communication is well established, but comparable information on chemical communication displays (CCDs) is lacking. We assessed the phenotypic integration of CCDs in a meta‐analysis to characterize patterns of covariation in CCDs and identified functional or biosynthetically constrained modules. Poorly integrated plant CCDs (i.e. low covariation between scent compounds) support the notion that plants often utilize one or few key compounds to repel antagonists or to attract pollinators and enemies of herbivores. Animal CCDs (mostly insect pheromones) were usually more integrated t…

0106 biological sciences0301 basic medicineEco evolutionaryanalysisPhysiologyPlant ScienceAnimal Breeding and GenomicsBiologyfloral scentsChemical communicationFloral scentsphenotypic integration010603 evolutionary biology01 natural sciencesChemical communication03 medical and health sciencesPhenotypic integrationbiosynthetic constraintsFokkerij en Genomicavegetative scentsLaboratory of Entomologycorrelation networkEcologyOrganic Chemistrychemical communicationPhenotypic integrationInsect pheromonesPE&RCLaboratorium voor Entomologiecorrelation network analysisOrganische ChemieCorrelation network analysisBiosynthetic constraints030104 developmental biologyEvolutionary biologyinternationalFloral scentIdentification (biology)EPSVegetative scentsNew Phytologist
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Low but contrasting neutral genetic differentiation shaped by winter temperature in European great tits.

2016

Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species - the great tit Parus major - at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), u…

0106 biological sciences0301 basic medicineSELECTIONZOOLOGIA[SDV]Life Sciences [q-bio]FLOWSOFTWARE01 natural sciencesmicrosatellitesBehavioral EcologyLOCAL ADAPTATIONParus majorComputingMilieux_MISCELLANEOUSeducation.field_of_studyLatitudeCLIMATE-CHANGEEcologyIsolation-by-distancelatitudePE&RCGedragsecologieWILD BIRD POPULATIONinternationalGenetic structureGene poolwinter severityPopulationAnimal Breeding and GenomicsBiologyPARUS-MAJOR010603 evolutionary biology03 medical and health sciencesPopulation genetic structureFokkerij en GenomicaMicrosatelliteseducationBiologyEcology Evolution Behavior and SystematicsLocal adaptationIsolation by distanceisolation-by-distance[SDV.GEN]Life Sciences [q-bio]/GeneticsGenetic diversityF-statisticsGenetic divergenceWinter severity030104 developmental biologyPARTIAL MIGRATIONF-statisticsNATAL DISPERSALRE-IMPLEMENTATIONWIAS570 Life sciences; biologyta1181Biological Journal of the Linnean Society
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The preference and costs of sleeping under light at night in forest and urban great tits

2019

Artificial light at night (ALAN) is an increasing phenomenon associated with worldwide urbanization. In birds, broad-spectrum white ALAN can have disruptive effects on activity patterns, metabolism, stress response and immune function. There has been growing research on whether the use of alternative light spectra can reduce these negative effects, but surprisingly, there has been no study to determine which light spectrum birds prefer. To test such a preference, we gave urban and forest great tits (Parus major) the choice where to roost using pairwise combinations of darkness, white light or green dim light at night (1.5 lux). Birds preferred to sleep under artificial light instead of dar…

0106 biological sciencesMaleLight pollutionForestsartificial light at night01 natural sciencesoxalic acidSleep debtOxalic acidParus majorPasseriformesGeneral Environmental Sciencevuorokausirytmi0303 health sciencesbiologyBehavior Animallight pollutionGeneral MedicinetalitiainenPE&RCSleep in non-human animalsPreferenceCircadian RhythmLight pollutioninternationalMAMMALSDarknessFemalekaupungistuminenGeneral Agricultural and Biological SciencesBEHAVIORenergiankulutus (aineenvaihdunta)ZoologyurbanizationAnimal Breeding and Genomics010603 evolutionary biologyGeneral Biochemistry Genetics and Molecular Biologyuni (lepotila)03 medical and health sciencesBiointeractions and Plant HealthAnimalsCOLORBehaviourFokkerij en GenomicaCircadian rhythmsleepPHYSIOLOGYARTIFICIAL-LIGHTLighting030304 developmental biologyParusWhite (horse)BIRDSGeneral Immunology and MicrobiologyINTENSITYMEMORYUrbanizationPERFORMANCEbiology.organism_classificationvalosaasteEnergy MetabolismEnvironmental PollutionSleepArtificial light at nightALTERS
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Next-generation biological control

2020

Biological control is widely successful at controlling pests, but effective biocontrol agents are now more difficult to import from countries of origin due to more restrictive international trade laws (the Nagoya Protocol). Coupled with increasing demand, the efficacy of existing and new biocontrol agents needs to be improved with genetic and genomic approaches. Although they have been underutilised in the past, application of genetic and genomic techniques is becoming more feasible from both technological and economic perspectives. We review current methods and provide a framework for using them. First, it is necessary to identify which biocontrol trait to select and in what direction. Nex…

0106 biological sciencesProteomicsH10 Pests of plantsInternationalityComputer science[SDV]Life Sciences [q-bio]Laboratory of VirologySequence assemblybiological controlmicrobiome01 natural sciencesGenome editinggeneticsNagoya ProtocolLaboratory of EntomologyCYTOPLASMIC INCOMPATIBILITY2. Zero hunger0303 health sciencesQUANTITATIVE TRAIT LOCICommercefood and beveragesCONTROL AGENTSPE&RCBiosystematiekNASONIA-VITRIPENNISGUT CONTENT-ANALYSIS[SDE]Environmental SciencesTraitinsect breedingAXYRIDIS COLEOPTERA-COCCINELLIDAEOriginal ArticleLaboratory of GeneticsLIFE-HISTORY TRAITSGeneral Agricultural and Biological SciencesGenomicsContext (language use)Computational biology[SDV.BID]Life Sciences [q-bio]/Biodiversityartificial selectionQuantitative trait locusAnimal Breeding and GenomicsLaboratorium voor Erfelijkheidsleer010603 evolutionary biologyGeneral Biochemistry Genetics and Molecular BiologyLaboratorium voor Virologiemodelling03 medical and health sciencesgenomics[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyFokkerij en GenomicaPARASITOID WASPSelection (genetic algorithm)modelling.030304 developmental biologySEX DETERMINATIONOriginal ArticlesLaboratorium voor EntomologieWIASgenome assemblyBiosystematicsEPSartificial selection biological control genetics genome assembly genomics insect breeding microbiome modellingBiological Reviews
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Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes

2020

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of …

0301 basic medicineGene ExpressionGene Expression Regulation/drug effectsPathology and Laboratory MedicineConvolutional neural networkTOXICITYMachine LearningVoeding Metabolisme en GenomicaTime Measurement0302 clinical medicineGene expressionMedicine and Health SciencesMeasurementClinical Trials as TopicMultidisciplinaryArtificial neural networkPharmaceuticsQRMetabolism and GenomicsTOXICOGENOMICS030220 oncology & carcinogenesisMetabolisme en GenomicaMedicineEngineering and TechnologyNutrition Metabolism and GenomicsHepatocytes/drug effectsAlgorithmsResearch ArticleComputer and Information SciencesClinical Trials as Topic/statistics & numerical dataNeural NetworksGenetic ToxicologyTOXICOLOGYSciencePredictive ToxicologyComputational biologyBiologyComputer03 medical and health sciencesDose Prediction MethodsDeep LearningVoedingArtificial IntelligenceIn vivoGeneticsLife ScienceAnimalsHumansGeneNutritionbusiness.industryDeep learningBiology and Life SciencesGold standard (test)REPRESENTATIONSRats030104 developmental biologyGene Expression RegulationHepatocytesArtificial intelligenceNeural Networks ComputerToxicogenomicsbusinessNeuroscience
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Multi-level integration of environmentally perturbed internal phenotypes reveals key points of connectivity between them

2017

The genotype and external phenotype of organisms are linked by so-called internal phenotypes which are influenced by environmental conditions. In this study, we used five existing -omics datasets representing five different layers of internal phenotypes, which were simultaneously measured in dietarily perturbed mice. We performed 10 pair-wise correlation analyses verified with a null model built from randomized data. Subsequently, the inferred networks were merged and literature mined for co-occurrences of identified linked nodes. Densely connected internal phenotypes emerged. Forty-five nodes have links with all other data-types and we denote them "connectivity hubs." In literature, we fou…

0301 basic medicineProteomicsPhysiologySystems biologyComputational biologyBiologyProteomicslcsh:PhysiologyCorrelation03 medical and health sciences0302 clinical medicineGenotype-phenotype distinctionGastrointestinal tractPhysiology (medical)GenotypeMetabolomicsSystems and Synthetic BiologyHost-Microbe InteractomicsFokkerij & GenomicaTranscriptomicsOriginal ResearchVLAGHost Pathogen Interaction & DiagnosticsGeneticsSysteem en Synthetische BiologieInternal phenotypelcsh:QP1-981Null modelMicrobiotaBacteriologieBacteriologyBacteriology Host Pathogen Interaction & DiagnosticsPhenotypeHost Pathogen Interactie & Diagnostiek030104 developmental biologyBacteriologie Host Pathogen Interactie & DiagnostiekKey (cryptography)Data integrationSystems biology030217 neurology & neurosurgeryAnimal Breeding & Genomics
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Ancient pigs reveal a near-complete genomic turnover following their introduction to Europe

2019

International audience; Archaeological evidence indicates that pig domestication had begun by ∼10,500 y before the present (BP) in the Near East, and mitochondrial DNA (mtDNA) suggests that pigs arrived in Europe alongside farmers ∼8,500 y BP. A few thousand years after the introduction of Near Eastern pigs into Europe, however, their characteristic mtDNA signature disappeared and was replaced by haplotypes associated with European wild boars. This turnover could be accounted for by substantial gene flow from local Euro-pean wild boars, although it is also possible that European wild boars were domesticated independently without any genetic contribution from the Near East. To test these hyp…

0301 basic medicineSwine[SHS.ANTHRO-BIO]Humanities and Social Sciences/Biological anthropologySkin Pigmentation[SHS]Humanities and Social SciencesGene flowDomesticationddc:590BREEDSDOMESTIC PIGS/dk/atira/pure/subjectarea/asjc/1000HISTORY0601 history and archaeologyNeolithicHistory AncientPhylogenyMultidisciplinary060102 archaeologyINTROGRESSIONEurope ; pigs ; domestication ; genomesWILD06 humanities and the artsArchaeological evidenceGene flowEuropeSPREADCoatMitochondrial DNAEvolutionZoology930Locus (genetics)BiologyAnimal Breeding and GenomicsDNA MitochondrialMiddle East03 medical and health sciencesAnimalsFokkerij en GenomicaDNA AncientGeneralDomesticationddc:930HaplotypeDNA900 Geschichte und Geografie::930 Geschichte des Altertums (bis ca. 499) Archäologie::930 Geschichte des Altertums bis ca. 499 ArchäologieLONGSIZE030104 developmental biologydomestication evolution gene flow NeolithicWIAS
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A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data

2019

Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial …

Adipose Tissue/metabolismDIETARY FATTY-ACIDSmedicine.medical_treatmentFatty Acids NonesterifiedBiochemistry0302 clinical medicineEndocrinologyModelsInsulinGlucose/metabolismBiology (General)Organic CompoundsFatty AcidsChemical ReactionsPostprandial Period/physiologyPostprandial PeriodLipidsPostprandialBloodComputational Theory and MathematicsAdipose TissueModeling and SimulationPhysical Sciencesmedicine.medical_specialtyQH301-705.5LipolysisCarbohydratesLIPOPROTEIN-LIPASECarbohydrate metabolism03 medical and health sciencesNEFASDG 3 - Good Health and Well-beingGeneticsLipolysisHumansComputer SimulationMolecular BiologyEcology Evolution Behavior and SystematicsBlood Glucose/metabolismArteriovenous AnastomosisChemical CompoundsBiology and Life SciencesComputational BiologyComputational Biology/methodsmedicine.diseaseLipid MetabolismBiologicalHormonesLipid Metabolism/physiology030104 developmental biologyEndocrinologyBiological TissueGlucoseMOBILIZATION030217 neurology & neurosurgery0301 basic medicineGlycerolBlood GlucosePhysiologyPATHOGENESISAdipose tissueLipids/physiologySDG 3 – Goede gezondheid en welzijnVoeding Metabolisme en GenomicaGlucose MetabolismIsotopesMedicine and Health SciencesMetabolitesINSULIN-RESISTANCEEcologyChemistryHydrolysisMonomersMonosaccharidesArteriovenous Anastomosis/metabolismMetabolism and GenomicsBody FluidsChemistryFatty Acids/metabolismMetabolisme en GenomicaCarbohydrate MetabolismNutrition Metabolism and GenomicsFatty Acids Nonesterified/metabolismAnatomyResearch ArticleInsulin/metabolismINHIBITIONWEIGHT-LOSSModels BiologicalBlood PlasmaMECHANISMSCellular and Molecular NeuroscienceInsulin resistanceVoedingInternal medicinemedicineLife ScienceNonesterified/metabolismNutritionDiabetic EndocrinologyInsulinOrganic ChemistryLipid metabolismECTOPIC FATPolymer ChemistryMetabolism
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Glycogen synthase 2 is a novel target gene of peroxisome proliferator-activated receptors.

2007

International audience; Glycogen synthase 2 (Gys-2) is the ratelimiting enzyme in the storage of glycogen in liver and adipose tissue, yet little is known about regulation of Gys-2 transcription. The peroxisome proliferator-activated receptors (PPARs) are transcription factors involved in the regulation of lipid and glucose metabolism and might be hypothesized to govern glycogen synthesis as well. Here, we show that Gys-2 is a direct target gene of PPARalpha, PPARbeta/delta and PPARgamma. Expression of Gys-2 is significantly reduced in adipose tissue of PPARalpha-/-, PPARbeta/delta-/- and PPARgamma+/- mice. Furthermore, synthetic PPARbeta/delta, and gamma agonists markedly up-regulate Gys-2…

Animals; Chromatin/ultrastructure; DNA Primers; Gene Expression Regulation Enzymologic; Glycogen Synthase/genetics; Hepatocytes/enzymology; Hepatocytes/physiology; Mice; Mice Knockout; Peroxisome Proliferator-Activated Receptors/deficiency; Peroxisome Proliferator-Activated Receptors/genetics; Polymerase Chain Reaction; RNA/genetics; RNA/isolation & purification; Rats; Transcription GeneticTranscription GeneticPeroxisome proliferator-activated receptorMESH : HepatocytesPPREPolymerase Chain Reactionadipose-tissuePPARMESH: HepatocytesMice0302 clinical medicineMESH: Animals610 Medicine &amp; healthchemistry.chemical_classificationRegulation of gene expression0303 health sciencesGlycogenglycogen-synthaseChromatinGlycogen Synthase030220 oncology & carcinogenesisMESH : DNA PrimersmicroarrayMESH: DNA Primersmedicine.medical_specialtyHealth aging / healthy living [IGMD 5]fatty-acid oxidationliverGene Expression Regulation EnzymologicMESH: Chromatin03 medical and health sciencesskeletal-muscleGlycogen synthaseMolecular Biology[ SDV.BBM ] Life Sciences [q-bio]/Biochemistry Molecular BiologyHNF4αVLAGPharmacologybeta/deltaMESH: Polymerase Chain Reactionresponse elementsMESH : Peroxisome Proliferator-Activated ReceptorsEndocrinologychemistryMicrobial pathogenesis and host defense [UMCN 4.1]Response elementPeroxisome Proliferator-Activated ReceptorsAdipose tissueMESH: Peroxisome Proliferator-Activated Receptorsin-vivoMESH: Mice KnockoutTransactivationchemistry.chemical_compoundVoeding Metabolisme en GenomicaMESH : RNAMESH : Polymerase Chain ReactionMice KnockoutMESH : ChromatinMESH : RatsMESH: Gene Expression Regulation EnzymologicMetabolism and Genomicsadipose tissueMetabolisme en GenomicaMolecular MedicineNutrition Metabolism and GenomicsMESH : Glycogen SynthaseResearch ArticleMESH: Ratsglycogen synthase 2610 Medicine & healthBiologyMESH : Gene Expression Regulation EnzymologicCellular and Molecular NeuroscienceVoedingMESH: RNAInternal medicineMESH : MicemedicineAnimals[SDV.BBM]Life Sciences [q-bio]/Biochemistry Molecular BiologyTranscription factorMESH: Micealpha ppar-alpha030304 developmental biologyNutritionDNA PrimersMESH: Glycogen SynthaseMESH: Transcription GeneticMESH : Transcription GeneticCell BiologyRatsgene transcriptionbiology.proteinHepatocytesRNAMESH : Mice KnockoutgammaMESH : Animalsmetabolism
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Triglyceride-rich lipoproteins and their remnants: metabolic insights, role in atherosclerotic cardiovascular disease, and emerging therapeutic strat…

2021

Abstract Recent advances in human genetics, together with a large body of epidemiologic, preclinical, and clinical trial results, provide strong support for a causal association between triglycerides (TG), TG-rich lipoproteins (TRL), and TRL remnants, and increased risk of myocardial infarction, ischaemic stroke, and aortic valve stenosis. These data also indicate that TRL and their remnants may contribute significantly to residual cardiovascular risk in patients on optimized low-density lipoprotein (LDL)-lowering therapy. This statement critically appraises current understanding of the structure, function, and metabolism of TRL, and their pathophysiological role in atherosclerotic cardiova…

CHOLESTERYL ESTER TRANSFERTO-MODERATE HYPERTRIGLYCERIDEMIALipoprotein remnants030204 cardiovascular system & hematologyBioinformaticsResidual riskBrain Ischemiachemistry.chemical_compoundVoeding Metabolisme en Genomica0302 clinical medicineIschaemic strokeAcademicSubjects/MED00200Myocardial infarctionLOW-GRADE INFLAMMATIONALL-CAUSE MORTALITY[SDV.MHEP.EM] Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism0303 health sciencesAtherosclerotic cardiovascular diseasedigestive oral and skin physiology[SDV.MHEP.EM]Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolismCardiovascular diseaseMetabolism and Genomics3. Good healthStrokeLOW-DENSITY LIPOPROTEINSCardiovascular DiseasesMetabolisme en GenomicaCORONARY-ARTERY-DISEASENutrition Metabolism and GenomicsCardiology and Cardiovascular MedicineB-CONTAINING LIPOPROTEINSLipoproteinsTriglyceride-rich lipoproteinsHEART-DISEASE03 medical and health sciencesSpecial ArticleVoedingmedicineHumansHOMOZYGOUS FAMILIAL HYPERCHOLESTEROLEMIATriglycerides030304 developmental biologyNutritionVLAGTriglyceridebusiness.industryAPO-Bmedicine.diseaseAtherosclerosisResidual riskIncreased riskchemistry3121 General medicine internal medicine and other clinical medicineEuropean atherosclerosis societybusinessLipoprotein
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