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
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