2024
Single-cell genomics and regulatory networks for 388 human brains
Emani P, Liu J, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee C, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken T, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard J, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman G, Huang A, Jiang Y, Jin T, Jorstad N, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran J, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan A, Riesenmy T, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini K, Wamsley B, Wang G, Xia Y, Xiao S, Yang A, Zheng S, Gandal M, Lee D, Lein E, Roussos P, Sestan N, Weng Z, White K, Won H, Girgenti M, Zhang J, Wang D, Geschwind D, Gerstein M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Berretta S, Bharadwaj R, Bhattacharya A, Brennand K, Capauto D, Champagne F, Chatzinakos C, Chen H, Cheng L, Chess A, Chien J, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Davila-Velderrain J, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duong D, Eagles N, Edelstein J, Galani K, Girdhar K, Goes F, Greenleaf W, Guo H, Guo Q, Hadas Y, Hallmayer J, Han X, Haroutunian V, He C, Hicks S, Ho M, Ho L, Huang Y, Huuki-Myers L, Hyde T, Iatrou A, Inoue F, Jajoo A, Jiang L, Jin P, Jops C, Jourdon A, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Li J, Li M, Lin X, Liu S, Liu C, Loupe J, Lu D, Ma L, Mariani J, Martinowich K, Maynard K, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Mukamel E, Nairn A, Nemeroff C, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Pinto D, Pochareddy S, Pollard K, Pollen A, Przytycki P, Purmann C, Qin Z, Qu P, Raj T, Reach S, Reimonn T, Ressler K, Ross D, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Seyfried N, Shao Z, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Voloudakis G, Wang T, Wang S, Wang Y, Wei Y, Weimer A, Weinberger D, Wen C, Whalen S, Willsey A, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang Y, Ziffra R, Zeier Z, Zintel T. Single-cell genomics and regulatory networks for 388 human brains. Science 2024, 384: eadi5199. PMID: 38781369, PMCID: PMC11365579, DOI: 10.1126/science.adi5199.Peer-Reviewed Original ResearchConceptsSingle-cell genomicsSingle-cell expression quantitative trait locusExpression quantitative trait lociDrug targetsQuantitative trait lociPopulation-level variationSingle-cell expressionCell typesDisease-risk genesTrait lociGene familyRegulatory networksGene expressionCell-typeMultiomics datasetsSingle-nucleiGenomeGenesCellular changesHeterogeneous tissuesExpressionCellsChromatinLociMultiomics
2022
A noncoding single-nucleotide polymorphism at 8q24 drives IDH1-mutant glioma formation
Yanchus C, Drucker K, Kollmeyer T, Tsai R, Winick-Ng W, Liang M, Malik A, Pawling J, De Lorenzo S, Ali A, Decker P, Kosel M, Panda A, Al-Zahrani K, Jiang L, Browning J, Lowden C, Geuenich M, Hernandez J, Gosio J, Ahmed M, Loganathan S, Berman J, Trcka D, Michealraj K, Fortin J, Carson B, Hollingsworth E, Jacinto S, Mazrooei P, Zhou L, Elia A, Lupien M, He H, Murphy D, Wang L, Abyzov A, Dennis J, Maass P, Campbell K, Wilson M, Lachance D, Wrensch M, Wiencke J, Mak T, Pennacchio L, Dickel D, Visel A, Wrana J, Taylor M, Zadeh G, Dirks P, Eckel-Passow J, Attisano L, Pombo A, Ida C, Kvon E, Jenkins R, Schramek D. A noncoding single-nucleotide polymorphism at 8q24 drives IDH1-mutant glioma formation. Science 2022, 378: 68-78. PMID: 36201590, PMCID: PMC9926876, DOI: 10.1126/science.abj2890.Peer-Reviewed Original ResearchConceptsNoncoding single nucleotide polymorphismSingle nucleotide polymorphismsCausal variantsMolecular pathwaysIsocitrate dehydrogenaseLethal gliomaHeritable predispositionGlioma formationTumor developmentLow-grade gliomasMutant lower grade gliomasPolymorphismMouse modelPromoterLociEnhancerSixfold greater riskRs55705857PathwayMechanisticallyDehydrogenaseDisruptsExpressionPenetranceCancer risk
2020
Chapter 5 Induced pluripotent stem cells as models of human neurodevelopmental disorders
Jourdon A, Mariani J, Scuderi S, Amiri A, Wu F, Yuen E, Abyzov A, Vaccarino F. Chapter 5 Induced pluripotent stem cells as models of human neurodevelopmental disorders. 2020, 99-127. DOI: 10.1016/b978-0-12-814409-1.00005-7.ChaptersPluripotent stem cellsStem cellsStudy of speciesHuman neurodevelopmental disordersEpigenome analysisGene regulationIPSC fieldGenomic variationGene expressionGenetic backgroundDisease modelingStudies of neurodevelopmentIPSCsExperimental approachNeurodevelopmental disordersTranscriptomeGenomeCellsCell phenotypingSpeciesExperimental design issuesPhenotypeRegulationExpressionPhenotyping
2016
A uniform survey of allele-specific binding and expression over 1000-Genomes-Project individuals
Chen J, Rozowsky J, Galeev TR, Harmanci A, Kitchen R, Bedford J, Abyzov A, Kong Y, Regan L, Gerstein M. A uniform survey of allele-specific binding and expression over 1000-Genomes-Project individuals. Nature Communications 2016, 7: 11101. PMID: 27089393, PMCID: PMC4837449, DOI: 10.1038/ncomms11101.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBinding SitesChromosome MappingComputational BiologyDatabases, GeneticGene ExpressionGene FrequencyGenome, HumanGenomicsGenotypeHigh-Throughput Nucleotide SequencingHuman Genome ProjectHumansInternetMolecular Sequence AnnotationPolymorphism, Single NucleotidePrecision MedicineConceptsSingle nucleotide variantsAllele-specific bindingFunctional genomics data setsAllele-specific behaviorLarge-scale sequencingGenomic data setsAllelic imbalanceNumber of readsChIP-seqRNA-seqGenome ProjectMaternal chromosomesNucleotide variantsPersonal genomesMapping biasAllelic variantsVariant catalogMultiple individualsFunctional effectsProject individualsBindingExpressionVariantsGenomeChromosomes
2012
Regulatory element copy number differences shape primate expression profiles
Iskow RC, Gokcumen O, Abyzov A, Malukiewicz J, Zhu Q, Sukumar AT, Pai AA, Mills RE, Habegger L, Cusanovich DA, Rubel MA, Perry GH, Gerstein M, Stone AC, Gilad Y, Lee C. Regulatory element copy number differences shape primate expression profiles. Proceedings Of The National Academy Of Sciences Of The United States Of America 2012, 109: 12656-12661. PMID: 22797897, PMCID: PMC3411951, DOI: 10.1073/pnas.1205199109.Peer-Reviewed Original ResearchConceptsCopy number differencesExpression differencesExpression profilesLong intergenic noncoding RNAsCopy numberIntergenic noncoding RNAsGene expression differencesSignificant expression differencesGene expression profilesLevel of RNAUltraconserved elementsRegulatory regionsNoncoding RNAsSelective pressureDifferent genesRegulatory moleculesDevelopmental pathwaysPhenotypic differencesPrimate speciesGenesRNANumber differenceSpeciesExpressionPseudogenes
2011
AlleleSeq: analysis of allele‐specific expression and binding in a network framework
Rozowsky J, Abyzov A, Wang J, Alves P, Raha D, Harmanci A, Leng J, Bjornson R, Kong Y, Kitabayashi N, Bhardwaj N, Rubin M, Snyder M, Gerstein M. AlleleSeq: analysis of allele‐specific expression and binding in a network framework. Molecular Systems Biology 2011, 7: msb201154. PMID: 21811232, PMCID: PMC3208341, DOI: 10.1038/msb.2011.54.Peer-Reviewed Original ResearchMeSH KeywordsAllelesCell LineChromosome MappingChromosomes, Human, XChromosomes, Human, YDatabases, GeneticDNA-Binding ProteinsGene Expression RegulationGene Regulatory NetworksGenome, HumanHumansMolecular Sequence AnnotationOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideSequence Analysis, RNATranscription FactorsConceptsAllele-specific expressionGenome sequenceFunctional genomics data setsAllele-specific behaviorAllele-specific eventsDiploid genome sequenceChIP-seq data setsGenomic data setsGenomic sequence variantsPersonal genome sequencesAlignment of readsRNA-seqGenome ProjectPaternal alleleComputational pipelineReads mappingSequence variantsNetwork motifsVariation dataReference alleleAllelesReadsSequenceExpressionMaternally