2016
A generic, cost-effective, and scalable cell lineage analysis platform
Biezuner T, Spiro A, Raz O, Amir S, Milo L, Adar R, Chapal-Ilani N, Berman V, Fried Y, Ainbinder E, Cohen G, Barr H, Halaban R, Shapiro E. A generic, cost-effective, and scalable cell lineage analysis platform. Genome Research 2016, 26: 1588-1599. PMID: 27558250, PMCID: PMC5088600, DOI: 10.1101/gr.202903.115.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsCell Line, TumorCell LineageCells, CulturedHumansMaleMicrofluidicsMiddle AgedSequence Analysis, DNASingle-Cell AnalysisConceptsLineage analysisSingle cell lineage analysisSingle-cell sequencing dataSingle-cell genomicsCurrent sequencing-based methodsIndividual cellsCell lineage analysisSingle-cell sequencingSequencing-based methodsLineage treesSequencing dataLineage relationsCellsTreesGenomicsAnalysis platformInput cellsSequencingBulk analysisVivoDiscoveryLandscape
2012
Type II p21-activated kinases (PAKs) are regulated by an autoinhibitory pseudosubstrate
Ha BH, Davis MJ, Chen C, Lou HJ, Gao J, Zhang R, Krauthammer M, Halaban R, Schlessinger J, Turk BE, Boggon TJ. Type II p21-activated kinases (PAKs) are regulated by an autoinhibitory pseudosubstrate. Proceedings Of The National Academy Of Sciences Of The United States Of America 2012, 109: 16107-16112. PMID: 22988085, PMCID: PMC3479536, DOI: 10.1073/pnas.1214447109.Peer-Reviewed Original ResearchConceptsP21-activated kinasePhosphorylated activation loopActivation loop phosphorylationCritical proline residueRho family GTPasesBcl-2/BclCellular morphological changesPAK regulationStructure-guided approachLoop phosphorylationPseudosubstrate regionAutoinhibitory pseudosubstratePseudosubstrate motifActivation loopCatalytic domainSrc SH3Cell motilityMolecular basisProline residuesKey effectorsCell deathPAK4SH3KinasePseudosubstrateExome sequencing identifies recurrent somatic RAC1 mutations in melanoma
Krauthammer M, Kong Y, Ha BH, Evans P, Bacchiocchi A, McCusker J, Cheng E, Davis MJ, Goh G, Choi M, Ariyan S, Narayan D, Dutton-Regester K, Capatana A, Holman EC, Bosenberg M, Sznol M, Kluger HM, Brash DE, Stern DF, Materin MA, Lo RS, Mane S, Ma S, Kidd KK, Hayward NK, Lifton RP, Schlessinger J, Boggon TJ, Halaban R. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nature Genetics 2012, 44: 1006-1014. PMID: 22842228, PMCID: PMC3432702, DOI: 10.1038/ng.2359.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCase-Control StudiesDNA Mutational AnalysisExomeFemaleGene FrequencyGenetic Predisposition to DiseaseHumansMaleMelanomaMiddle AgedModels, MolecularMutationProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)Rac1 GTP-Binding ProteinSequence Analysis, DNASkin NeoplasmsUveal NeoplasmsConceptsSun-exposed melanomas
2009
Genome-wide screen of promoter methylation identifies novel markers in melanoma
Koga Y, Pelizzola M, Cheng E, Krauthammer M, Sznol M, Ariyan S, Narayan D, Molinaro AM, Halaban R, Weissman SM. Genome-wide screen of promoter methylation identifies novel markers in melanoma. Genome Research 2009, 19: 1462-1470. PMID: 19491193, PMCID: PMC2720187, DOI: 10.1101/gr.091447.109.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Signal TransducingAdultAgedBiomarkers, TumorCells, CulturedCluster AnalysisCollagenCollagen Type IDNA MethylationFemaleGene Expression ProfilingGenome, HumanGenome-Wide Association StudyHSP20 Heat-Shock ProteinsHumansInfant, NewbornMaleMelanomaMetallothioneinMiddle AgedMolecular ChaperonesNuclear ProteinsNucleoplasminsOligonucleotide Array Sequence AnalysisPhosphoproteinsPromoter Regions, GeneticProteinsReproducibility of ResultsReverse Transcriptase Polymerase Chain ReactionSequence Analysis, DNATumor Cells, CulturedConceptsDifferential gene expressionGene expressionPromoter methylationGenome-wide promoter methylationGenome-wide integrative analysisPromoter CpG contentMethylation markersGenome-wide screenSequencing of bisulfiteTranscription start siteMelanoma cell strainsCell strainsTranscriptional machineryNovel genesEpigenetic modificationsDNA methylationIdentifies novel markersStart siteSnap-frozen tissuesCpG contentAdult melanocytesIntegrative analysisReal-time reverse transcriptase PCRHuman diseasesMethylation
2008
MEDME: An experimental and analytical methodology for the estimation of DNA methylation levels based on microarray derived MeDIP-enrichment
Pelizzola M, Koga Y, Urban AE, Krauthammer M, Weissman S, Halaban R, Molinaro AM. MEDME: An experimental and analytical methodology for the estimation of DNA methylation levels based on microarray derived MeDIP-enrichment. Genome Research 2008, 18: 1652-1659. PMID: 18765822, PMCID: PMC2556264, DOI: 10.1101/gr.080721.108.Peer-Reviewed Original ResearchConceptsDNA methylation levelsDNA methylationMethylation levelsRelative DNA methylation levelsChromosome-wide levelBisulfite genomic DNA sequencingGenome-wide studiesMelanoma cell strainsDNA methylation statusGenomic DNA sequencingTranscriptional machineryNormal human melanocytesMethylated CpGsMethylated fragmentsEpigenetic modificationsMethylation estimatesHigh-throughput settingHuman diseasesHuman melanocytesMethylationMethylation statusDNA sequencingAntibody enrichmentGenomeCell strains