2024
Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data
Dai R, Chu T, Zhang M, Wang X, Jourdon A, Wu F, Mariani J, Vaccarino F, Lee D, Fullard J, Hoffman G, Roussos P, Wang Y, Wang X, Pinto D, Wang S, Zhang C, consortium P, Chen C, Liu C. Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data. Science Advances 2024, 10: eadh2588. PMID: 38781336, PMCID: PMC11114236, DOI: 10.1126/sciadv.adh2588.Peer-Reviewed Original ResearchConceptsHuman brain transcriptome dataBrain transcriptomic dataRNA-seqTranscriptome dataCell-type gene expressionGene expressionCell-type proportionsSingle-cell dataMultiple brain disordersBrain cell typesCell deconvolution methodsPostmortem brainsRNA sequencingBrain disordersBrain developmentSchizophreniaEQTLAlzheimer's diseaseCell typesOrganoid samplesBrainBiological applications
2023
Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases
Garrison M, Jang Y, Bae T, Cherskov A, Emery S, Fasching L, Jones A, Moldovan J, Molitor C, Pochareddy S, Peters M, Shin J, Wang Y, Yang X, Akbarian S, Chess A, Gage F, Gleeson J, Kidd J, McConnell M, Mills R, Moran J, Park P, Sestan N, Urban A, Vaccarino F, Walsh C, Weinberger D, Wheelan S, Abyzov A. Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases. Scientific Data 2023, 10: 813. PMID: 37985666, PMCID: PMC10662356, DOI: 10.1038/s41597-023-02645-7.Peer-Reviewed Original Research
2022
Somatic genomic mosaicism in the brain during aging: Scratching the surface
Bae T, Wang Y, Vaccarino F, Abyzov A. Somatic genomic mosaicism in the brain during aging: Scratching the surface. Clinical And Translational Medicine 2022, 12: e1138. PMID: 36495113, PMCID: PMC9736788, DOI: 10.1002/ctm2.1138.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsAnalysis of somatic mutations in 131 human brains reveals aging-associated hypermutability
Bae T, Fasching L, Wang Y, Shin JH, Suvakov M, Jang Y, Norton S, Dias C, Mariani J, Jourdon A, Wu F, Panda A, Pattni R, Chahine Y, Yeh R, Roberts RC, Huttner A, Kleinman JE, Hyde TM, Straub RE, Walsh CA, Urban A, Leckman J, Weinberger D, Vaccarino F, Abyzov A, Walsh C, Park P, Sestan N, Weinberger D, Moran J, Gage F, Vaccarino F, Gleeson J, Mathern G, Courchesne E, Roy S, Chess A, Akbarian S, Bizzotto S, Coulter M, Dias C, D’Gama A, Ganz J, Hill R, Huang A, Khoshkhoo S, Kim S, Lee A, Lodato M, Maury E, Miller M, Borges-Monroy R, Rodin R, Zhou Z, Bohrson C, Chu C, Cortes-Ciriano I, Dou Y, Galor A, Gulhan D, Kwon M, Luquette J, Sherman M, Viswanadham V, Jones A, Rosenbluh C, Cho S, Langmead B, Thorpe J, Erwin J, Jaffe A, McConnell M, Narurkar R, Paquola A, Shin J, Straub R, Abyzov A, Bae T, Jang Y, Wang Y, Molitor C, Peters M, Linker S, Reed P, Wang M, Urban A, Zhou B, Zhu X, Pattni R, Serres Amero A, Juan D, Lobon I, Marques-Bonet T, Solis Moruno M, Garcia Perez R, Povolotskaya I, Soriano E, Antaki D, Averbuj D, Ball L, Breuss M, Yang X, Chung C, Emery S, Flasch D, Kidd J, Kopera H, Kwan K, Mills R, Moldovan J, Sun C, Zhao X, Zhou W, Frisbie T, Cherskov A, Fasching L, Jourdon A, Pochareddy S, Scuderi S. Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability. Science 2022, 377: 511-517. PMID: 35901164, PMCID: PMC9420557, DOI: 10.1126/science.abm6222.Peer-Reviewed Original ResearchConceptsTranscription factorsSomatic mutationsPutative transcription factorEnhancer-like regionSingle nucleotide mutationsWhole-genome sequencingGene regulationSomatic duplicationGenome sequencingDamaging mutationsBackground mutagenesisMutationsHypermutabilityClonal expansionMotifDiseased brainPotential linkVivo clonal expansionMutagenesisGenesDuplicationSequencingRegulation
2021
Comprehensive identification of somatic nucleotide variants in human brain tissue
Wang Y, Bae T, Thorpe J, Sherman MA, Jones AG, Cho S, Daily K, Dou Y, Ganz J, Galor A, Lobon I, Pattni R, Rosenbluh C, Tomasi S, Tomasini L, Yang X, Zhou B, Akbarian S, Ball LL, Bizzotto S, Emery SB, Doan R, Fasching L, Jang Y, Juan D, Lizano E, Luquette LJ, Moldovan JB, Narurkar R, Oetjens MT, Rodin RE, Sekar S, Shin JH, Soriano E, Straub RE, Zhou W, Chess A, Gleeson JG, Marquès-Bonet T, Park PJ, Peters MA, Pevsner J, Walsh CA, Weinberger DR, Vaccarino F, Moran J, Urban A, Kidd J, Mills R, Abyzov A. Comprehensive identification of somatic nucleotide variants in human brain tissue. Genome Biology 2021, 22: 92. PMID: 33781308, PMCID: PMC8006362, DOI: 10.1186/s13059-021-02285-3.Peer-Reviewed Original ResearchConceptsSomatic SNVsSomatic single nucleotide variantsWhole-genome sequencing dataSequencing dataBulk DNA samplesCell lineage treesSomatic mosaicismSingle nucleotide variantsLineage treesSomatic nucleotide variantsCellular processesDNA replicationHuman genomeSomatic tissuesDNA repairNucleotide variantsComprehensive identificationDNA samplesMosaic variantsNon-cancerous tissuesDNASingle individualMultiple replicatesHuman brain tissueVariants
2020
Complex mosaic structural variations in human fetal brains
Sekar S, Tomasini L, Proukakis C, Bae T, Manlove L, Jang Y, Scuderi S, Zhou B, Kalyva M, Amiri A, Mariani J, Sedlazeck F, Urban AE, Vaccarino F, Abyzov A. Complex mosaic structural variations in human fetal brains. Genome Research 2020, 30: gr.262667.120. PMID: 33122304, PMCID: PMC7706730, DOI: 10.1101/gr.262667.120.Peer-Reviewed Original ResearchConceptsSingle nucleotide variantsCopy number variantsStructural variantsMegabase-scale copy number variantsHuman fetal brainFunctional consequencesMobile element insertionsSimilar functional consequencesFetal brainMosaic single-nucleotide variantsAdult brain neuronsStructural variationsPotential functional consequencesKilobase scaleDNA eventsGenomic fragmentDifferent chromosomesElement insertionsClonal approachHuman brain cellsFetal human brainNucleotide variantsReplication errorsHuman brainNumber variantsPsychENCODE and beyond: transcriptomics and epigenomics of brain development and organoids
Jourdon A, Scuderi S, Capauto D, Abyzov A, Vaccarino FM. PsychENCODE and beyond: transcriptomics and epigenomics of brain development and organoids. Neuropsychopharmacology 2020, 46: 70-85. PMID: 32659782, PMCID: PMC7689467, DOI: 10.1038/s41386-020-0763-3.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsRecent single-cell technologiesGene regulatory networksSingle-cell technologiesMulti-omics investigationsPluripotent stem cellsTranscriptional dynamicsBrain developmentCell fateEpigenomic datasetsRegulatory networksElement activityNeural lineagesStem cellsBrain organoidsOrganoidsBiological modelsFetal brainPsychENCODEBrain biologyMajor questionsEpigenomicsFetal tissuesTranscriptomicsLineagesBiology
2019
Breakthrough Moments: Yoshiki Sasai’s Discoveries in the Third Dimension
Mariani J, Vaccarino FM. Breakthrough Moments: Yoshiki Sasai’s Discoveries in the Third Dimension. Cell Stem Cell 2019, 24: 837-838. PMID: 31173711, PMCID: PMC7085937, DOI: 10.1016/j.stem.2019.05.007.Commentaries, Editorials and Letters
2018
Comprehensive functional genomic resource and integrative model for the human brain
Wang D, Liu S, Warrell J, Won H, Shi X, Navarro FCP, Clarke D, Gu M, Emani P, Yang YT, Xu M, Gandal MJ, Lou S, Zhang J, Park JJ, Yan C, Rhie SK, Manakongtreecheep K, Zhou H, Nathan A, Peters M, Mattei E, Fitzgerald D, Brunetti T, Moore J, Jiang Y, Girdhar K, Hoffman GE, Kalayci S, Gümüş ZH, Crawford GE, Roussos P, Akbarian S, Jaffe A, White K, Weng Z, Sestan N, Geschwind D, Knowles J, Gerstein M, Ashley-Koch A, Crawford G, Garrett M, Song L, Safi A, Johnson G, Wray G, Reddy T, Goes F, Zandi P, Bryois J, Jaffe A, Price A, Ivanov N, Collado-Torres L, Hyde T, Burke E, Kleiman J, Tao R, Shin J, Akbarian S, Girdhar K, Jiang Y, Kundakovic M, Brown L, Kassim B, Park R, Wiseman J, Zharovsky E, Jacobov R, Devillers O, Flatow E, Hoffman G, Lipska B, Lewis D, Haroutunian V, Hahn C, Charney A, Dracheva S, Kozlenkov A, Belmont J, DelValle D, Francoeur N, Hadjimichael E, Pinto D, van Bakel H, Roussos P, Fullard J, Bendl J, Hauberg M, Mangravite L, Peters M, Chae Y, Peng J, Niu M, Wang X, Webster M, Beach T, Chen C, Jiang Y, Dai R, Shieh A, Liu C, Grennan K, Xia Y, Vadukapuram R, Wang Y, Fitzgerald D, Cheng L, Brown M, Brown M, Brunetti T, Goodman T, Alsayed M, Gandal M, Geschwind D, Won H, Polioudakis D, Wamsley B, Yin J, Hadzic T, De La Torre Ubieta L, Swarup V, Sanders S, State M, Werling D, An J, Sheppard B, Willsey A, White K, Ray M, Giase G, Kefi A, Mattei E, Purcaro M, Weng Z, Moore J, Pratt H, Huey J, Borrman T, Sullivan P, Giusti-Rodriguez P, Kim Y, Sullivan P, Szatkiewicz J, Rhie S, Armoskus C, Camarena A, Farnham P, Spitsyna V, Witt H, Schreiner S, Evgrafov O, Knowles J, Gerstein M, Liu S, Wang D, Navarro F, Warrell J, Clarke D, Emani P, Gu M, Shi X, Xu M, Yang Y, Kitchen R, Gürsoy G, Zhang J, Carlyle B, Nairn A, Li M, Pochareddy S, Sestan N, Skarica M, Li Z, Sousa A, Santpere G, Choi J, Zhu Y, Gao T, Miller D, Cherskov A, Yang M, Amiri A, Coppola G, Mariani J, Scuderi S, Szekely A, Vaccarino F, Wu F, Weissman S, Roychowdhury T, Abyzov A. Comprehensive functional genomic resource and integrative model for the human brain. Science 2018, 362 PMID: 30545857, PMCID: PMC6413328, DOI: 10.1126/science.aat8464.Peer-Reviewed Original ResearchConceptsQuantitative trait lociCell type proportionsComprehensive functional genomics resourceExpression quantitative trait lociFunctional genomics resourcesSingle-cell expression profilesGene regulatory networksFurther quantitative trait lociPsychENCODE ConsortiumGenomic resourcesComprehensive online resourceRegulatory networksKey genesCross-population variationExpression profilesMolecular mechanismsCell typesGenesAdult brainPolygenic risk scoresStudy variantsChromatinSplicingGenetic riskInterpretable deep learning model
2017
Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis
Bae T, Tomasini L, Mariani J, Zhou B, Roychowdhury T, Franjic D, Pletikos M, Pattni R, Chen BJ, Venturini E, Riley-Gillis B, Sestan N, Urban AE, Abyzov A, Vaccarino FM. Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis. Science 2017, 359: 550-555. PMID: 29217587, PMCID: PMC6311130, DOI: 10.1126/science.aan8690.Peer-Reviewed Original ResearchConceptsSingle nucleotide variationsMutation rateCancer cell genomeClonal cell populationsCell genomeCell lineagesBackground mutagenesisHuman cellsMutational rateSomatic mosaicismSingle cellsOxidative damageGenomeMutagenesisCell populationsMutation spectrumNeurogenesisCellsHuman fetusesIndividual neuronsLineagesPregastrulationHuman brainBrainMutationsIntersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network
McConnell MJ, Moran JV, Abyzov A, Akbarian S, Bae T, Cortes-Ciriano I, Erwin JA, Fasching L, Flasch DA, Freed D, Ganz J, Jaffe AE, Kwan KY, Kwon M, Lodato MA, Mills RE, Paquola ACM, Rodin RE, Rosenbluh C, Sestan N, Sherman MA, Shin JH, Song S, Straub RE, Thorpe J, Weinberger DR, Urban AE, Zhou B, Gage FH, Lehner T, Senthil G, Walsh CA, Chess A, Courchesne E, Gleeson JG, Kidd JM, Park PJ, Pevsner J, Vaccarino FM, Barton A, Bekiranov S, Bohrson C, Burbulis I, Chronister W, Coppola G, Daily K, D’Gama A, Emery S, Frisbie T, Gao T, Gulyás-Kovács A, Haakenson M, Keil J, Kopera H, Lam M, Lee E, Marques-Bonet T, Mathern G, Moldovan J, Oetjens M, Omberg L, Peters M, Pochareddy S, Pramparo T, Ratan A, Sanavia T, Shi L, Skarica M, Wang J, Wang M, Wang Y, Wierman M, Wolpert M, Woodworth M, Zhao X, Zhou W. Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. Science 2017, 356 PMID: 28450582, PMCID: PMC5558435, DOI: 10.1126/science.aal1641.Peer-Reviewed Original ResearchConceptsSomatic mutationsComplex genetic architectureStructural genomic variantsNeuronal genomeNeuronal transcriptomeGenetic architectureCell divisionCellular metabolismGenomic variantsLong life spanDNA damageComplex neuropsychiatric disorderCellular expansionNeuropsychiatric diseasesNeuropsychiatric disordersProgenitor cellsSomatic mosaicismIndividual neurodevelopmentSmall populationCell proliferationPopulation-based studyMutationsGermline variantsLife spanBrain developmentHuman induced pluripotent stem cells for modelling neurodevelopmental disorders
Ardhanareeswaran K, Mariani J, Coppola G, Abyzov A, Vaccarino FM. Human induced pluripotent stem cells for modelling neurodevelopmental disorders. Nature Reviews Neurology 2017, 13: 265-278. PMID: 28418023, PMCID: PMC5782822, DOI: 10.1038/nrneurol.2017.45.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsEmbryonic stem cellsNeurodevelopmental disordersPluripotent stem cellsBrain developmentStem cellsAbnormal brain developmentBrain cell typesDopaminergic neuronsCortical neuronsUnique genetic signatureEarly developmentKey PointsHumanHiPSC modelsSomatic cellsDisordersGenetic signaturesGenetic studiesAltered trajectoryCell typesAdult cellsNeuronsUnknown facetsCellsDrug discoveryHiPSCs
2015
The PsychENCODE project
Akbarian S, Liu C, Knowles JA, Vaccarino FM, Farnham PJ, Crawford GE, Jaffe AE, Pinto D, Dracheva S, Geschwind DH, Mill J, Nairn AC, Abyzov A, Pochareddy S, Prabhakar S, Weissman S, Sullivan PF, State MW, Weng Z, Peters MA, White KP, Gerstein MB, Amiri A, Armoskus C, Ashley-Koch AE, Bae T, Beckel-Mitchener A, Berman BP, Coetzee GA, Coppola G, Francoeur N, Fromer M, Gao R, Grennan K, Herstein J, Kavanagh DH, Ivanov NA, Jiang Y, Kitchen RR, Kozlenkov A, Kundakovic M, Li M, Li Z, Liu S, Mangravite LM, Mattei E, Markenscoff-Papadimitriou E, Navarro FC, North N, Omberg L, Panchision D, Parikshak N, Poschmann J, Price AJ, Purcaro M, Reddy TE, Roussos P, Schreiner S, Scuderi S, Sebra R, Shibata M, Shieh AW, Skarica M, Sun W, Swarup V, Thomas A, Tsuji J, van Bakel H, Wang D, Wang Y, Wang K, Werling DM, Willsey AJ, Witt H, Won H, Wong CC, Wray GA, Wu EY, Xu X, Yao L, Senthil G, Lehner T, Sklar P, Sestan N. The PsychENCODE project. Nature Neuroscience 2015, 18: 1707-1712. PMID: 26605881, PMCID: PMC4675669, DOI: 10.1038/nn.4156.Peer-Reviewed Original ResearchCreating Patient-Specific Neural Cells for the In Vitro Study of Brain Disorders
Brennand KJ, Marchetto MC, Benvenisty N, Brüstle O, Ebert A, Belmonte J, Kaykas A, Lancaster MA, Livesey FJ, McConnell MJ, McKay RD, Morrow EM, Muotri AR, Panchision DM, Rubin LL, Sawa A, Soldner F, Song H, Studer L, Temple S, Vaccarino FM, Wu J, Vanderhaeghen P, Gage FH, Jaenisch R. Creating Patient-Specific Neural Cells for the In Vitro Study of Brain Disorders. Stem Cell Reports 2015, 5: 933-945. PMID: 26610635, PMCID: PMC4881284, DOI: 10.1016/j.stemcr.2015.10.011.Peer-Reviewed Original ResearchImbalance of excitatory/inhibitory synaptic protein expression in iPSC-derived neurons from FOXG1+/− patients and in foxg1+/− mice
Patriarchi T, Amabile S, Frullanti E, Landucci E, Lo Rizzo C, Ariani F, Costa M, Olimpico F, W Hell J, M Vaccarino F, Renieri A, Meloni I. Imbalance of excitatory/inhibitory synaptic protein expression in iPSC-derived neurons from FOXG1+/− patients and in foxg1+/− mice. European Journal Of Human Genetics 2015, 24: 871-880. PMID: 26443267, PMCID: PMC4820038, DOI: 10.1038/ejhg.2015.216.Peer-Reviewed Original ResearchConceptsRett syndromeSynaptic markersInhibitory synapsesExcitatory/inhibitory balanceSynaptic protein expressionFetal mouse brainInhibitory synaptic markersPathogenesis of RTTExcitatory synaptic markersSevere neurodevelopmental disorderGlutamatergic markersInhibitory balanceAdult brainAdult micePrecise molecular mechanismsSynaptic differentiationPatientsMouse brainBrain synapsesPathological eventsNeuronsProtein expressionBrainGluD1Neurodevelopmental disordersContribution of maternal oxygenic state to the effects of chronic postnatal hypoxia on mouse body and brain development
Salmaso N, Dominguez M, Kravitz J, Komitova M, Vaccarino FM, Schwartz ML. Contribution of maternal oxygenic state to the effects of chronic postnatal hypoxia on mouse body and brain development. Neuroscience Letters 2015, 604: 12-17. PMID: 26222256, PMCID: PMC4568169, DOI: 10.1016/j.neulet.2015.07.033.Peer-Reviewed Original ResearchConceptsBrain weightEffects of hypoxiaDam exposureCortical volumeBody weightHypoxic conditionsBrain developmentChronic postnatal hypoxiaLow birth weightPup body weightSame hypoxic conditionsChronic hypoxia exposureEarly postnatal pupsBody weight conditionsHypoxic mothersNeurological sequelaePostnatal hypoxiaPremature infantsHypoxic pupsBirth weightChronic hypoxiaHypoxic chamberHypoxic exposureLive birthsMouse model
2014
Editorial commentary: “What does immunology have to do with brain development and neuropsychiatric disorders?”
Leckman JF, Vaccarino FM. Editorial commentary: “What does immunology have to do with brain development and neuropsychiatric disorders?”. Brain Research 2014, 1617: 1-6. PMID: 25283746, DOI: 10.1016/j.brainres.2014.09.052.Commentaries, Editorials and Letters
2013
Neurogenesis and Maturation in Neonatal Brain Injury
Salmaso N, Tomasi S, Vaccarino FM. Neurogenesis and Maturation in Neonatal Brain Injury. Clinics In Perinatology 2013, 41: 229-239. PMID: 24524457, PMCID: PMC3925307, DOI: 10.1016/j.clp.2013.10.007.ChaptersConceptsChronic perinatal hypoxiaConsequences of prematurityNeonatal brain injurySevere neurologic deficitsAttention deficit hyperactivityPerinatal hypoxiaNeurologic deficitsPreterm birthPremature birthBrain injuryAnimal modelsCognitive impairmentNeuropsychiatric conditionsMost childrenCognitive delayPartial recoveryIncidenceEnvironmental enrichmentAutism spectrum disorderBirthSpectrum disorderNormal developmentPrematurity
2012
Neurobiology meets genomic science: The promise of human-induced pluripotent stem cells
Stevens HE, Mariani J, Coppola G, Vaccarino FM. Neurobiology meets genomic science: The promise of human-induced pluripotent stem cells. Development And Psychopathology 2012, 24: 1443-1451. PMID: 23062309, PMCID: PMC3513939, DOI: 10.1017/s095457941200082x.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsHuman-induced pluripotent stem cellsPluripotent stem cellsStem cellsNeuronal cellsInduced pluripotent stem cell (iPSC) technologyPluripotent stem cell (iPSC) technologyNormal human brain developmentHuman genesSomatic cellsCell biologyStem cell technologyGene transcriptsHuman brain developmentAspects of developmentMessenger RNADevelopmental stepsGenomic scienceBiologySeries of eventsCellsBrain developmentGenesGeneticsHuman individualsTranscripts
2011
FGF Signaling Expands Embryonic Cortical Surface Area by Regulating Notch-Dependent Neurogenesis
Rash BG, Lim HD, Breunig JJ, Vaccarino FM. FGF Signaling Expands Embryonic Cortical Surface Area by Regulating Notch-Dependent Neurogenesis. Journal Of Neuroscience 2011, 31: 15604-15617. PMID: 22031906, PMCID: PMC3235689, DOI: 10.1523/jneurosci.4439-11.2011.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAnalysis of VarianceAnimalsBrainBromodeoxyuridineCaspase 3Cell CountCell DifferentiationCells, CulturedCerebral CortexDNA-Binding ProteinsElectroporationEmbryo, MammalianEye ProteinsFatty Acid-Binding Protein 7Fatty Acid-Binding ProteinsFibroblast Growth FactorsGene Expression Regulation, DevelopmentalGreen Fluorescent ProteinsHomeodomain ProteinsKi-67 AntigenMiceMice, TransgenicMutationNerve Tissue ProteinsNeurogenesisNeuronsPaired Box Transcription FactorsPAX6 Transcription FactorReceptors, Fibroblast Growth FactorReceptors, NotchRepressor ProteinsSignal TransductionStem CellsT-Box Domain ProteinsTranscription FactorsConceptsCortical neurogenesisCortical surface area expansionCortical surface expansionCortical surface areaGrowth factor receptorEmbryonic day 12.5Fibroblast growth factor receptorFGFR mutantsNormal miceCortical layer structureCortical developmentNeurogenic stagesDominant negative FGFRLoss of functionRadial progenitorsNeurogenesisNotch pathway genesSevere deficitsFactor receptorDay 12.5Notch pathwayMiceSimultaneous activationGreater proportionFGFR activity