2025
Modeling SMAD2 Mutations in Induced Pluripotent Stem Cells Provides Insights Into Cardiovascular Disease Pathogenesis
Ward T, Morton S, Venturini G, Tai W, Jang M, Gorham J, Delaughter D, Wasson L, Khazal Z, Homsy J, Gelb B, Chung W, Bruneau B, Brueckner M, Tristani-Firouzi M, DePalma S, Seidman C, Seidman J. Modeling SMAD2 Mutations in Induced Pluripotent Stem Cells Provides Insights Into Cardiovascular Disease Pathogenesis. Journal Of The American Heart Association 2025, 14: e036860. PMID: 40028843, PMCID: PMC12184555, DOI: 10.1161/jaha.124.036860.Peer-Reviewed Original ResearchConceptsLoss-of-functionCongenital heart diseaseChromatin accessibilityMissense variantsCHD probandsPluripotent stem cellsHomozygous loss-of-functionCHD-associated genesHeterozygous loss-of-functionTranscription factor bindingMutant induced pluripotent stem cellsChromatin immunoprecipitation dataChromatin peaksStem cellsChromatin interactionsInduced pluripotent stem cellsFactor bindingTranscription factor NanogExome sequencingImmunoprecipitation dataTranscription factorsRNA sequencingChromatinMissenseMolecular consequences
2024
EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics
Gao Z, Liu Q, Zeng W, Jiang R, Wong W. EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics. Genome Biology 2024, 25: 310. PMID: 39696471, PMCID: PMC11657395, DOI: 10.1186/s13059-024-03449-7.Peer-Reviewed Original ResearchConceptsTranscription factor activityChromatin interactionsEpigenomic signalsGenomic interactionsHuman epigenomeGene regulationVariant impactBiological sequencesCellular contextInteraction predictionFactor activityGenomeChromatinEpigenomeTranscriptionGenesHttp://healthSequenceRegulationTransformer-based modelsInteractionMassively parallel disruption of enhancers active in human neural stem cells
Geller E, Noble M, Morales M, Gockley J, Emera D, Uebbing S, Cotney J, Noonan J. Massively parallel disruption of enhancers active in human neural stem cells. Cell Reports 2024, 43: 113693. PMID: 38271204, PMCID: PMC11078116, DOI: 10.1016/j.celrep.2024.113693.Peer-Reviewed Original ResearchHuman neural stem cellsNeural stem cellsStem cellsProliferation phenotypeAssociated with neurodevelopmental disordersNeurodevelopmental disordersEnhanced disruptionHuman Accelerated RegionsNeural progenitor proliferationEffects of genetic variationHuman cortical evolutionProgenitor proliferationSelf-RenewalNeural progenitorsProgenitor populationsCerebral cortexChromatin interactionsHuman cerebral cortexNeural progenitor populationsGene regulationRegulatory elementsConserved regionGene disruptionGenetic variationRegulatory relationships
2023
The Transcriptional Landscape of Ph+B-ALL Is Orchestrated By Long-Range Enhancer-Promoter Interactions and the Coordinated Action of Phosphorylation-Dependent and Phosphorylation-Independent Transcription Factors
Ng H, Robinson M, Malysheva V, Deniz O, Crump N, Cosgun K, Helian K, Spivakov M, Müschen M, Feldhahn N. The Transcriptional Landscape of Ph+B-ALL Is Orchestrated By Long-Range Enhancer-Promoter Interactions and the Coordinated Action of Phosphorylation-Dependent and Phosphorylation-Independent Transcription Factors. Blood 2023, 142: 2779. DOI: 10.1182/blood-2023-173435.Peer-Reviewed Original ResearchTranscription factorsTranscriptional programsEnhancer signatureGene expressionChromatin interactionsTranscriptional changesTyrosine kinaseAdditional transcription factorsMotif enrichment analysisPromoter-enhancer interactionsCis-regulatory elementsEnhancer-promoter interactionsPromoter capture HiNon-promoter regionsUnique transcriptional programGene expression changesCoordinated actionMurine B cell precursorsOncogenic tyrosine kinasesEnhancer usageActive chromatinActive genesEnhancer landscapeTranscriptional landscapeActive enhancers
2021
Oncogenic extrachromosomal DNA functions as mobile enhancers to globally amplify chromosomal transcription
Zhu Y, Gujar A, Wong C, Tjong H, Ngan C, Gong L, Chen Y, Kim H, Liu J, Li M, Mil-Homens A, Maurya R, Kuhlberg C, Sun F, Yi E, deCarvalho A, Ruan Y, Verhaak R, Wei C. Oncogenic extrachromosomal DNA functions as mobile enhancers to globally amplify chromosomal transcription. Cancer Cell 2021, 39: 694-707.e7. PMID: 33836152, PMCID: PMC8119378, DOI: 10.1016/j.ccell.2021.03.006.Peer-Reviewed Original ResearchConceptsGenome-wide activationSingle-molecule resolutionMobile enhancerChromatin interactionsChromosomal interactionsChromatin contactsTranscription controlChromosomal transcriptionChromosomal targetsTranscriptional programsTranscriptional enhancersChromosomal genesChIA-PETGene transcriptionCancer genomesInteraction networksDNA functionH3K27ac signalProstate cancer cellsCircular DNAEcDNAsExpression levelsCancer cellsOncogenic alterationsTranscription
2020
Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals
Xu K, Li B, McGinnis KA, Vickers-Smith R, Dao C, Sun N, Kember RL, Zhou H, Becker WC, Gelernter J, Kranzler HR, Zhao H, Justice AC. Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals. Nature Communications 2020, 11: 5302. PMID: 33082346, PMCID: PMC7598939, DOI: 10.1038/s41467-020-18489-3.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesLarge genome-wide association studiesMillion Veteran ProgramAssociation studiesExpression quantitative trait lociQuantitative trait lociChromatin interactionsComplex traitsFunctional annotationTrait lociSequencing ConsortiumDozen genesSignificant lociSmoking phenotypesLociMultiple populationsNew insightsPhenotypeVeteran ProgramGenetic vulnerabilityGenesTraitsAnnotationEuropean AmericansConsortiumFine-mapping of 150 breast cancer risk regions identifies 191 likely target genes
Fachal L, Aschard H, Beesley J, Barnes DR, Allen J, Kar S, Pooley KA, Dennis J, Michailidou K, Turman C, Soucy P, Lemaçon A, Lush M, Tyrer JP, Ghoussaini M, Moradi Marjaneh M, Jiang X, Agata S, Aittomäki K, Alonso MR, Andrulis IL, Anton-Culver H, Antonenkova NN, Arason A, Arndt V, Aronson KJ, Arun BK, Auber B, Auer PL, Azzollini J, Balmaña J, Barkardottir RB, Barrowdale D, Beeghly-Fadiel A, Benitez J, Bermisheva M, Białkowska K, Blanco AM, Blomqvist C, Blot W, Bogdanova NV, Bojesen SE, Bolla MK, Bonanni B, Borg A, Bosse K, Brauch H, Brenner H, Briceno I, Brock IW, Brooks-Wilson A, Brüning T, Burwinkel B, Buys SS, Cai Q, Caldés T, Caligo MA, Camp NJ, Campbell I, Canzian F, Carroll JS, Carter BD, Castelao JE, Chiquette J, Christiansen H, Chung WK, Claes KBM, Clarke CL, Collée J, Cornelissen S, Couch F, Cox A, Cross S, Cybulski C, Czene K, Daly M, de la Hoya M, Devilee P, Diez O, Ding Y, Dite G, Domchek S, Dörk T, dos-Santos-Silva I, Droit A, Dubois S, Dumont M, Duran M, Durcan L, Dwek M, Eccles D, Engel C, Eriksson M, Evans D, Fasching P, Fletcher O, Floris G, Flyger H, Foretova L, Foulkes W, Friedman E, Fritschi L, Frost D, Gabrielson M, Gago-Dominguez M, Gambino G, Ganz P, Gapstur S, Garber J, García-Sáenz J, Gaudet M, Georgoulias V, Giles G, Glendon G, Godwin A, Goldberg M, Goldgar D, González-Neira A, Tibiletti M, Greene M, Grip M, Gronwald J, Grundy A, Guénel P, Hahnen E, Haiman C, Håkansson N, Hall P, Hamann U, Harrington P, Hartikainen J, Hartman M, He W, Healey C, Heemskerk-Gerritsen B, Heyworth J, Hillemanns P, Hogervorst F, Hollestelle A, Hooning M, Hopper J, Howell A, Huang G, Hulick P, Imyanitov E, Isaacs C, Iwasaki M, Jager A, Jakimovska M, Jakubowska A, James P, Janavicius R, Jankowitz R, John E, Johnson N, Jones M, Jukkola-Vuorinen A, Jung A, Kaaks R, Kang D, Kapoor P, Karlan B, Keeman R, Kerin M, Khusnutdinova E, Kiiski J, Kirk J, Kitahara C, Ko Y, Konstantopoulou I, Kosma V, Koutros S, Kubelka-Sabit K, Kwong A, Kyriacou K, Laitman Y, Lambrechts D, Lee E, Leslie G, Lester J, Lesueur F, Lindblom A, Lo W, Long J, Lophatananon A, Loud J, Lubiński J, MacInnis R, Maishman T, Makalic E, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Martinez M, Matsuo K, Maurer T, Mavroudis D, Mayes R, McGuffog L, McLean C, Mebirouk N, Meindl A, Miller A, Miller N, Montagna M, Moreno F, Muir K, Mulligan A, Muñoz-Garzon V, Muranen T, Narod S, Nassir R, Nathanson K, Neuhausen S, Nevanlinna H, Neven P, Nielsen F, Nikitina-Zake L, Norman A, Offit K, Olah E, Olopade O, Olsson H, Orr N, Osorio A, Pankratz V, Papp J, Park S, Park-Simon T, Parsons M, Paul J, Pedersen I, Peissel B, Peshkin B, Peterlongo P, Peto J, Plaseska-Karanfilska D, Prajzendanc K, Prentice R, Presneau N, Prokofyeva D, Pujana M, Pylkäs K, Radice P, Ramus S, Rantala J, Rau-Murthy R, Rennert G, Risch H, Robson M, Romero A, Rossing M, Saloustros E, Sánchez-Herrero E, Sandler D, Santamariña M, Saunders C, Sawyer E, Scheuner M, Schmidt D, Schmutzler R, Schneeweiss A, Schoemaker M, Schöttker B, Schürmann P, Scott C, Scott R, Senter L, Seynaeve C, Shah M, Sharma P, Shen C, Shu X, Singer C, Slavin T, Smichkoska S, Southey M, Spinelli J, Spurdle A, Stone J, Stoppa-Lyonnet D, Sutter C, Swerdlow A, Tamimi R, Tan Y, Tapper W, Taylor J, Teixeira M, Tengström M, Teo S, Terry M, Teulé A, Thomassen M, Thull D, Tischkowitz M, Toland A, Tollenaar R, Tomlinson I, Torres D, Torres-Mejía G, Troester M, Truong T, Tung N, Tzardi M, Ulmer H, Vachon C, van Asperen C, van der Kolk L, van Rensburg E, Vega A, Viel A, Vijai J, Vogel M, Wang Q, Wappenschmidt B, Weinberg C, Weitzel J, Wendt C, Wildiers H, Winqvist R, Wolk A, Wu A, Yannoukakos D, Zhang Y, Zheng W, Hunter D, Pharoah P, Chang-Claude J, García-Closas M, Schmidt M, Milne R, Kristensen V, French J, Edwards S, Antoniou A, Chenevix-Trench G, Simard J, Easton D, Kraft P, Dunning A. Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes. Nature Genetics 2020, 52: 56-73. PMID: 31911677, PMCID: PMC6974400, DOI: 10.1038/s41588-019-0537-1.Peer-Reviewed Original ResearchConceptsCausal variantsTranscription factorsTarget genesActive gene regulatory regionsHigh-confidence target genesGenomic feature annotationsGenome-wide association studiesBreast cancer risk variantsGene regulatory regionsCredible causal variantsGene ontology pathwaysChromatin interactionsFunctional annotationGenomic regionsOntology pathwaysRegulatory regionsGenomic featuresCancer driversGene expressionAssociation studiesAssociation analysisGenesLinkage disequilibriumRisk variantsHigh posterior probability
2018
NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise
Wong VC, Bass VL, Bullock ME, Chavali AK, Lee REC, Mothes W, Gaudet S, Miller-Jensen K. NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise. Cell Reports 2018, 22: 585-599. PMID: 29346759, PMCID: PMC5812697, DOI: 10.1016/j.celrep.2017.12.080.Peer-Reviewed Original ResearchConceptsTranscriptional noiseIntegration sitesDiverse phenotypesRNA polymerase II regulationNoisy gene expressionGenomic integration sitesLive-cell imagingNF-κB activationChromatin environmentChromatin stateViral activationChromatin interactionsTranscript abundanceTranscription factor nuclear factor κBDivergent phenotypesGene expressionNoisy expressionNF-κBTranscript numbersNuclear factor κBPhenotypeTumor necrosis factorFactor κBActivationExpression
2017
Developmentally regulated higher-order chromatin interactions orchestrate B cell fate commitment
Boya R, Yadavalli AD, Nikhat S, Kurukuti S, Palakodeti D, Pongubala JMR. Developmentally regulated higher-order chromatin interactions orchestrate B cell fate commitment. Nucleic Acids Research 2017, 45: 11070-11087. PMID: 28977418, PMCID: PMC5737614, DOI: 10.1093/nar/gkx722.Peer-Reviewed Original ResearchConceptsChromatin reorganizationHigher-order chromatin interactionsGenome-wide expression profilesCell fate choiceCell fate determinationCell fate commitmentHi-C analysisMulti-potent progenitorsB cell fate determinationGene expression patternsB cell fate choicesChromatin architectureGenome architectureGenome organizationChromatin interactionsTranscription regulationEpigenetic landscapeFate determinationGenomic lociFate commitmentB compartmentsCommitted stateDevelopmental switchInteraction landscapeExpression patterns
2016
Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions
Jiang T, Raviram R, Snetkova V, Rocha PP, Proudhon C, Badri S, Bonneau R, Skok JA, Kluger Y. Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions. Nucleic Acids Research 2016, 44: 8714-8725. PMID: 27439714, PMCID: PMC5062970, DOI: 10.1093/nar/gkw568.Peer-Reviewed Original ResearchConceptsMulti-locus interactionsDNA FISHGene regulationChromosome conformation capture techniquesFunctional importancePairwise chromatin interactionsChromatin interactionsTranscriptional outputRegulatory elementsEnhancer elementsBiological settingsSame cellsSimultaneous interactionFishNew insightsEnhancerRegulationReceptor enhancerCapture techniquesInteractionTCRBRAG1 targeting in the genome is dominated by chromatin interactions mediated by the non-core regions of RAG1 and RAG2
Maman Y, Teng G, Seth R, Kleinstein SH, Schatz DG. RAG1 targeting in the genome is dominated by chromatin interactions mediated by the non-core regions of RAG1 and RAG2. Nucleic Acids Research 2016, 44: 9624-9637. PMID: 27436288, PMCID: PMC5175335, DOI: 10.1093/nar/gkw633.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBinding SitesChromatinChromatin ImmunoprecipitationGenomeGenomic InstabilityHigh-Throughput Nucleotide SequencingHistonesHomeodomain ProteinsHumansMiceNucleotide MotifsPromoter Regions, GeneticProtein BindingProtein Interaction Domains and MotifsRecombination, GeneticV(D)J RecombinationConceptsAntigen receptor lociNon-core regionsReceptor locusPlant homeodomain (PHD) fingerChIP-seq dataWide bindingChromatin interactionsAdditional chromatinLysine 4Off-target activityGenomic featuresHistone 3Novel roleRAG1LociChromatinGenomeRAG2Observed patternsDistinct modesBindingH3K4me3H3K27acEndonucleaseRelative contribution
2014
Development of a novel method to create double-strand break repair fingerprints using next-generation sequencing
Soong CP, Breuer GA, Hannon RA, Kim SD, Salem AF, Wang G, Yu R, Carriero NJ, Bjornson R, Sundaram RK, Bindra RS. Development of a novel method to create double-strand break repair fingerprints using next-generation sequencing. DNA Repair 2014, 26: 44-53. PMID: 25547252, DOI: 10.1016/j.dnarep.2014.12.002.Peer-Reviewed Original ResearchConceptsHomologous recombinationNHEJ repairChromosomal lociDSB repair pathway choiceDNA double-strand break repairEndogenous chromosomal locusEfficient DNA double-strand break repairDouble-strand break repairDSB repair proteinsRepair pathway choiceDNA damaging agentsSequencing-based approachesDSB repair activityNext-generation sequencing-based approachChromatin interactionsGenomic integrityDSB repairMammalian cellsNext-generation sequencingBreak repairPathway choiceRepair proteinsReporter geneDamaging agentsRepair assays
2013
Transcriptional regulation in pluripotent stem cells by methyl CpG-binding protein 2 (MeCP2)
Tanaka Y, Kim KY, Zhong M, Pan X, Weissman SM, Park IH. Transcriptional regulation in pluripotent stem cells by methyl CpG-binding protein 2 (MeCP2). Human Molecular Genetics 2013, 23: 1045-1055. PMID: 24129406, PMCID: PMC3900111, DOI: 10.1093/hmg/ddt500.Peer-Reviewed Original ResearchConceptsPluripotent stem cellsMutant MECP2X chromosomeMethyl-CpGStem cellsGene expressionLong-range chromatin interactionsFundamental cellular physiologyRett syndromeMitochondrial membrane proteinInactive X chromosomeProtein 2Chromatin interactionsTranscriptional regulationTranscription regulatorsCellular physiologyTranscriptome analysisLoss of functionMembrane proteinsMeCP2 resultsDe novo mutationsRegulatory mechanismsMeCP2ChromosomesRTT patientsThe genomic landscape of cohesin-associated chromatin interactions
DeMare LE, Leng J, Cotney J, Reilly SK, Yin J, Sarro R, Noonan JP. The genomic landscape of cohesin-associated chromatin interactions. Genome Research 2013, 23: 1224-1234. PMID: 23704192, PMCID: PMC3730097, DOI: 10.1101/gr.156570.113.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBinding SitesCCCTC-Binding FactorCell Cycle ProteinsChromatinChromatin ImmunoprecipitationChromosomal Proteins, Non-HistoneEnhancer Elements, GeneticGene Expression Regulation, DevelopmentalGenomeHistonesLimb BudsMiceMice, Inbred C57BLOrgan SpecificityPromoter Regions, GeneticProtein SubunitsRepressor ProteinsConceptsPaired-end tag sequencingGenome-wide scaleInsulator protein CTCFChromatin interaction analysisEnhancer-promoter interactionsEnhancer-promoter communicationEmbryonic stem cellsChromatin stateProtein CTCFChromatin interactionsTag sequencingDNA loopsRegulatory architectureMouse limbRegulatory outputMouse embryosGenomic landscapeMultiple tissuesCohesinStem cellsCTCFPromoterDemarcate regionsInteraction analysisGenome
2011
Integrated Genome-Wide CTCF and CohesinSA1 Occupancy and Expression Analyses in Erythropoiesis
Schulz V, Steiner L, Maksimova Y, Gallagher P. Integrated Genome-Wide CTCF and CohesinSA1 Occupancy and Expression Analyses in Erythropoiesis. Blood 2011, 118: 1305. DOI: 10.1182/blood.v118.21.1305.1305.Peer-Reviewed Original ResearchSites of CTCFCTCF sitesCell-type specificIntergenic regionErythroid cellsChromatin domainsCohesin complexCell typesGene promoterRefSeq genesLong-range chromatin interactionsPrimary human erythroid cellsRepressive chromatin marksCell type-specific mannerDistal intergenic regionsMacromolecule catabolic processHigh-throughput sequencingHuman erythroid cellsMRNA transcriptome analysisChromatin marksChromatin interactionsChromosome segregationInduction of apoptosisCTCF bindingTranscriptional activator
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