2025
A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission
Sobkowiak B, Cudahy P, Chitwood M, Clark T, Colijn C, Grandjean L, Walter K, Crudu V, Cohen T. A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission. Genome Medicine 2025, 17: 8. PMID: 39871355, PMCID: PMC11771024, DOI: 10.1186/s13073-025-01430-y.Peer-Reviewed Original ResearchConceptsShort-read WGS dataWhole-genome sequencingStrain sequencesWGS dataMultiple strainsStrain proportionsMycobacterium tuberculosis populationMixed infectionGenome sequenceBioinformatics pipelineClustering allele frequenciesDownstream analysisAllele frequenciesEvidence of mixed infectionSequenceTuberculosis populationStrainIsolatesIn vitroTransmission clustersMixed samplesAllelesInfectionMycobacterium tuberculosis infectionPathogensPhenotypic and genotypic characterization of Mycobacterium tuberculosis pyrazinamide resistance—India, 2018–2020
Tamilzhalagan S, Justin E, Selvaraj A, Venkateswaran K, Sivakumar A, Chittibabu S, McLaughlin H, Moonan P, Smith J, Suba S, Narayanan M, Ho C, Kumar N, Tripathy S, Shanmugam S, Hall-Eidson P, Ranganathan U. Phenotypic and genotypic characterization of Mycobacterium tuberculosis pyrazinamide resistance—India, 2018–2020. Frontiers In Microbiology 2025, 15: 1515627. PMID: 39845030, PMCID: PMC11750862, DOI: 10.3389/fmicb.2024.1515627.Peer-Reviewed Original ResearchPZA resistancePyrazinamide resistanceMultidrug resistanceDuration of tuberculosis treatmentWhole-genome sequencingPrevalence of mutationsSecond-line drugsPZA-resistant isolatesResistance-conferring mutationsGenome sequenceTB burden countriesLineage 2Genotypic characterizationResistance markersNovel mutationsPhenotypic resistanceMutational diversityDiagnostic accuracyTuberculosis treatmentAntituberculosis drugsCo-resistanceBurden countriesPyrazinamideMutationsTB preventionCFTR haplotype phasing using long-read genome sequencing from ultralow input DNA
Gandotra N, Tyagi A, Tikhonova I, Storer C, Scharfe C. CFTR haplotype phasing using long-read genome sequencing from ultralow input DNA. Genetics In Medicine Open 2025, 3: 101962. PMID: 40027236, PMCID: PMC11869909, DOI: 10.1016/j.gimo.2025.101962.Peer-Reviewed Original ResearchLong-read genome sequencingSingle-nucleotide variantsHaplotype phasingGenome sequencePathogenic variantsSmall indelsShort-read genome sequencing dataDNA inputShort-read sequencingGenome sequence dataPoly-T tractRare pathogenic variantsGenetic disease screeningIdentified compound heterozygosityGenomic distanceLibrary preparationGenomic variantsAllelic phaseCystic fibrosis patientsSequence dataInput DNAGenotype concordanceGenomic DNAStructural variantsSingle-nucleotide
2024
Monitoring sewage and effluent water is an effective approach for the detection of the mobile colistin resistance genes (mcr) and associated bacterial hosts in the human population and environment in the USA
Hassan J, Osman M, Xu T, Naas T, Schiff S, Mann D, Esseili M, Deng X, Kassem I. Monitoring sewage and effluent water is an effective approach for the detection of the mobile colistin resistance genes (mcr) and associated bacterial hosts in the human population and environment in the USA. Environmental Pollution 2024, 366: 125515. PMID: 39662581, DOI: 10.1016/j.envpol.2024.125515.Peer-Reviewed Original ResearchWhole-genome sequencingMobile colistin resistance geneColistin resistance genesResistance genesMcr-9Whole-genome sequence analysisKirby-Bauer disk diffusionGram-negative bacterial isolatesBroth micro-dilution assayLast-resort antibioticsTreat recalcitrant infectionsMcr-positive isolatesAntibiotic resistance genesMicro-dilution assayGenome sequenceBacterial hostsHuman populationKirby-BauerIncHI2 plasmidsBiofilm assayBacterial isolatesDisk diffusionMcr-3Water samplesRecalcitrant infectionsRare 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 variantsAnalysis of Powassan Virus Genome Sequences from Human Cases Reveals Substantial Genetic Diversity with Implications for Molecular Assay Development
Klontz E, Chowdhury N, Holbrook N, Solomon I, Telford S, Aliota M, Vogels C, Grubaugh N, Helgager J, Hughes H, Velez J, Piantadosi A, Chiu C, Lemieux J, Branda J. Analysis of Powassan Virus Genome Sequences from Human Cases Reveals Substantial Genetic Diversity with Implications for Molecular Assay Development. Viruses 2024, 16: 1653. PMID: 39599768, PMCID: PMC11599074, DOI: 10.3390/v16111653.Peer-Reviewed Original ResearchGenome sequenceDiversity of genomic sequencesHuman infectionsPCR assay designVirus genome sequencesAssay designIn silico analysisBiology of infectionViral genomic dataGenetic diversityGenomic dataSensitivity of PCRGenomeCladePCR assayHuman diseasesVirulent strainsPCR designPowassan virusSequenceImmunocompromised patientsPCRTick-borne virusesAssay developmentClinical diagnosticsA phylogenetics and variant calling pipeline to support SARS-CoV-2 genomic epidemiology in the UK
Colquhoun R, O’Toole Á, Hill V, McCrone J, Yu X, Nicholls S, Poplawski R, Whalley T, Groves N, Ellaby N, Loman N, Connor T, Rambaut A. A phylogenetics and variant calling pipeline to support SARS-CoV-2 genomic epidemiology in the UK. Virus Evolution 2024, 10: veae083. PMID: 39493537, PMCID: PMC11529618, DOI: 10.1093/ve/veae083.Peer-Reviewed Original ResearchSARS-CoV-2 genome sequencesSARS-CoV-2 genomeGlobal phylogenetic contextCOVID-19 Genomics UKCOG-UKVariant callingGenome sequencePhylogenetic contextGenomic epidemiologyGenomic surveillanceSARS-CoV-2Public health decision makingHealth decision makingGenomeSequenceSARS-CoV-2 pandemicPhylogeneticallyUnited KingdomQuality controlDecision makingCOVID-19Increasing amountW32. A GENOME-WIDE ASSOCIATION STUDY OF BIPOLAR DISORDER FROM INDIA
Mahadevan J, Holla B, Ganesh S, Shankarappa B, Paul P, Sud R, Jain S, Purushottam M, Viswanath B. W32. A GENOME-WIDE ASSOCIATION STUDY OF BIPOLAR DISORDER FROM INDIA. European Neuropsychopharmacology 2024, 87: 118. DOI: 10.1016/j.euroneuro.2024.08.241.Peer-Reviewed Original ResearchGenome-wide association studiesGenomic risk lociRisk lociAssociation studiesGenome-wide association study of BDGenome wide association studiesAncestry principal componentsSevere mental illnessWhole-genome sequencingTissue expression analysisBiology of BdPatients of European ancestryBipolar disorderHRC panelGenome sequenceMental illnessAncestry samplesGenomic methodsEpisodes of depressionAllele dosageGenetic studiesEuropean ancestryICD-10Outpatient clinicTrained psychiatristsA cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders
Lee A, Ayers L, Kosicki M, Chan W, Fozo L, Pratt B, Collins T, Zhao B, Rose M, Sanchis-Juan A, Fu J, Wong I, Zhao X, Tenney A, Lee C, Laricchia K, Barry B, Bradford V, Jurgens J, England E, Lek M, MacArthur D, Lee E, Talkowski M, Brand H, Pennacchio L, Engle E. A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders. Nature Communications 2024, 15: 8268. PMID: 39333082, PMCID: PMC11436875, DOI: 10.1038/s41467-024-52463-7.Peer-Reviewed Original ResearchConceptsNon-coding variantsCranial motor neuronsMendelian disordersIn vivo transgenic assayPredictor of enhancer activityCis-regulatory elementsMulti-omic frameworkWhole-genome sequencingEnhanced activityVariant discoveryGenome sequenceChromatin accessibilityPutative enhancersHistone modificationsRegulatory elementsGene expression assaysGene predictionTransgenic assaysEpigenomic profilingMendelian casesExpression assaysMutational enhancementCongenital cranial dysinnervation disordersCell typesFunctional impactThe Australian Genomics Mitochondrial Flagship: A national program delivering mitochondrial diagnoses
Rius R, Compton A, Baker N, Balasubramaniam S, Best S, Bhattacharya K, Boggs K, Boughtwood T, Braithwaite J, Bratkovic D, Bray A, Brion M, Burke J, Casauria S, Chong B, Coman D, Cowie S, Cowley M, de Silva M, Delatycki M, Edwards S, Ellaway C, Fahey M, Finlay K, Fletcher J, Frajman L, Frazier A, Gayevskiy V, Ghaoui R, Goel H, Goranitis I, Haas M, Hock D, Howting D, Jackson M, Kava M, Kemp M, King-Smith S, Lake N, Lamont P, Lee J, Long J, MacShane M, Madelli E, Martin E, Marum J, Mattiske T, McGill J, Metke A, Murray S, Panetta J, Phillips L, Quinn M, Ryan M, Schenscher S, Simons C, Smith N, Stroud D, Tchan M, Tom M, Wallis M, Ware T, Welch A, Wools C, Wu Y, Christodoulou J, Thorburn D. The Australian Genomics Mitochondrial Flagship: A national program delivering mitochondrial diagnoses. Genetics In Medicine 2024, 27: 101271. PMID: 39305161, DOI: 10.1016/j.gim.2024.101271.Peer-Reviewed Original ResearchGenome sequencePhenocopy genesMitochondrial diseaseMtDNA sequencesMtDNA deletionsMD geneMtDNAChildhood-onset diseaseDiagnostic journeyDiagnostic yieldMolecular diagnosisGenesNational studySequenceGene etiologySuspected MDDiagnostic pathwayIncrease diagnostic yieldPediatric-onsetOnset diseaseAdult onsetAdult patientsChildrenSkeletal muscleScoresGenome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections
Li K, Chaguza C, Stamp J, Chew Y, Chen N, Ferguson D, Pandya S, Kerantzas N, Schulz W, Initiative Y, Hahn A, Ogbunugafor C, Pitzer V, Crawford L, Weinberger D, Grubaugh N. Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections. PLOS Computational Biology 2024, 20: e1012469. PMID: 39288189, PMCID: PMC11432881, DOI: 10.1371/journal.pcbi.1012469.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesSingle-nucleotide polymorphismsAssociation studiesWhole-genome sequencingAmino acid changesSingle nucleotide polymorphismsPairs of substitutionsViral copiesEpistasis testsGenome sequenceGenetic variationSpike geneAcid changesViral genomeNucleotide polymorphismsSARS-CoV-2Detect interactionsHost factorsVirus copiesCopyInfection dynamicsRT-qPCRPolymorphismOmicron BASARS-CoV-2 infectionA new lineage nomenclature to aid genomic surveillance of dengue virus
Hill V, Cleemput S, Pereira J, Gifford R, Fonseca V, Tegally H, Brito A, Ribeiro G, de Souza V, Brcko I, Ribeiro I, De Lima I, Slavov S, Sampaio S, Elias M, Tran V, Kien D, Huynh T, Yacoub S, Dieng I, Salvato R, Wallau G, Gregianini T, Godinho F, Vogels C, Breban M, Leguia M, Jagtap S, Roy R, Hapuarachchi C, Mwanyika G, Giovanetti M, Alcantara L, Faria N, Carrington C, Hanley K, Holmes E, Dumon W, Lima A, de Oliveira T, Grubaugh N. A new lineage nomenclature to aid genomic surveillance of dengue virus. PLOS Biology 2024, 22: e3002834. PMID: 39283942, PMCID: PMC11426435, DOI: 10.1371/journal.pbio.3002834.Peer-Reviewed Original ResearchConceptsGenomic surveillanceSub-genotype levelPartial genome sequencesDengue virusViral genomic diversityClade sizeGenome sequenceGenomic diversityPhylogenetic studiesPhylogenetic distanceSequence dataMinor lineageVirus classificationLineagesSurveillance of dengue virusDiversityAssignment toolComplex patternsVirusCladeSequenceGeographical areasGenotypesNomenclatureEndemic settingsInsights into the evolution, virulence and speciation of Babesia MO1 and Babesia divergens through multiomics analyses
Singh P, Vydyam P, Fang T, Estrada K, Gonzalez L, Grande R, Kumar M, Chakravarty S, Berry V, Ranwez V, Carcy B, Depoix D, Sánchez S, Cornillot E, Abel S, Ciampossin L, Lenz T, Harb O, Sanchez-Flores A, Montero E, Le Roch K, Lonardi S, Mamoun C. Insights into the evolution, virulence and speciation of Babesia MO1 and Babesia divergens through multiomics analyses. Emerging Microbes & Infections 2024, 13: 2386136. PMID: 39148308, PMCID: PMC11370697, DOI: 10.1080/22221751.2024.2386136.Peer-Reviewed Original ResearchLeveraging genomic informationHuman babesiosisTick-borne diseasesDiseases of significanceCases of human babesiosisGenomic divergenceGenome sequenceGenomic informationMultigene familyGene functionBabesia divergensMammalian hostsAnimal healthMultiomics analysisZoonotic pathogensBabesiosisProtozoan parasitesVirulent strainsPathogensVertebrate hostsEnvironmental changesVirulenceReplication rateAntiparasitic drugsParasitesUltra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction
Li X, Liu T, Bacchiocchi A, Li M, Cheng W, Wittkop T, Mendez F, Wang Y, Tang P, Yao Q, Bosenberg M, Sznol M, Yan Q, Faham M, Weng L, Halaban R, Jin H, Hu Z. Ultra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction. EMBO Molecular Medicine 2024, 16: 2188-2209. PMID: 39164471, PMCID: PMC11393307, DOI: 10.1038/s44321-024-00115-0.Peer-Reviewed Original ResearchMolecular residual diseaseCirculating tumor DNAWhole-genome sequencingCell-free DNAGenome sequenceDetection of molecular residual diseaseCirculating tumor DNA detectionResidual disease detectionConsistent with clinical outcomesVariant allele frequencyResidual diseaseMelanoma patientsMonitoring immunotherapyTumor DNAEsophageal cancerClinical outcomesColorectal cancerWGS technologiesAllele frequenciesCancerDNAAnalytical sensitivitySequenceImmunotherapyRelapseWhole genome sequencing study of identical twins discordant for psychosis
Ormond C, Ryan N, Hedman A, Cannon T, Sullivan P, Gill M, Hultman C, Heron E, Johansson V, Corvin A. Whole genome sequencing study of identical twins discordant for psychosis. Translational Psychiatry 2024, 14: 313. PMID: 39080272, PMCID: PMC11289105, DOI: 10.1038/s41398-024-02982-0.Peer-Reviewed Original ResearchConceptsCopy number variantsSequencing studiesGenic copy number variantsWhole-genome sequencing studiesRare genic copy number variantsDeleterious missense variantsWhole-genome sequencingExome sequencing studiesGenome sequencing studiesMZ twinsPost-zygotic eventsPairs of MZ twinsGenome sequenceIdentical genomesDNA variantsMissense variantsOverlapped genesPsychotic phenotypesPsychotic disordersBipolar disorderRare variantsMZ twin studiesPhenotypic discordanceTwin studiesTwin pairsNorth–south pathways, emerging variants, and high climate suitability characterize the recent spread of dengue virus serotypes 2 and 3 in the Dominican Republic
Miguel I, Feliz E, Agramonte R, Martinez P, Vergara C, Imbert Y, De la Cruz L, de Castro N, Cedano O, De la Paz Y, Fonseca V, Santiago G, Muñoz-Jordán J, Peguero A, Paulino-Ramírez R, Grubaugh N, de Filippis A, Alcantara L, Rico J, Lourenço J, Franco L, Giovanetti M. North–south pathways, emerging variants, and high climate suitability characterize the recent spread of dengue virus serotypes 2 and 3 in the Dominican Republic. BMC Infectious Diseases 2024, 24: 751. PMID: 39075335, PMCID: PMC11288047, DOI: 10.1186/s12879-024-09658-6.Peer-Reviewed Original ResearchConceptsGenome sequenceCombination of genome sequencingTrace transmission pathwaysDengue virusHistorical climatic patternsHigh climatic suitabilityCo-circulationDengue virus serotype 2Transmission pathwaysPhylogenetic analysisVirus transmission pathwaysBiodiversity hotspotHistorical climate dataVirus lineagesDominican RepublicImpacts of climate changeLineagesClimatic suitabilityClimate dataRising temperaturePathwaySerotype 2Subtropical regionsTransmission dynamicsImpact of climatic factorsResolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints
Zhou B, Purmann C, Guo H, Shin G, Huang Y, Pattni R, Meng Q, Greer S, Roychowdhury T, Wood R, Ho M, Dohna H, Abyzov A, Hallmayer J, Wong W, Ji H, Urban A. Resolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints. Proceedings Of The National Academy Of Sciences Of The United States Of America 2024, 121: e2322834121. PMID: 39042694, PMCID: PMC11295037, DOI: 10.1073/pnas.2322834121.Peer-Reviewed Original ResearchConceptsLong-read sequencingPulse-field gel electrophoresisBase-pair resolutionDNA methylation patternsCell-type specific analysisCell type-specificChromosomal interactionsSequence assemblySegmental duplicationsGenome sequenceGenomic rearrangementsGenomic regionsChromosomal breakpointsHuman genomeGenomic recombinationMethylation patternsSequence analysisHaplotype-specificDeletion haplotypesGel electrophoresisGenomeAmplification-freeBreakpoint locationsMicrodeletion disorderType-specificExpanding the genetics and phenotypes of ocular congenital cranial dysinnervation disorders
Jurgens J, Barry B, Chan W, MacKinnon S, Whitman M, Ruiz P, Pratt B, England E, Pais L, Lemire G, Groopman E, Glaze C, Russell K, Singer-Berk M, Di Gioia S, Lee A, Andrews C, Shaaban S, Wirth M, Bekele S, Toffoloni M, Bradford V, Foster E, Berube L, Rivera-Quiles C, Mensching F, Sanchis-Juan A, Fu J, Wong I, Zhao X, Wilson M, Weisburd B, Lek M, Consortium O, Abarca-Barriga H, Al-Haddad C, Berman J, Bothun E, Capasso J, Chacon-Camacho O, Chang L, Christiansen S, Ciccarelli M, Cordonnier M, Cox G, Curry C, Dagi L, Dahm T, David K, Davitt B, De Berardinis T, Demer J, Désir J, D’Esposito F, Drack A, Eggenberger E, Elder J, Elliott A, Epley K, Feldman H, Ferreira C, Flaherty M, Fulton A, Gerth-Kahlert C, Gottlob I, Grill S, Halliday D, Hanisch F, Hay E, Heidary G, Holder C, Horton J, Iannaccone A, Isenberg S, Johnston S, Kahana A, Katowitz J, Kazlas M, Kerr N, Kimonis V, Ko M, Koc F, Larsen D, Lay-Son G, Ledoux D, Levin A, Levy R, Lyons C, Mackey D, Magli A, Mantagos I, Marti C, Maystadt I, McKenzie F, Menezes M, Mikail C, Miller D, Miller K, Mills M, Miyana K, Moller H, Mullineaux L, Nishimura J, Noble A, Pandey P, Pavone P, Penzien J, Petersen R, Phalen J, Poduri A, Polo C, Prasov L, Ramos F, Ramos-Caceres M, Robb R, Rossillion B, Sahin M, Singer H, Smith L, Sorkin J, Soul J, Staffieri S, Stalker H, Stasheff S, Strassberg S, Strominger M, Taranath D, Thomas I, Traboulsi E, Ugrin M, VanderVeen D, Vincent A, G M, Wabbels B, Wong A, Woods C, Wu C, Yang E, Yeung A, Young T, Zenteno J, Zubcov-Iwantscheff A, Zwaan J, Brand H, Talkowski M, MacArthur D, O’Donnell-Luria A, Robson C, Hunter D, Engle E. Expanding the genetics and phenotypes of ocular congenital cranial dysinnervation disorders. Genetics In Medicine 2024, 27: 101216. PMID: 39033378, PMCID: PMC11739428, DOI: 10.1016/j.gim.2024.101216.Peer-Reviewed Original ResearchCongenital cranial dysinnervation disordersPrioritized variantsProtein-coding regionsSingle-nucleotide variantsDe novo variantsAnimal model phenotypesGenetically heterogeneous disorderAnalysis of pedigreesGenes associated with syndromesGenome sequenceStructural variantsMendelian conditionsModel phenotypesGenotype/phenotype correlationGenetic etiologyGenotype/phenotype associationsPathogenic variant(sGenesFunctional studiesSyndrome phenotypeSyndrome componentsPhenotypeGeneticsProbandsVariantsInsights into SARS-CoV-2 Surveillance among Prison Populations in Mato Grosso do Sul, Brazil, in 2022
da Silva L, Alcantara L, Fonseca V, Frias D, Zardin M, de Castro Lichs G, Esposito A, Xavier J, Fritsch H, Lima M, de Oliveira C, de Arruda L, de Mello Almeida Maziero L, Barretos E, Oshiro P, Menezes E, de Freitas Cardoso L, Lemos E, Lourenço J, de Albuquerque C, do Carmo Said R, Rosewell A, Demarchi L, Croda J, Giovanetti M, Gonçalves C. Insights into SARS-CoV-2 Surveillance among Prison Populations in Mato Grosso do Sul, Brazil, in 2022. Viruses 2024, 16: 1143. PMID: 39066305, PMCID: PMC11281713, DOI: 10.3390/v16071143.Peer-Reviewed Original ResearchConceptsNext-generation sequencingPrison populationIncarcerated populationsOvercrowded cellsGenome sequenceGenomic characteristicsPrisonGenomic surveillanceEnclosed populationMato GrossoAverage coverageIsolation protocolSARS-CoV-2RT-qPCR testSARS-CoV-2 surveillanceRT-qPCRSequenceFrequent transferEpidemiological monitoringLimited healthcare accessGenomeCellsOmicron variantRapid genome sequencing for critically ill infants: an inaugural pilot study from Turkey
Yilmaz B, Akgun-Dogan O, Ozdemir O, Yuksel B, Ng O, Bilguvar K, Ay B, Ozkose G, Aydin E, Yigit A, Bulut A, Esen F, Beken S, Aktas S, Demirel A, Arcagok B, Kazanci E, Bingol İ, Umur O, Sik G, Isik U, Ersoy M, Korkmaz A, Citak A, Mardinoglu A, Ozbek U, Alanay Y. Rapid genome sequencing for critically ill infants: an inaugural pilot study from Turkey. Frontiers In Pediatrics 2024, 12: 1412880. PMID: 39026936, PMCID: PMC11254770, DOI: 10.3389/fped.2024.1412880.Peer-Reviewed Original ResearchRapid genome sequencingHospital settingReducing unnecessary interventionsImprove patient careCost-effective approach to diagnosisTurkish healthcare systemClinical managementNext-generation sequencingPatient careHealthcare systemCritically ill infantsInclusion criteriaPediatric ICU patientsDelivery of resultsInfant morbidityMendelian conditionsDiagnostic odysseyApproach to diagnosisGenetic conditionsPilot studyUnnecessary interventionsTen infantsGenome sequenceDiagnostic yieldCongenital abnormalities
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