Featured Publications
Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk
Rajarajan P, Borrman T, Liao W, Schrode N, Flaherty E, Casiño C, Powell S, Yashaswini C, LaMarca EA, Kassim B, Javidfar B, Espeso-Gil S, Li A, Won H, Geschwind DH, Ho SM, MacDonald M, Hoffman GE, Roussos P, Zhang B, Hahn CG, Weng Z, Brennand KJ, Akbarian S. Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk. Science 2018, 362 PMID: 30545851, PMCID: PMC6408958, DOI: 10.1126/science.aat4311.Peer-Reviewed Original ResearchMeSH KeywordsBrainCells, CulturedChromatinChromatin Assembly and DisassemblyChromosomes, HumanConnectomeEpigenesis, GeneticGene Expression Regulation, DevelopmentalGenetic Predisposition to DiseaseGenome-Wide Association StudyGenome, HumanHumansMaleNeural Stem CellsNeurogenesisNeurogliaNeuronsNucleic Acid ConformationProtein Interaction MapsProteomicsRiskSchizophreniaTranscription, GeneticTranscriptomeConceptsCoordinated transcriptional regulationThree-dimensional genomeSpatial genome organizationChromosomal contact mapsNeural progenitor cellsSchizophrenia risk variantsGenome organizationChromatin remodelingChromosomal conformationTranscriptional regulationProteomic interactionsDevelopmental remodelingHeritable riskGlial differentiationRisk variantsContact mapsProgenitor cellsVariant sequencesGenesConformation changeNeuronal connectivitySchizophrenia riskSequenceNeuropsychiatric diseasesDistal targets
2024
Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain
Wen C, Margolis M, Dai R, Zhang P, Przytycki P, Vo D, Bhattacharya A, Matoba N, Tang M, Jiao C, Kim M, Tsai E, Hoh C, Aygün N, Walker R, Chatzinakos C, Clarke D, Pratt H, Peters M, Gerstein M, Daskalakis N, Weng Z, Jaffe A, Kleinman J, Hyde T, Weinberger D, Bray N, Sestan N, Geschwind D, Roeder K, Gusev A, Pasaniuc B, Stein J, Love M, Pollard K, Liu C, Gandal M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Bendl J, Berretta S, Bharadwaj R, Bicks L, Brennand K, Capauto D, Champagne F, Chatterjee T, Chatzinakos C, Chen Y, Chen H, Cheng Y, Cheng L, Chess A, Chien J, Chu Z, Clement A, Collado-Torres L, Cooper G, Crawford G, Davila-Velderrain J, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duan Z, Duong D, Dursun C, Eagles N, Edelstein J, Emani P, Fullard J, Galani K, Galeev T, Gaynor S, Girdhar K, Goes F, Greenleaf W, Grundman J, Guo H, Guo Q, Gupta C, Hadas Y, Hallmayer J, Han X, Haroutunian V, Hawken N, He C, Henry E, Hicks S, Ho M, Ho L, Hoffman G, Huang Y, Huuki-Myers L, Hwang A, Iatrou A, Inoue F, Jajoo A, Jensen M, Jiang L, Jin P, Jin T, Jops C, Jourdon A, Kawaguchi R, Kellis M, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Lee C, Lee D, Li J, Li M, Lin X, Liu S, Liu J, Liu J, Liu S, Lou S, Loupe J, Lu D, Ma S, Ma L, Mariani J, Martinowich K, Maynard K, Mazariegos S, Meng R, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Moore J, Moran J, Mukamel E, Nairn A, Nemeroff C, Ni P, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Phalke N, Pinto D, Pjanic M, Pochareddy S, Pollen A, Purmann C, Qin Z, Qu P, Quintero D, Raj T, Rajagopalan A, Reach S, Reimonn T, Ressler K, Ross D, Roussos P, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Seyfried N, Shao Z, Shedd N, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Voloudakis G, Wamsley B, Wang T, Wang S, Wang D, Wang Y, Warrell J, Wei Y, Weimer A, Whalen S, White K, Willsey A, Won H, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Xu S, Yap C, Zeng B, Zhang C, Zhang B, Zhang J, Zhang Y, Zhou X, Ziffra R, Zeier Z, Zintel T. Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain. Science 2024, 384: eadh0829. PMID: 38781368, DOI: 10.1126/science.adh0829.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide association study lociSplicing quantitative trait lociQuantitative trait lociSplicing regulationCross-ancestryTrait lociAssociation studiesRegulatory elementsCellular contextHuman brainTranscriptome regulationCoexpression networkRisk genesAutism spectrum disorderGenesCellular heterogeneityComprehensive landscapeSpectrum disorderIsoformsSplicingIncreased cellular heterogeneityLociNeuronal maturationRegulationSingle-cell multi-cohort dissection of the schizophrenia transcriptome
Ruzicka W, Mohammadi S, Fullard J, Davila-Velderrain J, Subburaju S, Tso D, Hourihan M, Jiang S, Lee H, Bendl J, Voloudakis G, Haroutunian V, Hoffman G, Roussos P, Kellis M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Berretta S, Bharadwaj R, Bhattacharya A, Bicks L, Brennand K, Capauto D, Champagne F, Chatterjee T, Chatzinakos C, Chen Y, Chen H, Cheng Y, Cheng L, Chess A, Chien J, Chu Z, Clarke D, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duan Z, Duong D, Dursun C, Eagles N, Edelstein J, Emani P, Galani K, Galeev T, Gandal M, Gaynor S, Gerstein M, Geschwind D, Girdhar K, Goes F, Greenleaf W, Grundman J, Guo H, Guo Q, Gupta C, Hadas Y, Hallmayer J, Han X, Hawken N, He C, Henry E, Hicks S, Ho M, Ho L, Huang Y, Huuki-Myers L, Hwang A, Hyde T, Iatrou A, Inoue F, Jajoo A, Jensen M, Jiang L, Jin P, Jin T, Jops C, Jourdon A, Kawaguchi R, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Lee C, Lee D, Li J, Li M, Lin X, Liu S, Liu J, Liu J, Liu C, Liu S, Lou S, Loupe J, Lu D, Ma S, Ma L, Margolis M, Mariani J, Martinowich K, Maynard K, Mazariegos S, Meng R, Myers R, Micallef C, Mikhailova T, Ming G, Monte E, Montgomery K, Moore J, Moran J, Mukamel E, Nairn A, Nemeroff C, Ni P, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Phalke N, Pinto D, Pjanic M, Pochareddy S, Pollard K, Pollen A, Pratt H, Przytycki P, Purmann C, Qin Z, Qu P, Quintero D, Raj T, Rajagopalan A, Reach S, Reimonn T, Ressler K, Ross D, Rozowsky J, Ruth M, Sanders S, Schneider J, Scuderi S, Sebra R, Sestan N, Seyfried N, Shao Z, Shedd N, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Wamsley B, Wang T, Wang S, Wang D, Wang Y, Warrell J, Wei Y, Weimer A, Weinberger D, Wen C, Weng Z, Whalen S, White K, Willsey A, Won H, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Xu S, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang J, Zhang Y, Zhou X, Ziffra R, Zeier Z, Zintel T. Single-cell multi-cohort dissection of the schizophrenia transcriptome. Science 2024, 384: eadg5136. PMID: 38781388, DOI: 10.1126/science.adg5136.Peer-Reviewed Original ResearchConceptsGenetic risk factorsRisk factorsTranscriptional changesHeterogeneity of schizophreniaNeuronal cell statesSchizophrenia pathophysiologySingle-cell dissectionExcitatory neuronsEffective therapySchizophrenia transcriptomicsCortical cytoarchitectureSingle-cell atlasGenomic variantsCell groupsHuman prefrontal cortexMolecular pathwaysSchizophreniaTranscriptional alterationsTranscriptomic changesPrefrontal cortexCell statesAlterationsTherapyPathophysiologyDissectionA data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex
Huuki-Myers L, Spangler A, Eagles N, Montgomery K, Kwon S, Guo B, Grant-Peters M, Divecha H, Tippani M, Sriworarat C, Nguyen A, Ravichandran P, Tran M, Seyedian A, Hyde T, Kleinman J, Battle A, Page S, Ryten M, Hicks S, Martinowich K, Collado-Torres L, Maynard K, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Bendl J, Berretta S, Bharadwaj R, Bhattacharya A, Bicks L, Brennand K, Capauto D, Champagne F, Chatterjee T, Chatzinakos C, Chen Y, Chen H, Cheng Y, Cheng L, Chess A, Chien J, Chu Z, Clarke D, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Davila-Velderrain J, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duan Z, Duong D, Dursun C, Eagles N, Edelstein J, Emani P, Fullard J, Galani K, Galeev T, Gandal M, Gaynor S, Gerstein M, Geschwind D, Girdhar K, Goes F, Greenleaf W, Grundman J, Guo H, Guo Q, Gupta C, Hadas Y, Hallmayer J, Han X, Haroutunian V, Hawken N, He C, Henry E, Hicks S, Ho M, Ho L, Hoffman G, Huang Y, Huuki-Myers L, Hwang A, Hyde T, Iatrou A, Inoue F, Jajoo A, Jensen M, Jiang L, Jin P, Jin T, Jops C, Jourdon A, Kawaguchi R, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Lee C, Lee D, Li J, Li M, Lin X, Liu S, Liu J, Liu J, Liu C, Liu S, Lou S, Loupe J, Lu D, Ma S, Ma L, Margolis M, Mariani J, Martinowich K, Maynard K, Mazariegos S, Meng R, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Moore J, Moran J, Mukamel E, Nairn A, Nemeroff C, Ni P, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Phalke N, Pinto D, Pjanic M, Pochareddy S, Pollard K, Pollen A, Pratt H, Przytycki P, Purmann C, Qin Z, Qu P, Quintero D, Raj T, Rajagopalan A, Reach S, Reimonn T, Ressler K, Ross D, Roussos P, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Sestan N, Seyfried N, Shao Z, Shedd N, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Voloudakis G, Wamsley B, Wang T, Wang S, Wang D, Wang Y, Warrell J, Wei Y, Weimer A, Weinberger D, Wen C, Weng Z, Whalen S, White K, Willsey A, Won H, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Xu S, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang J, Zhang Y, Zhou X, Ziffra R, Zeier Z, Zintel T. A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex. Science 2024, 384: eadh1938. PMID: 38781370, PMCID: PMC11398705, DOI: 10.1126/science.adh1938.Peer-Reviewed Original ResearchConceptsRNA sequencing dataCell type compositionGene expression platformSpatial transcriptomics technologiesAnterior-posterior axisCell-cell interactionsTranscriptome mapExpression platformHuman dorsolateral prefrontal cortexTranscriptomic technologiesSingle-cellCell typesPrefrontal cortexMolecular organizationDorsolateral prefrontal cortexHuman prefrontal cortex
2023
Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings
Hicks E, Seah C, Cote A, Marchese S, Brennand K, Nestler E, Girgenti M, Huckins L. Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings. Translational Psychiatry 2023, 13: 129. PMID: 37076454, PMCID: PMC10115809, DOI: 10.1038/s41398-023-02412-7.Peer-Reviewed Original ResearchConceptsBioinformatics approachTranscriptomic dataBrain transcriptomeGenome-wide analysisDynamic transcriptional landscapeBrain gene expression dataGene expression dataTranscriptional landscapeTranscriptomic studiesIntegrating GeneticExpression dataPhenotypic signaturesGenomic driversTranscriptomeMajor depressive disorderValuable resourceRecent findingsEnvironmental influencesTranscriptomicsDepressive disorderGeneticsMultiple approachesPathophysiology of depressionSignaturesDysregulation
2022
Population-level variation in enhancer expression identifies disease mechanisms in the human brain
Dong P, Hoffman G, Apontes P, Bendl J, Rahman S, Fernando M, Zeng B, Vicari J, Zhang W, Girdhar K, Townsley K, Misir R, Brennand K, Haroutunian V, Voloudakis G, Fullard J, Roussos P. Population-level variation in enhancer expression identifies disease mechanisms in the human brain. Nature Genetics 2022, 54: 1493-1503. PMID: 36163279, PMCID: PMC9547946, DOI: 10.1038/s41588-022-01170-4.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociPopulation-level variationTranscriptome-wide association studyQuantitative trait lociSpecific transcriptomeTrait lociTrait heritabilitySpecific transcriptionEnhancer functionGenetic mechanismsTarget genesAssociation studiesDisease locusNeuropsychiatric diseasesRisk variantsGenesRobust expressionTranscriptomeFunctional interpretationDisease mechanismsEnhancerDiseased statesLociHuman brainBrain samples
2021
Using the dCas9-KRAB system to repress gene expression in hiPSC-derived NGN2 neurons
Li A, Cartwright S, Yu A, Ho SM, Schrode N, Deans PJM, Matos MR, Garcia MF, Townsley KG, Zhang B, Brennand KJ. Using the dCas9-KRAB system to repress gene expression in hiPSC-derived NGN2 neurons. STAR Protocols 2021, 2: 100580. PMID: 34151300, PMCID: PMC8188621, DOI: 10.1016/j.xpro.2021.100580.Peer-Reviewed Original ResearchConceptsCRISPR inhibitionGene expressionDCas9-KRAB systemEndogenous gene expressionMultiple target genesGene repressionGene activationTarget genesGene manipulationFusion proteinComplete detailsPluripotent stemExpressionGlutamatergic neuronsRepressionGenesPhenotypicProteinStemNeuronsActivationBrain diseasesInhibitionAnalysis framework and experimental design for evaluating synergy-driving gene expression
Schrode N, Seah C, Deans P, Hoffman G, Brennand K. Analysis framework and experimental design for evaluating synergy-driving gene expression. Nature Protocols 2021, 16: 812-840. PMID: 33432232, PMCID: PMC8609447, DOI: 10.1038/s41596-020-00436-7.Peer-Reviewed Original ResearchConceptsRaw read countsPluripotent stem cell-derived neuronsRNA sequencing experimentsRNA sequencing datasetsStem cell-derived neuronsDifferential expression analysisCell-derived neuronsComplex genetic disorderNon-additive interactionsGenetic risk variantsChemical perturbagensBioinformatics skillsExpression analysisSequencing datasetsGene expressionTranscriptomic effectsSequencing experimentsComputational pipelineRead countsRisk variantsCareful experimental designCombinatorial manipulationGenetic variantsComplex diseasesPerturbation studies
2020
Cell Type-Specific In Vitro Gene Expression Profiling of Stem Cell-Derived Neural Models
Gregory JA, Hoelzli E, Abdelaal R, Braine C, Cuevas M, Halpern M, Barretto N, Schrode N, Akbalik G, Kang K, Cheng E, Bowles K, Lotz S, Goderie S, Karch CM, Temple S, Goate A, Brennand KJ, Phatnani H. Cell Type-Specific In Vitro Gene Expression Profiling of Stem Cell-Derived Neural Models. Cells 2020, 9: 1406. PMID: 32516938, PMCID: PMC7349756, DOI: 10.3390/cells9061406.Peer-Reviewed Original ResearchConceptsCell type-restricted expressionDisease-associated interactionsGene expression profilingHiPSC-derived motor neuronsHuman-induced pluripotent stem cellsPluripotent stem cellsCell-type specific perturbationsImmortalized cell linesRibosomal proteinsGenomic studiesExpression profilingMolecular mechanismsOff-target RNAMouse tissuesCell typesStem cellsPrimary mouse astrocytesExperimental replicatesCell linesMixed speciesMouse astrocytesExpressionMotor neuronsRiboTagCells
2018
Expression-based drug screening of neural progenitor cells from individuals with schizophrenia
Readhead B, Hartley BJ, Eastwood BJ, Collier DA, Evans D, Farias R, He C, Hoffman G, Sklar P, Dudley JT, Schadt EE, Savić R, Brennand KJ. Expression-based drug screening of neural progenitor cells from individuals with schizophrenia. Nature Communications 2018, 9: 4412. PMID: 30356048, PMCID: PMC6200740, DOI: 10.1038/s41467-018-06515-4.Peer-Reviewed Original ResearchConceptsNeural progenitor cellsHiPSC neural progenitor cellsCell typesCancer cell linesGene expression differencesProgenitor cellsDisease-associated genesPatient-specific platformPluripotent stem cellsTranscriptional responseExpression differencesTranscriptional signatureTranscriptomic signaturesStem cellsCell linesDependent mannerDrug discoveryDrug screeningCellsNeuropsychiatric disordersSchizophreniaBest treatmentDrugsDiscoveryGenesTHC exposure of human iPSC neurons impacts genes associated with neuropsychiatric disorders
Guennewig B, Bitar M, Obiorah I, Hanks J, O’Brien E, Kaczorowski DC, Hurd YL, Roussos P, Brennand KJ, Barry G. THC exposure of human iPSC neurons impacts genes associated with neuropsychiatric disorders. Translational Psychiatry 2018, 8: 89. PMID: 29691375, PMCID: PMC5915454, DOI: 10.1038/s41398-018-0137-3.Peer-Reviewed Original ResearchConceptsHuman-induced pluripotent stem cellsPluripotent stem cellsHuman iPSC neuronsTranscriptional responseTranscriptomic analysisRNA transcriptomic analysisHuman neural cellsIPSC-neuronsMolecular pathwaysNeuropsychiatric disordersStem cellsNeural cellsDiagnosis-specific differencesGenesTHC exposureNeuronal depolarizationTHC administrationChronic exposureCannabis useNeuronsΔ9-tetrahydrocannabinolStrong associationSignificant alterationsCellsDynamic changes
2017
Transcriptional signatures of schizophrenia in hiPSC-derived NPCs and neurons are concordant with post-mortem adult brains
Hoffman GE, Hartley BJ, Flaherty E, Ladran I, Gochman P, Ruderfer DM, Stahl EA, Rapoport J, Sklar P, Brennand KJ. Transcriptional signatures of schizophrenia in hiPSC-derived NPCs and neurons are concordant with post-mortem adult brains. Nature Communications 2017, 8: 2225. PMID: 29263384, PMCID: PMC5738408, DOI: 10.1038/s41467-017-02330-5.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAntigens, SurfaceAutopsyBrainCase-Control StudiesChildDNA Copy Number VariationsFemaleHumansInduced Pluripotent Stem CellsLinear ModelsMaleNanog Homeobox ProteinNestinNeural Stem CellsNeuronsOctamer Transcription Factor-3ProteoglycansRNA, MessengerSchizophreniaSequence Analysis, RNASOXB1 Transcription FactorsStage-Specific Embryonic AntigensSynapsinsTranscriptomeYoung AdultEvaluating Synthetic Activation and Repression of Neuropsychiatric-Related Genes in hiPSC-Derived NPCs, Neurons, and Astrocytes
Ho S, Hartley B, Flaherty E, Rajarajan P, Abdelaal R, Obiorah I, Barretto N, Muhammad H, Phatnani H, Akbarian S, Brennand K. Evaluating Synthetic Activation and Repression of Neuropsychiatric-Related Genes in hiPSC-Derived NPCs, Neurons, and Astrocytes. Stem Cell Reports 2017, 9: 615-628. PMID: 28757163, PMCID: PMC5550013, DOI: 10.1016/j.stemcr.2017.06.012.Peer-Reviewed Original ResearchConceptsSynthetic activationRisk genesCell typesModulation of transcriptionNeuropsychiatric risk genesCommon single nucleotide variantsCas9 fusion proteinsEndogenous expression levelsNeural cell typesPluripotent stem cell-derived neural progenitor cellsRare copy number variationsCopy number variationsSingle nucleotide variantsNeural progenitor cellsGene functionFunctional annotationGenetic studiesGenesRisk variantsProgenitor cellsExpression levelsTranscriptionRepressionPositional effectsProteinAn Efficient Platform for Astrocyte Differentiation from Human Induced Pluripotent Stem Cells
Julia T, Wang M, Pimenova A, Bowles K, Hartley B, Lacin E, Machlovi S, Abdelaal R, Karch C, Phatnani H, Slesinger P, Zhang B, Goate A, Brennand K. An Efficient Platform for Astrocyte Differentiation from Human Induced Pluripotent Stem Cells. Stem Cell Reports 2017, 9: 600-614. PMID: 28757165, PMCID: PMC5550034, DOI: 10.1016/j.stemcr.2017.06.018.Peer-Reviewed Original ResearchCommon developmental genome deprogramming in schizophrenia — Role of Integrative Nuclear FGFR1 Signaling (INFS)
Narla S, Lee Y, Benson C, Sarder P, Brennand K, Stachowiak E, Stachowiak M. Common developmental genome deprogramming in schizophrenia — Role of Integrative Nuclear FGFR1 Signaling (INFS). Schizophrenia Research 2017, 185: 17-32. PMID: 28094170, PMCID: PMC5507209, DOI: 10.1016/j.schres.2016.12.012.Peer-Reviewed Original ResearchMeSH KeywordsAdultCell DifferentiationCells, CulturedFemaleGene Expression Regulation, DevelopmentalGene Regulatory NetworksGenomeGenomicsHumansInduced Pluripotent Stem CellsMaleMicroRNAsModels, BiologicalMutationReceptor, Fibroblast Growth Factor, Type 1Receptor, Notch1SchizophreniaSignal TransductionTranscriptomeYoung AdultConceptsMRNA networkMajor developmental pathwaysIntegrative nuclear FGFR1MiRNA-mRNA networkHuman gene promotersCommon developmental genomesMiRNA genesMiRNA transcriptomeGene networksUpregulated genesGene promoterNuclear FGFR1Genomic etiologyGene dysregulationDisease ontogenyNuclear formGlobal dysregulationDevelopmental pathwaysGenesNeuron formationDistinct pathwaysConcerted actionPotential therapeutic targetTranscriptomeGenome