2019
Integrating multiomics longitudinal data to reconstruct networks underlying lung development
Ding J, Ahangari F, Espinoza CR, Chhabra D, Nicola T, Yan X, Lal CV, Hagood JS, Kaminski N, Bar-Joseph Z, Ambalavanan N. Integrating multiomics longitudinal data to reconstruct networks underlying lung development. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2019, 317: l556-l568. PMID: 31432713, PMCID: PMC6879899, DOI: 10.1152/ajplung.00554.2018.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAnimals, NewbornChildChild, PreschoolDNA MethylationEpigenesis, GeneticFemaleGene Expression ProfilingGene Expression Regulation, DevelopmentalGene Regulatory NetworksHigh-Throughput Nucleotide SequencingHumansImmunity, InnateInfantInfant, NewbornLungMaleMiceMice, Inbred C57BLMicroRNAsOrganogenesisProteomicsPulmonary AlveoliRNA, MessengerSingle-Cell AnalysisTranscriptomeConceptsSingle-cell RNA-seq dataLung developmentDynamic regulatory networksOmics data setsRNA-seq dataIndividual cell typesHuman lung developmentRegulatory networksDNA methylationLaser capture microdissectionEpigenetic changesExpression trajectoriesKey pathwaysCell typesActive pathwaysCapture microdissectionRegulatorKey eventsInnate immunityNew insightsSpecific key eventsPathwayComprehensive understandingProteomicsMethylation
2017
Selecting the most appropriate time points to profile in high-throughput studies
Kleyman M, Sefer E, Nicola T, Espinoza C, Chhabra D, Hagood JS, Kaminski N, Ambalavanan N, Bar-Joseph Z. Selecting the most appropriate time points to profile in high-throughput studies. ELife 2017, 6: e18541. PMID: 28124972, PMCID: PMC5319842, DOI: 10.7554/elife.18541.Peer-Reviewed Original ResearchConceptsMolecular dataMouse lung developmentHigh-throughput profilingHigh-throughput studiesDNA methylationGene expressionThroughput profilingExpression dataTime series experimentsExpression valuesLung developmentSeries experimentsBiological systemsGenesMethylationMiRNAProteinProfilingExpressionTime pointsKey design strategiesLarge setAppropriate time points
2015
Alterations in Gene Expression and DNA Methylation during Murine and Human Lung Alveolar Septation
Cuna A, Halloran B, Faye-Petersen O, Kelly D, Crossman DK, Cui X, Pandit K, Kaminski N, Bhattacharya S, Ahmad A, Mariani TJ, Ambalavanan N. Alterations in Gene Expression and DNA Methylation during Murine and Human Lung Alveolar Septation. American Journal Of Respiratory Cell And Molecular Biology 2015, 53: 60-73. PMID: 25387348, PMCID: PMC4566107, DOI: 10.1165/rcmb.2014-0160oc.Peer-Reviewed Original ResearchConceptsDNA methylationNormal septationGene expressionGenome-wide DNA methylation dataMajor epigenetic mechanismsLung developmentNumber of genesMouse lung developmentGene of interestDNA methylation dataGene expression dataMicroarray gene expression dataAlveolar septationCoordinated expressionEpigenetic mechanismsMethylated DNAMultiple genesMicroarray analysisMethylation dataExpression dataGenesMethylationExtracellular matrixAltered expressionAntioxidant defense
2014
Relationship of DNA Methylation and Gene Expression in Idiopathic Pulmonary Fibrosis
Yang IV, Pedersen BS, Rabinovich E, Hennessy CE, Davidson EJ, Murphy E, Guardela BJ, Tedrow JR, Zhang Y, Singh MK, Correll M, Schwarz MI, Geraci M, Sciurba FC, Quackenbush J, Spira A, Kaminski N, Schwartz DA. Relationship of DNA Methylation and Gene Expression in Idiopathic Pulmonary Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2014, 190: 1263-1272. PMID: 25333685, PMCID: PMC4315819, DOI: 10.1164/rccm.201408-1452oc.Peer-Reviewed Original ResearchConceptsGene expressionDNA methylationMethylation marksMethylation changesQuantitative trait lociTrans-gene expressionIntegrative genomic analysisTrait lociEpigenetic mechanismsTranscriptional changesGenomic analysisTranscription factorsCASZ1 expressionTarget genesFunctional validationExpression relationshipsMethylationGenesDMRsExpressionEnvironmental factorsTargeted analysisPathogenesis of IPFComplex interactionsTranscriptome