2024
Comparing newly developed SNP barcode panels with microsatellites to explore population genetics of malaria parasites in the Peruvian Amazon
Cabrera-Sosa L, Safarpour M, Kattenberg J, Ramirez R, Vinetz J, Rosanas-Urgell A, Gamboa D, Delgado-Ratto C. Comparing newly developed SNP barcode panels with microsatellites to explore population genetics of malaria parasites in the Peruvian Amazon. Frontiers In Genetics 2024, 15: 1488109. PMID: 39748949, PMCID: PMC11693692, DOI: 10.3389/fgene.2024.1488109.Peer-Reviewed Original ResearchInvestigate population geneticsPopulation geneticsSNP barcodesPairwise F<sub>ST<Pairwise genetic differentiationPolyclonal infectionsMalaria parasitesPopulation genetic estimatesPer-sample costProportion of polyclonal infectionsPlasmodium falciparum</i> parasitesPlasmodium vivax</i>Genetic differentiationGenetic resolutionGenetic diversityPeruvian AmazonGenetic estimatesMicrosatelliteSNPsAmpliSeqBarcodingDiversity trendsMolecular surveillanceResource availabilityMS panelRobustness in population-structure and demographic-inference results derived from the Aedes aegypti genotyping chip and whole-genome sequencing data
Gómez-Palacio A, Morinaga G, Turner P, Micieli M, Elnour M, Salim B, Surendran S, Ramasamy R, Powell J, Soghigian J, Gloria-Soria A. Robustness in population-structure and demographic-inference results derived from the Aedes aegypti genotyping chip and whole-genome sequencing data. G3: Genes, Genomes, Genetics 2024, 14: jkae082. PMID: 38626295, PMCID: PMC11152066, DOI: 10.1093/g3journal/jkae082.Peer-Reviewed Original ResearchWhole-genome sequencingPopulation genetic studiesSNP chipGenome sequenceSequencing approachWhole-genome sequencing dataLow-depth whole-genome sequencingWhole-genome sequencing approachCoverage whole genome sequencingLow-coverage whole-genome sequencingSNP chip dataAllele frequency spectrumDiverse AeVectors of human diseasesPhylogenetic analysisSequence dataPopulation geneticsPopulation structureGenomic studiesInvasive rangeMosquito Aedes aegyptiPopulation-structureChip dataGenetic studiesSNPs
2023
Chapter 5 Measurement and meaning in gene expression evolution
Diaz R, Wang Z, Townsend J. Chapter 5 Measurement and meaning in gene expression evolution. 2023, 111-129. DOI: 10.1016/b978-0-323-91810-7.00008-x.ChaptersGene expressionPhenotypic evolutionGene expression evolutionMessenger RNAEffects of epistasisIndividual gene expressionRibonucleic acid sequencingExpression evolutionNonmodel speciesFunctional genomicsGenomic scaleTranscriptional networksGene functionRelative mRNA abundancePhenotypic variationPopulation geneticsReference genomeTranscriptome profilingBiological traitsMolecular adjustmentsQuantitative traitsPhenotypic varianceGene interactionsGenetic controlExpression variation
2022
Population genetics of an invasive mosquito vector, Aedes albopictus in the Northeastern USA
Gloria-Soria A, Shragai T, Ciota A, Duval T, Alto B, Martins A, Westby K, Medley K, Unlu I, Campbell S, Kawalkowski M, Tsuda Y, Higa Y, Indelicato N, Leisnham P, Caccone A, Armstrong P. Population genetics of an invasive mosquito vector, Aedes albopictus in the Northeastern USA. NeoBiota 2022, 78: 99-127. PMID: 37408738, PMCID: PMC10321554, DOI: 10.3897/neobiota.78.84986.Peer-Reviewed Original ResearchPopulations of AeGenetic structureGenetic diversityPopulation geneticsGenetic cladesMicrosatellite markersAsian tiger mosquitoNortheastern USARange northwardsNorthern rangeAlbopictus populationsFounder effectPopulation turnoverVector suppressionEast coastTiger mosquitoEastern USAInvasive mosquito vectorsMosquito vectorsAedes albopictusLocal populationWarming conditionsAlbopictusCold wintersConsecutive yearsDiversity and distribution of MHC class I and II alleles in chicken populations worldwide
Martin R, Tregaskes C, Kaufman J. Diversity and distribution of MHC class I and II alleles in chicken populations worldwide. Molecular Immunology 2022, 150: 27. DOI: 10.1016/j.molimm.2022.05.092.Peer-Reviewed Original ResearchMinimal essential MHCClass II lociPeptide binding specificityPopulation bottlenecksClass II genesFancy breedsIllumina MiSeqPopulation geneticsLinkage disequilibriumCommercial flocksLow diversityChicken populationsArtificial selectionBinding specificityFree-range local chickensExon 2Genetic associationII lociHaplotypesResponse to infectionTapasin geneII genesTranslocation specificityExpress class II genesMHC allelesReversion is most likely under high mutation supply when compensatory mutations do not fully restore fitness costs
Pennings P, Ogbunugafor C, Hershberg R. Reversion is most likely under high mutation supply when compensatory mutations do not fully restore fitness costs. G3: Genes, Genomes, Genetics 2022, 12: jkac190. PMID: 35920784, PMCID: PMC9434179, DOI: 10.1093/g3journal/jkac190.Peer-Reviewed Original ResearchConceptsCompensatory mutationsPopulation geneticsExperimental evolutionDynamics of adaptationMutation rateWild typeEvolution of antibiotic resistanceQuality of mutationsTheoretical population geneticsDynamics of compensationEvolution of mutationsMutation supplyMicrobial evolutionNonmutant strainsProbability of reversalMutated strainsEvolutionary dynamicsFitness costsAntibiotic resistanceFitness effectsMutationsAdaptive dynamicsGeneticsStrainPotential rolePopulation genetics meets single-cell sequencing
Sumida TS, Hafler DA. Population genetics meets single-cell sequencing. Science 2022, 376: 134-135. PMID: 35389792, DOI: 10.1126/science.abq0426.Peer-Reviewed Original ResearchPopulation Genomics Approaches for Genetic Characterization of SARS-CoV-2 Lineages
Mostefai F, Gamache I, N'Guessan A, Pelletier J, Huang J, Murall CL, Pesaranghader A, Gaonac'h-Lovejoy V, Hamelin DJ, Poujol R, Grenier JC, Smith M, Caron E, Craig M, Wolf G, Krishnaswamy S, Shapiro BJ, Hussin JG. Population Genomics Approaches for Genetic Characterization of SARS-CoV-2 Lineages. Frontiers In Medicine 2022, 9: 826746. PMID: 35265640, PMCID: PMC8899026, DOI: 10.3389/fmed.2022.826746.Peer-Reviewed Original ResearchPopulation genomic approachesStandard phylogenetic approachesGenome sequencing dataHaplotype networkGenomic approachesPhylogenetic approachTajima's DHigh-quality consensus sequencesGenetic diversityPopulation geneticsGenomic variationConsensus sequenceLineage expansionSequencing dataSARS-CoV-2 diversityGenetic characterizationLineage identificationDiversity landscapeInfection pathwaySARS-CoV-2 lineagesRecurrent mutationsGISAID databaseSARS-CoV-2DiversityPathogensThe mutation effect reaction norm (mu‐rn) highlights environmentally dependent mutation effects and epistatic interactions
Ogbunugafor C. The mutation effect reaction norm (mu‐rn) highlights environmentally dependent mutation effects and epistatic interactions. Evolution 2022, 76: 37-48. PMID: 34989399, DOI: 10.1111/evo.14428.Peer-Reviewed Original ResearchConceptsReaction normsFitness effects of mutationsPhenotypic consequences of mutationsEvolution of antimicrobial resistanceEffects of mutationsConsequences of mutationsGenetic interactionsPopulation geneticsEpistatic interactionsPhenotypic consequencesGenetic informationMutational effectsFunction of environmental contextUnpredictability of evolutionFitness effectsMutationsAntimicrobial resistanceLayer of complexityEnvironmental contextModern SynthesisPerformance of genotypesReverse evolutionEpistasisGeneticsPublic health
2017
Temporal genetic differentiation in Glossina pallidipes tsetse fly populations in Kenya
Okeyo WA, Saarman NP, Mengual M, Dion K, Bateta R, Mireji PO, Okoth S, Ouma JO, Ouma C, Ochieng J, Murilla G, Aksoy S, Caccone A. Temporal genetic differentiation in Glossina pallidipes tsetse fly populations in Kenya. Parasites & Vectors 2017, 10: 471. PMID: 29017572, PMCID: PMC5635580, DOI: 10.1186/s13071-017-2415-y.Peer-Reviewed Original ResearchConceptsTemporal genetic differentiationGenetic diversityGenetic differentiationGenetic bottleneckGenetic variationNational ParkTemporal genetic variationExtensive control measuresAnimal African trypanosomiasisAllelic richnessPairwise FSTGenetic driftNe estimatesHabitat alterationPopulation geneticsTemporal differentiationMicrosatellite markersRuma National ParkClosest sampling sitesG. pallidipesMajor vectorTsetse fliesVector populationsDifferentiationDiversity
2016
Asymmetric hybridization between non-native winter moth, Operophtera brumata (Lepidoptera: Geometridae), and native Bruce spanworm, Operophtera bruceata, in the Northeastern United States, assessed with novel microsatellites and SNPs
Havill N, Elkinton J, Andersen J, Hagen S, Broadley H, Boettner G, Caccone A. Asymmetric hybridization between non-native winter moth, Operophtera brumata (Lepidoptera: Geometridae), and native Bruce spanworm, Operophtera bruceata, in the Northeastern United States, assessed with novel microsatellites and SNPs. Bulletin Of Entomological Research 2016, 107: 241-250. PMID: 27876095, DOI: 10.1017/s0007485316000857.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsMicrosatellite lociBruce spanwormAsymmetric hybridizationWinter mothSpecies-diagnostic single nucleotide polymorphismsOperophtera brumataVariable microsatellite lociNon-native pestsTypes of markersBacterial symbiontsGenetic incompatibilitiesGenomic approachesLaboratory crossesNative speciesAsymmetrical hybridizationPopulation geneticsPutative hybridsHybrid backcrossesNovel microsatellitesForest treesOperophtera bruceataO. bruceataReciprocal crossesGenetic markersA New Take on John Maynard Smith's Concept of Protein Space for Understanding Molecular Evolution
Ogbunugafor C, Hartl D. A New Take on John Maynard Smith's Concept of Protein Space for Understanding Molecular Evolution. PLOS Computational Biology 2016, 12: e1005046. PMID: 27736867, PMCID: PMC5063322, DOI: 10.1371/journal.pcbi.1005046.Peer-Reviewed Original ResearchProposed nomenclature for microhaplotypes
Kidd KK. Proposed nomenclature for microhaplotypes. Human Genomics 2016, 10: 16. PMID: 27316555, PMCID: PMC4912715, DOI: 10.1186/s40246-016-0078-y.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsHUGO Gene Nomenclature CommitteeGene Nomenclature CommitteeGroup of genesGene familyPopulation geneticsChromosome numberChromosome 1Related genesGenetic markersNucleotide polymorphismsNomenclature CommitteeGenesMicrohaplotypesRootsChromosomesFamilyLociUnique characterStandardized nomenclatureGeneticsNomenclatureSequencePolymorphism
2014
Evolutionary Systems Biology: Shifting Focus to the Context‐Dependency of Genetic Effects
Pavličev M, Wagner G. Evolutionary Systems Biology: Shifting Focus to the Context‐Dependency of Genetic Effects. 2014, 91-108. DOI: 10.1002/9781118398814.ch6.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsLineage fusion in Galápagos giant tortoises
Garrick R, Benavides E, Russello M, Hyseni C, Edwards D, Gibbs J, Tapia W, Ciofi C, Caccone A. Lineage fusion in Galápagos giant tortoises. Molecular Ecology 2014, 23: 5276-5290. PMID: 25223395, DOI: 10.1111/mec.12919.Peer-Reviewed Original ResearchConceptsLineage fusionGiant tortoise speciesGalápagos giant tortoisesWidespread introgressive hybridizationLong generation timesWolf VolcanoCryptic lineagesReticulate evolutionIntrogressive hybridizationLineage splittingMicrosatellite dataGalápagos tortoisesPopulation geneticsEvolutionary phenomenaMate selectivityTortoise speciesGiant tortoisesLineagesGeneration timeRapid extinctionTortoisesPurebred femalesFusionIslandsHistorical reconstructionHuman pharmacogenomic variation of antihypertensive drugs: from population genetics to personalized medicine
Polimanti R, Iorio A, Piacentini S, Manfellotto D, Fuciarelli M. Human pharmacogenomic variation of antihypertensive drugs: from population genetics to personalized medicine. Pharmacogenomics 2014, 15: 157-167. PMID: 24444406, DOI: 10.2217/pgs.13.231.Peer-Reviewed Original ResearchConceptsInterpopulation differencesNext-generation sequencing technologiesAntihypertensive drug responseFunctionality of genesPopulation geneticsGenetic variationSequencing technologiesDrug responseSilico analysisGeographic originPharmacogenomic variationGenetic variantsGeneticsRare variantsPharmacogenesPharmacogenetic variationVariantsGenesPersonalized medicineVariationImportant knowledgeStageSLC6A4 polymorphism, population genetics, and psychiatric traits
Gelernter J. SLC6A4 polymorphism, population genetics, and psychiatric traits. Human Genetics 2014, 133: 459-461. PMID: 24385047, PMCID: PMC3992709, DOI: 10.1007/s00439-013-1412-2.Peer-Reviewed Original Research
2013
An historical perspective on “The world-wide distribution of allele frequencies at the human dopamine D4 receptor locus”
Kidd KK, Pakstis AJ, Yun L. An historical perspective on “The world-wide distribution of allele frequencies at the human dopamine D4 receptor locus”. Human Genetics 2013, 133: 431-433. PMID: 24162668, DOI: 10.1007/s00439-013-1386-0.Peer-Reviewed Original ResearchConceptsThousands of lociGene frequency patternsPatterns of divergenceRandom genetic driftHuman population geneticsLow-frequency allelesDopamine D4 receptor locusGenetic driftPopulation geneticsImportant genesPopulation variationWorld-wide distributionReceptor locusFrequency allelesDifferent allelesLociDistinct populationsNative American populationsEast Asian populationsAllelesAllele frequenciesSame populationAmerican populationGenesGeneticsUrban population genetics of slum‐dwelling rats (Rattus norvegicus) in Salvador, Brazil
Kajdacsi B, Costa F, Hyseni C, Porter F, Brown J, Rodrigues G, Farias H, Reis MG, Childs JE, Ko AI, Caccone A. Urban population genetics of slum‐dwelling rats (Rattus norvegicus) in Salvador, Brazil. Molecular Ecology 2013, 22: 5056-5070. PMID: 24118116, PMCID: PMC3864905, DOI: 10.1111/mec.12455.Peer-Reviewed Original ResearchConceptsGenetic structurePopulation genetic structureComplex genetic structureSmall geographical distancesGene flowGenetic clustersGenetic diversityMicrosatellite lociPopulation geneticsUrban landscapeGenetic variationPopulation ecologyGenetic dataHeterogeneous urban landscapesDistinct sampling sitesGeographical distanceRodent control measuresRodent control strategiesZoonotic pathogensR. norvegicusSampling sitesSpatial connectivityRat populationsOvergrown vegetationBayesian analysisEpidemiological mechanisms of genetic resistance to kuru
Atkins KE, Townsend JP, Medlock J, Galvani AP. Epidemiological mechanisms of genetic resistance to kuru. Journal Of The Royal Society Interface 2013, 10: 20130331. PMID: 23740487, PMCID: PMC4043168, DOI: 10.1098/rsif.2013.0331.Peer-Reviewed Original ResearchConceptsTransmissible spongiform encephalopathiesGenotype frequency dataPopulation geneticsProtein geneGenetic resistanceEpidemiological mechanismsPrion protein geneMechanistic basisPrion proteinHost resistanceFatal neurodegenerative conditionHuman populationHuman resistancePapua New GuineaNew GuineaSpongiform encephalopathiesIncubation periodCodon 129Neurodegenerative conditionsIncidence dataReduced susceptibilityLong incubation periodKuruGenesMechanism
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