2022
Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from a Data-Driven Perspective
Gu J, Dai J, Lu H, Zhao H. Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from a Data-Driven Perspective. Genomics Proteomics & Bioinformatics 2022, 21: 164-176. PMID: 35569803, PMCID: PMC10373092, DOI: 10.1016/j.gpb.2021.08.017.Peer-Reviewed Original ResearchConceptsGlobal expression patternsHuman transcriptomeExpression patternsHuman genesTemporal gene expression patternsVaried expression patternsGene expression patternsInternal reference genesHuman genomeTranscriptomeRegulatory codeGene clusteringMolecular mechanismsReference genesStable expressionIslet beta cellsHuman diseasesGenesExpression measurementsBeta cellsUbiquitouslyPhysiological conditionsValuable resourceComprehensive characterizationExtensive collection
2019
A statistical framework for cross-tissue transcriptome-wide association analysis
Hu Y, Li M, Lu Q, Weng H, Wang J, Zekavat SM, Yu Z, Li B, Gu J, Muchnik S, Shi Y, Kunkle BW, Mukherjee S, Natarajan P, Naj A, Kuzma A, Zhao Y, Crane PK, Lu H, Zhao H. A statistical framework for cross-tissue transcriptome-wide association analysis. Nature Genetics 2019, 51: 568-576. PMID: 30804563, PMCID: PMC6788740, DOI: 10.1038/s41588-019-0345-7.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association analysisAssociation analysisGene-trait associationsGene expression dataGene expression levelsGenetic architectureComplex traitsMore genesGene expressionSingle tissueExpression dataAssociation resultsExpression levelsPowerful approachImputation modelHuman tissuesImputation accuracyGenotypesStatistical frameworkTissueGenesKey componentTraitsPowerful metricExpression
2017
RNA‐seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential
Gu J, Chukhman M, Lu Y, Liu C, Liu S, Lu H. RNA‐seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential. BioMed Research International 2017, 2017: 9829175. PMID: 29181411, PMCID: PMC5664375, DOI: 10.1155/2017/9829175.Peer-Reviewed Original ResearchConceptsOncogenic potentialFusion mutationsFusion geneHigh-throughput sequencing technologyClonal evolution theoryTranscriptome sequencing datasetsLarger clonal sizeSequencing technologiesSequencing datasetsGene fusionsClone ratioGenesFusion breakpointsGenomic alterationsMutationsFunctional featuresNeoplastic cellsTMPRSS2-ERGNormal samplesClonal sizeTumor samplesRecent studiesCellsEvolution theoryBreakpoints
2013
Deep mRNA Sequencing Analysis to Capture the Transcriptome Landscape of Zebrafish Embryos and Larvae
Yang H, Zhou Y, Gu J, Xie S, Xu Y, Zhu G, Wang L, Huang J, Ma H, Yao J. Deep mRNA Sequencing Analysis to Capture the Transcriptome Landscape of Zebrafish Embryos and Larvae. PLOS ONE 2013, 8: e64058. PMID: 23700457, PMCID: PMC3659048, DOI: 10.1371/journal.pone.0064058.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBlastulaCleavage Stage, OvumEmbryonic DevelopmentGastrulaGene Expression ProfilingGene Expression Regulation, DevelopmentalHigh-Throughput Nucleotide SequencingLarvaOligonucleotide Array Sequence AnalysisSequence Analysis, RNATranscription FactorsTranscriptomeWnt Signaling PathwayZebrafishZebrafish ProteinsConceptsTranscriptome dynamicsZebrafish embryonic developmentTranscription factor familyDistinct expression patternsRNA-seq dataGene expression profilesZygotic genomeZebrafish developmentDeep mRNATranscriptome landscapeAverage expression levelEarly gastrulationGene clusterZebrafish embryosEmbryonic developmentTranscriptomic researchFactor familyExpression patternsExpression profilesFunctional pathwaysMolecular eventsEmbryonic stagesGenesCellular mechanismsExpression levels