2021
Comprehensive identification of somatic nucleotide variants in human brain tissue
Wang Y, Bae T, Thorpe J, Sherman MA, Jones AG, Cho S, Daily K, Dou Y, Ganz J, Galor A, Lobon I, Pattni R, Rosenbluh C, Tomasi S, Tomasini L, Yang X, Zhou B, Akbarian S, Ball LL, Bizzotto S, Emery SB, Doan R, Fasching L, Jang Y, Juan D, Lizano E, Luquette LJ, Moldovan JB, Narurkar R, Oetjens MT, Rodin RE, Sekar S, Shin JH, Soriano E, Straub RE, Zhou W, Chess A, Gleeson JG, Marquès-Bonet T, Park PJ, Peters MA, Pevsner J, Walsh CA, Weinberger DR, Vaccarino F, Moran J, Urban A, Kidd J, Mills R, Abyzov A. Comprehensive identification of somatic nucleotide variants in human brain tissue. Genome Biology 2021, 22: 92. PMID: 33781308, PMCID: PMC8006362, DOI: 10.1186/s13059-021-02285-3.Peer-Reviewed Original ResearchMeSH KeywordsAllelesBrainChromosome MappingComputational BiologyGenetic Association StudiesGenetic VariationGenomicsGerm CellsHigh-Throughput Nucleotide SequencingHumansOrgan SpecificityPolymorphism, Single NucleotideConceptsSomatic SNVsSomatic single nucleotide variantsWhole-genome sequencing dataSequencing dataBulk DNA samplesCell lineage treesSomatic mosaicismSingle nucleotide variantsLineage treesSomatic nucleotide variantsCellular processesDNA replicationHuman genomeSomatic tissuesDNA repairNucleotide variantsComprehensive identificationDNA samplesMosaic variantsNon-cancerous tissuesDNASingle individualMultiple replicatesHuman brain tissueVariantsEarly developmental asymmetries in cell lineage trees in living individuals
Fasching L, Jang Y, Tomasi S, Schreiner J, Tomasini L, Brady MV, Bae T, Sarangi V, Vasmatzis N, Wang Y, Szekely A, Fernandez TV, Leckman JF, Abyzov A, Vaccarino FM. Early developmental asymmetries in cell lineage trees in living individuals. Science 2021, 371: 1245-1248. PMID: 33737484, PMCID: PMC8324008, DOI: 10.1126/science.abe0981.Peer-Reviewed Original Research
2020
SCELLECTOR: ranking amplification bias in single cells using shallow sequencing
Sarangi V, Jourdon A, Bae T, Panda A, Vaccarino F, Abyzov A. SCELLECTOR: ranking amplification bias in single cells using shallow sequencing. BMC Bioinformatics 2020, 21: 521. PMID: 33183232, PMCID: PMC7663899, DOI: 10.1186/s12859-020-03858-y.Peer-Reviewed Original ResearchConceptsMultiple displacement amplificationShallow sequencingSingle-cell platformsSingle-cell sequencingCoverage sequencing dataSingle cellsHuman neuronal cellsMosaic mutationsAmount of DNAAmplification qualityCell sequencingCoverage sequencingHigh-coverage dataSequencing dataHaplotype informationPhi29 polymeraseDNA damageIndividual cellsNeuronal cellsSequencingAmplification biasAllelic imbalancePresence of sitesMutationsFragment length
2017
Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis
Bae T, Tomasini L, Mariani J, Zhou B, Roychowdhury T, Franjic D, Pletikos M, Pattni R, Chen BJ, Venturini E, Riley-Gillis B, Sestan N, Urban AE, Abyzov A, Vaccarino FM. Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis. Science 2017, 359: 550-555. PMID: 29217587, PMCID: PMC6311130, DOI: 10.1126/science.aan8690.Peer-Reviewed Original ResearchMeSH KeywordsBrainCell LineageGastrulationGenome, HumanHumansMosaicismMutagenesisMutationMutation RateNeoplasmsNeurogenesisNeuronsPolymorphism, Single NucleotideSingle-Cell AnalysisConceptsSingle nucleotide variationsMutation rateCancer cell genomeClonal cell populationsCell genomeCell lineagesBackground mutagenesisHuman cellsMutational rateSomatic mosaicismSingle cellsOxidative damageGenomeMutagenesisCell populationsMutation spectrumNeurogenesisCellsHuman fetusesIndividual neuronsLineagesPregastrulationHuman brainBrainMutations