Featured Publications
A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases
Liu W, Deng W, Chen M, Dong Z, Zhu B, Yu Z, Tang D, Sauler M, Lin C, Wain L, Cho M, Kaminski N, Zhao H. A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases. PLOS Genetics 2023, 19: e1010825. PMID: 37523391, PMCID: PMC10414598, DOI: 10.1371/journal.pgen.1010825.Peer-Reviewed Original ResearchConceptsCell typesDisease-associated tissuesWide association studyComplex diseasesCell type proportionsDisease-relevant tissuesReal GWAS dataFunctional genesTranscriptomic dataGWAS dataGenetic dataAssociation studiesNovel statistical frameworkChronic obstructive pulmonary diseaseStatistical frameworkObstructive pulmonary diseaseIdiopathic pulmonary fibrosisBreast cancer riskType proportionsBlood CD8Pulmonary diseasePulmonary fibrosisPredictive biomarkersLung tissueBreast cancer
2024
Single-cell transcriptomic and proteomic analysis of Parkinson’s disease brains
Zhu B, Park J, Coffey S, Russo A, Hsu I, Wang J, Su C, Chang R, Lam T, Gopal P, Ginsberg S, Zhao H, Hafler D, Chandra S, Zhang L. Single-cell transcriptomic and proteomic analysis of Parkinson’s disease brains. Science Translational Medicine 2024, 16: eabo1997. PMID: 39475571, DOI: 10.1126/scitranslmed.abo1997.Peer-Reviewed Original ResearchConceptsProteomic analysisAlzheimer's diseasePrefrontal cortexBrain cell typesGenetics of PDParkinson's diseaseCell-cell interactionsChaperone expressionSingle-nucleus transcriptomesExpressed genesTranscriptional changesPostmortem human brainPostmortem brain tissueDiseased brainSynaptic proteinsSingle-cellDown-regulationBrain cell populationsBrain regionsCell typesNeurodegenerative disordersLate-stage PDParkinson's disease brainsDisease etiologyNeuronal vulnerability
2023
eQTL studies: from bulk tissues to single cells
Zhang J, Zhao H. eQTL studies: from bulk tissues to single cells. Journal Of Genetics And Genomics 2023, 50: 925-933. PMID: 37207929, PMCID: PMC10656365, DOI: 10.1016/j.jgg.2023.05.003.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociBulk tissueIdentification of eQTLContext-dependent gene regulationCell typesQuantitative trait lociMost eQTL studiesSingle cellsComplex traitsGene regulationEQTL studiesFunctional genesTrait lociSpecific genesChromosomal regionsDynamic regulationGene expressionBiological processesDifferent tissuesGenetic variantsExpression levelsDisease mechanismsGenesRegulationRecent studies
2022
Benchmarking automated cell type annotation tools for single-cell ATAC-seq data
Wang Y, Sun X, Zhao H. Benchmarking automated cell type annotation tools for single-cell ATAC-seq data. Frontiers In Genetics 2022, 13: 1063233. PMID: 36583014, PMCID: PMC9792779, DOI: 10.3389/fgene.2022.1063233.Peer-Reviewed Original ResearchCell type annotationScATAC-seq dataScRNA-seq dataScATAC-seqCell typesSingle-cell ATAC-seq dataAvailable single-cell datasetsRegulatory genomic regionsScRNA-seq data setsSingle-cell datasetsATAC-seq dataNovel cell typesSimilar cell typesSeurat v3Genomic regionsSequencing depthComplex tissuesDeep annotationAnnotationCellular compositionHuman tissuesType annotationsAnnotation toolAnnotation methodLabel transferPan-Cancer Single-Cell Analysis Reveals the Core Factors and Pathway in Specific Cancer Stem Cells of Upper Gastrointestinal Cancer
Li L, Zhang Y, Ren Y, Cheng Z, Zhang Y, Wang X, Zhao H, Lu H. Pan-Cancer Single-Cell Analysis Reveals the Core Factors and Pathway in Specific Cancer Stem Cells of Upper Gastrointestinal Cancer. Frontiers In Bioengineering And Biotechnology 2022, 10: 849798. PMID: 35646860, PMCID: PMC9136039, DOI: 10.3389/fbioe.2022.849798.Peer-Reviewed Original ResearchUpper gastrointestinal cancerCancer stem cellsPoor eating habitsTumor stem cellsChronic inflammationGastrointestinal cancerEating habitsStem cellsGastrointestinal cancer stem cellsPersistent chronic inflammationGastrointestinal cancer diagnosisCore signal pathwaysWnt pathway genesMucosa damagePoor outcomeAggressive carcinomasInflammatory genesSpecific cancer stem cellsCancer diagnosisCancerSignal pathwayInflammationWnt pathwayCell typesCells
2019
Genome-wide Association Study of Maximum Habitual Alcohol Intake in >140,000 U.S. European and African American Veterans Yields Novel Risk Loci
Gelernter J, Sun N, Polimanti R, Pietrzak RH, Levey DF, Lu Q, Hu Y, Li B, Radhakrishnan K, Aslan M, Cheung KH, Li Y, Rajeevan N, Sayward F, Harrington K, Chen Q, Cho K, Honerlaw J, Pyarajan S, Lencz T, Quaden R, Shi Y, Hunter-Zinck H, Gaziano JM, Kranzler HR, Concato J, Zhao H, Stein MB, Program D, Program M. Genome-wide Association Study of Maximum Habitual Alcohol Intake in >140,000 U.S. European and African American Veterans Yields Novel Risk Loci. Biological Psychiatry 2019, 86: 365-376. PMID: 31151762, PMCID: PMC6919570, DOI: 10.1016/j.biopsych.2019.03.984.Peer-Reviewed Original ResearchConceptsAdditional genome-wide significant lociRisk lociWide association study (GWAS) analysisAssociation studiesGenome-wide significant lociGenome-wide association studiesGenetic correlationsWide association studyNovel risk lociAlcohol-related traitsStrong statistical supportSmoking-related traitsAdditional genomesSignificant lociPancreatic delta cellsChromosome 4Chromosome 11Protein productsChromosome 8Quantitative phenotypesMillion Veteran ProgramVeterans Affairs Million Veteran ProgramLociCell typesChromosome 17
2018
Integrative functional genomic analysis of human brain development and neuropsychiatric risks
Li M, Santpere G, Imamura Kawasawa Y, Evgrafov OV, Gulden FO, Pochareddy S, Sunkin SM, Li Z, Shin Y, Zhu Y, Sousa AMM, Werling DM, Kitchen RR, Kang HJ, Pletikos M, Choi J, Muchnik S, Xu X, Wang D, Lorente-Galdos B, Liu S, Giusti-Rodríguez P, Won H, de Leeuw C, Pardiñas AF, Hu M, Jin F, Li Y, Owen M, O’Donovan M, Walters J, Posthuma D, Reimers M, Levitt P, Weinberger D, Hyde T, Kleinman J, Geschwind D, Hawrylycz M, State M, Sanders S, Sullivan P, Gerstein M, Lein E, Knowles J, Sestan N, Willsey A, Oldre A, Szafer A, Camarena A, Cherskov A, Charney A, Abyzov A, Kozlenkov A, Safi A, Jones A, Ashley-Koch A, Ebbert A, Price A, Sekijima A, Kefi A, Bernard A, Amiri A, Sboner A, Clark A, Jaffe A, Tebbenkamp A, Sodt A, Guillozet-Bongaarts A, Nairn A, Carey A, Huttner A, Chervenak A, Szekely A, Shieh A, Harmanci A, Lipska B, Carlyle B, Gregor B, Kassim B, Sheppard B, Bichsel C, Hahn C, Lee C, Chen C, Kuan C, Dang C, Lau C, Cuhaciyan C, Armoskus C, Mason C, Liu C, Slaughterbeck C, Bennet C, Pinto D, Polioudakis D, Franjic D, Miller D, Bertagnolli D, Lewis D, Feng D, Sandman D, Clarke D, Williams D, DelValle D, Fitzgerald D, Shen E, Flatow E, Zharovsky E, Burke E, Olson E, Fulfs E, Mattei E, Hadjimichael E, Deelman E, Navarro F, Wu F, Lee F, Cheng F, Goes F, Vaccarino F, Liu F, Hoffman G, Gürsoy G, Gee G, Mehta G, Coppola G, Giase G, Sedmak G, Johnson G, Wray G, Crawford G, Gu G, van Bakel H, Witt H, Yoon H, Pratt H, Zhao H, Glass I, Huey J, Arnold J, Noonan J, Bendl J, Jochim J, Goldy J, Herstein J, Wiseman J, Miller J, Mariani J, Stoll J, Moore J, Szatkiewicz J, Leng J, Zhang J, Parente J, Rozowsky J, Fullard J, Hohmann J, Morris J, Phillips J, Warrell J, Shin J, An J, Belmont J, Nyhus J, Pendergraft J, Bryois J, Roll K, Grennan K, Aiona K, White K, Aldinger K, Smith K, Girdhar K, Brouner K, Mangravite L, Brown L, Collado-Torres L, Cheng L, Gourley L, Song L, Ubieta L, Habegger L, Ng L, Hauberg M, Onorati M, Webster M, Kundakovic M, Skarica M, Reimers M, Johnson M, Chen M, Garrett M, Sarreal M, Reding M, Gu M, Peters M, Fisher M, Gandal M, Purcaro M, Smith M, Brown M, Shibata M, Brown M, Xu M, Yang M, Ray M, Shapovalova N, Francoeur N, Sjoquist N, Mastan N, Kaur N, Parikshak N, Mosqueda N, Ngo N, Dee N, Ivanov N, Devillers O, Roussos P, Parker P, Manser P, Wohnoutka P, Farnham P, Zandi P, Emani P, Dalley R, Mayani R, Tao R, Gittin R, Straub R, Lifton R, Jacobov R, Howard R, Park R, Dai R, Abramowicz S, Akbarian S, Schreiner S, Ma S, Parry S, Shapouri S, Weissman S, Caldejon S, Mane S, Ding S, Scuderi S, Dracheva S, Butler S, Lisgo S, Rhie S, Lindsay S, Datta S, Souaiaia T, Roychowdhury T, Gomez T, Naluai-Cecchini T, Beach T, Goodman T, Gao T, Dolbeare T, Fliss T, Reddy T, Chen T, Hyde T, Brunetti T, Lemon T, Desta T, Borrman T, Haroutunian V, Spitsyna V, Swarup V, Shi X, Jiang Y, Xia Y, Chen Y, Jiang Y, Wang Y, Chae Y, Yang Y, Kim Y, Riley Z, Krsnik Z, Deng Z, Weng Z, Lin Z, Li Z. Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science 2018, 362 PMID: 30545854, PMCID: PMC6413317, DOI: 10.1126/science.aat7615.Peer-Reviewed Original ResearchConceptsIntegrative functional genomic analysisFunctional genomic analysisCell typesGene coexpression modulesDistinct cell typesCell type-specific dynamicsGenomic basisEpigenomic reorganizationEpigenomic landscapeEpigenomic regulationGenomic analysisCoexpression modulesIntegrative analysisHuman brain developmentFetal transitionHuman neurodevelopmentGenetic associationCellular compositionNeuropsychiatric riskBrain developmentNeurodevelopmental processesGenesTraitsPostnatal developmentNeuropsychiatric disorders
2017
Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease
Lu Q, Powles RL, Abdallah S, Ou D, Wang Q, Hu Y, Lu Y, Liu W, Li B, Mukherjee S, Crane PK, Zhao H. Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease. PLOS Genetics 2017, 13: e1006933. PMID: 28742084, PMCID: PMC5546707, DOI: 10.1371/journal.pgen.1006933.Peer-Reviewed Original ResearchConceptsTissue typesNon-coding elementsNon-coding genomeComplex human diseasesLate-onset Alzheimer's diseaseIndividual cell typesRelevant tissue typesGWAS traitsTranscriptomic annotationGenome annotationFunctional annotationDNA elementsHeritability enrichmentHuman genomeLarge international consortiaVariety of cellsGenomeHuman diseasesAnnotation dataCell typesGenetic variantsOrgan system categoriesComplex diseasesSimilar localizationAnnotation
2008
The promise of systems biology for deciphering the control of C 4 leaf development: transcriptome profiling of leaf cell types
Nelson T, Tausta S, Gandotra N, Liu T, Ceserani T, Chen M, Jiao Y, Ma L, Deng X, Sun N, Holfold M, Li N, Zhao H. The promise of systems biology for deciphering the control of C 4 leaf development: transcriptome profiling of leaf cell types. 2008, 317-332. DOI: 10.1142/9789812709523_0018.Peer-Reviewed Original Research