2021
Sex-Biased Aging Effects on Ig Somatic Hypermutation Targeting
Cui A, Chawla DG, Kleinstein SH. Sex-Biased Aging Effects on Ig Somatic Hypermutation Targeting. The Journal Of Immunology 2021, 206: 101-108. PMID: 33288546, PMCID: PMC8582005, DOI: 10.4049/jimmunol.2000576.Peer-Reviewed Original ResearchConceptsOlder individualsDNA mismatch repair genesSex groupsObserved clinical differencesMismatch repair genesB cell IgDecreased expression levelDNA repair activityImmunologic responseClinical differencesAb responsesFemale human subjectsOld maleAged individualsImpaired levelDifferent agesYounger counterpartsPhase ILargest fold changeYoung individualsError-prone DNA repair activityExpression levelsHuman subjectsMutation patternsRepair activity
2016
A Model of Somatic Hypermutation Targeting in Mice Based on High-Throughput Ig Sequencing Data
Cui A, Di Niro R, Vander Heiden JA, Briggs AW, Adams K, Gilbert T, O'Connor KC, Vigneault F, Shlomchik MJ, Kleinstein SH. A Model of Somatic Hypermutation Targeting in Mice Based on High-Throughput Ig Sequencing Data. The Journal Of Immunology 2016, 197: 3566-3574. PMID: 27707999, PMCID: PMC5161250, DOI: 10.4049/jimmunol.1502263.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsB-LymphocytesCells, CulturedClonal Selection, Antigen-MediatedDNA RepairFemaleGerminal CenterHigh-Throughput Nucleotide SequencingHumansImmunoglobulin Heavy ChainsImmunoglobulin Variable RegionMiceMice, Inbred BALB CMice, TransgenicModels, GeneticMutationMutation RateSomatic Hypermutation, ImmunoglobulinConceptsSpecific DNA motifsSimilar biological processesObserved mutation patternDNA repair activityIg sequencesNonfunctional sequencesDNA motifsMutation patternsHigh mutation frequencySelection pressureUnselected mutationsSequencing dataBiological processesFunctional sequencesRepair activityTransition mutationsSomatic hypermutation patternsGerminal center B cellsSomatic hypermutationNext-generation methodsHypermutation patternsMutation frequencyMutationsSequenceMotif
2015
The mutation patterns in B-cell immunoglobulin receptors reflect the influence of selection acting at multiple time-scales
Yaari G, Benichou JI, Vander Heiden J, Kleinstein SH, Louzoun Y. The mutation patterns in B-cell immunoglobulin receptors reflect the influence of selection acting at multiple time-scales. Philosophical Transactions Of The Royal Society B Biological Sciences 2015, 370: 20140242. PMID: 26194756, PMCID: PMC4528419, DOI: 10.1098/rstb.2014.0242.Peer-Reviewed Original ResearchMeSH KeywordsAntibody AffinityAntibody DiversityB-LymphocytesCell LineageClonal Selection, Antigen-MediatedComplementarity Determining RegionsGenes, ImmunoglobulinHumansImmunoglobulin Heavy ChainsImmunoglobulin Variable RegionModels, GeneticModels, ImmunologicalMutationReceptors, Antigen, B-CellSomatic Hypermutation, ImmunoglobulinTime FactorsConceptsLineage treesPositive selectionStrong selection pressureLong-term selectionInfluence of selectionGene familyVariable gene familiesComplementarity determining regionsClone membersMutation patternsSelection pressureB cell populationsImmunoglobulin genesB cellsFramework regionsSomatic hypermutationSomatic mutationsAffinity maturationMutationsClone sizeMaturation processLong trunkAffinity maturation processSignificant diversityMultiple roundsA model of somatic hypermutation targeting in mice based on high-throughput immunoglobulin sequencing data (TECH2P.910)
Cui A, Diniro R, Briggs A, Adams K, Vander Heiden J, O'Connor K, Vigneault F, Shlomchik M, Kleinstein S. A model of somatic hypermutation targeting in mice based on high-throughput immunoglobulin sequencing data (TECH2P.910). The Journal Of Immunology 2015, 194: 206.20-206.20. DOI: 10.4049/jimmunol.194.supp.206.20.Peer-Reviewed Original ResearchSimilar biological processesNon-functional sequencesObserved mutation patternDNA repair activityMutation patternsDNA motifsNext-generation sequencingHigh mutation frequencyUnselected mutationsSelection pressureSequencing dataBiological processesFunctional sequencesImmunoglobulin genesRepair activitySomatic hypermutation patternsSomatic hypermutationHypermutation patternsMutation frequencyIg sequencesT transitionSequenceHeavy chain transgenic miceMotifTransgenic mice
2012
Quantifying selection in high-throughput Immunoglobulin sequencing data sets
Yaari G, Uduman M, Kleinstein SH. Quantifying selection in high-throughput Immunoglobulin sequencing data sets. Nucleic Acids Research 2012, 40: e134-e134. PMID: 22641856, PMCID: PMC3458526, DOI: 10.1093/nar/gks457.Peer-Reviewed Original ResearchConceptsQuantifying selectionDifferent selection pressuresHigh-throughput immunoglobulinSomatic hypermutationNext-generation sequencing dataDNA mutation patternsSomatic mutation patternsGroups of sequencesAntigen-driven selection processMutation patternsSequence dataSelection pressureSequencing dataB cell affinity maturationB-cell cancersNegative selectionQuantifying selection in high-throughput Immunoglobulin sequencing datasets (58.4)
Yaari G, Uduman M, Kleinstein S. Quantifying selection in high-throughput Immunoglobulin sequencing datasets (58.4). The Journal Of Immunology 2012, 188: 58.4-58.4. DOI: 10.4049/jimmunol.188.supp.58.4.Peer-Reviewed Original Research
2011
Somatic hypermutation targeting is influenced by location within the immunoglobulin V region
Cohen RM, Kleinstein SH, Louzoun Y. Somatic hypermutation targeting is influenced by location within the immunoglobulin V region. Molecular Immunology 2011, 48: 1477-1483. PMID: 21592579, PMCID: PMC3109224, DOI: 10.1016/j.molimm.2011.04.002.Peer-Reviewed Original ResearchConceptsObserved mutation patternSpecific DNA motifsBiased codon usageImmunoglobulin V genesMutation accumulationGene positionCodon usageMutation patternsDNA motifsPositive selectionPosition-specific effectsImmunoglobulin V regionsNegative selectionB cellsMutationsMutation frequencyV geneGenesPeripheral B cellsSubstitution typeV regionsTargetingSpecific targetingCellsSequence