Search results for "genomic"

showing 10 items of 1737 documents

Tremblaya phenacola PPER: an evolutionary beta-gammaproteobacterium collage

2017

Many insects rely on bacterial endosymbionts to obtain nutrients that are scarce in their highly specialized diets. The most surprising example corresponds to the endosymbiotic system found in mealybugs from subfamily Pseudococcinae in which two bacteria, the betaproteobacterium 'Candidatus Tremblaya princeps' and a gammaproteobacterium, maintain a nested endosymbiotic consortium. In the sister subfamily Phenacoccinae, however, a single beta-endosymbiont, 'Candidatus Tremblaya phenacola', has been described. In a previous study, we detected a trpB gene of gammaproteobacterial origin in 'Ca. Tremblaya phenacola' from two Phenacoccus species, apparently indicating an unusual case of horizonta…

0301 basic medicineSubfamilyGene Transfer HorizontalPopulationBiologyMicrobiologyGenomeHemiptera03 medical and health sciencesSymbiosisBacterial ProteinsPhylogeneticsAnimalseducationSymbiosisGeneEcology Evolution Behavior and SystematicsPhylogenySubgenomic mRNAGeneticseducation.field_of_studyBetaproteobacteriabiochemical phenomena metabolism and nutritionBiological Evolution030104 developmental biologyHorizontal gene transferOriginal ArticleGenome Bacterial
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Ancient pigs reveal a near-complete genomic turnover following their introduction to Europe

2019

International audience; Archaeological evidence indicates that pig domestication had begun by ∼10,500 y before the present (BP) in the Near East, and mitochondrial DNA (mtDNA) suggests that pigs arrived in Europe alongside farmers ∼8,500 y BP. A few thousand years after the introduction of Near Eastern pigs into Europe, however, their characteristic mtDNA signature disappeared and was replaced by haplotypes associated with European wild boars. This turnover could be accounted for by substantial gene flow from local Euro-pean wild boars, although it is also possible that European wild boars were domesticated independently without any genetic contribution from the Near East. To test these hyp…

0301 basic medicineSwine[SHS.ANTHRO-BIO]Humanities and Social Sciences/Biological anthropologySkin Pigmentation[SHS]Humanities and Social SciencesGene flowDomesticationddc:590BREEDSDOMESTIC PIGS/dk/atira/pure/subjectarea/asjc/1000HISTORY0601 history and archaeologyNeolithicHistory AncientPhylogenyMultidisciplinary060102 archaeologyINTROGRESSIONEurope ; pigs ; domestication ; genomesWILD06 humanities and the artsArchaeological evidenceGene flowEuropeSPREADCoatMitochondrial DNAEvolutionZoology930Locus (genetics)BiologyAnimal Breeding and GenomicsDNA MitochondrialMiddle East03 medical and health sciencesAnimalsFokkerij en GenomicaDNA AncientGeneralDomesticationddc:930HaplotypeDNA900 Geschichte und Geografie::930 Geschichte des Altertums (bis ca. 499) Archäologie::930 Geschichte des Altertums bis ca. 499 ArchäologieLONGSIZE030104 developmental biologydomestication evolution gene flow NeolithicWIAS
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The hidden diversity of lichenized Trebouxiophyceae (Chlorophyta).

2018

The class Trebouxiophyceae is comprised of coccoid to ellipsoid unicells, filaments, blades and colony-forming species of green algae occurring in diverse terrestrial and aquatic environments. Some representatives have evolved parasitic heterotrophic lifestyles, others have been investigated for their biotechnological potential and others have evolved as integral components of lichen symbioses. In this review, we provide an overview of the current understanding of diversity, taxonomy and evolutionary context for the important lichen-forming algal class Trebouxiophyceae (Chlorophyta). In particular, we focus on members of the family Trebouxiaceae (Trebouxiales), the best-known, most widespre…

0301 basic medicineSystematicsSystematicPlant ScienceChlorophytaAquatic ScienceBiologyPhylogenticAsterochloriAsterochloris; Coexistence; Ecology; Genomic; Microalgae; Phylogentics; Species; Systematic03 medical and health sciencesSpecieTrebouxialesPhylogeneticsMicroalgaeLichenSpeciesEcologyEcologyTrebouxiophyceaeAsterochlorisbiology.organism_classificationPhylogentics030104 developmental biologyGenomicTaxonomy (biology)Green algaeCoexistence
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Do next-generation sequencing results drive diagnostic and therapeutic decisions in MDS?

2019

Este artículo se encuentra disponible en la siguiente URL: https://ashpublications.org/bloodadvances/article/3/21/3454/422749/Do-next-generation-sequencing-results-drive

0301 basic medicineSíndromes mielodisplásicos - Aspectos moleculares.Clinical Decision-MakingMEDLINEComputational biologyDNA sequencing03 medical and health sciences0302 clinical medicineText miningHumansMedicineGenetic Predisposition to DiseaseSangre - Células - Aspectos moleculares.Molecular Targeted TherapyGenes.Genetic Association StudiesBlood cells - Molecular aspects.business.industryDecision TreesDisease ManagementHigh-Throughput Nucleotide SequencingGenomicsHematologyPrognosisCombined Modality TherapyMyelodysplastic syndrome - Molecular aspects.030104 developmental biologyMyelodysplastic Syndromes030220 oncology & carcinogenesisMutationPoint-CounterpointMolecular biology.Biología molecular.businessBiomarkersBlood Advances
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Role of the antioxidant defence system and telomerase in arsenic-induced genomic instability

2016

Arsenic (AS) is a reactive oxygen species (ROS)-inducer carcinogen, whose mode of action is still unclear. To defend against ROS, cells use enzymatic and non-enzymatic antioxidants, such as superoxide dismutase (SOD) and catalase. Failure of antioxidant systems (AXS) can result in dicentric chromosomes formation as well as telomere associations for the reduced activity of telomerase. In order to clarify the long-term effects of a past AS exposure, we evaluated the efficiency of the AXS and the telomerase activity in the progeny of arsenite-treated cells named ASO (arsenic shake-off) cells, previously obtained from arsenite-treated V79 cells and selected by shake-off. Despite SOD1 expression…

0301 basic medicineTelomeraseArsenitesHealth Toxicology and MutagenesisClone (cell biology)ToxicologyAntioxidantsGenomic InstabilitySuperoxide dismutase03 medical and health sciencesTelomerase RNA componentCricetulus0302 clinical medicineGeneticsAnimalsTelomerase reverse transcriptaseArsenic Genomic instability Antioxidant defense system SOD CAT Telomerase.TelomeraseGenetics (clinical)chemistry.chemical_classificationReactive oxygen speciesbiologySuperoxide DismutaseCatalaseMolecular biologyTelomereSettore BIO/18 - Genetica030104 developmental biologyGene Expression RegulationchemistryCatalase030220 oncology & carcinogenesisbiology.proteinReactive Oxygen SpeciesMutagenesis
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Parallel and Space-Efficient Construction of Burrows-Wheeler Transform and Suffix Array for Big Genome Data

2016

Next-generation sequencing technologies have led to the sequencing of more and more genomes, propelling related research into the era of big data. In this paper, we present ParaBWT, a parallelized Burrows-Wheeler transform (BWT) and suffix array construction algorithm for big genome data. In ParaBWT, we have investigated a progressive construction approach to constructing the BWT of single genome sequences in linear space complexity, but with a small constant factor. This approach has been further parallelized using multi-threading based on a master-slave coprocessing model. After gaining the BWT, the suffix array is constructed in a memory-efficient manner. The performance of ParaBWT has b…

0301 basic medicineTheoretical computer scienceBurrows–Wheeler transformComputer scienceGenomicsData_CODINGANDINFORMATIONTHEORYParallel computingGenomelaw.invention03 medical and health scienceslawGeneticsHumansEnsemblMulti-core processorApplied MathematicsLinear spaceSuffix arrayChromosome MappingHigh-Throughput Nucleotide SequencingGenomicsSequence Analysis DNA030104 developmental biologyAlgorithmsBiotechnologyReference genomeIEEE/ACM Transactions on Computational Biology and Bioinformatics
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Biomolecular computers with multiple restriction enzymes

2017

Abstract The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann “bottleneck”. Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro’s group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton t…

0301 basic medicineTheoretical computer scienceDNA computerlcsh:QH426-4700102 computer and information sciencesBiology01 natural scienceslaw.inventionrestriction enzymesGenomics and Bioinformatics03 medical and health sciencessymbols.namesakeSoftwareDNA computinglawGeneticsNondeterministic finite automatonMolecular BiologyQuantum computerFinite-state machinebusiness.industryConstruct (python library)bioinformaticsDNARestriction enzymelcsh:Genetics030104 developmental biology010201 computation theory & mathematicssymbolsbusinessVon Neumann architectureGenetics and Molecular Biology
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Accelerating metagenomic read classification on CUDA-enabled GPUs.

2016

Metagenomic sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification; i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes software tools for fast and accurate metagenomic read classification are urgently needed. We present cuCLARK, a read-level classifier for CUDA-enabled GPUs, based on the fast and accurate classification of metagenomic sequences using reduced k-mers (…

0301 basic medicineTheoretical computer scienceWorkstationGPUsComputer scienceContext (language use)CUDAParallel computingBiochemistryGenomelaw.invention03 medical and health sciencesCUDAUser-Computer Interface0302 clinical medicineStructural BiologylawTaxonomic assignmentHumansMicrobiomeMolecular BiologyInternetXeonApplied MathematicsHigh-Throughput Nucleotide SequencingSequence Analysis DNAExact k-mer matchingComputer Science Applications030104 developmental biologyTitan (supercomputer)Metagenomics030220 oncology & carcinogenesisMetagenomicsDNA microarraySoftwareBMC bioinformatics
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Deep learning models for bacteria taxonomic classification of metagenomic data.

2018

Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…

0301 basic medicineTime FactorsDBNComputer scienceBiochemistryStructural BiologyRNA Ribosomal 16SDatabases Geneticlcsh:QH301-705.5Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionibiologySettore INF/01 - InformaticaShotgun sequencingApplied MathematicsAmpliconClassificationComputer Science Applicationslcsh:R858-859.7DNA microarrayShotgunAlgorithmsCNN030106 microbiologyk-mer representationlcsh:Computer applications to medicine. Medical informaticsDNA sequencing03 medical and health sciencesMetagenomicDeep LearningMolecular BiologyBacteriaModels GeneticPhylumbusiness.industryDeep learningResearchReproducibility of ResultsPattern recognitionBiological classification16S ribosomal RNAbiology.organism_classificationAmpliconHypervariable region030104 developmental biologyTaxonlcsh:Biology (General)MetagenomicsMetagenomeArtificial intelligenceMetagenomicsNeural Networks ComputerbusinessClassifier (UML)BacteriaBMC bioinformatics
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Long-term genomic coevolution of host-parasite interaction in the natural environment

2017

Antagonistic coevolution of parasite infectivity and host resistance may alter the biological functionality of species, yet these dynamics in nature are still poorly understood. Here we show the molecular details of a long-term phage–bacterium arms race in the environment. Bacteria (Flavobacterium columnare) are generally resistant to phages from the past and susceptible to phages isolated in years after bacterial isolation. Bacterial resistance selects for increased phage infectivity and host range, which is also associated with expansion of phage genome size. We identified two CRISPR loci in the bacterial host: a type II-C locus and a type VI-B locus. While maintaining a core set of conse…

0301 basic medicineTime Factorsmedicine.medical_treatmentvirusesGeneral Physics and AstronomyGenomeCRISPR SpacersbakteeritBacteriophageEnvironmental MicrobiologyCRISPRBacteriophagesClustered Regularly Interspaced Short Palindromic RepeatsANTAGONISTIC COEVOLUTIONADAPTATIONbacteriaInfectivityGenetics0303 health scienceseducation.field_of_studyMultidisciplinaryQgenomiikkaBACTERIOPHAGE RESISTANCE MECHANISMSresistance (medicine)bacteriophagesPhage therapyScienceAntagonistic Coevolution030106 microbiologyPopulationevoluutioVirulencePHAGELocus (genetics)Genome ViralBiologyFlavobacteriumArticlebakteriofagitGeneral Biochemistry Genetics and Molecular BiologyHost-Parasite InteractionsEvolution Molecular03 medical and health sciencesCRISPR-CAS SYSTEMSFISHevolutionmedicinegenomicseducationGenome size1172 Environmental sciences030304 developmental biology030306 microbiologyGeneral Chemistrybiology.organism_classificationEVOLUTIONresistenssiPATHOGEN FLAVOBACTERIUM-COLUMNARE030104 developmental biologyMutationCRISPR LociVIRULENCEIMMUNE-SYSTEMGenome BacterialNature Communications
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