2024
Rare genetic variation in fibronectin 1 (FN1) protects against APOE ɛ4 in Alzheimer’s Disease
Bhattarai P, Gunasekaran T, Uzrek B, Reyes‐Dumeyer D, Jülich D, Lee A, Yilmaz E, Tayran H, Lantigua R, Medrano M, Mejia D, Recio P, Flaherty D, Dalgard C, Nuriel T, Ertekin‐Taner N, Dickson D, Teich A, Holley S, Mayeux R, Kizil C, Vardarajan B. Rare genetic variation in fibronectin 1 (FN1) protects against APOE ɛ4 in Alzheimer’s Disease. Alzheimer's & Dementia 2024, 20: e089111. PMCID: PMC11710415, DOI: 10.1002/alz.089111.Peer-Reviewed Original ResearchWhole-genome sequencingLoss-of-functionIn vivo functional studiesFibronectin 1Genetic variationAlzheimer's diseaseFunctional studiesWhole-genome sequence analysisTarget genesRare genetic variationLoss-of-function mutationsPotential gene variantsZebrafish modelGenome sequenceProtective variantsAPOE variantsGenetic variantsECM proteinsZebrafish AD modelBioinformatics analysisAD pathologyPotential therapeutic interventional targetsPathway analysisPostmortem human brain tissueRare variantsContext-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes
Long E, Yin J, Shin J, Li Y, Li B, Kane A, Patel H, Sun X, Wang C, Luong T, Xia J, Han Y, Byun J, Zhang T, Zhao W, Landi M, Rothman N, Lan Q, Chang Y, Yu F, Amos C, Shi J, Lee J, Kim E, Choi J. Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes. Nature Communications 2024, 15: 7995. PMID: 39266564, PMCID: PMC11392933, DOI: 10.1038/s41467-024-52356-9.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide association study lociSusceptibility genesLung cancer susceptibility genesTranscription factor footprintsChromatin accessibility mapsCis-regulatory elementsRisk-associated variantsRare cell typesRegulate gene expressionCell typesCell type-specificCancer susceptibility genesCausal variantsAssociation studiesGene regulationGene functionMultiomics approachTarget genesLociGene expressionGenesType-specificHuman lung cellsCCREsSRBD1 Regulates the Cell Cycle, Apoptosis, and M2 Macrophage Polarization via the RPL11‐MDM2‐p53 Pathway in Glioma
Chen H, Gao S, Wang P, Xie M, Zhang H, Fan Y, Nie E, Lan Q. SRBD1 Regulates the Cell Cycle, Apoptosis, and M2 Macrophage Polarization via the RPL11‐MDM2‐p53 Pathway in Glioma. Environmental Toxicology 2024, 40: 66-78. PMID: 39258423, DOI: 10.1002/tox.24396.Peer-Reviewed Original ResearchRNA-binding proteinsP53 signalingInhibits Mdm2-mediated p53 ubiquitinationMDM2-mediated p53 ubiquitinationRPL11-MDM2-p53 pathwayElevated p53 levelsRibosomal protein expressionBinding to MDM2Tumor-associated macrophagesP53 signaling pathwayInactivation of p53P53 ubiquitinationRibosomal proteinsRNA translationM2 macrophage polarizationP53 levelsTumor growthRPL11Mouse xenograft modelEctopic expressionGlioma tumor growthCell cycleBinding proteinTarget genesSignaling pathwaymiR-33 deletion in hepatocytes attenuates NAFLD-NASH-HCC progression
Fernández-Tussy P, Cardelo M, Zhang H, Sun J, Price N, Boutagy N, Goedeke L, Cadena-Sandoval M, Xirouchaki C, Brown W, Yang X, Pastor-Rojo O, Haeusler R, Bennett A, Tiganis T, Suárez Y, Fernández-Hernando C. miR-33 deletion in hepatocytes attenuates NAFLD-NASH-HCC progression. JCI Insight 2024, 9: e168476. PMID: 39190492, PMCID: PMC11466198, DOI: 10.1172/jci.insight.168476.Peer-Reviewed Original ResearchMiR-33Regulation of biological processesMitochondrial fatty acid oxidationRegulation of lipid metabolismNon-alcoholic fatty liver diseaseDevelopment of effective therapeuticsFatty acid oxidationLipid synthesisProgression of non-alcoholic fatty liver diseaseMitochondrial functionTarget genesBiological processesComplex diseasesNon-alcoholic steatohepatitisLipid accumulationDeletionDevelopment of non-alcoholic fatty liver diseasePathway activationLipid metabolismProgress to non-alcoholic steatohepatitisAcid oxidationHCC progressionEffective therapeuticsTherapeutic targetHepatocellular carcinomaModulated Cell Internalization Behavior of Icosahedral DNA Framework with Programmable Surface Modification
Huang K, Yang Q, Bao M, Wang S, Zhao L, Shi Q, Yang Y. Modulated Cell Internalization Behavior of Icosahedral DNA Framework with Programmable Surface Modification. Journal Of The American Chemical Society 2024, 146: 21442-21452. PMID: 39038211, DOI: 10.1021/jacs.4c04106.Peer-Reviewed Original ResearchAccelerated evolution in the human lineage led to gain and loss of transcriptional enhancers in the RBFOX1 locus
Berasain L, Beati P, Trigila A, Rubinstein M, Franchini L. Accelerated evolution in the human lineage led to gain and loss of transcriptional enhancers in the RBFOX1 locus. Science Advances 2024, 10: eadl1049. PMID: 38924416, PMCID: PMC11204294, DOI: 10.1126/sciadv.adl1049.Peer-Reviewed Original ResearchConceptsTranscriptional enhancersGoal of evolutionary biologyHuman lineageZebrafish reporter assayGene regulatory networksPotential regulatory elementsHuman-specific traitsChimpanzee sequencesRBFOX1 locusRegulatory elementsRegulatory networksRegulatory modificationsEvolutionary biologyAccelerated evolutionTarget genesGene expressionGenesDevelopmental stagesLociLineagesReporter assayExpressionRBFOX1SplicingTemporal changesCell signaling and tissue remodeling in the pulmonary autograft after the Ross procedure: A computational study
Maes L, Vervenne T, Hendrickx A, Estrada A, Van Hoof L, Verbrugghe P, Rega F, Jones E, Humphrey J, Famaey N. Cell signaling and tissue remodeling in the pulmonary autograft after the Ross procedure: A computational study. Journal Of Biomechanics 2024, 171: 112180. PMID: 38906711, DOI: 10.1016/j.jbiomech.2024.112180.Peer-Reviewed Original ResearchRoss procedurePulmonary autograftPatient's pulmonary valveTranscription factorsPulmonary valveSmooth muscleActivation of genesAortic positionRelevant transcription factorsTissue remodelingAutograftExcessive dilatationTranscriptome dataGene activationCell signalingSignaling pathwayTarget genesMultiscale modelGenesTissueCellsFailure mechanismCell-scaleMechanical propertiesCell-scale modelmicroRNA-33 controls hunger signaling in hypothalamic AgRP neurons
Price N, Fernández-Tussy P, Varela L, Cardelo M, Shanabrough M, Aryal B, de Cabo R, Suárez Y, Horvath T, Fernández-Hernando C. microRNA-33 controls hunger signaling in hypothalamic AgRP neurons. Nature Communications 2024, 15: 2131. PMID: 38459068, PMCID: PMC10923783, DOI: 10.1038/s41467-024-46427-0.Peer-Reviewed Original ResearchConceptsAgRP neuronsFeeding behaviorFatty acid metabolismNon-coding RNAsMitochondrial biogenesisRegulatory pathwaysTarget genesHypothalamic AgRP neuronsExcessive nutrient intakeCentral regulatorBioenergetic processesAcid metabolismActivation of AgRP neuronsModulate feeding behaviorCentral regulation of feeding behaviorRegulation of feeding behaviorMiR-33Hunger signalsMicroRNA-33Metabolic diseasesAlternative therapeutic approachLoss of miR-33Mouse modelMetabolic dysfunctionRegulation
2023
Elevated CDKN1a (p21) mediates β-thalassemia erythroid apoptosis but its loss does not improve β-thalassemic erythropoiesis
Liang R, Lin M, Menon V, Qiu J, Menon A, Breda L, Arif T, Rivella S, Ghaffari S. Elevated CDKN1a (p21) mediates β-thalassemia erythroid apoptosis but its loss does not improve β-thalassemic erythropoiesis. Blood Advances 2023, 7: 6873-6885. PMID: 37672319, PMCID: PMC10685172, DOI: 10.1182/bloodadvances.2022007655.Peer-Reviewed Original ResearchConceptsErythroid cell maturationErythroid cell survivalCell cycle inhibitor Cdkn1aFoxO3 target genesErythroid apoptosisFoxO3 transcription factorElevated reactive oxygen speciesΒ-globin geneCell maturationEmbryonic lethalityTranscription factorsTarget genesErythroid maturationReactive oxygen speciesMolecular networksMolecular mechanismsThalassemic erythropoiesisCell survivalProgenitor compartmentErythroid compartmentFOXO3Extramedullary erythropoiesisΒ-thalassemiaApoptosisHemoglobin productiontRFtarget 2.0: expanding the targetome landscape of transfer RNA-derived fragments
Li N, Yao S, Yu G, Lu L, Wang Z. tRFtarget 2.0: expanding the targetome landscape of transfer RNA-derived fragments. Nucleic Acids Research 2023, 52: d345-d350. PMID: 37811890, PMCID: PMC10767876, DOI: 10.1093/nar/gkad815.Peer-Reviewed Original Research
2022
Histone H3 proline 16 hydroxylation regulates mammalian gene expression
Liu X, Wang J, Boyer J, Gong W, Zhao S, Xie L, Wu Q, Zhang C, Jain K, Guo Y, Rodriguez J, Li M, Uryu H, Liao C, Hu L, Zhou J, Shi X, Tsai Y, Yan Q, Luo W, Chen X, Strahl B, von Kriegsheim A, Zhang Q, Wang G, Baldwin A, Zhang Q. Histone H3 proline 16 hydroxylation regulates mammalian gene expression. Nature Genetics 2022, 54: 1721-1735. PMID: 36347944, PMCID: PMC9674084, DOI: 10.1038/s41588-022-01212-x.Peer-Reviewed Original ResearchConceptsPost-translational modificationsHistone post-translational modificationsMammalian gene expressionGene expressionHistone H3Mammalian cellsDNA-templated processesTranscriptome-wide analysisTarget gene expressionHydroxylation of prolineWnt/β-cateninChromatin recruitmentHistone codeTarget genesRegulatory marksLysine residuesDirect bindingTriple-negative breast cancerΒ-cateninResidues 16H3ExpressionH3K4me3TrimethylationGenomeIntegrative analyses for the identification of idiopathic pulmonary fibrosis-associated genes and shared loci with other diseases
Chen M, Zhang Y, Adams T, Ji D, Jiang W, Wain LV, Cho M, Kaminski N, Zhao H. Integrative analyses for the identification of idiopathic pulmonary fibrosis-associated genes and shared loci with other diseases. Thorax 2022, 78: 792-798. PMID: 36216496, PMCID: PMC10083187, DOI: 10.1136/thorax-2021-217703.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association analysisLocal genetic correlationsSingle-cell expression dataCandidate genesTranscription factorsIntegrative analysisGenomic regionsGenetic correlationsExpression dataTF target genesComplex genetic architectureTF binding sitesWide association studyPower of GWASSpecific DEGsGenetic architectureNew genesNovel genesCausal genesTarget genesGenetic basisEnrichment analysisAssociation studiesRegulatory roleAssociation analysisStem Cell Models for Context-Specific Modeling in Psychiatric Disorders
Seah C, Huckins L, Brennand K. Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders. Biological Psychiatry 2022, 93: 642-650. PMID: 36658083, DOI: 10.1016/j.biopsych.2022.09.033.Peer-Reviewed Original ResearchConceptsStem cell modelCell typesTarget genesGenome-wide association study (GWAS) lociExpression quantitative trait lociGenome-wide association studiesParallel reporter assaysQuantitative trait lociStem cell-derived cell typesPluripotent stem cell modelsComplex polygenic architectureContext-specific mannerPsychiatric disorder riskTrait lociRegulates transcriptionStudy lociGenetic regulationPolygenic architectureCRISPR screensCell modelCausal variantsRegulated expressionPatient-specific humanReporter assaysAssociation studiesPopulation-level variation in enhancer expression identifies disease mechanisms in the human brain
Dong P, Hoffman G, Apontes P, Bendl J, Rahman S, Fernando M, Zeng B, Vicari J, Zhang W, Girdhar K, Townsley K, Misir R, Brennand K, Haroutunian V, Voloudakis G, Fullard J, Roussos P. Population-level variation in enhancer expression identifies disease mechanisms in the human brain. Nature Genetics 2022, 54: 1493-1503. PMID: 36163279, PMCID: PMC9547946, DOI: 10.1038/s41588-022-01170-4.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociPopulation-level variationTranscriptome-wide association studyQuantitative trait lociSpecific transcriptomeTrait lociTrait heritabilitySpecific transcriptionEnhancer functionGenetic mechanismsTarget genesAssociation studiesDisease locusNeuropsychiatric diseasesRisk variantsGenesRobust expressionTranscriptomeFunctional interpretationDisease mechanismsEnhancerDiseased statesLociHuman brainBrain samplesA transcriptional cycling model recapitulates chromatin-dependent features of noisy inducible transcription
Bullock ME, Moreno-Martinez N, Miller-Jensen K. A transcriptional cycling model recapitulates chromatin-dependent features of noisy inducible transcription. PLOS Computational Biology 2022, 18: e1010152. PMID: 36084132, PMCID: PMC9491597, DOI: 10.1371/journal.pcbi.1010152.Peer-Reviewed Original ResearchConceptsGene expression noiseExpression noiseTranscriptional burstingPromoter statesDifferent chromatin environmentsChromatin environmentChromatin statePause releaseTranscription factor NFChromatin accessibilityChromatin remodelingTranscriptional noiseChromatin locationsInducible transcriptionSubstantial phenotypic heterogeneityTranscriptional activationTranscription factorsTranscript distributionPolymerase complexTarget genesPolymerase bindingGene expressionPromoter activityViral activationBiological processesRNA m6A demethylase ALKBH5 regulates the development of γδ T cells
Ding C, Xu H, Yu Z, Roulis M, Qu R, Zhou J, Oh J, Crawford J, Gao Y, Jackson R, Sefik E, Li S, Wei Z, Skadow M, Yin Z, Ouyang X, Wang L, Zou Q, Su B, Hu W, Flavell RA, Li HB. RNA m6A demethylase ALKBH5 regulates the development of γδ T cells. Proceedings Of The National Academy Of Sciences Of The United States Of America 2022, 119: e2203318119. PMID: 35939687, PMCID: PMC9388086, DOI: 10.1073/pnas.2203318119.Peer-Reviewed Original ResearchConceptsDemethylase ALKBH5Messenger RNAΓδ T cellsΓδ T cell biologyCommon posttranscriptional modificationΓδ T cell developmentT cell biologyT cell developmentCell precursorsT cell precursorsMammalian cellsRNA modificationsPosttranscriptional modificationsTissue homeostasisCell biologyT cellsTarget genesCheckpoint roleCell developmentM6A demethylase ALKBH5ALKBH5Γδ T-cell originΓδ T cell repertoireCell populationsEarly developmentMicroenvironmental sensing by fibroblasts controls macrophage population size
Zhou X, Franklin RA, Adler M, Carter TS, Condiff E, Adams TS, Pope SD, Philip NH, Meizlish ML, Kaminski N, Medzhitov R. Microenvironmental sensing by fibroblasts controls macrophage population size. Proceedings Of The National Academy Of Sciences Of The United States Of America 2022, 119: e2205360119. PMID: 35930670, PMCID: PMC9371703, DOI: 10.1073/pnas.2205360119.Peer-Reviewed Original ResearchConceptsCell typesDensity-dependent gene expressionTGF-β target genesDiverse cell typesActin-dependent mechanismLineage-specific growth factorsDistinct cell typesGrowth factor availabilityActivation of YAP1Different cell typesExpression programsMicroenvironmental sensingTranscriptional coactivatorTarget genesGene expressionPopulation sizeFactor availabilityPopulation numbersTissue environmentTissue integrityHippoProliferation of macrophagesYAP1Animal tissuesMechanical forcesPPARγ phase separates with RXRα at PPREs to regulate target gene expression
Li Z, Luo L, Yu W, Li P, Ou D, Liu J, Ma H, Sun Q, Liang A, Huang C, Chi T, Huang X, Zhang Y. PPARγ phase separates with RXRα at PPREs to regulate target gene expression. Cell Discovery 2022, 8: 37. PMID: 35473936, PMCID: PMC9043196, DOI: 10.1038/s41421-022-00388-0.Peer-Reviewed Original ResearchPPAR response elementNuclear condensatesTranscriptional activationPPRE siteZinc finger motifsDNA binding domainsKey transcription activatorSpecific transcriptional activationTarget gene expressionPPARγ/RXRαRetinoid X receptor αPPARγ target genesFinger motifPhase-separated dropletsTranscription activatorTranscriptional responseObligate heterodimersTarget genesX receptor αBinding domainsGene expressionResponse elementPeroxisome proliferator-activated receptorNovel mechanismProliferator-activated receptorLoss of PBRM1 alters promoter histone modifications and activates ALDH1A1 to drive renal cell carcinomaPBRM1 loss increases H3K4me3 marks and expression of ALDH1A1
Schoenfeld D, Zhou R, Zairis S, Su W, Steinbach N, Mathur D, Bansal A, Zachem A, Tavarez B, Hasson D, Bernstein E, Rabadan R, Parsons R. Loss of PBRM1 alters promoter histone modifications and activates ALDH1A1 to drive renal cell carcinomaPBRM1 loss increases H3K4me3 marks and expression of ALDH1A1. Molecular Cancer Research 2022, 20: 1193-1207. PMID: 35412614, PMCID: PMC9357026, DOI: 10.1158/1541-7786.mcr-21-1039.Peer-Reviewed Original ResearchConceptsRetinoic acid biosynthesisSuch target genesPromoter histone modificationsAcid biosynthesisHistone modificationsClear cell renal cell carcinomaTarget genesLoss of PBRM1SWI/SNF complexSWI/SNF chromatinSWI/SNF subunitsHistone modification ChIP-seqSWI/SNF componentsATAC-seq dataCcRCC cell linesDe novo gainPBAF subunitsH3K4me3 peaksH3K4me3 marksPBAF complexSNF complexEpigenomic approachesChIP-seqRNA-seqHigh mutation frequencyHigh-content CRISPR screening
Bock C, Datlinger P, Chardon F, Coelho M, Dong M, Lawson K, Lu T, Maroc L, Norman T, Song B, Stanley G, Chen S, Garnett M, Li W, Moffat J, Qi L, Shapiro R, Shendure J, Weissman J, Zhuang X. High-content CRISPR screening. Nature Reviews Methods Primers 2022, 2: 8. DOI: 10.1038/s43586-021-00093-4.Peer-Reviewed Original ResearchCRISPR screeningCRISPR screensBiological discoverySingle-cell RNA sequencingPooled CRISPR screensList of genesHigh-content methodBiological challengesGene functionCell competitionUnbiased interrogationGuide RNARNA sequencingBioinformatics analysisDetailed biological insightsTarget genesBasic biologyPool of cellsBiological insightsCRISPR technologyMolecular mechanismsSuch screensGenesMedical GeneticsBroad utility
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