2017
Detection of Regional Variation in Selection Intensity within Protein-Coding Genes Using DNA Sequence Polymorphism and Divergence
Zhao ZM, Campbell MC, Li N, Lee DSW, Zhang Z, Townsend JP. Detection of Regional Variation in Selection Intensity within Protein-Coding Genes Using DNA Sequence Polymorphism and Divergence. Molecular Biology And Evolution 2017, 34: 3006-3022. PMID: 28962009, PMCID: PMC5850860, DOI: 10.1093/molbev/msx213.Peer-Reviewed Original ResearchConceptsPoisson random fieldRandom fieldsEnsemble of modelsRandom field frameworkField frameworkClustering modelHistorical demographic trendsAmino acid-altering substitutionsSelection intensityEnsembleHigh powerUniform selectionProtein-coding genesProtein coding genesHeterogeneity of selectionDNA sequence polymorphismsComparison of polymorphisms
2015
Solving the ecological puzzle of mycorrhizal associations using data from annotated collections and environmental samples – an example of saddle fungi
Hwang J, Zhao Q, Yang ZL, Wang Z, Townsend JP. Solving the ecological puzzle of mycorrhizal associations using data from annotated collections and environmental samples – an example of saddle fungi. Environmental Microbiology Reports 2015, 7: 658-667. PMID: 26033481, DOI: 10.1111/1758-2229.12303.Peer-Reviewed Original ResearchConceptsPotential plant hostsEnvironmental sequencesDiversity of ecologyEctomycorrhizal fungiEcological roleGenetic divergenceGeographic distributionUnculturable fungiPhylogenetic informativenessPlant hostsEcologyITS phylogenyITS sequencesRoot tipsEnvironmental samplesSpeciesMetagenomic investigationSequence alignmentHost typeHelvellaDiversityFungiDiversity of relationshipsSequenceSoilH-CLAP: hierarchical clustering within a linear array with an application in genetics
Ghosh S, Townsend JP. H-CLAP: hierarchical clustering within a linear array with an application in genetics. Statistical Applications In Genetics And Molecular Biology 2015, 14: 125-141. PMID: 25803088, DOI: 10.1515/sagmb-2013-0076.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBayes TheoremCluster AnalysisComputational BiologyGene Expression ProfilingGeneticsOligonucleotide Array Sequence Analysis
2014
Epidemiological and Viral Genomic Sequence Analysis of the 2014 Ebola Outbreak Reveals Clustered Transmission
Scarpino SV, Iamarino A, Wells C, Yamin D, Ndeffo-Mbah M, Wenzel NS, Fox SJ, Nyenswah T, Altice FL, Galvani AP, Meyers LA, Townsend JP. Epidemiological and Viral Genomic Sequence Analysis of the 2014 Ebola Outbreak Reveals Clustered Transmission. Clinical Infectious Diseases 2014, 60: 1079-1082. PMID: 25516185, PMCID: PMC4375398, DOI: 10.1093/cid/ciu1131.Peer-Reviewed Original Research
2012
Transcriptome analyses during fruiting body formation in Fusarium graminearum and Fusarium verticillioides reflect species life history and ecology
Sikhakolli UR, López-Giráldez F, Li N, Common R, Townsend JP, Trail F. Transcriptome analyses during fruiting body formation in Fusarium graminearum and Fusarium verticillioides reflect species life history and ecology. Fungal Genetics And Biology 2012, 49: 663-673. PMID: 22705880, DOI: 10.1016/j.fgb.2012.05.009.Peer-Reviewed Original ResearchConceptsF. graminearumOrthologous genesLife historyFusarium graminearumF. verticillioidesGene expressionSexual developmentStage-specific gene expressionSpecies' life historyDifferent life historiesPrevious morphological analysesMorphological developmentLife cycleSexual sporesCereal pathogensUnclassified proteinsFunctional assignmentTranscriptional programsTranscriptome analysisTranscriptional analysisType genesEcological characteristicsApoptotic processFusarium speciesGraminearumAbundant Gene-by-Environment Interactions in Gene Expression Reaction Norms to Copper within Saccharomyces cerevisiae
Hodgins-Davis A, Adomas AB, Warringer J, Townsend JP. Abundant Gene-by-Environment Interactions in Gene Expression Reaction Norms to Copper within Saccharomyces cerevisiae. Genome Biology And Evolution 2012, 4: 1061-1079. PMID: 23019066, PMCID: PMC3514956, DOI: 10.1093/gbe/evs084.Peer-Reviewed Original ResearchMeSH KeywordsCluster AnalysisCopperDNA-Binding ProteinsDose-Response Relationship, DrugGene Expression ProfilingGene Expression Regulation, FungalGene-Environment InteractionGenes, FungalGenetic VariationMetabolic Networks and PathwaysMicroarray AnalysisNuclear ProteinsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTranscription FactorsTranscriptomeConceptsPopulation variationReaction normsGene expression reaction normsGene expressionNovel ecological contextsGenome-wide mRNA levelsGenetic backgroundRelevant copper concentrationsAbundance of variationMitotic fitnessSulfur homeostasisPlastic phenotypesDownstream metabolic consequencesPlastic variationMost genesCopper stressPhenotypic variationGene networksAbundant genesGenetic variationCopper gradientExpression variationEcological contextDifferential expressionGenes
2009
Maximum-Likelihood Model Averaging To Profile Clustering of Site Types across Discrete Linear Sequences
Zhang Z, Townsend JP. Maximum-Likelihood Model Averaging To Profile Clustering of Site Types across Discrete Linear Sequences. PLOS Computational Biology 2009, 5: e1000421. PMID: 19557160, PMCID: PMC2695770, DOI: 10.1371/journal.pcbi.1000421.Peer-Reviewed Original ResearchConceptsInformation criterionModel averagingBayesian information criterionMaximum likelihood methodModel likelihoodModel uncertaintyModel selectionDescription of clustersLevel of clusteringPrecision of estimationAkaike information criterionParameter rangeCluster countsLikelihood methodComputational biologyCluster sizeGood accuracyConquer strategyAveragingClusteringModelHierarchical clusteringClustersStatisticsEstimation
2005
Long-oligomer microarray profiling in Neurospora crassa reveals the transcriptional program underlying biochemical and physiological events of conidial germination
Kasuga T, Townsend JP, Tian C, Gilbert LB, Mannhaupt G, Taylor JW, Glass NL. Long-oligomer microarray profiling in Neurospora crassa reveals the transcriptional program underlying biochemical and physiological events of conidial germination. Nucleic Acids Research 2005, 33: 6469-6485. PMID: 16287898, PMCID: PMC1283539, DOI: 10.1093/nar/gki953.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBayes TheoremBlotting, NorthernCluster AnalysisDatabases, Nucleic AcidDictyosteliumExpressed Sequence TagsGene Expression ProfilingGenes, FungalNeurospora crassaOligonucleotide Array Sequence AnalysisOligonucleotide ProbesPromoter Regions, GeneticReproducibility of ResultsRNA, MessengerSpores, FungalTranscription, GeneticUstilagoConceptsConidial germinationGene expression levelsNeurospora crassaGene expressionPhytopathogenic fungus Ustilago maydisSocial amoeba Dictyostelium discoideumFilamentous ascomycete speciesPutative regulatory componentFungus Ustilago maydisAmoeba Dictyostelium discoideumExpression levelsAscomycete speciesRibosomal biogenesisRelative gene expression levelsNovel genesTranscriptional programsUstilago maydisTranscriptional profilingDictyostelium discoideumFunctional predictionTranscriptional mechanismsRegulatory componentsFilamentous fungiExpression profilesMicroarray profiling