2024
Dysregulation of miRNA expression and excitation in MEF2C autism patient hiPSC-neurons and cerebral organoids
Trudler D, Ghatak S, Bula M, Parker J, Talantova M, Luevanos M, Labra S, Grabauskas T, Noveral S, Teranaka M, Schahrer E, Dolatabadi N, Bakker C, Lopez K, Sultan A, Patel P, Chan A, Choi Y, Kawaguchi R, Stankiewicz P, Garcia-Bassets I, Kozbial P, Rosenfeld M, Nakanishi N, Geschwind D, Chan S, Lin W, Schork N, Ambasudhan R, Lipton S. Dysregulation of miRNA expression and excitation in MEF2C autism patient hiPSC-neurons and cerebral organoids. Molecular Psychiatry 2024, 30: 1479-1496. PMID: 39349966, PMCID: PMC11919750, DOI: 10.1038/s41380-024-02761-9.Peer-Reviewed Original ResearchMEF2C haploinsufficiency syndromeLoss-of-function mutationsCerebral organoidsHaploinsufficiency syndromeReceptor antagonistHiPSC-neuronsDecreased neurogenesisSevere formCerebrocortical neuronsAnimal studiesExtrasynaptic activationMEF2CAbnormal phenotypesNeurodevelopmentNeuronsDeficitsOrganoidsTranscription factorsMutationsNitroSynapsinGene networksDysregulation of miRNA expressionCRISPR-based dissection of microRNA-23a ~ 27a ~ 24-2 cluster functionality in hepatocellular carcinoma
Cui M, Liu Z, Wang S, Bae S, Guo H, Zhou J, Liu R, Wang L. CRISPR-based dissection of microRNA-23a ~ 27a ~ 24-2 cluster functionality in hepatocellular carcinoma. Oncogene 2024, 43: 2708-2721. PMID: 39112518, PMCID: PMC11364504, DOI: 10.1038/s41388-024-03115-z.Peer-Reviewed Original ResearchConceptsMiR-23aMiR-27aCRISPR interferenceCRISPR activationHigh-throughput RNA-seqCell migrationCDK1/cyclin B activityReduced cell growth in vitroMiRNA target predictionCell cycle arrestMiRNA clusterHepatocellular carcinoma cellsCell growth in vitroRNA-seqGene networksTarget predictionCRISPR knockoutOncogenic roleGrowth in vitroCycle arrestMature miRNAsMiRNAsG2/M phaseSignaling pathwayOncogenic functionCell-specific gene networks and drivers in rheumatoid arthritis synovial tissues
Pelissier A, Laragione T, Gulko P, Martínez M. Cell-specific gene networks and drivers in rheumatoid arthritis synovial tissues. Frontiers In Immunology 2024, 15: 1428773. PMID: 39161769, PMCID: PMC11330812, DOI: 10.3389/fimmu.2024.1428773.Peer-Reviewed Original ResearchTranscription factorsNatural killer TPhenotypic differencesGene regulatory networksCo-regulatory networkRNA-seq databaseCell typesFibroblast-like synoviocytesRNA-seqRegulatory networksGene networksTF clustersMultiple cell typesB cellsCell regulationKiller TRheumatoid arthritis synovial tissuePhenotypic groupsRA pathogenesisRA synovial tissuePathway changesTissue genesGenesCompare network propertiesComputational approachComputational reassessment of RNA-seq data reveals key genes in active tuberculosis
Arya R, Shakya H, Chaurasia R, Kumar S, Vinetz J, Kim J. Computational reassessment of RNA-seq data reveals key genes in active tuberculosis. PLOS ONE 2024, 19: e0305582. PMID: 38935691, PMCID: PMC11210783, DOI: 10.1371/journal.pone.0305582.Peer-Reviewed Original ResearchConceptsMolecular Complex DetectionProtein-protein interactionsDeregulated genesGene OntologyRNA-seq dataGene Expression Omnibus (GEO) databaseIncreasing prevalence of multidrug-resistantGEO2R online toolPrevalence of multidrug resistancePathway enrichment analysisExpression levelsPatterns of variationGene expression levelsArea under curveInnate immune responseGene networksCore genesMicroarray datasetsSTRING databaseTranscript levelsEnrichment analysisGenesInterferon SignalingInterferon-gamma signalingResponse to Mtb infection
2023
Sis2 regulates yeast replicative lifespan in a dose-dependent manner
Ölmez T, Moreno D, Liu P, Johnson Z, McGinnis M, Tu B, Hochstrasser M, Acar M. Sis2 regulates yeast replicative lifespan in a dose-dependent manner. Nature Communications 2023, 14: 7719. PMID: 38012152, PMCID: PMC10682402, DOI: 10.1038/s41467-023-43233-y.Peer-Reviewed Original ResearchConceptsYeast replicative lifespanReplicative lifespanRNA-seq experimentsCoenzyme A biosynthesis pathwayYeast lifespanYeast strainsStrain librariesLifespan regulationRNA-seqGene networksDose-dependent mannerLifespan extensionTranscriptional increaseYeastLifespan measurementsWild-typeGenesMachinery componentsStrainMicrofluidic platformApplications of microfluidic platformsLifespanDeletionCoenzymePathwayProfiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex
Rompala G, Nagamatsu S, Martínez-Magaña J, Nuñez-Ríos D, Wang J, Girgenti M, Krystal J, Gelernter J, Hurd Y, Montalvo-Ortiz J. Profiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex. Nature Communications 2023, 14: 4544. PMID: 37507366, PMCID: PMC10382503, DOI: 10.1038/s41467-023-40285-y.Peer-Reviewed Original ResearchConceptsOpioid use disorderMulti-omics findingsGene expression patternsCo-methylation analysisGene expression profilesMulti-omics profilingGene networksDNA methylationNeuronal methylomesDNA hydroxymethylationMethylomic analysisExpression patternsExpression profilesEpigenetic disturbancesUse disordersPsychiatric traitsOrbitofrontal cortexOpioid-related drugsPostmortem orbitofrontal cortexEnvironmental factorsDrug interaction analysisOUD treatmentHuman orbitofrontal cortexOpioid signalingInteraction analysis
2022
B.3 Activated gene pathways in post-infectious hydrocephalus (PIH):: proteogenomics and the PIH expressome
Isaacs A, Morton S, Movassagh M, Zhang Q, Hehnly C, Zhang L, Morales D, Townsend R, Limbrick D, Paulson J, Schiff S. B.3 Activated gene pathways in post-infectious hydrocephalus (PIH):: proteogenomics and the PIH expressome. Canadian Journal Of Neurological Sciences / Journal Canadien Des Sciences Neurologiques 2022, 49: s5-s5. DOI: 10.1017/cjn.2022.98.Peer-Reviewed Original ResearchProteins/genesGene pathwaysDifferential expressionIntegration of proteomicsGene networksOxidative stressGene setsProteogenomicsMolecular mechanismsPaenibacillus sppMolecular identificationPost-infectious hydrocephalusGenesDNA sequencingNovel insightsPathogenetic bacteriaProteomicsRNAseqViral pathogensPathwayHost responseExpressionExpressomeCerebrospinal fluidImmune systemThe microRNA-3622 family at the 8p21 locus exerts oncogenic effects by regulating the p53-downstream gene network in prostate cancer progression
Zhang Y, Xu Z, Wen W, Liu Z, Zhang C, Li M, Hu F, Wei S, Bae S, Zhou J, Liu R, Wang L. The microRNA-3622 family at the 8p21 locus exerts oncogenic effects by regulating the p53-downstream gene network in prostate cancer progression. Oncogene 2022, 41: 3186-3196. PMID: 35501464, PMCID: PMC9177620, DOI: 10.1038/s41388-022-02289-8.Peer-Reviewed Original ResearchConceptsGene networksHuman prostate cancerDual-luciferase assayRepression of p53 signalingInvasion of human prostate cancer cellsOncogenic functionHuman prostate cancer cellsOncogenic effectsCell proliferationHuman prostate cancer cell linesProstate cancer cell linesCRISPR interferenceControl apoptosisCancer cell linesProstate cancer cellsTumor progressionInvasion in vitroP53 signalingUpregulation of vimentinMetastasis in vivoHuman prostate cancer tissuesCell cycleImmunoprecipitation assaysC-MycCell migrationChapter 14 Integration with systems biology approaches and -omics data to characterize risk variation
Young H, Cote A, Huckins L. Chapter 14 Integration with systems biology approaches and -omics data to characterize risk variation. 2022, 289-315. DOI: 10.1016/b978-0-12-819602-1.00017-6.Peer-Reviewed Original ResearchAssociation studiesPatterns of linkage disequilibriumTranscriptome-wide association studyGenome-wide association studiesFunctional genomic annotationsSystems biology approachGenome annotationNoncoding variantsNoncoding regionsLinkage disequilibriumGene regulationRegulatory regionsGene networksGenetic variantsBiology approachFunctional pathwaysRisk variationDevelopmental stagesGenetic riskGenesPathwayUnique considerationsVariantsVariation researchPsychiatric disorders
2021
Dyrk1b promotes autophagy during skeletal muscle differentiation by upregulating 4e-bp1
Bhat N, Narayanan A, Fathzadeh M, Shah K, Dianatpour M, Abou Ziki MD, Mani A. Dyrk1b promotes autophagy during skeletal muscle differentiation by upregulating 4e-bp1. Cellular Signalling 2021, 90: 110186. PMID: 34752933, PMCID: PMC8712395, DOI: 10.1016/j.cellsig.2021.110186.Peer-Reviewed Original ResearchConceptsSkeletal muscle differentiationMuscle differentiationC2C12 cellsHuman skeletal muscle developmentSkeletal muscle developmentGlobal gene networksPost-transcriptional targetEmbryonic lethalGene networksZebrafish embryosMyofiber differentiationOverexpression approachesMuscle developmentCRISPR/DYRK1BRare gainDownstream targetsTranslational inhibitorKey regulatorUntargeted proteomicsFunction mutationsAutophagic fluxEnhances AutophagyDifferentiationAutophagyC.3 Activated Gene Pathways in Post-Infectious Hydrocephalus (PIH): Proteogenomics and the PIH Expressome
Isaacs A, Morton S, Movassagh M, Zhang Q, Hehnly C, Zhang L, Morales D, Townsend R, Limbrick D, Paulson J, Schiff S. C.3 Activated Gene Pathways in Post-Infectious Hydrocephalus (PIH): Proteogenomics and the PIH Expressome. Canadian Journal Of Neurological Sciences / Journal Canadien Des Sciences Neurologiques 2021, 48: s18-s19. DOI: 10.1017/cjn.2021.279.Peer-Reviewed Original ResearchProteins/genesGene pathwaysDifferential expressionIntegration of proteomicsGene networksOxidative stressGene setsProteogenomicsMolecular mechanismsPaenibacillus sppMolecular identificationPost-infectious hydrocephalusGenesDNA sequencingNovel insightsPathogenetic bacteriaProteomicsRNAseqViral pathogensPathwayHost responseExpressionExpressomeCerebrospinal fluidImmune systemJoint single-cell measurements of nuclear proteins and RNA in vivo
Chung H, Parkhurst C, Magee E, Phillips D, Habibi E, Chen F, Yeung B, Waldman J, Artis D, Regev A. Joint single-cell measurements of nuclear proteins and RNA in vivo. Nature Methods 2021, 18: 1204-1212. PMID: 34608310, PMCID: PMC8532076, DOI: 10.1038/s41592-021-01278-1.Peer-Reviewed Original ResearchConceptsGene expressionNuclear proteinsAnalysis of transcription factor (TFTranscription factor (TFGenome-wide associationRNA in vivoQuantitate protein levelsNative tissue contextModel gene expressionGene expression in vivoGene networksExpression in vivoInduction of neuronal activityGene targetingClinical specimensTissue contextGenesTranscriptomeProtein levelsProteinMouse brainExpressionCellular indicesPharmacological inductionTFACE2 Netlas: In silico Functional Characterization and Drug-Gene Interactions of ACE2 Gene Network to Understand Its Potential Involvement in COVID-19 Susceptibility
Pathak GA, Wendt FR, Goswami A, Koller D, De Angelis F, Initiative C, Polimanti R. ACE2 Netlas: In silico Functional Characterization and Drug-Gene Interactions of ACE2 Gene Network to Understand Its Potential Involvement in COVID-19 Susceptibility. Frontiers In Genetics 2021, 12: 698033. PMID: 34512723, PMCID: PMC8429844, DOI: 10.3389/fgene.2021.698033.Peer-Reviewed Original ResearchGenome-wide association studiesGenetic variationFunctional characterizationCOVID-19 susceptibilityHuman genetic variationSilico functional characterizationDrug-gene interaction databaseTranscriptomic regulationGene networksGenetic variant associationsMetabolic domainsMulti-level characterizationPhenome-wide associationAssociation studiesDrug-gene interactionsVariant associationsInteraction databasesGenesKey adhesion moleculeGenetic variantsPhenotype categoriesPotential involvementMiRNAsAdhesion moleculesPotential mechanisms
2020
Cutting-edge genetics in obsessive-compulsive disorder
Saraiva L, Cappi C, Simpson H, Stein D, Viswanath B, van den Heuvel O, Reddy Y, Miguel E, Shavitt R. Cutting-edge genetics in obsessive-compulsive disorder. Faculty Reviews 2020, 9: 30. PMID: 33659962, PMCID: PMC7886082, DOI: 10.12703/r/9-30.Peer-Reviewed Original ResearchGenetic architectureWide association studyNumber variation studiesCutting-edge geneticsWhole-exome sequencing studiesUnderlying biological pathwaysHuman cell modelsGene networksStudy of endophenotypesGene expressionBiological pathwaysSequencing studiesAssociation studiesAnimal systemsGeneticsGene-environment interactionsCell modelBiological basisPolygenic risk scoresEvidence pointsSynaptic transmissionRecent advancesVariation studiesExperimental animal systemsNeuropsychiatric disordersTranscriptomic organization of the human brain in post-traumatic stress disorder
Girgenti MJ, Wang J, Ji D, Cruz DA, Stein M, Gelernter J, Young K, Huber B, Williamson D, Friedman M, Krystal J, Zhao H, Duman R. Transcriptomic organization of the human brain in post-traumatic stress disorder. Nature Neuroscience 2020, 24: 24-33. PMID: 33349712, DOI: 10.1038/s41593-020-00748-7.Peer-Reviewed Original ResearchMeSH KeywordsAdultAutopsyBrain ChemistryCohort StudiesDepressive Disorder, MajorFemaleGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInterneuronsMaleMiddle AgedNerve Tissue ProteinsSex CharacteristicsStress Disorders, Post-TraumaticTranscriptomeYoung AdultConceptsGenome-wide association studiesSignificant gene networksDifferential gene expressionSystems-level evidenceSignificant genetic liabilityMajor depressive disorder cohortGene networksTranscriptomic organizationTranscriptomic landscapeDownregulated setsGenomic networksGene expressionAssociation studiesMolecular determinantsExtensive remodelingGenotype dataSexual dimorphismSignificant divergenceMolecular profileNetwork analysisELFN1TranscriptsDimorphismPostmortem tissueDivergenceReprogramming of Stem Cell Activity to Convert Thorns into Branches
Zhang F, Rossignol P, Huang T, Wang Y, May A, Dupont C, Orbovic V, Irish VF. Reprogramming of Stem Cell Activity to Convert Thorns into Branches. Current Biology 2020, 30: 2951-2961.e5. PMID: 32559443, DOI: 10.1016/j.cub.2020.05.068.Peer-Reviewed Original ResearchConceptsGene networksShoot stem cell nicheStem cellsTCP transcription factorsExpression of WUSCHELStem cell quiescenceStem cell nicheStem cell activityStem cell proliferationCitrus genesAngiosperm speciesPlant architectureShoot apicalApical meristemTranscription factorsCell nicheCell quiescenceMeristemFunction of componentsWUSCHELCell proliferationConcomitant conversionCrop yieldFunction resultsCellsGene X environment: the cellular environment governs the transcriptional response to environmental chemicals
Burman A, Garcia-Milian R, Whirledge S. Gene X environment: the cellular environment governs the transcriptional response to environmental chemicals. Human Genomics 2020, 14: 19. PMID: 32448403, PMCID: PMC7247264, DOI: 10.1186/s40246-020-00269-1.Peer-Reviewed Original ResearchConceptsTranscriptional responseCellular environmentCellular contextGenetic sexUnique gene networksGene regulatory networksEnvironment interactionEnvironmental chemicalsGene expression studiesUnique transcriptional profileGene expression array dataExpression array dataPhenotype of cellsGene networksRegulatory networksTranscriptional profilesBiological functionsCellular organizationExpression studiesFemale cellsCellular responsesPhysiological cuesHuman gene expression studiesMolecular pathwaysGenetic resultsAmygdala 5-HTT Gene Network Moderates the Effects of Postnatal Adversity on Attention Problems: Anatomo-Functional Correlation and Epigenetic Changes
de Lima RMS, Barth B, Arcego DM, de Mendonça Filho EJ, Clappison A, Patel S, Wang Z, Pokhvisneva I, Sassi RB, Hall GBC, Kobor MS, O'Donnell KJ, de Vasconcellos Bittencourt A, Meaney MJ, Dalmaz C, Silveira PP. Amygdala 5-HTT Gene Network Moderates the Effects of Postnatal Adversity on Attention Problems: Anatomo-Functional Correlation and Epigenetic Changes. Frontiers In Neuroscience 2020, 14: 198. PMID: 32256307, PMCID: PMC7093057, DOI: 10.3389/fnins.2020.00198.Peer-Reviewed Original Research
2019
Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses
Hess JL, Tylee DS, Barve R, de Jong S, Ophoff RA, Kumarasinghe N, Tooney P, Schall U, Gardiner E, Beveridge NJ, Scott RJ, Yasawardene S, Perera A, Mendis J, Carr V, Kelly B, Cairns M, Unit T, Tsuang MT, Glatt SJ. Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses. Schizophrenia Research 2019, 217: 124-135. PMID: 31391148, PMCID: PMC6997041, DOI: 10.1016/j.schres.2019.07.036.Peer-Reviewed Original ResearchConceptsGene modulesSZ casesGene co-expression network analysisCo-expression network analysisGene expression profilesGene expression alterationsChromatin regulationChromatin remodelingNineteen genesGene networksTranscriptomic abnormalitiesDisorder-specific changesGene expressionExpression profilesBiological processesImmune signalingExpression alterationsTranscriptomic signaturesGenesReactive oxygenUnaffected comparison subjectsMajor psychosesOxidative stressBD casesApoptosis
2018
Using evolutionary genomics, transcriptomics, and systems biology to reveal gene networks underlying fungal development
Wang Z, Gudibanda A, Ugwuowo U, Trail F, Townsend J. Using evolutionary genomics, transcriptomics, and systems biology to reveal gene networks underlying fungal development. Fungal Biology Reviews 2018, 32: 249-264. DOI: 10.1016/j.fbr.2018.02.001.ChaptersModel speciesFungal developmentGenome-wide gene expression dataEvolutionary developmental biologyEvo-devo researchGenome-wide analysisSystems biology strategiesGene expression dataEvolutionary genomicsSpecies phylogenyGenetic screenDevelopmental biologyDevelopmental traitsGene networksRegulatory networksFungal modelCell biologyModern biologyFossil recordKnockout strategiesDevelopmental processesMultiple speciesSystems biologyMolecular geneticsExpression data
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