2025
Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review
Lan Y, Rancu I, Chitwood M, Sobkowiak B, Nyhan K, Lin H, Wu C, Mathema B, Brown T, Colijn C, Warren J, Cohen T. Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review. The Lancet Microbe 2025, 101094. PMID: 40228509, DOI: 10.1016/j.lanmic.2025.101094.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsGenome sequencing approachGenetic similarityGenomic dataSequencing approachGenotyping methodsPathogen geneticsGenetic methodsPathogen sequencesSampling completenessTuberculosis isolatesTransmission patternsTuberculosis casesPathogensTuberculosis transmissionM tuberculosis isolatesInfection-related mortalityEnvironmental factorsTuberculosis transmission dynamicsSpatial proximityTransmission clustersGenomeSpatial patternsTuberculosisTransmission dynamicsGeneticsPsychiatric genetics in the diverse landscape of Latin American populations
Bruxel E, Rovaris D, Belangero S, Chavarría-Soley G, Cuellar-Barboza A, Martínez-Magaña J, Nagamatsu S, Nievergelt C, Núñez-Ríos D, Ota V, Peterson R, Sloofman L, Adams A, Albino E, Alvarado A, Andrade-Brito D, Arguello-Pascualli P, Bandeira C, Bau C, Bulik C, Buxbaum J, Cappi C, Corral-Frias N, Corrales A, Corsi-Zuelli F, Crowley J, Cupertino R, da Silva B, De Almeida S, De la Hoz J, Forero D, Fries G, Gelernter J, González-Giraldo Y, Grevet E, Grice D, Hernández-Garayua A, Hettema J, Ibáñez A, Ionita-Laza I, Lattig M, Lima Y, Lin Y, López-León S, Loureiro C, Martínez-Cerdeño V, Martínez-Levy G, Melin K, Moreno-De-Luca D, Muniz Carvalho C, Olivares A, Oliveira V, Ormond R, Palmer A, Panzenhagen A, Passos-Bueno M, Peng Q, Pérez-Palma E, Prieto M, Roussos P, Sanchez-Roige S, Santamaría-García H, Shansis F, Sharp R, Storch E, Tavares M, Tietz G, Torres-Hernández B, Tovo-Rodrigues L, Trelles P, Trujillo-ChiVacuan E, Velásquez M, Vera-Urbina F, Voloudakis G, Wegman-Ostrosky T, Zhen-Duan J, Zhou H, Santoro M, Nicolini H, Atkinson E, Giusti-Rodríguez P, Montalvo-Ortiz J. Psychiatric genetics in the diverse landscape of Latin American populations. Nature Genetics 2025, 57: 1074-1088. PMID: 40175716, PMCID: PMC12133068, DOI: 10.1038/s41588-025-02127-z.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesPsychiatric genomicsPsychiatric genome-wide association studiesLarge-scale genome-wide association studiesGenetic risk lociNon-European populationsGenetic diversityRisk lociGenetic admixtureBurden of psychiatric disordersAssociation studiesPsychiatric disordersEuropean ancestryPsychiatric geneticsGenomeHealthcare disparitiesConsortium effortLatin American populationsPromote equityEnvironmental factorsDiversityAmerican populationDiverse landscapeLociAncestryPlant graph-based pangenomics: techniques, applications, and challenges
Du Z, He J, Jiao W. Plant graph-based pangenomics: techniques, applications, and challenges. ABIOTECH 2025, 1-16. DOI: 10.1007/s42994-025-00206-7.Peer-Reviewed Original ResearchNovo-assembled genomeMolecular breeding of cropsDNA sequencing technologiesInvestigate population diversityAgronomically important genesBreeding of cropsPangenome graphsGenetic mapSmall variantsGenomic regionsGenetic diversityGraph pangenomeSequencing technologiesGenomic analysisPangenomic studiesGenomic studiesGenetic variationImportant genesMolecular breedingStructural variantsPangenomeGenomeCrop breedingPlantsVariantsSynthetic Genetic Elements Enable Rapid Characterization of Inorganic Carbon Uptake Systems in Cupriavidus necator H16
Nakamura A, Fulk E, Johnson C, Isaacs F. Synthetic Genetic Elements Enable Rapid Characterization of Inorganic Carbon Uptake Systems in Cupriavidus necator H16. ACS Synthetic Biology 2025, 14: 943-953. PMID: 40048245, DOI: 10.1021/acssynbio.4c00869.Peer-Reviewed Original ResearchConceptsSynthetic genetic elementsExpression of heterologous pathwaysUptake systemCupriavidus necator H16Genome engineering technologiesHeterologous pathwaysHeterotrophic conditionsGenetic elementsChromosomal expressionTunable expressionInducible promoterGenetic engineering technologyModel microbesCarbon sourceGene expressionFacultative chemolithotrophsUptake pathwayH16PathwayLanding padExpressionGenomeGenesMicrobesChemolithotrophsIntegrating epidemiology and genomics data to estimate the prevalence of acquired cysteine drug targets in the U.S. cancer patient population
Arun A, Liarakos D, Mendiratta G, Kim J, Goshua G, Olson P, Stites E. Integrating epidemiology and genomics data to estimate the prevalence of acquired cysteine drug targets in the U.S. cancer patient population. The Pharmacogenomics Journal 2025, 25: 5. PMID: 40044654, DOI: 10.1038/s41397-025-00364-3.Peer-Reviewed Original ResearchConceptsGenomic dataEstimates of mutation ratesSomatic missense mutationsGenomic informationPopulation-level estimatesCancer patient populationMissense mutationsNon-epidemiologicallyCancer patientsMutation ratePathogenic mutationsCysteine residuesCancer epidemiologyMutation-specificMutation abundanceDrug targetsMutationsIntegrates epidemiologyAbundancePatient populationEpidemiologyGenomePopulationTargeted therapyResiduesExperiences from dual genome next-generation sequencing panel testing for mitochondrial disorders: a comprehensive molecular diagnosis
Gorman E, Dai H, Feng Y, Craigen W, Chen D, Xia F, Meng L, Liu P, Rigobello R, Neogi A, Eng C, Wang Y. Experiences from dual genome next-generation sequencing panel testing for mitochondrial disorders: a comprehensive molecular diagnosis. Frontiers In Genetics 2025, 16: 1488956. PMID: 40110048, PMCID: PMC11920145, DOI: 10.3389/fgene.2025.1488956.Peer-Reviewed Original ResearchNext-generation sequencingMitochondrial genomeComprehensive molecular diagnosisMitochondrial disordersMitochondrial diseaseMolecular diagnosisNext-generation sequencing panel testingMolecular diagnosis of mitochondrial disordersDiagnosis of mitochondrial disordersDisease-causing genesPanel testingMtDNA genomeNuclear genomeNuclear genesMtDNA heteroplasmyDiagnosing mitochondrial disordersMitochondrial heteroplasmyHeteroplasmy levelsGenomeP/LP variantsGenetic heterogeneityMtDNAHeteroplasmyGenomic testingPhenotypic variabilityp53 enhances DNA repair and suppresses cytoplasmic chromatin fragments and inflammation in senescent cells
Miller K, Li B, Pierce-Hoffman H, Patel S, Lei X, Rajesh A, Teneche M, Havas A, Gandhi A, Macip C, Lyu J, Victorelli S, Woo S, Lagnado A, LaPorta M, Liu T, Dasgupta N, Li S, Davis A, Korotkov A, Hultenius E, Gao Z, Altman Y, Porritt R, Garcia G, Mogler C, Seluanov A, Gorbunova V, Kaech S, Tian X, Dou Z, Chen C, Passos J, Adams P. p53 enhances DNA repair and suppresses cytoplasmic chromatin fragments and inflammation in senescent cells. Nature Communications 2025, 16: 2229. PMID: 40044657, PMCID: PMC11882782, DOI: 10.1038/s41467-025-57229-3.Peer-Reviewed Original ResearchConceptsCytoplasmic chromatin fragmentsDNA repairGenome integrityChromatin fragmentsNuclear DNA damage signalsGenomic instabilitySenescent cellsActivation of p53Controlling DNA repairATM-dependent mannerDNA damage signalingSignatures of agingAge-associated accumulationActivate p53P53 activationHallmarks of agingDamage signalingAge-associated diseasesSignaling circuitsP53Molecular circuitsEnhanced DNA repairGenomePharmacological inhibitionAge-associated inflammationIdentification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities
Loesch D, Garg M, Matelska D, Vitsios D, Jiang X, Ritchie S, Sun B, Runz H, Whelan C, Holman R, Mentz R, Moura F, Wiviott S, Sabatine M, Udler M, Gause-Nilsson I, Petrovski S, Oscarsson J, Nag A, Paul D, Inouye M. Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities. Nature Communications 2025, 16: 2124. PMID: 40032831, PMCID: PMC11876343, DOI: 10.1038/s41467-025-56695-z.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkersCardiovascular DiseasesComorbidityDiabetes Mellitus, Type 2Extracellular Matrix ProteinsFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInsulin-Like Growth Factor Binding Protein 2MaleMiddle AgedMultifactorial InheritanceProteomicsRisk FactorsUnited KingdomConceptsPolygenic scoresNon-coding variantsEtiology of type 2 diabetesMolecular dataVariant effectsPathway enrichmentPlasma proteomic markersPotential therapeutic targetType 2 diabetesProteinDisease biologyPolygenic riskUK BiobankProteomic markersTherapeutic targetPathwayCirculating proteinsGenomeRisk of type 2 diabetesCardiometabolic scoreBiologyInteractive portalVariantsEnrichmentDiabetes comorbiditiesTravel-associated international spread of Oropouche virus beyond the Amazon
de Melo Iani F, Pereira F, de Oliveira E, Rodrigues J, Machado M, Fonseca V, Adelino T, Guimarães N, Tomé L, Gómez M, Nardy V, Ribeiro A, Rosewell A, Ferreira Á, de Mello A, Fernandes B, de Albuquerque C, dos Santos Pereira D, Pimentel E, Lima F, Silva F, de Carvalho Pereira G, Tegally H, Almeida J, Moreno K, Vasconcelos K, Santos L, Silva L, Frutuoso L, Lamounier L, Costa M, de Oliveira M, dos Anjos M, Ciccozzi M, Lima M, Pereira M, Rocha M, da Silva P, Rabinowitz P, de Almeida P, Lessells R, Gazzinelli R, da Cunha R, Gonçalves S, dos Santos S, de Alcântara Belettini S, Pedroso S, Araújo S, da Silva S, Croda J, Maciel E, Van Voorhis W, Martin D, Holmes E, de Oliveira T, Lourenço J, Alcantara L, Giovanetti M. Travel-associated international spread of Oropouche virus beyond the Amazon. Journal Of Travel Medicine 2025, 32: taaf018. PMID: 40037296, PMCID: PMC11955161, DOI: 10.1093/jtm/taaf018.Peer-Reviewed Original ResearchOropouche virusAmazon basinWhole-genome sequencingViral adaptationLocal ecological conditionsMonophyletic groupGenome segmentsPhylogenetic analysisGenomic analysisViral movementGenomic changesPhenotypic traitsEpidemiological metadataReassortment eventsBrazilian Amazon basinPublic health laboratoriesEcological conditionsHuman population changeGenomeCentral Public Health LaboratoryReassortmentPublic health significanceHealth laboratoriesGeographic expansionSequenceA compendium of human gene functions derived from evolutionary modelling
Ramsey J, Siegele D, Chisholm R, Fey P, Giglio M, Nadendla S, Antonazzo G, Attrill H, Brown N, Garapati P, Marygold S, Ahmed S, Asanitthong P, Buitrago D, Erdol M, Gage M, Huang S, Kadhum M, Li K, Long M, Michalak A, Pesala A, Pritazahra A, Saverimuttu S, Su R, Xu Q, Lovering R, Blake J, Christie K, Corbani L, Dolan M, Ni L, Sitnikov D, Smith C, Lera-Ramirez M, Rutherford K, Wood V, D’Eustachio P, Demos W, De Pons J, Dwinell M, Hayman G, Kaldunski M, Kwitek A, Laulederkind S, Smith J, Tutaj M, Vedi M, Wang S, Engel S, Karra K, Miyasato S, Nash R, Skrzypek M, Weng S, Wong E, Achsel T, Andres-Alonso M, Bagni C, Bayés À, Biederer T, Brose N, Chua J, Coba M, Cornelisse L, de Juan-Sanz J, Goldschmidt H, Gundelfinger E, Huganir R, Imig C, Jahn R, Jung H, Kaeser P, Kim E, Koopmans F, Kreutz M, Lipstein N, MacGillavry H, McPherson P, O’Connor V, Pielot R, Ryan T, Sala C, Sheng M, Smalla K, Smit A, Toonen R, van Weering J, Verhage M, Verpelli C, Bakker E, Berardini T, Reiser L, Auchincloss A, Axelsen K, Argoud-Puy G, Blatter M, Boutet E, Breuza L, Bridge A, Casals-Casas C, Coudert E, Estreicher A, Famiglietti M, Gos A, Gruaz-Gumowski N, Hulo C, Hyka-Nouspikel N, Jungo F, Le Mercier P, Lieberherr D, Masson P, Morgat A, Pedruzzi I, Pourcel L, Poux S, Rivoire C, Sundaram S, Bowler-Barnett E, Bye-A-Jee H, Denny P, Ignatchenko A, Ishtiaq R, Lock A, Lussi Y, Magrane M, Martin M, Orchard S, Raposo P, Speretta E, Tyagi N, Warner K, Zaru R, Chan J, Diamantakis S, Raciti D, Fisher M, James-Zorn C, Ponferrada V, Zorn A, Ramachandran S, Ruzicka L, Westerfield M. A compendium of human gene functions derived from evolutionary modelling. Nature 2025, 1-9. PMID: 40011791, DOI: 10.1038/s41586-025-08592-0.Peer-Reviewed Original ResearchHuman gene functionHuman protein-coding genesProtein-coding genesGene functionFunctional repertoireGene Ontology enrichment analysisGene Ontology ConsortiumOntology enrichment analysisHuman genomeHuman genesEvolutionary timeEvolutionary originGenomic techniquesEvolutionary modeling approachExpert-curatedEnrichment analysisGenesRegulatory functionsFunctional characteristicsEvolutionary modelsBiomedical researchGenomeRepertoireOrganisms1,2Body of informationEngineering a genomically recoded organism with one stop codon
Grome M, Nguyen M, Moonan D, Mohler K, Gurara K, Wang S, Hemez C, Stenton B, Cao Y, Radford F, Kornaj M, Patel J, Prome M, Rogulina S, Sozanski D, Tordoff J, Rinehart J, Isaacs F. Engineering a genomically recoded organism with one stop codon. Nature 2025, 639: 512-521. PMID: 39910296, PMCID: PMC11903333, DOI: 10.1038/s41586-024-08501-x.Peer-Reviewed Original ResearchGenomics yields biological and phenotypic insights into bipolar disorder
Lee B, Kim J, Lee Y, Kang J, Cheon M, Kim D, Aslan M, Harvey P, Huang G. Genomics yields biological and phenotypic insights into bipolar disorder. Nature 2025, 639: 968-975. PMID: 39843750, DOI: 10.1038/s41586-024-08468-9.Peer-Reviewed Original ResearchFine-mappingGenetic architectureGenome-wide significant lociMulti-ancestry meta-analysisGenetic architecture of bipolar disorderRare variant signalsSignificant lociGenetic determinantsBipolar disorderVariant signalsLatino ancestryCell typesEast Asian cohortsPhenotypic insightsPathophysiology of bipolar disorderGenesMedium spiny neuronsBipolar disorder subtypesPatient ascertainmentAetiology of bipolar disorderGABAergic interneuronsSpiny neuronsAsian cohortGenomeGlobal burdenThe Alia Camel of Jordan: a genetically distinct dromedary breed
Haddad N, Al-Araishi M, Awabdeh S, Patidar R, Bell R, Jawasreh K, Alhurani H, Elharbid L, Sweidan R, Al-Anaswah E, Brake M, Sadder M, Blanco O, Sbeih L, Uduman M, Lakhani S, Khokha M, Weir A. The Alia Camel of Jordan: a genetically distinct dromedary breed. Journal Of Heredity 2025, esae076. PMID: 39761336, DOI: 10.1093/jhered/esae076.Peer-Reviewed Original ResearchA Comprehensive Bioinformatics Approach to Analysis of Variants: Variant Calling, Annotation, and Prioritization
Koroglu M, Bilguvar K. A Comprehensive Bioinformatics Approach to Analysis of Variants: Variant Calling, Annotation, and Prioritization. Methods In Molecular Biology 2025, 2889: 207-233. PMID: 39745615, DOI: 10.1007/978-1-0716-4322-8_15.Peer-Reviewed Original ResearchConceptsGenomic dataHigh-throughput sequencing technologyGenomic data analysisField of genomicsNext-generation sequencingVariant callingNGS technologiesSequencing technologiesBioinformatics approachComprehensive computational approachSequenceComputational approachCancer researchGenomeTranscriptomeBioinformaticsNGSProteomicsNext-generationDNARNAEfficient sequenceAnnotationVariantsFragmentsTime to Admit Genes and Epigenetics are Indeed the Blueprint for a Rewardful Life Whereby the Organism Controls the Genome
Blum K, Braverman E, Lewandowski K, Gold M, Gardner E, Elman I, OscarBerman M, Cadet J, Sharafshah A, A Dennen C, Bowirrat A, Pinhasov A, Baron D, Levin C, Gondre-Lewis M, Badgaiyan R, Khalsa J, Sunder K, Murphy K, Makale M, Modestino E, Jafari N, Zeine F, PL Lewandrowski A, A Madigan M, Fuehrlein B, K Thanos P. Time to Admit Genes and Epigenetics are Indeed the Blueprint for a Rewardful Life Whereby the Organism Controls the Genome. Acta Scientific Neurology 2025, 03-09. DOI: 10.31080/asne.2025.08.0794.Peer-Reviewed Original Research
2024
Evaluation of imputation performance of multiple reference panels in a Pakistani population
Xu J, Liu D, Hassan A, Genovese G, Cote A, Fennessy B, Cheng E, Charney A, Knowles J, Ayub M, Peterson R, Bigdeli T, Huckins L. Evaluation of imputation performance of multiple reference panels in a Pakistani population. Human Genetics And Genomics Advances 2024, 6: 100395. PMID: 39696820, PMCID: PMC11759560, DOI: 10.1016/j.xhgg.2024.100395.Peer-Reviewed Original ResearchGenome-wide association studiesReference panelImputation accuracyMultiple reference panelsPakistani individualsGenotype imputationAssociation studiesGenotype dataAncestry compositionEuropean individualsSample sizeTOPMedDiverse populationsPakistani populationImputationGenomeAncestryIndividualsGenotypesPopulationVariantsFuture panelsπ-HuB: the proteomic navigator of the human body
He F, Aebersold R, Baker M, Bian X, Bo X, Chan D, Chang C, Chen L, Chen X, Chen Y, Cheng H, Collins B, Corrales F, Cox J, E W, Van Eyk J, Fan J, Faridi P, Figeys D, Gao G, Gao W, Gao Z, Goda K, Goh W, Gu D, Guo C, Guo T, He Y, Heck A, Hermjakob H, Hunter T, Iyer N, Jiang Y, Jimenez C, Joshi L, Kelleher N, Li M, Li Y, Lin Q, Liu C, Liu F, Liu G, Liu Y, Liu Z, Low T, Lu B, Mann M, Meng A, Moritz R, Nice E, Ning G, Omenn G, Overall C, Palmisano G, Peng Y, Pineau C, Poon T, Purcell A, Qiao J, Reddel R, Robinson P, Roncada P, Sander C, Sha J, Song E, Srivastava S, Sun A, Sze S, Tang C, Tang L, Tian R, Vizcaíno J, Wang C, Wang C, Wang X, Wang X, Wang Y, Weiss T, Wilhelm M, Winkler R, Wollscheid B, Wong L, Xie L, Xie W, Xu T, Xu T, Yan L, Yang J, Yang X, Yates J, Yun T, Zhai Q, Zhang B, Zhang H, Zhang L, Zhang L, Zhang P, Zhang Y, Zheng Y, Zhong Q, Zhu Y. π-HuB: the proteomic navigator of the human body. Nature 2024, 636: 322-331. PMID: 39663494, DOI: 10.1038/s41586-024-08280-5.Peer-Reviewed Original ResearchAn integrative TAD catalog in lymphoblastoid cell lines discloses the functional impact of deletions and insertions in human genomes.
Li C, Bonder M, Syed S, Jensen M, Gerstein M, Zody M, Chaisson M, Talkowski M, Marschall T, Korbel J, Eichler E, Lee C, Shi X. An integrative TAD catalog in lymphoblastoid cell lines discloses the functional impact of deletions and insertions in human genomes. Genome Research 2024, 34: 2304-2318. PMID: 39638559, PMCID: PMC11694747, DOI: 10.1101/gr.279419.124.Peer-Reviewed Original ResearchConceptsTopologically associating domainsTopologically associating domains boundariesImpact of structural variantsLymphoblastoid cell linesStructural variantsHuman genomeGene regulationAdjacent TADsHuman lymphoblastoid cell linesCell linesSub-TADGenomic structureInsulate genesChromatin architectureImpact of deletionChromatin structureGenomeAberrant regulationAnalysis pipelineMammalian speciesGenesCCREsFunctional impactChromatinRegulationcis- and trans-regulatory contributions to a hierarchy of factors influencing gene expression variation
Kalra S, Lanno S, Sanchez G, Coolon J. cis- and trans-regulatory contributions to a hierarchy of factors influencing gene expression variation. Communications Biology 2024, 7: 1563. PMID: 39587248, PMCID: PMC11589579, DOI: 10.1038/s42003-024-07255-6.Peer-Reviewed Original ResearchConceptsGene expression variationTrait variationExpression variationTrans-regulatory changesGene expression traitsSource of trait variationTrans-regulationExpression traitsDiverse organismsMolecular mechanismsDevelopmental stagesTransgenerational effectsGenesLife stagesTraitsDrosophilaGenomeEnvironmental responsibilityAssociated with changesMultiple different sourcesVariationGENCODE 2025: reference gene annotation for human and mouse
Mudge J, Carbonell-Sala S, Diekhans M, Martinez J, Hunt T, Jungreis I, Loveland J, Arnan C, Barnes I, Bennett R, Berry A, Bignell A, Cerdán-Vélez D, Cochran K, Cortés L, Davidson C, Donaldson S, Dursun C, Fatima R, Hardy M, Hebbar P, Hollis Z, James B, Jiang Y, Johnson R, Kaur G, Kay M, Mangan R, Maquedano M, Gómez L, Mathlouthi N, Merritt R, Ni P, Palumbo E, Perteghella T, Pozo F, Raj S, Sisu C, Steed E, Sumathipala D, Suner M, Uszczynska-Ratajczak B, Wass E, Yang Y, Zhang D, Finn R, Gerstein M, Guigó R, Hubbard T, Kellis M, Kundaje A, Paten B, Tress M, Birney E, Martin F, Frankish A. GENCODE 2025: reference gene annotation for human and mouse. Nucleic Acids Research 2024, 53: d966-d975. PMID: 39565199, PMCID: PMC11701607, DOI: 10.1093/nar/gkae1078.Peer-Reviewed Original ResearchGene annotationLong-read transcriptome sequencingMulti-genome alignmentsRibo-Seq experimentsUCSC Genome BrowserState-of-the-art proteomicsGenome browserRibo-seqSpecies genomesMouse genomeTranscriptome sequencingGENCODEGenomeAnnotation workflowAnnotationSequencePangenomeMiceGenesetsState-of-the-artUCSCProteomicsTranscriptionGenesSpecies
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