2024
Somatic mosaicism in schizophrenia brains reveals prenatal mutational processes
Maury E, Jones A, Seplyarskiy V, Nguyen T, Rosenbluh C, Bae T, Wang Y, Abyzov A, Khoshkhoo S, Chahine Y, Zhao S, Venkatesh S, Root E, Voloudakis G, Roussos P, Network B, Park P, Akbarian S, Brennand K, Reilly S, Lee E, Sunyaev S, Walsh C, Chess A. Somatic mosaicism in schizophrenia brains reveals prenatal mutational processes. Science 2024, 386: 217-224. PMID: 39388546, PMCID: PMC11490355, DOI: 10.1126/science.adq1456.Peer-Reviewed Original ResearchConceptsTranscription factor binding sitesWhole-genome sequencingOpen chromatinMutational processesSomatic mutationsFactor binding sitesSchizophrenia casesSchizophrenia risk genesSomatic mosaicismSomatic variantsRisk genesG mutationGene expressionGermline mutationsBinding sitesGenesMutationsIncreased somatic mutationsChromatinMosaic somatic mutationsPrenatal neurogenesisContext of schizophreniaBrain neuronsSchizophrenia brainVariantsSingle-cell genomics and regulatory networks for 388 human brains
Emani P, Liu J, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee C, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken T, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard J, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman G, Huang A, Jiang Y, Jin T, Jorstad N, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran J, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan A, Riesenmy T, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini K, Wamsley B, Wang G, Xia Y, Xiao S, Yang A, Zheng S, Gandal M, Lee D, Lein E, Roussos P, Sestan N, Weng Z, White K, Won H, Girgenti M, Zhang J, Wang D, Geschwind D, Gerstein M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Berretta S, Bharadwaj R, Bhattacharya A, Brennand K, Capauto D, Champagne F, Chatzinakos C, Chen H, Cheng L, Chess A, Chien J, 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, Duong D, Eagles N, Edelstein J, Galani K, Girdhar K, Goes F, Greenleaf W, Guo H, Guo Q, Hadas Y, Hallmayer J, Han X, Haroutunian V, He C, Hicks S, Ho M, Ho L, Huang Y, Huuki-Myers L, Hyde T, Iatrou A, Inoue F, Jajoo A, Jiang L, Jin P, Jops C, Jourdon A, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Li J, Li M, Lin X, Liu S, Liu C, Loupe J, Lu D, Ma L, Mariani J, Martinowich K, Maynard K, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Mukamel E, Nairn A, Nemeroff C, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Pinto D, Pochareddy S, Pollard K, Pollen A, Przytycki P, Purmann C, Qin Z, Qu P, Raj T, Reach S, Reimonn T, Ressler K, Ross D, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Seyfried N, Shao Z, 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, Wang T, Wang S, Wang Y, Wei Y, Weimer A, Weinberger D, Wen C, Whalen S, Willsey A, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang Y, Ziffra R, Zeier Z, Zintel T. Single-cell genomics and regulatory networks for 388 human brains. Science 2024, 384: eadi5199. PMID: 38781369, PMCID: PMC11365579, DOI: 10.1126/science.adi5199.Peer-Reviewed Original ResearchConceptsSingle-cell genomicsSingle-cell expression quantitative trait locusExpression quantitative trait lociDrug targetsQuantitative trait lociPopulation-level variationSingle-cell expressionCell typesDisease-risk genesTrait lociGene familyRegulatory networksGene expressionCell-typeMultiomics datasetsSingle-nucleiGenomeGenesCellular changesHeterogeneous tissuesExpressionCellsChromatinLociMultiomicsCross-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 maturationRegulationCharacterization of enhancer activity in early human neurodevelopment using Massively Parallel Reporter Assay (MPRA) and forebrain organoids
Capauto D, Wang Y, Wu F, Norton S, Mariani J, Inoue F, Crawford G, Ahituv N, Abyzov A, Vaccarino F. Characterization of enhancer activity in early human neurodevelopment using Massively Parallel Reporter Assay (MPRA) and forebrain organoids. Scientific Reports 2024, 14: 3936. PMID: 38365907, PMCID: PMC10873509, DOI: 10.1038/s41598-024-54302-7.Peer-Reviewed Original ResearchConceptsMassively parallel reporter assaysGene expressionRegulation of gene expressionForebrain organoidsHuman fetal tissuesHigh-throughput assayReporter assayFetal tissuesStem cellsNeurodevelopmentHuman neurodevelopmentActivation signalsEnhanced activityGenesOrganoidsForebrainBrain organoidsAssayBrain
2023
Comprehensive multi-omic profiling of somatic mutations in malformations of cortical development
Chung C, Yang X, Bae T, Vong K, Mittal S, Donkels C, Westley Phillips H, Li Z, Marsh A, Breuss M, Ball L, Garcia C, George R, Gu J, Xu M, Barrows C, James K, Stanley V, Nidhiry A, Khoury S, Howe G, Riley E, Xu X, Copeland B, Wang Y, Kim S, Kang H, Schulze-Bonhage A, Haas C, Urbach H, Prinz M, Limbrick D, Gurnett C, Smyth M, Sattar S, Nespeca M, Gonda D, Imai K, Takahashi Y, Chen H, Tsai J, Conti V, Guerrini R, Devinsky O, Silva W, Machado H, Mathern G, Abyzov A, Baldassari S, Baulac S, Gleeson J. Comprehensive multi-omic profiling of somatic mutations in malformations of cortical development. Nature Genetics 2023, 55: 209-220. PMID: 36635388, PMCID: PMC9961399, DOI: 10.1038/s41588-022-01276-9.Peer-Reviewed Original ResearchConceptsSingle-nucleus RNA sequencingSpatiotemporal expression patternsSomatic mutationsTarget amplicon sequencingLow allelic fractionsMulti-omics profilingGene setsRNA sequencingFunctional validationCellular organizationExpression patternsGenotype-phenotype correlation analysisGenetic landscapeCortical developmentMutationsGenetic causeUtero electroporationSomatic mosaic mutationsGenesCritical roleMosaic mutationsSequencingNeuronal hyperexcitabilityBrain resectionProfiling
2022
Analysis 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
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 Research
2013
Analysis of variable retroduplications in human populations suggests coupling of retrotransposition to cell division
Abyzov A, Iskow R, Gokcumen O, Radke DW, Balasubramanian S, Pei B, Habegger L, Consortium T, Lee C, Gerstein M. Analysis of variable retroduplications in human populations suggests coupling of retrotransposition to cell division. Genome Research 2013, 23: 2042-2052. PMID: 24026178, PMCID: PMC3847774, DOI: 10.1101/gr.154625.113.Peer-Reviewed Original ResearchConceptsCell divisionCorrect phylogenetic treeGenomes Project ConsortiumHuman populationTranscription of mRNARetroduplicationPhylogenetic treeParent genesGenomic integrationCell cycleG1 transitionMore copiesGenesRetrotranspositionHuman subpopulationsMultiple linesRetrogenesPseudogenesTranscriptionDivisionRNAVariantsProteinMRNACopies
2012
Architecture of the human regulatory network derived from ENCODE data
Gerstein MB, Kundaje A, Hariharan M, Landt SG, Yan KK, Cheng C, Mu XJ, Khurana E, Rozowsky J, Alexander R, Min R, Alves P, Abyzov A, Addleman N, Bhardwaj N, Boyle AP, Cayting P, Charos A, Chen DZ, Cheng Y, Clarke D, Eastman C, Euskirchen G, Frietze S, Fu Y, Gertz J, Grubert F, Harmanci A, Jain P, Kasowski M, Lacroute P, Leng J, Lian J, Monahan H, O’Geen H, Ouyang Z, Partridge EC, Patacsil D, Pauli F, Raha D, Ramirez L, Reddy TE, Reed B, Shi M, Slifer T, Wang J, Wu L, Yang X, Yip KY, Zilberman-Schapira G, Batzoglou S, Sidow A, Farnham PJ, Myers RM, Weissman SM, Snyder M. Architecture of the human regulatory network derived from ENCODE data. Nature 2012, 489: 91-100. PMID: 22955619, PMCID: PMC4154057, DOI: 10.1038/nature11245.Peer-Reviewed Original ResearchMeSH KeywordsAllelesCell LineDNAEncyclopedias as TopicGATA1 Transcription FactorGene Expression ProfilingGene Regulatory NetworksGenome, HumanGenomicsHumansK562 CellsMolecular Sequence AnnotationOrgan SpecificityPhosphorylationPolymorphism, Single NucleotideProtein Interaction MapsRegulatory Sequences, Nucleic AcidRNA, UntranslatedSelection, GeneticTranscription FactorsTranscription Initiation SiteConceptsTranscription factorsRegulatory networksHuman transcriptional regulatory networkHuman regulatory networkSpecific genomic locationsTranscription-related factorsState of genesTranscriptional regulatory networksAllele-specific activityPersonal genome sequencesGenomic locationStrong selectionGenome sequenceENCODE dataGenomic informationInformation-flow bottlenecksRegulatory informationConnected network componentsCombinatorial fashionInfluences expressionHuman biologyBinding informationNetwork motifsCo-associationGenesRegulatory element copy number differences shape primate expression profiles
Iskow RC, Gokcumen O, Abyzov A, Malukiewicz J, Zhu Q, Sukumar AT, Pai AA, Mills RE, Habegger L, Cusanovich DA, Rubel MA, Perry GH, Gerstein M, Stone AC, Gilad Y, Lee C. Regulatory element copy number differences shape primate expression profiles. Proceedings Of The National Academy Of Sciences Of The United States Of America 2012, 109: 12656-12661. PMID: 22797897, PMCID: PMC3411951, DOI: 10.1073/pnas.1205199109.Peer-Reviewed Original ResearchConceptsCopy number differencesExpression differencesExpression profilesLong intergenic noncoding RNAsCopy numberIntergenic noncoding RNAsGene expression differencesSignificant expression differencesGene expression profilesLevel of RNAUltraconserved elementsRegulatory regionsNoncoding RNAsSelective pressureDifferent genesRegulatory moleculesDevelopmental pathwaysPhenotypic differencesPrimate speciesGenesRNANumber differenceSpeciesExpressionPseudogenes
2010
Analysis of Combinatorial Regulation: Scaling of Partnerships between Regulators with the Number of Governed Targets
Bhardwaj N, Carson MB, Abyzov A, Yan KK, Lu H, Gerstein MB. Analysis of Combinatorial Regulation: Scaling of Partnerships between Regulators with the Number of Governed Targets. PLOS Computational Biology 2010, 6: e1000755. PMID: 20523742, PMCID: PMC2877725, DOI: 10.1371/journal.pcbi.1000755.Peer-Reviewed Original Research
2007
Structure SNP (StSNP): a web server for mapping and modeling nsSNPs on protein structures with linkage to metabolic pathways
Uzun A, Leslin C, Abyzov A, Ilyin V. Structure SNP (StSNP): a web server for mapping and modeling nsSNPs on protein structures with linkage to metabolic pathways. Nucleic Acids Research 2007, 35: w384-w392. PMID: 17537826, PMCID: PMC1933130, DOI: 10.1093/nar/gkm232.Peer-Reviewed Original ResearchConceptsMetabolic pathwaysSNP databasePathway informationProtein structureMulti-protein complexesOpen reading frameAmino acid sequenceMetabolic pathway informationDisease-related pathwaysNCBI SNP databaseProtein databaseReading frameMolecular basisAcid sequencePathway relationsNsSNPsFunctional consequencesComparative modelingProteinEdu/PathwayGenesWeb serverSNPsStructure data