2024
Spatially exploring RNA biology in archival formalin-fixed paraffin-embedded tissues
Bai Z, Zhang D, Gao Y, Tao B, Zhang D, Bao S, Enninful A, Wang Y, Li H, Su G, Tian X, Zhang N, Xiao Y, Liu Y, Gerstein M, Li M, Xing Y, Lu J, Xu M, Fan R. Spatially exploring RNA biology in archival formalin-fixed paraffin-embedded tissues. Cell 2024, 187: 6760-6779.e24. PMID: 39353436, DOI: 10.1016/j.cell.2024.09.001.Peer-Reviewed Original ResearchRNA biologyWhole-transcriptome sequencingMicroRNA regulatory networkSplicing dynamicsDeterministic barcodingRNA speciesRNA processingRNA variantsFFPE tissuesRegulatory networksTranscriptome sequencingSpliced isoformsNon-malignant cellsTumor clonal architecturesClonal architectureGene expressionCellular dynamicsRNAArchival formalin-fixed paraffin-embedded tissueMalignant subclonesFormalin-fixed paraffin-embedded (FFPEFFPE samplesParaffin-embedded (FFPEBiologyHuman lymphomasRepresenting core gene expression activity relationships using the latent structure implicit in Bayesian networks
Gao J, Gerstein M. Representing core gene expression activity relationships using the latent structure implicit in Bayesian networks. Bioinformatics 2024, 40: btae463. PMID: 39051682, PMCID: PMC11316617, DOI: 10.1093/bioinformatics/btae463.Peer-Reviewed Original ResearchTranscriptional regulatory networksGene regulatory networksCo-expression networkGene expression activityChIP-seqGene conservationCluster genesSupplementary dataRegulatory networksBiological networksClearer clusteringCo-expressionExpression activityBioinformaticsGenesBiomedical studiesConservationExpressionClustersSingle-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 tissuesExpressionCellsChromatinLociMultiomics
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-associationGenes
2010
Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks
Yan KK, Fang G, Bhardwaj N, Alexander RP, Gerstein M. Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks. Proceedings Of The National Academy Of Sciences Of The United States Of America 2010, 107: 9186-9191. PMID: 20439753, PMCID: PMC2889091, DOI: 10.1073/pnas.0914771107.Peer-Reviewed Original ResearchConceptsTranscriptional regulatory networksRegulatory networksCellular design principlesCall graphEvolutionary ratesGlobal regulatorOperating systemRandom mutationsSoftware systemsLiving organismBiological evolutionRapid evolutionSubsequent selectionFunctional modulesComputer operating systemsRegulatorNetwork hubsBiological systemsDesign principlesControl networkGeneric componentsHierarchical layoutGenomeEvolutionTerms of topology
2006
Genomic analysis of the hierarchical structure of regulatory networks
Yu H, Gerstein M. Genomic analysis of the hierarchical structure of regulatory networks. Proceedings Of The National Academy Of Sciences Of The United States Of America 2006, 103: 14724-14731. PMID: 17003135, PMCID: PMC1595419, DOI: 10.1073/pnas.0508637103.Peer-Reviewed Original ResearchConceptsTranscription factorsMaster transcription factorRegulatory networksRegulatory hierarchyProtein-protein interaction networkMost transcription factorsExpression of thousandsExpression level changesGenomic analysisProtein interactionsInteraction networksTarget genesDirect targetGenesEukaryotesProkaryotesCellsFundamental questionsBiologyTargetExpression